In-operation learning of optimal wind farm operation strategy
Oliva Gratacós, Joan
2017-01-01
In a wind farm, power losses due to wind turbine wake effects can be up to 30-40% under certain conditions. As the global installed wind power capacity increases, the mitigation of wake effects in wind farms is gaining more importance. Following a conventional control strategy, each individual turbine maximizes its own power production without taking into consideration its effects on the performance of downstream turbines. Therefore, this control scheme results in operation con...
DEFF Research Database (Denmark)
Lund, Henrik; Salgi, Georges; Elmegaard, Brian
2009-01-01
on electricity spot markets by storing energy when electricity prices are low and producing electricity when prices are high. In order to make a profit on such markets, CAES plant operators have to identify proper strategies to decide when to sell and when to buy electricity. This paper describes three...... plants will not be able to achieve such optimal operation, since the fluctuations of spot market prices in the coming hours and days are not known. Consequently, two simple practical strategies have been identified and compared to the results of the optimal strategy. This comparison shows that...... independent computer-based methodologies which may be used for identifying the optimal operation strategy for a given CAES plant, on a given spot market and in a given year. The optimal strategy is identified as the one which provides the best business-economic net earnings for the plant. In practice, CAES...
Integrated Emission Management strategy for cost-optimal engine-aftertreatment operation
Cloudt, R.P.M.; Willems, F.P.T.
2011-01-01
A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of
An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles
Directory of Open Access Journals (Sweden)
Yinghua Han
2014-01-01
Full Text Available Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost.
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2010-01-01
markets in some ways, is chosen as the studied power system in this paper. Two kinds of BESS, based on polysulfide-bromine (PSB) and vanadium redox (VRB) battery technologies, are studies in the paper. Simulation results show, that the proposed optimal operation strategy is an effective measure to achieve......Since the hourly spot market price is available one day ahead, the price could be transferred to the consumers and they may have some motivations to install an energy storage system in order to save their energy costs. This paper presents an optimal operation strategy for a battery energy storage...
Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand
Directory of Open Access Journals (Sweden)
Chunyan Tang
2017-01-01
Full Text Available An optimization approach for designing a transit service system is proposed. Its objective would be the maximization of total social welfare, by providing a profitable fare structure and tailoring operational strategies to passenger demand. These operational strategies include full route operation (FRO, limited stop, short turn, and a mix of the latter two strategies. The demand function is formulated to reflect the attributes of these strategies, in-vehicle crowding, and fare effects on demand variation. The fare is either a flat fare or a differential fare structure; the latter is based on trip distance and achieved service levels. This proposed methodology is applied to a case study of Dalian, China. The optimal results indicate that an optimal combination of operational strategies integrated with a differential fare structure results in the highest potential for increasing total social welfare, if the value of parameter ε related to additional service fee is low. When this value increases up to more than a threshold, strategies with a flat fare show greater benefits. If this value increases beyond yet another threshold, the use of skipped stop strategies is not recommended.
Optimal offering and operating strategies for wind-storage systems with linear decision rules
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2016-01-01
The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy...... to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF...
Directory of Open Access Journals (Sweden)
Mun-Kyeom Kim
2017-09-01
Full Text Available This study introduces a frequency regulation strategy to enable the participation of wind turbines with permanent magnet synchronous generators (PMSGs. The optimal strategy focuses on developing the frequency support capability of PMSGs connected to the power system. Active power control is performed using maximum power point tracking (MPPT and de-loaded control to supply the required power reserve following a disturbance. A kinetic energy (KE reserve control is developed to enhance the frequency regulation capability of wind turbines. The coordination with the de-loaded control prevents instability in the PMSG wind system due to excessive KE discharge. A KE optimization method that maximizes the sum of the KE reserves at wind farms is also adopted to determine the de-loaded power reference for each PMSG wind turbine using the particle swarm optimization (PSO algorithm. To validate the effectiveness of the proposed optimal control and operation strategy, three different case studies are conducted using the PSCAD/EMTDC simulation tool. The results demonstrate that the optimal strategy enhances the frequency support contribution from PMSG wind turbines.
Comparison of three control strategies for optimization of spray dryer operation
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2017-01-01
controllers for operation of a four-stage spray dryer. The three controllers are a proportional-integral (PI) controller that is used in industrial practice for spray dryer operation, a linear model predictive controller with real-time optimization (MPC with RTO, MPC-RTO), and an economically optimizing...... nonlinear model predictive controller (E-NMPC). The MPC with RTO is based on the same linear state space model in the MPC and the RTO layer. The E-NMPC consists of a single optimization layer that uses a nonlinear system of ordinary differential equations for its predictions. The PI control strategy has...... the production rate, while minimizing the energy consumption, keeping the residual moisture content of the powder below a maximum limit, and avoiding that the powder sticks to the chamber walls. We use an industrially recorded disturbance scenario in order to produce realistic simulations and conclusions...
A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System
Directory of Open Access Journals (Sweden)
Aipeng Jiang
2014-01-01
Full Text Available In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.
International Nuclear Information System (INIS)
Gu, Wei; Lu, Shuai; Wu, Zhi; Zhang, Xuesong; Zhou, Jinhui; Zhao, Bo; Wang, Jun
2017-01-01
Highlights: •A bilateral transaction mode for the residential CCHP microgrid is proposed. •An energy pricing strategy for the residential CCHP system is proposed. •A novel integrated demand response for the residential loads is proposed. •Two-stage operation optimization model for the CCHP microgrid is proposed. •Operations of typical days and annual scale of the CCHP microgrid are studied. -- Abstract: As the global energy crisis, environmental pollution, and global warming grow in intensity, increasing attention is being paid to combined cooling, heating, and power (CCHP) systems that realize high-efficiency cascade utilization of energy. This paper proposes a bilateral transaction mechanism between a residential CCHP system and a load aggregator (LA). The variable energy cost of the CCHP system is analyzed, based on which an energy pricing strategy for the CCHP system is proposed. Under this pricing strategy, the electricity price is constant, while the heat/cool price is ladder-shaped and dependent on the relationship between the electrical, heat, and cool loads. For the LA, an integrated demand response program is proposed that combines electricity-load shifting and a flexible heating/cooling supply, in which a thermodynamic model of buildings is used to determine the appropriate range of heating/cooling supply. Subsequently, a two-stage optimal dispatch model is proposed for the energy system that comprises the CCHP system and the LA. Case studies consisting of three scenarios (winter, summer, and excessive seasons) are delivered to demonstrate the effectiveness of the proposed approach, and the performance of the proposed pricing strategy is also evaluated by annual operation simulations.
Optimal strategies for real-time sparse actuator compensation in RFX-mod MHD control operations
Energy Technology Data Exchange (ETDEWEB)
Pigatto, L., E-mail: leonardo.pigatto@igi.cnr.it [Consorzio RFX, Corso Stati Uniti 4, 35127 Padova (Italy); University of Padova, Padova (Italy); Bettini, P. [Consorzio RFX, Corso Stati Uniti 4, 35127 Padova (Italy); University of Padova, Padova (Italy); Bolzonella, T.; Marchiori, G. [Consorzio RFX, Corso Stati Uniti 4, 35127 Padova (Italy); Villone, F. [CREATE, DIEI, Università di Cassino e del Lazio Meridionale, Cassino (Italy)
2015-10-15
Highlights: • Sparse missing actuator compensation is solved with a new real-time strategy. • Testing is carried out with a dynamical model to prove feasibility and limits. • Dedicated experiments have been run to validate simulated results. - Abstract: In many devices aiming at magnetic confinement of fusion relevant plasmas, feedback control of MHD instabilities by means of active coils is nowadays mandatory to ensure the robustness of high performance operational scenarios. Actuators involved in the control loop are often coupled in the sensor measurements and an optimal strategy for decoupling can be limited by the need of reducing as much as possible the cycle time of the control loop itself. It is also important to stress the fact that the problem is intrinsically 3D, involving different non-axisymmetric contributions. The baseline situation in RFX-mod is documented, where the identity matrix is chosen to represent the simplest case of mutual coupling matrix. The problem of missing or broken actuators is introduced and tackled with dedicated compensation strategies. A detailed description is given for a possible compensation concept which can be applied in real-time operation thanks to its implementation strategy, yielding very promising results in terms of local field reconstruction.
Operating cost reduction by optimization of I and C backfitting strategy
International Nuclear Information System (INIS)
Kraft, Heinz-U.
2002-01-01
Full text: The safe and economic operation of a nuclear power plant requires a large scope of automation systems to act properly in combination. The associated maintenance costs, necessary to test these systems periodically and to repair or to replace them partly or completely, are one important factor in the overall operating costs of a nuclear power plant. Reducing these costs by reducing the maintenance effort could decrease the availability of the power plant and by this way increase the operating costs significantly. The minimization of the overall operating costs requires a well-balanced maintenance strategy taking into account all these opposite influences. The replacement of an existing I and C system by a new one reduces the maintenance cost in the long term and increases the plant availability. However, it requires some investments in the short term. On the other hand the repair of an I and C system avoids investments, but it doesn't solve the aging problems. That means maintenance costs will increase in the long term and the plant availability could be decreased. An optimized maintenance strategy can be elaborated on a plant specific base taking into account the residual lifetime of the plant, the properties of the installed I and C systems as well as their influence on the plant availability. As a general result of such an optimization performed by FANP it has been found as a rule that the replacement of I and C systems becomes the most economic way the longer the expected lifetime is and the stronger the I and C system influences, the availability of the plant. (author)
Institute of Scientific and Technical Information of China (English)
Feng Zhao; Chenghui Zhang; Bo Sun
2016-01-01
This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2012-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2013-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
Parameter Optimization and Operating Strategy of a TEG System for Railway Vehicles
Heghmanns, A.; Wilbrecht, S.; Beitelschmidt, M.; Geradts, K.
2016-03-01
A thermoelectric generator (TEG) system demonstrator for diesel electric locomotives with the objective of reducing the mechanical load on the thermoelectric modules (TEM) is developed and constructed to validate a one-dimensional thermo-fluid flow simulation model. The model is in good agreement with the measurements and basis for the optimization of the TEG's geometry by a genetic multi objective algorithm. The best solution has a maximum power output of approx. 2.7 kW and does not exceed the maximum back pressure of the diesel engine nor the maximum TEM hot side temperature. To maximize the reduction of the fuel consumption, an operating strategy regarding the system power output for the TEG system is developed. Finally, the potential consumption reduction in passenger and freight traffic operating modes is estimated under realistic driving conditions by means of a power train and lateral dynamics model. The fuel savings are between 0.5% and 0.7%, depending on the driving style.
Wang, Yan; Huang, Song; Ji, Zhicheng
2017-07-01
This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.
VALORAGUA: A model for the optimal operating strategy of mixed hydrothermal generating systems
International Nuclear Information System (INIS)
1992-01-01
To provide assistance to its developing Member States in carrying out integrated power system expansion analysis, the International Atomic Energy Agency (IAEA) has developed the computer model called WASP (Wien Automatic System Planning Package). The WASP model has proven to be very useful for this purpose and is accepted worldwide as a sound tool for electricity planning. Notwithstanding its many advantages, certain shortcomings of the methodology have been noticed, in particular with regard to representation of hydroelectric power plants. In order to overcome these shortcomings, the IAEA decided to acquire the computer model called VALORAGUA, developed by the Electricidade de Portugal (EDP), for optimizing the operating strategy of a mixed hydro-thermal power system. This program, when used together with WASP, would allow economic optimization of hydro-thermal power systems with a large hydro component. The objective of the present document is to assist in the use of the VALORAGUA model and its auxiliary codes, as well as to clarify the interconnection between VALORAGUA and the WASP-III model. This report is organized into five main chapters. The first chapter serves as an introduction to all remaining chapters. Chapter 2 defines the input data needed for every component of the electric power system. Chapter 3 presents the output variables of the model within the standard output tables that can be produced by VALORAGUA. Chapter 4 describes in detail all the input data needed by each program. It also includes the list of computer input data corresponding to the example described in Chapter 5, which is used to illustrate the execution of the VALORAGUA modules. Description of how to prepare the hydro data for the WASP-III model from the results obtained with the VALORAGUA model is given in Appendix A. Some auxiliary programs of the VALORAGUA model system, developed by EDP to help the user with the input data preparation, are described in Appendix B. Refs, figs and
Optimal Offering and Operating Strategy for a Large Wind-Storage System as a Price Maker
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2017-01-01
Wind farms and energy storage systems are playing increasingly more important roles in power systems, which makes their offering non-negligible in some markets. From the perspective of wind farm-energy storage systems (WF-ESS), this paper proposes an integrated strategy of day-ahead offering...... and real-time operation policies to maximize their overall profit. As participants with large capacity in electricity markets can influence cleared prices by strategic offering, a large scaled WFESS is assumed to be a price maker in day-ahead markets. Correspondingly, the strategy considers influence...
Directory of Open Access Journals (Sweden)
Fei Wang
2017-11-01
Full Text Available The optimal dispatching model for a stand-alone microgrid (MG is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL and multi-distributed generations (DGs. The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend and weather categories (sunny or rainy to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation.
Optimal GENCO bidding strategy
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
Directory of Open Access Journals (Sweden)
Jian Chen
2018-02-01
Full Text Available In this paper, a hierarchical optimal operation strategy for a hybrid energy storage system (HESS is proposed, which is suitable to be utilized in distribution networks (DNs with high photovoltaic (PV penetration to achieve PV power smoothing, voltage regulation and price arbitrage. Firstly, a fuzzy-logic based variable step-size control strategy for an ultracapacitor (UC with the improvement of the lifetime of UC and tracking performance is adopted to smooth PV power fluctuations. The impact of PV forecasting errors is eliminated by adjusting the UC power in real time. Secondly, a coordinated control strategy, which includes centralized and local controls, is proposed for lithium-ion batteries. The centralized control is structured to determine the optimal battery unit for voltage regulation or price arbitrage according to lithium-ion battery performance indices. A modified lithium-ion battery aging model with better accuracy is proposed and the coupling relationship between the lifetime and the effective capacity is also considered. Additionally, the local control of the selected lithium-ion battery unit determines the charging/discharging power. A case study is used to validate the operation strategy and the results show that the lifetime equilibrium among different lithium-ion battery units can be achieved using the proposed strategy.
Wu, Dongjun
Network industries have technologies characterized by a spatial hierarchy, the "network," with capital-intensive interconnections and time-dependent, capacity-limited flows of products and services through the network to customers. This dissertation studies service pricing, investment and business operating strategies for the electric power network. First-best solutions for a variety of pricing and investment problems have been studied. The evaluation of genetic algorithms (GA, which are methods based on the idea of natural evolution) as a primary means of solving complicated network problems, both w.r.t. pricing: as well as w.r.t. investment and other operating decisions, has been conducted. New constraint-handling techniques in GAs have been studied and tested. The actual application of such constraint-handling techniques in solving practical non-linear optimization problems has been tested on several complex network design problems with encouraging initial results. Genetic algorithms provide solutions that are feasible and close to optimal when the optimal solution is know; in some instances, the near-optimal solutions for small problems by the proposed GA approach can only be tested by pushing the limits of currently available non-linear optimization software. The performance is far better than several commercially available GA programs, which are generally inadequate in solving any of the problems studied in this dissertation, primarily because of their poor handling of constraints. Genetic algorithms, if carefully designed, seem very promising in solving difficult problems which are intractable by traditional analytic methods.
Directory of Open Access Journals (Sweden)
Xing Liu
2014-12-01
Full Text Available Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.
Directory of Open Access Journals (Sweden)
Tinggui Chen
2014-01-01
Full Text Available Artificial bee colony (ABC algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA, artificial colony optimization (ACO, and particle swarm optimization (PSO. However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.
2012-03-01
"With skip-stop rail transit operation, transit agencies can reduce their operating costs and fleet size, : and passengers can experience reduced in-transit travel times without extra track and technological : improvement. However, since skip-stop op...
Directory of Open Access Journals (Sweden)
Jianjun Hu
2018-03-01
Full Text Available The strict operational condition of driving motors for vehicles propels the development of more complicated configurations in pure electric vehicles (PEVs. Multi-power-source powertrain configurations are one of the efficient technologies to reduce the manufacturing difficulty of driving motors. However, most of the existing studies are predominantly focused on optimal designs of powertrains and power distribution between the engine and motor of hybrid electric vehicles, which are not appropriate for PEVs. This paper proposes a novel dual-motor coupling-propulsion powertrain system that improves the dynamic and economic performance of the powertrain system in PEVs. The proposed powertrain system can realize both the single-motor driving mode and dual-motor coupling driving mode. The driving modes are divided and a power distribution strategy for the different driving modes based on an optimal system efficiency rule is employed, which enhances the performance of the proposed system. Further, a mode-switching strategy that ensures driving comfort by preventing jerk during mode switching is incorporated into the system. The results of comparative evaluations that were conducted using a dual-motor electric vehicle model implemented in MATLAB/Simulink, indicate that the mileage and dynamic performance of the proposed powertrain system are significantly better than those of the traditional single-motor powertrain system.
Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di
2018-01-01
To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.
Strategy for optimal operation of a biomass-fired cogeneration power plant
International Nuclear Information System (INIS)
Prasertsan, S.; Krukanont, P.; Nigamsritragul, P.; Kirirat, P.
2001-01-01
Biomass-fired cogeneration not only is an environmentally friendly energy production, but also possesses high energy conversion efficiency. Generally, the wood product industry requires both heat and electricity. Combined heat and power generation (cogeneration) using wood residue has a three-fold benefit: waste minimization, reduction of an energy-related production cost and additional income from selling the excess electricity to the utility. In reality, the process heat demand fluctuates according to the production activities in the factory. The fluctuation of process heat demand affects the cogeneration efficiency and the electricity output and, consequently, the financial return, since the prices of heat and electricity are different. A study by computer simulation to establish a guideline for optimum operation of a process heat fluctuating cogeneration power plant is presented. The power plant was designed for a sawmill and an adjacent plywood factory using wood wastes from these two processes. The maximum boiler thermal load is 81.9 MW while the electricity output is in the range 19-24 MW and the process heat 10-30 MW. Two modes of operation were studied, namely the full (boiler) load and the partial (boiler) load. In the full load operation, the power plant is operated at a maximum boiler thermal load, while the extracted steam is varied to meet the steam demand of the wood-drying kilns and the plywood production. The partial load operation was designed for the partially fuelled boiler to provide sufficient steam for the process and to generate electricity at a desired capacity ranging from the firmed contract of 19 MW to the turbine maximum capacity of 24 MW. It was found that the steam for process heat has an allowable extracting range, which is limited by the low pressure feed water heater. The optimum operation for both full and partial load occurs at the lower limit of the extracting steam. A guideline for optimum operation at various combinations of
Directory of Open Access Journals (Sweden)
Xumei Chen
2017-09-01
Full Text Available The idea of corporate social responsibility has promoted bus operation agencies to rethink how to provide not only efficient but also environmentally friendly services for residents. A study on the potential of using an optimized design of skip-stop services, one of the essential operational strategies in practice, to reduce emissions is conducted in this paper. The underlying scheduling problem is formulated as a nonlinear programming problem with the primary objective of optimizing the total costs for both passengers and operating agencies, as well as with the secondary objective of minimizing bus emissions. A solution method is developed to solve the problem. A real-world case of Route 16 in Beijing is studied, in which the optimal scheduling strategy that maximizes the cost savings and environmental benefits is determined. The costs and emissions of the proposed scheduling strategy are compared with the optimal scheduling with skip-stop services without considering bus emissions. The results show that the proposed scheduling strategy outperforms the other operating strategy with respect to operational costs and bus emissions. A sensitivity study is then conducted to investigate the impact of the fleet size in operations and passenger demand on the effectiveness of the proposed stop-skipping strategy considering bus emissions.
Optimal intermittent search strategies
International Nuclear Information System (INIS)
Rojo, F; Budde, C E; Wio, H S
2009-01-01
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion
Optimal fuel inventory strategies
International Nuclear Information System (INIS)
Caspary, P.J.; Hollibaugh, J.B.; Licklider, P.L.; Patel, K.P.
1990-01-01
In an effort to maintain their competitive edge, most utilities are reevaluating many of their conventional practices and policies in an effort to further minimize customer revenue requirements without sacrificing system reliability. Over the past several years, Illinois Power has been rethinking its traditional fuel inventory strategies, recognizing that coal supplies are competitive and plentiful and that carrying charges on inventory are expensive. To help the Company achieve one of its strategic corporate goals, an optimal fuel inventory study was performed for its five major coal-fired generating stations. The purpose of this paper is to briefly describe Illinois Power's system and past practices concerning coal inventories, highlight the analytical process behind the optimal fuel inventory study, and discuss some of the recent experiences affecting coal deliveries and economic dispatch
Optimal intermittent search strategies
Energy Technology Data Exchange (ETDEWEB)
Rojo, F; Budde, C E [FaMAF, Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina); Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC E-39005 Santander (Spain)
2009-03-27
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion.
Operations Strategy in practice
DEFF Research Database (Denmark)
Rytter, Niels Gorm; Koch, Christian; Boer, Harry
2005-01-01
In this paper, we describe and illustrate a new, action-based longitudinal case study approach, which aims at helping scholars narrow the gap between the theory and practice of Operations Strategy (OS). First, we elaborate on the need for new research methods for studying OS in practice. Then, we...... and disadvantages of the method. Finally, we draw conclusions on its potential for operations strategy and operations management studies.......In this paper, we describe and illustrate a new, action-based longitudinal case study approach, which aims at helping scholars narrow the gap between the theory and practice of Operations Strategy (OS). First, we elaborate on the need for new research methods for studying OS in practice. Then, we...
International Nuclear Information System (INIS)
Chen, C.Y.; Shih, L.H.
1992-01-01
Recently, the main power company in Taiwan has shifted the primary energy resource from oil to coal and tried to diversify the coal supply from various sources. The company wants to have the imported coal meet the environmental standards and operation requirements as well as to have high heating value. In order to achieve these objectives, establishment of a coal blending system for Taiwan is necessary. A mathematical model using mixed integer programming technique is used to model the import strategy and the blending system. 6 refs., 1 tab
Resilient Grid Operational Strategies
Energy Technology Data Exchange (ETDEWEB)
Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-01
Extreme weather-related disturbances, such as hurricanes, are a leading cause of grid outages historically. Although physical asset hardening is perhaps the most common way to mitigate the impacts of severe weather, operational strategies may be deployed to limit the extent of societal and economic losses associated with weather-related physical damage.1 The purpose of this study is to examine bulk power-system operational strategies that can be deployed to mitigate the impact of severe weather disruptions caused by hurricanes, thereby increasing grid resilience to maintain continuity of critical infrastructure during extreme weather. To estimate the impacts of resilient grid operational strategies, Los Alamos National Laboratory (LANL) developed a framework for hurricane probabilistic risk analysis (PRA). The probabilistic nature of this framework allows us to estimate the probability distribution of likely impacts, as opposed to the worst-case impacts. The project scope does not include strategies that are not operations related, such as transmission system hardening (e.g., undergrounding, transmission tower reinforcement and substation flood protection) and solutions in the distribution network.
International Nuclear Information System (INIS)
Zhang, Lin; Jiang, Jianhua; Cheng, Huan; Deng, Zhonghua; Li, Xi
2015-01-01
Highlights: • Efficiency optimization associated with simultaneous power and thermal management. • Fast load tracing, fuel starvation, high efficiency and operating safety are considered. • Open loop pre-conditioning current strategy is proposed for load step-up transients. • Feedback control scheme is proposed for load step-up transients. - Abstract: The slow power tracking, operating safety, especially the fuel exhaustion, and high efficiency considerations are the key issues for integrated solid oxide fuel cell (SOFC) systems during power step up transients, resulting in the relatively poor dynamic capabilities and make the transient load following very challenging and must be enhanced. To this end, this paper first focus on addressing the efficiency optimization associated with simultaneous power and thermal management of a 5-kW SOFC system. Particularly, a traverse optimization process including cubic convolution interpolation algorithm are proposed to obtain optimal operating points (OOPs) with the maximum efficiency. Then this paper investigate the current implications on system step-up transient performance, then a two stage pre-conditioning current strategy and a feedback power reference control scheme is proposed for load step-up transients to balance fast load following and fuel starvation, after that safe thermal transient is validated. Simulation results show the efficacy of the control design by demonstrating the fast load following ability while maintaining the safe operation, thus safe; efficient and fast load transition can be achieved
Yu Wei; Matthew P. Thompson; Jessica R. Haas; Gregory K. Dillon; Christopher D. O’Connor
2018-01-01
This study introduces a large fire containment strategy that builds upon recent advances in spatial fire planning, notably the concept of potential wildland fire operation delineations (PODs). Multiple PODs can be clustered together to form a âboxâ that is referred as the âresponse PODâ (or rPOD). Fire lines would be built along the boundary of an rPOD to contain a...
International Nuclear Information System (INIS)
Longhi, Antonio Eduardo Bier; Pessoa, Artur Alves; Garcia, Pauli Adriano de Almada
2015-01-01
Since low-demand safety instrumented systems (SISs) do not operate continuously, their failures are often only detected when the system is demanded or tested. The conduction of tests, besides adding costs, can raise risks of failure on demand during their execution and also increase the frequency of spurious activation. Additionally, it is often necessary to interrupt production to carry out tests. In light of this scenario, this paper presents a model to optimize strategies for operation and testing of these systems, applying modeling by fault trees associated with optimization by a genetic algorithm. Its main differences are: (i) ability to represent four modes of operation and test them for each SIS subsystem; (ii) ability to represent a SIS that executes more than one safety instrumented function; (iii) ability to keep track of the down-time generated in the production system; and (iv) alteration of a genetic selection mechanism that permits identification of more efficient solutions with smaller influence on the optimization parameters. These aspects are presented by applying this model in three case studies. The results obtained show the applicability of the proposed approach and its potential to help make more informed decisions. - Highlights: • Models the integrity and cost related to operation and testing of low-demand SISs. • Keeps track of the production down-time generated by SIS tests and repairs. • Allows multiobjective optimization to identify operation and testing strategies. • Enables integrated assessment of an SIS that executes more than one SIF. • Allows altering the selection mechanism to identify the most efficient strategies
Determining an optimal supply chain strategy
Directory of Open Access Journals (Sweden)
Intaher M. Ambe
2012-11-01
Full Text Available In today’s business environment, many companies want to become efficient and flexible, but have struggled, in part, because they have not been able to formulate optimal supply chain strategies. Often this is as a result of insufficient knowledge about the costs involved in maintaining supply chains and the impact of the supply chain on their operations. Hence, these companies find it difficult to manufacture at a competitive cost and respond quickly and reliably to market demand. Mismatched strategies are the root cause of the problems that plague supply chains, and supply-chain strategies based on a one-size-fits-all strategy often fail. The purpose of this article is to suggest instruments to determine an optimal supply chain strategy. This article, which is conceptual in nature, provides a review of current supply chain strategies and suggests a framework for determining an optimal strategy.
Implementing optimal thinning strategies
Kurt H. Riitters; J. Douglas Brodie
1984-01-01
Optimal thinning regimes for achieving several management objectives were derived from two stand-growth simulators by dynamic programming. Residual mean tree volumes were then plotted against stand density management diagrams. The results supported the use of density management diagrams for comparing, checking, and implementing the results of optimization analyses....
Conceptualizing operations strategy processes
DEFF Research Database (Denmark)
Rytter, Niels Gorm; Boer, Harry; Koch, Christian
2007-01-01
Purpose - The purpose of this paper is to present insights into operations strategy (OS) in practice. It outlines a conceptualization and model of OS processes and, based on findings from an in-depth and longitudinal case study, contributes to further development of extant OS models and methods......; taking place in five dimensions of change - technical-rational, cultural, political, project management, and facilitation; and typically unfolding as a sequential and parallel, ordered and disordered, planned and emergent as well as top-down and bottom-up process. The proposed OS conceptualization...
Energy Technology Data Exchange (ETDEWEB)
Nasr, T. N.; Golbeck, H.; Korpany, G.; Pierce, G. [Alberta Research Council, Edmonton, AB (Canada)
1998-12-31
Steam-assisted gravity drainage (SAGD) has become one of the most effective means of recovering oil from oil sands deposits that are too deeply buried for surface mining. In general terms, the process involves drilling paired horizontal wells, one well above the other, and separated by a distance, near the bottom of the oil-bearing formation. The top well is used to inject the steam, heating up the oil and allowing it to drain under the action of gravity, into the bottom well. This paper reviews advances in SAGD operating strategies, based on work at the Underground Test Facility (UTF) in Alberta. Problems that continue to challenge researchers and operators, and concepts to overcome these challenges are discussed in terms of laboratory studies at UTF, designed to improve SAGD oil-to-steam ratios and to reduce water requirements for the process. 8 refs., 20 figs.
Optimizing decommissioning strategies
International Nuclear Information System (INIS)
Passant, F.H.
1993-01-01
Many different approaches can be considered for achieving satisfactory decommissioning of nuclear installations. These can embrace several different engineering actions at several stages, with time variations between the stages. Multi-attribute analysis can be used to help in the decision making process and to establish the optimum strategy. It has been used in the Usa and the UK to help in selecting preferred sites for radioactive waste repositories, and also in UK to help with the choice of preferred sites for locating PWR stations, and in selecting optimum decommissioning strategies
Burhan, Muhammad; Shahzad, Muhammad Wakil; Ng, Kim Choon
2017-01-01
Despite highest energy potential, solar energy is only available during diurnal period with varying intensity. Therefore, owing to solar intermittency, solar energy systems need to operate in standalone configuration for steady power supply which requires reliable and sustainable energy storage. Hydrogen production has proved to be the most reliable and sustainable energy storage option for medium and long term operation. However, at the first priority, solar energy must be captured with high efficiency, in order to reduce the overall size of the system and energy storage. Multi-junction solar cells (MJCs) provide highest energy efficiency among all of the photovoltaic technologies and the concentrated photovoltaic (CPV) system concept makes their use cost effective. However, literature is lacking the performance model and optimization strategy for standalone operation of the CPV-hydrogen system. In addition, there is no commercial tool available that can analyze CPV performance, utilizing multi-junction solar cell. This paper proposes the performance model for the CPV-hydrogen systems and the multi-objective optimization strategy for its standalone operation and techno-economic analysis, using micro genetic algorithm (micro-GA). The electrolytic hydrogen production with compression storage and fuel cell, is used as energy storage system. The CPV model is verified for the experimental data of InGaP/InGaAs/Ge triple junction solar cell. An optimal CPV system design is provided for uninterrupted power supply, even under seasonal weather variations. Such approach can be easily integrated with commercial tools and the presented performance data can be used for the design of individual components of the system.
Burhan, Muhammad
2017-09-16
Despite highest energy potential, solar energy is only available during diurnal period with varying intensity. Therefore, owing to solar intermittency, solar energy systems need to operate in standalone configuration for steady power supply which requires reliable and sustainable energy storage. Hydrogen production has proved to be the most reliable and sustainable energy storage option for medium and long term operation. However, at the first priority, solar energy must be captured with high efficiency, in order to reduce the overall size of the system and energy storage. Multi-junction solar cells (MJCs) provide highest energy efficiency among all of the photovoltaic technologies and the concentrated photovoltaic (CPV) system concept makes their use cost effective. However, literature is lacking the performance model and optimization strategy for standalone operation of the CPV-hydrogen system. In addition, there is no commercial tool available that can analyze CPV performance, utilizing multi-junction solar cell. This paper proposes the performance model for the CPV-hydrogen systems and the multi-objective optimization strategy for its standalone operation and techno-economic analysis, using micro genetic algorithm (micro-GA). The electrolytic hydrogen production with compression storage and fuel cell, is used as energy storage system. The CPV model is verified for the experimental data of InGaP/InGaAs/Ge triple junction solar cell. An optimal CPV system design is provided for uninterrupted power supply, even under seasonal weather variations. Such approach can be easily integrated with commercial tools and the presented performance data can be used for the design of individual components of the system.
International Nuclear Information System (INIS)
Benajes, Jesús; García, Antonio; Monsalve-Serrano, Javier; Boronat, Vicente
2017-01-01
Highlights: • Optimized dual-fuel strategy to cover the whole engine load-speed map. • EURO VI NOx levels up to 14 bar IMEP with fully and highly premixed RCCI strategies. • Dual-fuel provides up to 7% higher efficiency than CDC if urea consumption is considered. - Abstract: This experimental work investigates the capabilities of the reactivity controlled compression ignition combustion concept to be operated in the whole engine map and discusses its benefits when compared to conventional diesel combustion. The experiments were conducted using a single-cylinder medium-duty diesel engine fueled with regular gasoline and diesel fuels. The main modification on the stock engine architecture was the addition of a port fuel injector in the intake manifold. In addition, with the aim of extending the reactivity controlled compression ignition operating range towards higher loads, the piston bowl volume was increased to reduce the compression ratio of the engine from 17.5:1 (stock) down to 15.3:1. To allow the dual-fuel operation over the whole engine map without exceeding the mechanical limitations of the engine, an optimized dual-fuel combustion strategy is proposed in this research. The combustion strategy changes as the engine load increases, starting from a fully premixed reactivity controlled compression ignition combustion up to around 8 bar IMEP, then switching to a highly premixed reactivity controlled compression ignition combustion up to 15 bar IMEP, and finally moving to a mainly diffusive dual-fuel combustion to reach the full load operation. The engine mapping results obtained using this combustion strategy show that reactivity controlled compression ignition combustion allows fulfilling the EURO VI NOx limit up to 14 bar IMEP. Ultra-low soot emissions are also achieved when the fully premixed combustion is promoted, however, the soot levels rise notably as the combustion strategy moves to a less premixed pattern. Finally, the direct comparison of
Operations Strategy with Paper Boats
Sumukadas, Narendar
2010-01-01
When participants in introductory business courses encounter the term "operations strategy," it is not easy for them to appreciate what operations strategy is about, or how it fits with overall business strategy. This game breaks down highfalutin jargon into experiences that participants can readily relate to. While working in teams to make paper…
Park, Chan B; Suri, Rakesh M; Burkhart, Harold M; Greason, Kevin L; Dearani, Joseph A; Schaff, Hartzell V; Sundt, Thoralf M
2011-06-01
The optimal myocardial preservation strategy at re-operation for aortic valve replacement (AVR) after prior coronary artery bypass grafting (CABG) in the presence of a patent internal thoracic artery (ITA) remains undefined. Patients undergoing AVR after prior CABG at our institution between 1 January 1996 and 31 December 2007 were identified; operative notes and outcomes were reviewed. Of 628 patients with prior CABG undergoing AVR with or without concomitant procedures, 427 patients had a patent ITA. In 390, management of the ITA was detailed in the operative note, including 251 in whom it was clamped and 139 in whom it was left uncontrolled. Groups were demographically similar, although re-operative CABG was more frequent in the clamped group (42% vs 23%, poptimal perfusion temperature when the ITA was left uncontrolled. Efforts to control the patent ITA at re-operation for AVR after prior CABG increase risk of injury and may actually increase operative mortality rate compared with leaving this critical graft open and perfusing the heart. Copyright © 2010 European Association for Cardio-Thoracic Surgery. All rights reserved.
Optimization of power system operation
Zhu, Jizhong
2015-01-01
This book applies the latest applications of new technologies topower system operation and analysis, including new and importantareas that are not covered in the previous edition. Optimization of Power System Operation covers both traditional andmodern technologies, including power flow analysis, steady-statesecurity region analysis, security constrained economic dispatch,multi-area system economic dispatch, unit commitment, optimal powerflow, smart grid operation, optimal load shed, optimalreconfiguration of distribution network, power system uncertaintyanalysis, power system sensitivity analysis, analytic hierarchicalprocess, neural network, fuzzy theory, genetic algorithm,evolutionary programming, and particle swarm optimization, amongothers. New topics such as the wheeling model, multi-areawheeling, the total transfer capability computation in multipleareas, are also addressed. The new edition of this book continues to provide engineers andac demics with a complete picture of the optimization of techn...
Switching strategies to optimize search
International Nuclear Information System (INIS)
Shlesinger, Michael F
2016-01-01
Search strategies are explored when the search time is fixed, success is probabilistic and the estimate for success can diminish with time if there is not a successful result. Under the time constraint the problem is to find the optimal time to switch a search strategy or search location. Several variables are taken into account, including cost, gain, rate of success if a target is present and the probability that a target is present. (paper: interdisciplinary statistical mechanics)
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonia...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
DEFF Research Database (Denmark)
Zheng, Yingying; Jenkins, Bryan M.; Kornbluth, Kurt
2018-01-01
An economic linear programming model with a sliding time window was developed to assess designing and scheduling a biomass-fueled combined heat and power system consisting of biomass gasifier, internal combustion engine, heat recovery set, heat-only boiler, producer gas storage and thermal energy......, utility tariff structure and technical and finical performance of the system components. Engine partial load performance was taken into consideration. Sensitivity analyses demonstrate how the optimal BCHP configuration changes with varying demands and utility tariff rates....
Energy Technology Data Exchange (ETDEWEB)
Harold, Michael [Univ. of Houston, TX (United States); Crocker, Mark [Univ. of Kentucky, Lexington, KY (United States); Balakotaiah, Vemuri [Univ. of Houston, TX (United States); Luss, Dan [Univ. of Houston, TX (United States); Choi, Jae-Soon [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Dearth, Mark [Ford Motor Company, Dearborn, MI (United States); McCabe, Bob [Ford Motor Company, Dearborn, MI (United States); Theis, Joe [Ford Motor Company, Dearborn, MI (United States)
2013-09-30
Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO_{2}) commonly referred to as NO_{x}, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NO_{x}} is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NO_{x} in the presence of excess O_{2}. Catalytic abatement measures that are effective for gasoline-fueled engines such as the precious metal containing three-way catalytic converter (TWC) cannot be used to treat O_{2}-laden exhaust containing NO_{x}. Two catalytic technologies that have emerged as effective for NO_{x} abatement are NO_{x} storage and reduction (NSR) and selective catalytic reduction (SCR). NSR is similar to TWC but requires much larger quantities of expensive precious metals and sophisticated periodic switching operation, while SCR requires an on-board source of ammonia which serves as the chemical reductant of the NO_{x}. The fact that NSR produces ammonia as a byproduct while SCR requires ammonia to work has led to interest in combining the two together to avoid the need for the cumbersome ammonia generation system. In this project a comprehensive study was carried out of the fundamental aspects and application feasibility of combined NSR/SCR. The project team, which included university, industry, and national lab researchers, investigated the kinetics and mechanistic features of the underlying chemistry in the lean NOx trap (LNT) wherein NSR was carried out, with particular focus on identifying the operating conditions such as temperature and catalytic properties which lead to the production of ammonia in the LNT. The performance features of SCR on both model and commercial catalysts focused on the synergy between the LNT and SCR converters in terms of utilizing the upstream-generated ammonia and
International Nuclear Information System (INIS)
Mascarenhas, Darren; Moleiro, Edgar; Bancelin, Estelle; Bretelle, Jean-Luc
2014-01-01
Pleated fibreglass media filter cartridges are used throughout the auxiliary systems at nuclear power plants across the 58 reactors of EDF fleet. The main role of these filters is to remove suspended solids from coolant to prevent them accumulating in circuits or in equipments. In the primary circuit, these filters therefore limit the deposition of solids that are active or could become active if allowed to recirculate throughout the primary circuit, avoiding potential consequences such as an increase in dose rates, axial offset anomalies, demineralisers fouling, higher pressure losses in primary loop, and clogging of the primary pumps. Since 2008, a steady increase in the consumption of filters has been noticed, and therefore an increase in the amount of solid waste to treat. Preliminary studies have identified the primary circuit high-flow filters of the 1300/1450 MWe reactors as the main source of this increase. Not only has this stretched of solid waste containers production to the limit, as well as strained site resources and increased risks of operational errors during periods of frequent filter changes; it has also suggested that there is an underlying problem that could pose a serious risk to the primary circuit if untreated. Further studies have been carried out to identify more precisely the impact of possible causes, including increased quality surveillance of the filters, correlation of consumption data with the concentrations of various conditioning products and typical pollutants, and an impact analysis of events such as steam generator replacements or new practices like zinc injection. Work has been done with the filter manufacturer to improve their service lifetime and a simulation tool has been developed in order to understand and optimise filtration. We are also working with sites on creating good practices and avoiding bad ones. These actions should reduce the consumption in the short term while still assuring a high quality of filtration and
Quantum Strategies and Local Operations
Gutoski, Gus
2010-02-01
This thesis is divided into two parts. In Part I we introduce a new formalism for quantum strategies, which specify the actions of one party in any multi-party interaction involving the exchange of multiple quantum messages among the parties. This formalism associates with each strategy a single positive semidefinite operator acting only upon the tensor product of the input and output message spaces for the strategy. We establish three fundamental properties of this new representation for quantum strategies and we list several applications, including a quantum version of von Neumann's celebrated 1928 Min-Max Theorem for zero-sum games and an efficient algorithm for computing the value of such a game. In Part II we establish several properties of a class of quantum operations that can be implemented locally with shared quantum entanglement or classical randomness. In particular, we establish the existence of a ball of local operations with shared randomness lying within the space spanned by the no-signaling operations and centred at the completely noisy channel. The existence of this ball is employed to prove that the weak membership problem for local operations with shared entanglement is strongly NP-hard. We also provide characterizations of local operations in terms of linear functionals that are positive and "completely" positive on a certain cone of Hermitian operators, under a natural notion of complete positivity appropriate to that cone. We end the thesis with a discussion of the properties of no-signaling quantum operations.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Schroedinger operators and evolutionary strategies
International Nuclear Information System (INIS)
Asselmeyer, T.
1997-01-01
First we introduce a simple model for the description of evolutionary algorithms, which is based on 2nd order partial differential equations for the distribution function of the individuals. Then we turn to the properties of Boltzmann's and Darwin's strategy. the next chapter is dedicated to the mathematical properties of Schroedinger operators. Both statements on the spectral density and their reproducibility during the simulation are summarized. The remaining of this chapter are dedicated to the analysis of the kernel as well as the dependence of the Schroedinger operator on the potential. As conclusion from the results of this chapter we obtain the classification of the strategies in dependence of the fitness. We obtain the classification of the evolutionary strategies, which are described by a 2nd order partial differential equation, in relation to their solution behaviour. Thereafter we are employed with the variation of the mutation distribution
Evolution strategies for robust optimization
Kruisselbrink, Johannes Willem
2012-01-01
Real-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for, optimization may fail or may yield solutions that are optimal in the classical strict notion of optimality, but
Rodrigo, Deepal
2007-12-01
This dissertation introduces a novel approach for optimally operating a day-ahead electricity market not only by economically dispatching the generation resources but also by minimizing the influences of market manipulation attempts by the individual generator-owning companies while ensuring that the power system constraints are not violated. Since economic operation of the market conflicts with the individual profit maximization tactics such as market manipulation by generator-owning companies, a methodology that is capable of simultaneously optimizing these two competing objectives has to be selected. Although numerous previous studies have been undertaken on the economic operation of day-ahead markets and other independent studies have been conducted on the mitigation of market power, the operation of a day-ahead electricity market considering these two conflicting objectives simultaneously has not been undertaken previously. These facts provided the incentive and the novelty for this study. A literature survey revealed that many of the traditional solution algorithms convert multi-objective functions into either a single-objective function using weighting schemas or undertake optimization of one function at a time. Hence, these approaches do not truly optimize the multi-objectives concurrently. Due to these inherent deficiencies of the traditional algorithms, the use of alternative non-traditional solution algorithms for such problems has become popular and widely used. Of these, multi-objective evolutionary algorithms (MOEA) have received wide acceptance due to their solution quality and robustness. In the present research, three distinct algorithms were considered: a non-dominated sorting genetic algorithm II (NSGA II), a multi-objective tabu search algorithm (MOTS) and a hybrid of multi-objective tabu search and genetic algorithm (MOTS/GA). The accuracy and quality of the results from these algorithms for applications similar to the problem investigated here
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Optimization strategies in complex systems
Bussolari, L.; Contucci, P.; Giardinà, C.; Giberti, C.; Unguendoli, F.; Vernia, C.
2003-01-01
We consider a class of combinatorial optimization problems that emerge in a variety of domains among which: condensed matter physics, theory of financial risks, error correcting codes in information transmissions, molecular and protein conformation, image restoration. We show the performances of two
Optimal Advance Selling Strategy under Price Commitment
Chenhang Zeng
2012-01-01
This paper considers a two-period model with experienced consumers and inexperienced consumers. The retailer determines both advance selling price and regular selling price at the beginning of the first period. I show that advance selling weekly dominates no advance selling, and the optimal advance selling price may be at a discount, at a premium or at the regular selling price. To help the retailer choose the optimal pricing strategy, conditions for each possible advance selling strategy to ...
Following an Optimal Batch Bioreactor Operations Model
DEFF Research Database (Denmark)
Ibarra-Junquera, V.; Jørgensen, Sten Bay; Virgen-Ortíz, J.J.
2012-01-01
The problem of following an optimal batch operation model for a bioreactor in the presence of uncertainties is studied. The optimal batch bioreactor operation model (OBBOM) refers to the bioreactor trajectory for nominal cultivation to be optimal. A multiple-variable dynamic optimization of fed...... as the master system which includes the optimal cultivation trajectory for the feed flow rate and the substrate concentration. The “real” bioreactor, the one with unknown dynamics and perturbations, is considered as the slave system. Finally, the controller is designed such that the real bioreactor...
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
which are related to electrical system topology. This paper proposed an optimized power dispatch strategy (OPD) for minimizing the levelized production cost (LPC) of a wind farm. Particle swarm optimization (PSO) is employed to obtain final solution for the optimization problem. Both regular shape......Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...... and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy....
Asymptotic estimation of reactor fueling optimal strategy
International Nuclear Information System (INIS)
Simonov, V.D.
1985-01-01
The problem of improving the technical-economic factors of operating. and designed nuclear power plant blocks by developino. internal fuel cycle strategy (reactor fueling regime optimization), taking into account energy system structural peculiarities altogether, is considered. It is shown, that in search of asymptotic solutions of reactor fueling planning tasks the model of fuel energy potential (FEP) is the most ssuitable and effective. FEP represents energy which may be produced from the fuel in a reactor with real dimensions and power, but with hypothetical fresh fuel supply, regime, providing smilar burnup of all the fuel, passing through the reactor, and continuous overloading of infinitely small fuel portion under fule power, and infinitely rapid mixing of fuel in the reactor core volume. Reactor fuel run with such a standard fuel cycle may serve as FEP quantitative measure. Assessment results of optimal WWER-440 reactor fresh fuel supply periodicity are given as an example. The conclusion is drawn that with fuel enrichment x=3.3% the run which is 300 days, is economically justified, taking into account that the cost of one energy unit production is > 3 cop/KW/h
Tank Waste Remediation System optimized processing strategy
International Nuclear Information System (INIS)
Slaathaug, E.J.; Boldt, A.L.; Boomer, K.D.; Galbraith, J.D.; Leach, C.E.; Waldo, T.L.
1996-03-01
This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility
Optimal operation of batch membrane processes
Paulen, Radoslav
2016-01-01
This study concentrates on a general optimization of a particular class of membrane separation processes: those involving batch diafiltration. Existing practices are explained and operational improvements based on optimal control theory are suggested. The first part of the book introduces the theory of membrane processes, optimal control and dynamic optimization. Separation problems are defined and mathematical models of batch membrane processes derived. The control theory focuses on problems of dynamic optimization from a chemical-engineering point of view. Analytical and numerical methods that can be exploited to treat problems of optimal control for membrane processes are described. The second part of the text builds on this theoretical basis to establish solutions for membrane models of increasing complexity. Each chapter starts with a derivation of optimal operation and continues with case studies exemplifying various aspects of the control problems under consideration. The authors work their way from th...
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Operator assisted optimization of sludge dewatering
DEFF Research Database (Denmark)
Grüttner, Henrik
1991-01-01
by the operator. By graphical presentation and an advisory service these data are used to support the operator in his dewatering operations and to secure a running optimization of the sludge dewatering. Evaluations show that this system is a useful tool for data collection and presentation and that the data...
Optimal Pricing Strategy in Marketing Research Consulting.
Chang, Chun-Hao; Lee, Chi-Wen Jevons
1994-01-01
This paper studies the optimal pricing scheme for a monopolistic marketing research consultant who sells high-cost proprietary marketing information to her oligopolistic clients in the manufacturing industry. In designing an optimal pricing strategy, the consultant needs to fully consider the behavior of her clients, the behavior of the existing and potential competitors to her clients, and the behavior of her clients' customers. The authors show how the environment uncertainty, the capabilit...
Optimal Deterministic Investment Strategies for Insurers
Directory of Open Access Journals (Sweden)
Ulrich Rieder
2013-11-01
Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.
Optimization strategies for complex engineering applications
Energy Technology Data Exchange (ETDEWEB)
Eldred, M.S.
1998-02-01
LDRD research activities have focused on increasing the robustness and efficiency of optimization studies for computationally complex engineering problems. Engineering applications can be characterized by extreme computational expense, lack of gradient information, discrete parameters, non-converging simulations, and nonsmooth, multimodal, and discontinuous response variations. Guided by these challenges, the LDRD research activities have developed application-specific techniques, fundamental optimization algorithms, multilevel hybrid and sequential approximate optimization strategies, parallel processing approaches, and automatic differentiation and adjoint augmentation methods. This report surveys these activities and summarizes the key findings and recommendations.
Optimal mode of operation for biomass production
Betlem, Ben H.L.; Roffel, Brian; Mulder, P.
2002-01-01
The rate of biomass production is optimised for a predefined feed exhaustion using the residue ratio as a degree of freedom. Three modes of operation are considered: continuous, repeated batch, and repeated fed-batch operation. By means of the Production Curve, the transition points of the optimal
Service Operations Optimization: Recent Development in Supply Chain Management
Directory of Open Access Journals (Sweden)
Bin Shen
2015-01-01
Full Text Available Services are the key of success in operation management. Designing the effective strategies by optimization techniques is the fundamental and important condition for performance increase in service operations (SOs management. In this paper, we mainly focus on investigating SOs optimization in the areas of supply chain management, which create the greatest business values. Specifically, we study the recent development of SOs optimization associated with supply chain by categorizing them into four different industries (i.e., e-commerce industry, consumer service industry, public sector, and fashion industry and four various SOs features (i.e., advertising, channel coordination, pricing, and inventory. Moreover, we conduct the technical review on the stylish industries/topics and typical optimization models. The classical optimization approaches for SOs management in supply chain are presented. The managerial implications of SOs in supply chain are discussed.
Optimal control of operation efficiency of belt conveyor systems
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2010-01-01
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study.
Optimal control of operation efficiency of belt conveyor systems
Energy Technology Data Exchange (ETDEWEB)
Zhang, Shirong [Department of Automation, Wuhan University, Wuhan 430072 (China); Xia, Xiaohua [Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002 (South Africa)
2010-06-15
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study. (author)
Operational radiation protection: A guide to optimization
International Nuclear Information System (INIS)
1990-01-01
The purpose of this publication is to provide practical guidance on the application of the dose limitation system contained in the Basic Safety Standards for Radiation Protection to operational situations both in large nuclear installations and in much smaller facilities. It is anticipated that this Guide will be useful to both the management and radiation protection staff of operations in which there is a potential for occupational radiation exposures and to the competent authorities with responsibilities for providing a programme of regulatory control. Contents: Dose limitation system; Optimization and its practical application to operational radiation protection; Major elements of an effective operational radiation protection programme; Review of selected parts of the basic safety standards with special reference to operational radiation protection; Optimization of radiation protection; Techniques for the systematic appraisal of operational radiation protection programmes. Refs and figs
Institute of Scientific and Technical Information of China (English)
肖运启
2017-01-01
Nowadays,wind farm power control strategies are generally lack of concern on the wind turbine operation health condition,which easily result in economic loss due to equipment failure.Therefore,in order to improve wind turbine operation health condition,a novel wind farm power scheduling strategy is proposed.Firstly,a wind turbine operation health condition evaluation model and method is designed.Secondly,in order to improve wind turbine operation health condition,a multi-objective optimization model with the normal control objectives is established.Finally,the example results showed that the strategy proposed can achieve the power control and improve operating wind turbines health level efficiently,which has a good practical value to improve generation performance of the wind farm.%目前风电场运行调度策略中对机组设备状态关注不足,易发生由于设备故障造成的发电量损失.为此提出一种基于风电机群健康状态优化的风电场负荷分配控制策略.首先设计风电机组运行状态多层次评估模型及分析方法,然后以提高风电机群健康状态为优化目标,综合风电场常规控制要求建立多目标优化模型.通过算例验证该文策略在良好实现风电场功率控制的基础上,优选运行状况良好的机组承担发电任务,这对保证风电场限电运行下可靠出力具有良好作用.
Optimal operation of hybrid-SITs under a SBO accident
International Nuclear Information System (INIS)
Jeon, In Seop; Heo, Sun; Kang, Hyun Gook
2016-01-01
Highlights: • Operation strategy of hybrid-SIT (H-SIT) in station blackout (SBO) is developed. • There are five main factors which have to be carefully treated in the development of the operation strategy. • Optimal value of each main factor is investigated analytically and then through thermal-hydraulic analysis using computer code. • The optimum operation strategy is suggested based on the optimal value of the main factors. - Abstract: A hybrid safety injection tank (H-SIT) is designed to enhance the capability of pressurized water reactors against high-pressure accidents which might be caused by the combined accidents accompanied by station blackout (SBO), and is suggested as a useful alternative to electricity-driven motor injection pumps. The main purpose of the H-SIT is to provide coolant to the core so that core safety can be maintained for a longer period. As H-SITs have a limited inventory, their efficient use in cooling down the core is paramount to maximize the available time for long-term cooling component restoration. Therefore, an optimum operation strategy must be developed to support the operators for the most efficient H-SIT use. In this study, the main factors which have to be carefully treated in the development of an operation strategy are first identified. Then the optimal value of each main factor is investigated analytically, a process useful to get the basis of the global optimum points. Based on these analytical optimum points, a thermal-hydraulic analysis using MARS code is performed to get more accurate values and to verify the results of the analytical study. The available time for long-term cooling component restoration is also estimated. Finally, an integrated optimum operation strategy for H-SITs in SBO is suggested.
Strategy to maximize maintenance operation
Espinoza, Michael
2005-01-01
This project presents a strategic analysis to maximize maintenance operations in Alcan Kitimat Works in British Columbia. The project studies the role of maintenance in improving its overall maintenance performance. It provides strategic alternatives and specific recommendations addressing Kitimat Works key strategic issues and problems. A comprehensive industry and competitive analysis identifies the industry structure and its competitive forces. In the mature aluminium industry, the bargain...
Parallel strategy for optimal learning in perceptrons
International Nuclear Information System (INIS)
Neirotti, J P
2010-01-01
We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha-Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.
Optimal energy management strategy for battery powered electric vehicles
International Nuclear Information System (INIS)
Xi, Jiaqi; Li, Mian; Xu, Min
2014-01-01
Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios
The Optimal Nash Equilibrium Strategies Under Competition
Institute of Scientific and Technical Information of China (English)
孟力; 王崇喜; 汪定伟; 张爱玲
2004-01-01
This paper presented a game theoretic model to study the competition for a single investment oppertunity under uncertainty. It models the hazard rate of investment as a function of competitors' trigger level. Under uncertainty and different information structure, the option and game theory was applied to researching the optimal Nash equilibrium strategies of one or more firm. By means of Matlab software, the paper simulates a real estate developing project example and illustrates how parameter affects investment strategies. The paper's work will contribute to the present investment practice in China.
Optimized Strategies for Detecting Extrasolar Space Weather
Hallinan, Gregg
2018-06-01
Fully understanding the implications of space weather for the young solar system, as well as the wider population of planet-hosting stars, requires remote sensing of space weather in other stellar systems. Solar coronal mass ejections can be accompanied by bright radio bursts at low frequencies (typically measurement of the magnetic field strength of the planet, informing on whether the atmosphere of the planet can survive the intense magnetic activity of its host star. However, both stellar and planetary radio emission are highly variable and optimal strategies for detection of these emissions requires the capability to monitor 1000s of nearby stellar/planetary systems simultaneously. I will discuss optimized strategies for both ground and space-based experiments to take advantage of the highly variable nature of the radio emissions powered by extrasolar space weather to enable detection of stellar CMEs and planetary magnetospheres.
Control strategies for wind farm power optimization: LES study
Ciri, Umberto; Rotea, Mario; Leonardi, Stefano
2017-11-01
Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.
Optimization of Operations Resources via Discrete Event Simulation Modeling
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
Optimization of pocket machining strategy in HSM
Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher
2012-01-01
International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...
Optimal strategies for pricing general insurance
Emms, P.; Haberman, S.; Savoulli, I.
2006-01-01
Optimal premium pricing policies in a competitive insurance environment are investigated using approximation methods and simulation of sample paths. The market average premium is modelled as a diffusion process, with the premium as the control function and the maximization of the expected total utility of wealth, over a finite time horizon, as the objective. In order to simplify the optimisation problem, a linear utility function is considered and two particular premium strategies are adopted...
Optimizing refiner operation with statistical modelling
Energy Technology Data Exchange (ETDEWEB)
Broderick, G [Noranda Research Centre, Pointe Claire, PQ (Canada)
1997-02-01
The impact of refining conditions on the energy efficiency of the process and on the handsheet quality of a chemi-mechanical pulp was studied as part of a series of pilot scale refining trials. Statistical models of refiner performance were constructed from these results and non-linear optimization of process conditions were conducted. Optimization results indicated that increasing the ratio of specific energy applied in the first stage led to a reduction of some 15 per cent in the total energy requirement. The strategy can also be used to obtain significant increases in pulp quality for a given energy input. 20 refs., 6 tabs.
An optimal inspection strategy for randomly failing equipment
International Nuclear Information System (INIS)
Chelbi, Anis; Ait-Kadi, Daoud
1999-01-01
This paper addresses the problem of generating optimal inspection strategies for randomly failing equipment where imminent failure is not obvious and can only be detected through inspection. Inspections are carried out following a condition-based procedure. The equipment is replaced if it has failed or if it shows imminent signs of failure. The latter state is indicated by measuring certain predetermined control parameters during inspection. Costs are associated with inspection, idle time and preventive or corrective actions. An optimal inspection strategy is defined as the inspection sequence minimizing the expected total cost per time unit over an infinite span. A mathematical model and a numerical algorithm are developed to generate an optimal inspection sequence. As a practical example, the model is applied to provide a machine tool operator with a time sequence for inspecting the cutting tool. The tool life time distribution and the trend of one control parameter defining its actual condition are supposed to be known
Optimization of ejector design and operation
Directory of Open Access Journals (Sweden)
Kuzmenko Konstantin
2016-01-01
Full Text Available The investigation aims at optimization of gas ejector operation. The goal consists in the improvement of the inflator design so that to enable 50 liters of gas inflation within ~30 milliseconds. For that, an experimental facility was developed and fabricated together with the measurement system to study pressure patterns in the inflator path.
Optimization of the bank's operating portfolio
Borodachev, S. M.; Medvedev, M. A.
2016-06-01
The theory of efficient portfolios developed by Markowitz is used to optimize the structure of the types of financial operations of a bank (bank portfolio) in order to increase the profit and reduce the risk. The focus of this paper is to check the stability of the model to errors in the original data.
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
generator operating point in the P-Q plane. Four computer programs were developed to automatically perform the market auction simulations using the equal incremental cost rule. The software calculates the payoffs for the two competing competitors, dispatches six generators, and allocates ancillary services for 64 combinations of bidding strategies, three levels of system demand, and three different types of competitors. Matrix Game theory was utilized to calculate Nash Equilibrium solutions and mixed-strategy Nash solutions as the optimal generator bidding strategies. A method to incorporate ancillary services into the generation bidding strategy, to assure an adequate supply of ancillary services, and to allocate these necessary resources to the on-line units was devised. The optimal generator bid strategy in a power auction was shown to be the Nash Equilibrium solution found in two-player variable-sum matrix games.
Emergency strategy optimization for the environmental control system in manned spacecraft
Li, Guoxiang; Pang, Liping; Liu, Meng; Fang, Yufeng; Zhang, Helin
2018-02-01
It is very important for a manned environmental control system (ECS) to be able to reconfigure its operation strategy in emergency conditions. In this article, a multi-objective optimization is established to design the optimal emergency strategy for an ECS in an insufficient power supply condition. The maximum ECS lifetime and the minimum power consumption are chosen as the optimization objectives. Some adjustable key variables are chosen as the optimization variables, which finally represent the reconfigured emergency strategy. The non-dominated sorting genetic algorithm-II is adopted to solve this multi-objective optimization problem. Optimization processes are conducted at four different carbon dioxide partial pressure control levels. The study results show that the Pareto-optimal frontiers obtained from this multi-objective optimization can represent the relationship between the lifetime and the power consumption of the ECS. Hence, the preferred emergency operation strategy can be recommended for situations when there is suddenly insufficient power.
Nuclear Power Plant Outage Optimization Strategy. 2016 Edition
International Nuclear Information System (INIS)
2016-10-01
This publication is an update of IAEA-TECDOC-1315, Nuclear Power Plant Outage Optimisation Strategy, which was published in 2002, and aims to communicate good outage management practices in a manner that can be used by operators and utilities in Member States. Nuclear power plant outage management is a key factor for safe and economic nuclear power plant performance. This publication discusses plant outage strategy and how this strategy is actually implemented. The main areas that are important for outage optimization that were identified by the utilities and government organizations participating in this report are: 1) organization and management; 2) outage planning and preparation; 3) outage execution; 4) safety outage review; and 5) counter measures to avoid the extension of outages and to facilitate the work in forced outages. Good outage management practices cover many different areas of work and this publication aims to communicate these good practices in a way that they can be used effectively by operators and utilities
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-08-03
Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Directory of Open Access Journals (Sweden)
Fei Wang
2017-07-01
Full Text Available The optimized dispatch of different distributed generations (DGs in stand-alone microgrid (MG is of great significance to the operation’s reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL and combined cooling-heating-power (CCHP model of micro-gas turbine (MT, a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV, wind turbine (WT, fuel cell (FC, diesel engine (DE, MT and energy storage (ES. Four typical scenarios were designed according to different day types (work day or weekend and weather conditions (sunny or rainy in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers’ comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO to propose modified chaos particle swarm optimization (MCPSO whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.
Rule Optimization monthly reservoir operation Salvajina
International Nuclear Information System (INIS)
Sandoval Garcia, Maria Clemencia; Santacruz Salazar, Santiago; Ramirez Callejas, Carlos A
2007-01-01
In the present study a model was designed for the optimization of the rule for monthly operation of the Salvajina dam (Colombia) based in the technology) of dynamic programming. The model maximizes the benefits for electric power generation, ensuring at the same time flood regulation in winter and pollution relief during the summer. For the optimization of the rule of operation, it was necessary to define the levels and volumes of reserve and holding required for the control of flood zones in the Cauca river and to provide an effluent minimal flow and assure a daily flow at the Juanchito station (located 141 km downstream from the dam) of the Cauca river, 90 % of the time during the most critical summer periods.
Optimal day-ahead operational planning of microgrids
International Nuclear Information System (INIS)
Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad; Siano, Pierluigi
2016-01-01
Highlights: • A new multi-objective model for optimal day-ahead operational planning of microgrids is proposed. • A new concept called seamlessness is introduced to control the sustainability of microgrid. • A new method is developed to manage the load and renewable energy resources estimation errors. • A new solution based on a combination of numerical and evolutionary approaches is proposed. - Abstract: Providing a cost-efficient, eco-friendly and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of microgrid technology have provided huge potentials while distributing electricity more effectively, economically and securely. Accordingly, this paper presents a new multi-objective generation management model for optimal day-ahead operational planning of medium voltage microgrids. The proposed model optimizes both pollutant emission and operating cost of a microgrid by using multi-objective optimization. Besides, a seamlessness-selective algorithm is integrated into the model, which can be adopted to achieve the desired self-sufficiency level for microgrids along a specified planning horizon. Furthermore, the model is characterized by a reserve-assessment strategy developed to handle the load and renewable energy resources estimation errors. The introduced model is solved using a combination of numerical and evolutionary methods of species-based quantum particle swarm optimization to find the optimal scheduling scheme and minos-based optimal power flow to optimize the operating cost and emission. In addition, the suggested solution approach also incorporates an efficient mechanism for considering energy storage systems and coding the candidate solutions in the evolutionary algorithm. The proposed model is implemented on a test microgrid and is investigated through simulations to study the different aspects of the problem. The results show significant improvements and benefits which are obtained by
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Local Optimization Strategies in Urban Vehicular Mobility.
Directory of Open Access Journals (Sweden)
Pierpaolo Mastroianni
Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.
Control strategy optimization of HVAC plants
Energy Technology Data Exchange (ETDEWEB)
Facci, Andrea Luigi; Zanfardino, Antonella [Department of Engineering, University of Napoli “Parthenope” (Italy); Martini, Fabrizio [Green Energy Plus srl (Italy); Pirozzi, Salvatore [SIAT Installazioni spa (Italy); Ubertini, Stefano [School of Engineering (DEIM) University of Tuscia (Italy)
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Control strategy optimization of HVAC plants
International Nuclear Information System (INIS)
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-01-01
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting
Optimal allocation of trend following strategies
Grebenkov, Denis S.; Serror, Jeremy
2015-09-01
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies...... the generated power by changing the power reference of the individual wind turbines. We use the optimization setup to compare power production of the wind farm models. This paper shows that for the most frequent wind velocities (below and around the rated values), the generated powers of the wind farms...
Emission operational strategy for combined cooling, heating, and power systems
International Nuclear Information System (INIS)
Fumo, Nelson; Mago, Pedro J.; Chamra, Louay M.
2009-01-01
Integrated Energy Systems (IES), as technology that use thermal activated components to recover waste heat, are energy systems that offer key solution to global warming and energy security through high overall energy efficiency and better fuel use. Combined Cooling, Heating, and Power (CCHP) Systems are IES that use recovered thermal energy from the prime mover to produce heating and cooling for the building. The CCHP operational strategy is critical and it has to be considered in a well designed system since it defines the ultimate goal for the benefits expected from the system. One of the most common operational strategies is the cost-oriented strategy, which allows the system to operate at the lowest cost. A primary energy strategy (PES) optimizes energy consumption instead of cost. However, as a result of the worldwide concern about global warming, projects that target reduction of greenhouse gas (GHG) emissions have gained a lot of interest. Therefore, for a CCHP system, an emission strategy (ES) would be an operational strategy oriented to minimize emission of pollutants. In this study, the use of an ES is proposed for CCHP systems targeted to reduce emission of pollutants. The primary energy consumption (PEC) reduction and carbon dioxide (CO 2 ) emission reduction obtained using the proposed ES are compared with results obtained from the use of a PES. Results show that lower emission of CO 2 is achieved with the ES when compared with the PES, which prove the advantage of the ES for the design of CCHP systems targeted to emissions reduction.
Sleep As A Strategy For Optimizing Performance.
Yarnell, Angela M; Deuster, Patricia
2016-01-01
Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2011-01-01
represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. The impact of the optimal operation strategy for electric vehicles together with the optimal load response to spot market price on the distribution power system with high wind power penetrations...... are also discussed in the paper. Simulation results show that the proposed optimal operation strategy is an effective measure to achieve minimum energy costs of the PEV. The optimal operation strategy of the PEV and the optimal load response may have significant effects on the distribution power system......Since the hourly spot market price is available one day ahead in Denmark, the electricity price could be transferred to the consumers and they may make some optimal charge and discharge schedules for their electric vehicles in order to minimize their energy costs. This paper presents an optimal...
A new Methodology for Operations Strategy
DEFF Research Database (Denmark)
Koch, Christian; Rytter, Niels Gorm; Boer, Harry
2005-01-01
This paper proposes a new methodology for developing and implementing Operations Strategy (OS). It encompasses both content and process aspects of OS and differs thereby from many of the present OS methodologies. The paper outlines its paradigmatic foundation and presents aim, process, dimensions...
International Nuclear Information System (INIS)
Wang, Xinli; Cai, Wenjian; Lu, Jiangang; Sun, Youxian; Zhao, Lei
2015-01-01
This study presents a model-based optimization strategy for an actual chiller driven dehumidifier of liquid desiccant dehumidification system operating with lithium chloride solution. By analyzing the characteristics of the components, energy predictive models for the components in the dehumidifier are developed. To minimize the energy usage while maintaining the outlet air conditions at the pre-specified set-points, an optimization problem is formulated with an objective function, the constraints of mechanical limitations and components interactions. Model-based optimization strategy using genetic algorithm is proposed to obtain the optimal set-points for desiccant solution temperature and flow rate, to minimize the energy usage in the dehumidifier. Experimental studies on an actual system are carried out to compare energy consumption between the proposed optimization and the conventional strategies. The results demonstrate that energy consumption using the proposed optimization strategy can be reduced by 12.2% in the dehumidifier operation. - Highlights: • Present a model-based optimization strategy for energy saving in LDDS. • Energy predictive models for components in dehumidifier are developed. • The Optimization strategy are applied and tested in an actual LDDS. • Optimization strategy can achieve energy savings by 12% during operation
Operational Optimization in Port Container Terminals
DEFF Research Database (Denmark)
As a result of the significant increase in worldwide containerized transportation the development of efficient handling systems in marine terminals has become very important for port competitiveness. In order to optimize the productivity the total handling time for containers in the terminal must...... be minimized. An overview of the different operational problems in port container terminals is presented and an aggregated model and solution approach is shown. Next, there will be focused on the yard storage problem and a mathematical formulation and solution proposals will be presented....
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Directory of Open Access Journals (Sweden)
Seung Wan Kim
2016-01-01
Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.
Testing of Strategies for the Acceleration of the Cost Optimization
Energy Technology Data Exchange (ETDEWEB)
Ponciroli, Roberto [Argonne National Lab. (ANL), Argonne, IL (United States); Vilim, Richard B. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-08-31
The general problem addressed in the Nuclear-Renewable Hybrid Energy System (N-R HES) project is finding the optimum economical dispatch (ED) and capacity planning solutions for the hybrid energy systems. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES). In addition, there is an Industrial Process (IP), which is devoted to hydrogen generation. At this preliminary stage, the goal is to find the power outputs of each one of the N-R HES unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously satisfying individual component operational constraints. The optimization problem is meant to be solved in the Risk Analysis Virtual Environment (RAVEN) framework. The dynamic response of the N-R HES unit components is simulated by using dedicated object-oriented models written in the Modelica modeling language. Though this code coupling provides for very accurate predictions, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a method to better estimate the initial guess for the optimization problem solution was developed. The proposed approach led to the definition of a suitable Monte Carlo-based optimization algorithm (called the preconditioner), which provides an initial guess for the optimal N-R HES power dispatch and the optimal installed capacity for each one of the unit components. The preconditioner samples a set of stochastic power scenarios for each one of the N-R HES unit components, and then for each of them the corresponding value of a suitably defined cost function is evaluated. After having simulated a sufficient number of power histories, the configuration which ensures the highest profit is selected as the optimal
Production optimization of remotely operated gas wells
Energy Technology Data Exchange (ETDEWEB)
Juell, Aleksander
2012-07-01
From the introduction: The Remote Operations in Oklahoma Intended for Education (ROOKIE) project is a remote field laboratory constructed as a part of this research project. ROOKIE was initiated to provide data in research on production optimization of low productivity gas wells. In addition to this, ROOKIE is used as a teaching tool. Much of the remote operations technology used in the ROOKIE project has been used by the industry for several decades. The first use of remote data acquisition in Oklahoma was in 1989, as described by Luppens [7]. Even though this, for the most part, is old technology, the ROOKIE project is the first remote operations project set up with research and teaching as the main focus. This chapter will discuss the process of establishing the remote field laboratory and the data storage facilities. Results from the project will also be discussed. All testing, instrumentation installation, and modifications to the wells discussed in this chapter was performed by the author. The communication system between the well and NTNU, and the storage database was installed and configured by the author.(Author)
Impact of Fluctuating Energy Prices on the Operation Strategy of a Trigeneration System
Directory of Open Access Journals (Sweden)
Dražen Balić
2015-09-01
The optimization method is based on two criteria – energy and economic criterion, which were applied hierarchically. Therefore, two optimal operation strategies are introduced. A mixed integer non-linear programming model provides energy and cost savings up to 32% and 28% respectively in comparison with conventional system. In addition, optimal capacity of trigeneration system is explored.
Production of sugar and alcohol: financial and operational strategies
Directory of Open Access Journals (Sweden)
Celma de Oliveira Ribeiro
2014-12-01
Full Text Available This article proposes the construction of an optimization model to define the product portfolio of a sugarcane mill, taking into account operational and financial aspects. It is considered that the revenue earned by a producer comes from the sale of sugar and alcohol in the physical market and the results obtained through hedging in the derivatives market of sugar. Employing CVaR (Conditional Value-at-Risk, as the risk measure, the model allows the construction of an efficient frontier and, according to the producer's risk tolerance, defines the optimal strategy of production (production mix and activity in the derivatives market (hedge ratio. Through the model the article also seeks to analyze the advantage of using the options market in the construction of financial hedging strategies in agricultural commodities markets.
Optimal energy management strategy for self-reconfigurable batteries
International Nuclear Information System (INIS)
Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter
2017-01-01
This paper proposes a novel energy management strategy for multi-cell high voltage batteries where the current through each cell can be controlled, called self-reconfigurable batteries. An optimized control strategy further enhances the energy efficiency gained by the hardware architecture of those batteries. Currently, achieving cell equalization by using the active balancing circuits is considered as the best way to optimize the energy efficiency of the battery pack. This study demonstrates that optimizing the energy efficiency of self-reconfigurable batteries is no more strongly correlated to the cell balancing. According to the features of this novel battery architecture, the energy management strategy is formulated as nonlinear dynamic optimization problem. To solve this optimal control, an optimization algorithm that generates the optimal discharge policy for a given driving cycle is developed based on dynamic programming and code vectorization. The simulation results show that the designed energy management strategy maximizes the system efficiency across the battery lifetime over conventional approaches. Furthermore, the present energy management strategy can be implemented online due to the reduced complexity of the optimization algorithm. - Highlights: • The energy efficiency of self-reconfigurable batteries is maximized. • The energy management strategy for the battery is formulated as optimal control problem. • Developing an optimization algorithm using dynamic programming techniques and code vectorization. • Simulation studies are conducted to validate the proposed optimal strategy.
Particle Swarm Optimization With Interswarm Interactive Learning Strategy.
Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui
2016-10-01
The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.
Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs
Directory of Open Access Journals (Sweden)
Jiajun Liu
2017-10-01
Full Text Available Energy storage systems (ESS play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs and supercapacitors (SCs is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS of 14-ton underground load-haul-dump vehicles (LHDs. Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.
Optimized control strategy for crowbarless solid state modular power supply
International Nuclear Information System (INIS)
Upadhyay, R.; Badapanda, M.K.; Tripathi, A.; Hannurkar, P.R.; Pithawa, C.K.
2009-01-01
Solid state modular power supply with series connected IGBT based power modules have been employed as high voltage bias power supply of klystron amplifier. Auxiliary compensation of full wave inverter bridge with ZVS/ZCS operations of all IGBTs over entire operating range is incorporated. An optimized control strategy has been adopted for this power supply needing no output filter, making this scheme crowbarless and is presented in this paper. DSP based fully digital control with same duty cycle for all power modules, have been incorporated for regulating this power supply along with adequate protection features. Input to this power supply is taken directly from 11 kV line and the input system is intentionally made 24 pulsed to reduce the input harmonics, improve the input power factor significantly, there by requiring no line filters. Various steps have been taken to increase the efficiency of major subsystems, so as to improve the overall efficiency of this power supply significantly. (author)
A quantum particle swarm optimizer with chaotic mutation operator
International Nuclear Information System (INIS)
Coelho, Leandro dos Santos
2008-01-01
Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a social psychological metaphor motivated by collective behaviors of bird and other social organisms instead of the survival of the fittest individual. Inspired by the classical PSO method and quantum mechanics theories, this work presents a novel Quantum-behaved PSO (QPSO) using chaotic mutation operator. The application of chaotic sequences based on chaotic Zaslavskii map instead of random sequences in QPSO is a powerful strategy to diversify the QPSO population and improve the QPSO's performance in preventing premature convergence to local minima. The simulation results demonstrate good performance of the QPSO in solving a well-studied continuous optimization problem of mechanical engineering design
Lean Strategies in the Operating Room.
Robinson, Stephen T; Kirsch, Jeffrey R
2015-12-01
Lean strategies can be readily applied to health care in general and operating rooms specifically. The emphasis is on the patient as the customer, respect and engagement of all providers, and leadership from management. The strategy of lean is to use continuous improvement to eliminate waste from the care process, leaving only value-added activities. This iterative process progressively adds the steps of identifying the 7 common forms of waste (transportation, inventory, motion, waiting, overproduction, overprocessing, and defects), 5S (sort, simplify, sweep, standardize, sustain), visual controls, just-in-time processing, level-loaded work, and built-in quality to achieve the highest quality of patient care. Copyright © 2015 Elsevier Inc. All rights reserved.
Optimization strategies for ultrasound volume registration
International Nuclear Information System (INIS)
Ijaz, Umer Zeeshan; Prager, Richard W; Gee, Andrew H; Treece, Graham M
2010-01-01
This paper considers registration of 3D ultrasound volumes acquired in multiple views for display in a single image volume. One way to acquire 3D data is to use a mechanically swept 3D probe. However, the usefulness of these probes is restricted by their limited field of view. This problem can be overcome by attaching a six-degree-of-freedom (DOF) position sensor to the probe, and displaying the information from multiple sweeps in their proper positions. However, an external six-DOF position sensor can be an inconvenience in a clinical setting. The objective of this paper is to propose a hybrid strategy that replaces the sensor with a combination of three-DOF image registration and an unobtrusive inertial sensor for measuring orientation. We examine a range of optimization algorithms and similarity measures for registration and compare them in in vitro and in vivo experiments. We register based on multiple reslice images rather than a whole voxel array. In this paper, we use a large number of reslices for improved reliability at the expense of computational speed. We have found that the Levenberg–Marquardt method is very fast but is not guaranteed to give the correct solution all the time. We conclude that normalized mutual information used in the Nelder–Mead simplex algorithm is potentially suitable for the registration task with an average execution time of around 5 min, in the majority of cases, with two restarts in a C++ implementation on a 3.0 GHz Intel Core 2 Duo CPU machine
Optimizing metapopulation sustainability through a checkerboard strategy.
Directory of Open Access Journals (Sweden)
Yossi Ben Zion
2010-01-01
Full Text Available The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent of stable solutions and the structure of their basin of attraction (dependence on initial population size. Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Operational Strategy for Mobile Banking in India
Manjunath, Gowtham
2010-01-01
Mobile banking (m-banking) business concepts have become ‘talk of the town’ these days. There has been considerable development in this field and what m-banking concept can offer. M-Rupee has developed a business model and plan to establish a mobile banking business in India taking the opportunity of the new unexplored market. This report is constructed in conjunction with the business plan, which describes the formulation and broader aspects of M-Rupee operational strategy. To understand ...
Operational strategies for nitrogen removal in granular sequencing batch reactor
International Nuclear Information System (INIS)
Chen, Fang-yuan; Liu, Yong-Qiang; Tay, Joo-Hwa; Ning, Ping
2011-01-01
This study investigated the effects of different operational strategies for nitrogen removal by aerobic granules with mean granule sizes of 1.5 mm and 0.7 mm in a sequencing batch reactor (SBR). With an alternating anoxic/oxic (AO) operation mode without control of dissolve oxygen (DO), the granular sludge with different size achieved the total inorganic nitrogen (TIN) removal efficiencies of 67.8-71.5%. While under the AO condition with DO controlled at 2 mg/l at the oxic phase, the TIN removal efficiency was improved up to 75.0-80.4%. A novel operational strategy of alternating anoxic/oxic combined with the step-feeding mode was developed for nitrogen removal by aerobic granules. It was found that nitrogen removal efficiencies could be further improved to 93.0-95.9% with the novel strategy. Obviously, the alternating anoxic/oxic strategy combined with step-feeding is the optimal way for TIN removal by granular sludge, which is independent of granule size.
Operational strategy of adsorption desalination systems
Thu, Kyaw
2009-03-01
This paper presents the performances of an adsorption desalination (AD) system in two-bed and four-bed operational modes. The tested results are calculated in terms of key performance parameters namely, (i) specific daily water production (SDWP), (ii) cycle time, and (iii) performance ratio (PR) for various heat source temperatures, mass flow rates, cycle times along with a fixed heat sink temperature. The optimum input parameters such as driving heat source and cycle time of the AD cycle are also evaluated. It is found from the present experimental data that the maximum potable water production per tonne of adsorbent (silica gel) per day is about 10 m3 whilst the corresponding performance ratio is 0.61, and a longer cycle time is required to achieve maximum water production at lower heat source temperatures. This paper also provides a useful guideline for the operational strategy of the AD cycle. © 2008 Elsevier Ltd. All rights reserved.
Developing an Integrated Design Strategy for Chip Layout Optimization
Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.
2011-01-01
This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized
Optimal Spatial Harvesting Strategy and Symmetry-Breaking
International Nuclear Information System (INIS)
Kurata, Kazuhiro; Shi Junping
2008-01-01
A reaction-diffusion model with logistic growth and constant effort harvesting is considered. By minimizing an intrinsic biological energy function, we obtain an optimal spatial harvesting strategy which will benefit the population the most. The symmetry properties of the optimal strategy are also discussed, and related symmetry preserving and symmetry breaking phenomena are shown with several typical examples of habitats
Multi-objective optimal operation of smart reconfigurable distribution grids
Directory of Open Access Journals (Sweden)
Abdollah Kavousi-Fard
2016-02-01
Full Text Available Reconfiguration is a valuable technique that can support the distribution grid from different aspects such as operation cost and loss reduction, reliability improvement, and voltage stability enhancement. An intelligent and efficient optimization framework, however, is required to reach the desired efficiency through the reconfiguration strategy. This paper proposes a new multi-objective optimization model to make use of the reconfiguration strategy for minimizing the power losses, improving the voltage profile, and enhancing the load balance in distribution grids. The proposed model employs the min-max fuzzy approach to find the most satisfying solution from a set of nondominated solutions in the problem space. Due to the high complexity and the discrete nature of the proposed model, a new optimization method based on harmony search (HS algorithm is further proposed. Moreover, a new modification method is suggested to increase the harmony memory diversity in the improvisation stage and increase the convergence ability of the algorithm. The feasibility and satisfying performance of the proposed model are examined on the IEEE 32-bus distribution system.
Synthesis of Optimal Strategies Using HyTech
DEFF Research Database (Denmark)
Bouyer, Patricia; Cassez, Franck; Larsen, Kim Guldstrand
2005-01-01
Priced timed (game) automata extend timed (game) automata with costs on both locations and transitions. The problem of synthesizing an optimal winning strategy for a priced timed game under some hypotheses has been shown decidable in [P. Bouyer, F. Cassez, E. Fleury, and K.G. Larsen. Optimal...... strategies in priced timed game automata. Research Report BRICS RS-04-4, Denmark, Feb. 2004. Available at http://www.brics.dk/RS/04/4/]. In this paper, we present an algorithm for computing the optimal cost and for synthesizing an optimal strategy in case there exists one. We also describe the implementation...
Optimization Strategies for Hardware-Based Cofactorization
Loebenberger, Daniel; Putzka, Jens
We use the specific structure of the inputs to the cofactorization step in the general number field sieve (GNFS) in order to optimize the runtime for the cofactorization step on a hardware cluster. An optimal distribution of bitlength-specific ECM modules is proposed and compared to existing ones. With our optimizations we obtain a speedup between 17% and 33% of the cofactorization step of the GNFS when compared to the runtime of an unoptimized cluster.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
In an electricity market generating companies and large consumers need suitable bidding models to maximize their profits. Therefore, each supplier and large consumer will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. In this paper, bidding strategy problem modeled as an ...
Optimization strategies for discrete multi-material stiffness optimization
DEFF Research Database (Denmark)
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....
Reconfiguration strategies for electrical devices for operation within feasibility margins
Energy Technology Data Exchange (ETDEWEB)
Gandor, Malin; Blank, Marita [Oldenburg Univ. (Germany); Lehnhoff, Sebastian [OFFIS - Institut fuer Informatik, Oldenburg (Germany)
2012-07-01
Due to a transition of the energy system towards a sustainable energy supply by the integration of renewable, decentralized energy resources, new challenges regarding a safe and secure energy supply appear. With renewable energy resources the power fee-in will be highly volatile. Furthermore, due to a correlated feed-in depending on e.g. weather phenomena or control strategies on the demand side, the system might be operated beyond feasible boundaries. However, the satisfaction of viable operational boundaries must be guaranteed. In this paper a method is presented that allows the utilization of degrees of freedom in form of decentralized flexible electric consumers and products in order to optimize an operational state with regard to its feasibility. First results are presented in a case study. (orig.)
Fetal DNA: strategies for optimal recovery
Legler, Tobias J.; Heermann, Klaus-Hinrich; Liu, Zhong; Soussan, Aicha Ait; van der Schoot, C. Ellen
2008-01-01
For fetal DNA extraction, in principle each DNA extraction method can be used; however, because most methods have been optimized for genomic DNA from leucocytes, we describe here the methods that have been optimized for the extraction of fetal DNA from maternal plasma and validated for this purpose
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
An optimal tuning strategy for tidal turbines.
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This 'impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing 'patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a 'smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
Optimal Economic Operation of Islanded Microgrid by Using a Modified PSO Algorithm
Directory of Open Access Journals (Sweden)
Yiwei Ma
2015-01-01
Full Text Available An optimal economic operation method is presented to attain a joint-optimization of cost reduction and operation strategy for islanded microgrid, which includes renewable energy source, the diesel generator, and battery storage system. The optimization objective is to minimize the overall generating cost involving depreciation cost, operation cost, emission cost, and economic subsidy available for renewable energy source, while satisfying various equality and inequality constraints. A novel dynamic optimization process is proposed based on two different operation control modes where diesel generator or battery storage acts as the master unit to maintain the system frequency and voltage stability, and a modified particle swarm optimization algorithm is applied to get faster solution to the practical economic operation problem of islanded microgrid. With the example system of an actual islanded microgrid in Dongao Island, China, the proposed models, dynamic optimization strategy, and solution algorithm are verified and the influences of different operation strategies and optimization algorithms on the economic operation are discussed. The results achieved demonstrate the effectiveness and feasibility of the proposed method.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
A considerable amount of work has also been reported on the game theory applications ... probability distribution function (Song et al, 1999) and as a continuous ..... compared with GA and Monte Carlo method, therefore the bidding strategies.
Optimizing integrated airport surface and terminal airspace operations under uncertainty
Bosson, Christabelle S.
In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is
Optimal portfolio strategies under a shortfall constraint
African Journals Online (AJOL)
we make precise the optimal control problem to be solved. .... is closely related to the concept of Value-at-Risk, but overcomes some of the conceptual .... We adapt a dynamic programming approach to solve the HJB equation associated with.
Optimal Pricing Strategy for New Products
Trichy V. Krishnan; Frank M. Bass; Dipak C. Jain
1999-01-01
Robinson and Lakhani (1975) initiated a long research stream in marketing when they used the Bass model (1969) to develop optimal pricing path for a new product. A careful analysis of the extant literature reveals that the research predominantly suggests that the optimal price path should be largely based on the sales growth pattern. However, in the real world we rarely find new products that have such pricing pattern. We observe either a monotonically declining pricing pattern or an increase...
Balanced Sourcing As An Important Attribute Of Operations Strategy ...
African Journals Online (AJOL)
Balanced Sourcing As An Important Attribute Of Operations Strategy: Reality Or ... the questions “who should perform an activity or process in the value chain? ... Operations Strategy, Strategic Sourcing, Sustainable Competitive Advantage, ...
An optimal tuning strategy for tidal turbines
2016-01-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This ‘impatient-tuning strategy’ results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing ‘patient-tuning strategy’ which maximizes the power output averaged over the tidal cycle. This paper presents a ‘smart patient tuning strategy’, which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine’s average power output. PMID:27956870
Issues and Strategies in Solving Multidisciplinary Optimization Problems
Patnaik, Surya
2013-01-01
Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the
Attitude Control Optimization for ROCSAT-2 Operation
Chern, Jeng-Shing; Wu, A.-M.
one revolution. The purpose of this paper is to present the attitude control design optimization such that the maximum solar energy is ingested while minimum maneuvering energy is dissipated. The strategy includes the maneuvering sequence design, the minimization of angular path, the sizing of three magnetic torquers, and the trade-off of the size, number and orientations arrangement of momentum wheels.
Optimal strategy for selling on group-buying website
Directory of Open Access Journals (Sweden)
Xuan Jiang
2014-09-01
Full Text Available Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1 How to make a decision on maximum deal size with coordination of the deal price? (2 Will selling on GB websites always be better than staying with offline channel only? (3 What kind of products is more appropriate to sell on GB website? (4How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal
The Optimal Operation Criteria for a Gas Turbine Cogeneration System
Directory of Open Access Journals (Sweden)
Atsushi Akisawa
2009-04-01
Full Text Available The study demonstrated the optimal operation criteria of a gas turbine cogeneration system based on the analytical solution of a linear programming model. The optimal operation criteria gave the combination of equipment to supply electricity and steam with the minimum energy cost using the energy prices and the performance of equipment. By the comparison with a detailed optimization result of an existing cogeneration plant, it was shown that the optimal operation criteria successfully provided a direction for the system operation under the condition where the electric power output of the gas turbine was less than the capacity
An Overview of Optimizing Strategies for Flotation Banks
Directory of Open Access Journals (Sweden)
Miguel Maldonado
2012-10-01
Full Text Available A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity profiling and Peak Air Recovery (PAR profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.
Optimizing urology group partnerships: collaboration strategies and compensation best practices.
Jacoby, Dana L; Maller, Bruce S; Peltier, Lisa R
2014-10-01
Market forces in health care have created substantial regulatory, legislative, and reimbursement changes that have had a significant impact on urology group practices. To maintain viability, many urology groups have merged into larger integrated entities. Although group operations vary considerably, the majority of groups have struggled with the development of a strong culture, effective decision-making, and consensus-building around shared resources, income, and expense. Creating a sustainable business model requires urology group leaders to allocate appropriate time and resources to address these issues in a proactive manner. This article outlines collaboration strategies for creating an effective culture, governance, and leadership, and provides practical suggestions for optimizing the performance of the urology group practice.
Evolution strategy based optimal chiller loading for saving energy
International Nuclear Information System (INIS)
Chang, Y.-C.; Lee, C.-Y.; Chen, C.-R.; Chou, C.-J.; Chen, W.-H.; Chen, W.-H.
2009-01-01
This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems
Operative strategy for the spectral hardening
International Nuclear Information System (INIS)
Mejia S, D.M.; Torres A, C.
2004-01-01
This work describes the possibility to be able to operate the reactor of the unit one of the Laguna Verde Nuclear power plant (CNLV) to a low flow, compared with the one cycle 10 fellow man. The main objective is to analyze the advantages or disadvantages that they obtain when going down the flow from the reactor to an interval that varies from 81% to 106%, being a flow window but big of the one that is used that it is from 93.1% to 100.8%. The calculations that were carried out for the realization of this work were elaborated in the Core Master Presto Code, giving him like name Operative Strategy to the case that we propose and it Reference to the case with which will be compared. They take very in account the intervals allowed for the thermic limits and for the K eff . It is considered a possible movement of control bars if in some case the thermal limits or the K eff doesn't end up being inside these allowed intervals, and one has much care in maintaining the potential to 100%. It is found that making this type of changes, to the core of the reactor, this gives a favorable answer, without any possibility of fault of the same one and there is also a difference of 219 pcm among these cases. (Author)
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
Modeling and optimization of laser cutting operations
Directory of Open Access Journals (Sweden)
Gadallah Mohamed Hassan
2015-01-01
Full Text Available Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta, surface roughness (Ra and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.
Intelligent fault recognition strategy based on adaptive optimized multiple centers
Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong
2018-06-01
For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.
Long-run savings and investment strategy optimization.
Gerrard, Russell; Guillén, Montserrat; Nielsen, Jens Perch; Pérez-Marín, Ana M
2014-01-01
We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor's risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Long-Run Savings and Investment Strategy Optimization
Directory of Open Access Journals (Sweden)
Russell Gerrard
2014-01-01
Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Optimal inspection strategies for offshore structural systems
DEFF Research Database (Denmark)
Faber, M. H.; Sorensen, J. D.; Kroon, I. B.
1992-01-01
a mathematical framework for the estimation of the failure and repair costs a.ssociated with systems failure. Further a strategy for selecting the components to inspect based on decision tree analysis is suggested. Methods and analysis schemes are illustrated by a simple example....
What SCADA systems can offer to optimize field operations
International Nuclear Information System (INIS)
McLean, D.J.
1997-01-01
A new technology developed by Kenomic Controls Ltd. of Calgary was designed to solve some of the problems associated with producing gas wells with high gas to liquids ratios. The rationale and the system architecture of the SCADA (Supervisory Control and Data Acquisition) system were described. The most common application of SCADA is the Electronic Flow Measurement (EFM) installation using a solar or thermo-electric generator as a power source for the local electronics. Benefits that the SCADA system can provide to producing fields such as increased revenue, decreased operating costs, decreased fixed capital and working capital requirements, the planning and implementation strategies for SCADA were outlined. A case history of a gas well production optimization system in the Pierceland area of northwest Saskatchewan was provided as an illustrative example. 9 figs
DEFF Research Database (Denmark)
Connolly, David; Lund, Henrik; Finn, P.
2011-01-01
In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360 MW pump, 300 MW turbine, and a 2 GWh storage utilising price arbitrage on 13 electricity spot markets. The results indicate...... that almost all (not, vert, similar97%) of the profits can be obtained by a PHES facility when it is optimised using the 24Optimal strategy developed, which optimises the energy storage based on the day-ahead electricity prices. However, to maximise profits with the 24Optimal strategy, the day......-ahead electricity prices must be the actual prices which the PHES facility is charged or the PHES operator must have very accurate price predictions. Otherwise, the predicted profit could be significantly reduced and even become a loss. Finally, using the 24Optimal strategy, the PHES profit can surpass the annual...
Optimal Licensing Strategy: Royalty or Fixed Fee?
Andrea Fosfuri; Esther Roca
2004-01-01
Licensing a cost-reducing innovation through a royalty has been shown to be superior to licensing by means of a fixed fee for an incumbent licensor. This note shows that this result relies crucially on the assumption that the incumbent licensor can sell its cost-reducing inno-vation to all industry players. If, for any reason, only some competitors could be reached through a licensing contract, then a fixed fee might be optimally chosen.
Optimal processor for malfunction detection in operating nuclear reactor
International Nuclear Information System (INIS)
Ciftcioglu, O.
1990-01-01
An optimal processor for diagnosing operational transients in a nuclear reactor is described. Basic design of the processor involves real-time processing of noise signal obtained from a particular in core sensor and the optimality is based on minimum alarm failure in contrast to minimum false alarm criterion from the safe and reliable plant operation viewpoint
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
A strategy for optimizing item-pool management
Ariel, A.; van der Linden, Willem J.; Veldkamp, Bernard P.
2006-01-01
Item-pool management requires a balancing act between the input of new items into the pool and the output of tests assembled from it. A strategy for optimizing item-pool management is presented that is based on the idea of a periodic update of an optimal blueprint for the item pool to tune item
Directory of Open Access Journals (Sweden)
Azwar Aziz
2015-06-01
Full Text Available Jumlah pelanggan ketiga operator telekomunikasi seluler pada akhir tahun 2013, yaitu PT. Telkomsel Tbk, PT. XL Axiata Tbk, dan PT. Indosat Tbk, sebanyak 251,285 juta. Jumlah pelanggan telekomunikasi seluler ini telah melebihi jumlah penduduk Indonesia sebesar 242,013 juta pada akhir tahun 2013. Ketiga operator telekomunikasi seluler tersebut mendominasi pangsa pasar seluler di Indonesia dan sangat menentukan tingkat harga, kualitas layanan dan strategi persaingan lainnya. Persaingan di telekomunikasi seluler saat ini sudah masuk ke masa jenuh untuk suara dan SMS, tetapi sudah beralih ke layanan data atau menggunaan internet. Para operator telekomunikasi seluler berlomba-lomba untuk meningkatkan kualitas layanan internet kepada pelanggan yang menggunakan prabayar dan pascabayar untuk suara dan SMS.Kajian ini menggunakan metodologi penelitian kualitatif, dengan melakukan observasi atau pengamatan langsung ke lapangan kepada Telkomsel, XL Axiata dan Indosat.Teknik analisis data menggunakan teknik analisis deskritif. Berdasarkan hasil analisis diperoleh bahwa strategi persaingan ketiga operator tersebut dari aspekcore competence, time based competition, disiplin nilai sama-sama mengimplementasikannya. Dari aspek expeditionary marketing sangat tergantung pada luas jaringan yang dimiliki, aspek standar produk, memiliki sertifikat ISO yang lebih baik dan kompetensi manajemen fokus pada sumber daya manusia dengan belajar ke luar negeri. *****The number of subscribers of three mobile telecommunication operators by the end of 2013, namely PT. Telkomsel Tbk, PT. XL Axiata Tbk, and PT. Indosat Tbk is 251.285 million. The number of mobile telecommunication subscribers has exceeded the population of Indonesia amounted to 242.013 million at the end of 2013. Those operators dominate the market in Indonesia and determine the level of price, quality of service and other competitive strategies. Competition in the mobile telecommunications currently
Future xenon system operational parameter optimization
International Nuclear Information System (INIS)
Lowrey, J.D.; Eslinger, P.W.; Miley, H.S.
2016-01-01
Any atmospheric monitoring network will have practical limitations in the density of its sampling stations. The classical approach to network optimization has been to have 12 or 24-h integration of air samples at the highest station density possible to improve minimum detectable concentrations. The authors present here considerations on optimizing sampler integration time to make the best use of any network and maximize the likelihood of collecting quality samples at any given location. In particular, this work makes the case that shorter duration sample integration (i.e. <12 h) enhances critical isotopic information and improves the source location capability of a radionuclide network, or even just one station. (author)
Energy Technology Data Exchange (ETDEWEB)
Aha, Ulrich
2013-07-01
Maintenance strategies are aimed to keep a technical facility functioning in spite of damaging processes (wear, corrosion, fatigue) with simultaneous control of these processes. The project optimization of maintenance strategies in case of data uncertainties is aimed to optimize maintenance measures like preventive measures (lubrication etc.), inspections and replacements to keep the facility/plant operating including the minimization of financial costs. The report covers the following topics: modeling assumptions, model development and optimization procedure, results for a conventional power plant and an oxyfuel plant.
Optimization Criteria of Power Transformer Operation
Directory of Open Access Journals (Sweden)
A. A. Gonchar
2006-01-01
Full Text Available It has been shown that minimum losses in active power of a power transformer do not correspond to its maximum efficiency. For a transformer being operated there are no so called «zones of its economical operation». In this case strictly specified value of active power losses corresponds to a particular current of the winding.
Li, Haichen; Qin, Tao; Wang, Weiping; Lei, Xiaohui; Wu, Wenhui
2018-02-01
Due to the weakness in holding diversity and reaching global optimum, the standard particle swarm optimization has not performed well in reservoir optimal operation. To solve this problem, this paper introduces downhill simplex method to work together with the standard particle swarm optimization. The application of this approach in Goupitan reservoir optimal operation proves that the improved method had better accuracy and higher reliability with small investment.
Blackjack in Holland Casino's : Basic, optimal and winning strategies
van der Genugten, B.B.
1995-01-01
This paper considers the cardgame Blackjack according to the rules of Holland Casino's in the Netherlands. Expected gains of strategies are derived with simulation and also with analytic tools. New effiency concepts based on the gains of the basic and the optimal strategy are introduced. A general
Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks
Directory of Open Access Journals (Sweden)
M. Hadi Amini
2018-01-01
Full Text Available Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs with competing charging stations, to exchange data such as electricity price, energy demand, and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs’ charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices were communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e., optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks.
Modelling and operation strategies of DLR's large scale thermocline test facility (TESIS)
Odenthal, Christian; Breidenbach, Nils; Bauer, Thomas
2017-06-01
In this work an overview of the TESIS:store thermocline test facility and its current construction status will be given. Based on this, the TESIS:store facility using sensible solid filler material is modelled with a fully transient model, implemented in MATLAB®. Results in terms of the impact of filler site and operation strategies will be presented. While low porosity and small particle diameters for the filler material are beneficial, operation strategy is one key element with potential for optimization. It is shown that plant operators have to ponder between utilization and exergetic efficiency. Different durations of the charging and discharging period enable further potential for optimizations.
Optimal robust control strategy of a solid oxide fuel cell system
Wu, Xiaojuan; Gao, Danhui
2018-01-01
Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
A new inertia weight control strategy for particle swarm optimization
Zhu, Xianming; Wang, Hongbo
2018-04-01
Particle Swarm Optimization is a member of swarm intelligence algorithms, which is inspired by the behavior of bird flocks. The inertia weight, one of the most important parameters of PSO, is crucial for PSO, for it balances the performance of exploration and exploitation of the algorithm. This paper proposes a new inertia weight control strategy and PSO with this new strategy is tested by four benchmark functions. The results shows that the new strategy provides the PSO with better performance.
Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.
2017-03-01
General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.
Noise-dependent optimal strategies for quantum metrology
Huang, Zixin; Macchiavello, Chiara; Maccone, Lorenzo
2018-03-01
For phase estimation using qubits, we show that for some noise channels, the optimal entanglement-assisted strategy depends on the noise level. We note that there is a nontrivial crossover between the parallel-entangled strategy and the ancilla-assisted strategy: in the former the probes are all entangled; in the latter the probes are entangled with a noiseless ancilla but not among themselves. The transition can be explained by the fact that separable states are more robust against noise and therefore are optimal in the high-noise limit, but they are in turn outperformed by ancilla-assisted ones.
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Operations Optimization of Hybrid Energy Systems under Variable Markets
Energy Technology Data Exchange (ETDEWEB)
Chen, Jun; Garcia, Humberto E.
2016-07-01
Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper investigates the operations flexibility of HES, and develops a methodology for operations optimization to maximize its economic value based on predicted renewable generation and market information. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value, and is illustrated by numerical results.
An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines
Directory of Open Access Journals (Sweden)
Stephan Zentner
2014-02-01
Full Text Available One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO2 emissions is reformulated as an unconstrained minimization of the CO2 emissions and the weighted pollutant emissions (i.e., equivalent emissions. However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton–Jacobi–Bellman (HJB equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.
Optimal intermittent search strategies: smelling the prey
International Nuclear Information System (INIS)
Revelli, J A; Wio, H S; Rojo, F; Budde, C E
2010-01-01
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of α (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Optimal intermittent search strategies: smelling the prey
Energy Technology Data Exchange (ETDEWEB)
Revelli, J A; Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC, E-39005 Santander (Spain); Rojo, F; Budde, C E [Fa.M.A.F., Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina)
2010-05-14
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of {alpha} (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Optimal Inspection and Maintenance Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.
The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies....... For structures with several almost similar components it is suggested that individual inspection strategies should be determined for each component or a group of components based on the reliability of the actual component. The benefit of this procedure is assessed in connection with the structures considered....... Furthermore, in relation to the calculations performed the intention is to modify an existing program for determination of optimal inspection strategies. The main purpose of inspection and maintenance of structural systems is to prevent or delay damage or deterioration to protect people, environment...
An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model
International Nuclear Information System (INIS)
Liu, Kailong; Li, Kang; Yang, Zhile; Zhang, Cheng; Deng, Jing
2017-01-01
Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed. Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared. The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.
Optimization of fuel-cell tram operation based on two dimension dynamic programming
Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu
2018-02-01
This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.
Energetic optimization of the chilled water systems operation at hotels
Directory of Open Access Journals (Sweden)
Reineris Montero Laurencio
2015-12-01
Full Text Available The hotel exploitation, while continuing to satisfy the customers, needs to decrease the requests of electric power as the principal energy carrier. Solving issues regarding the occupation of a hotel integrally, taking the air conditioning as center of attention, which demands the bigger consumptions of electricity, results in a complex task. To solve this issue, a procedure was implemented to optimize the operation of the water-chilled systems. The procedure integrates an energy model with a strategy of low occupation following energetic criteria based on combinatorial-evolutionary criteria. To classify the information, the formulation of the tasks and the synthesis of the solutions, a methodology of analysis and synthesis of engineering is used. The energetic model considers the variability of the local climatology and the occupation of the selected rooms, and includes: the thermal model of the building obtained by means of artificial neural networks, the hydraulic model and the model of the compression work. These elements allow to find the variable of decision occupation, performing intermediate calculations to obtain the velocity of rotation in the centrifugal pump and the output temperature of the cooler water, minimizing the requirements of electric power in the water-chilled systems. To evaluate the states of the system, a combinatorial optimization is used through the following methods: simple exhaustive, stepped exhaustive or genetic algorithm depending on the quantity of variants of occupation. All calculation tasks and algorithms of the procedure were automated through a computer application.
UMTS network planning, optimization, and inter-operation with GSM
Rahnema, Moe
2008-01-01
UMTS Network Planning, Optimization, and Inter-Operation with GSM is an accessible, one-stop reference to help engineers effectively reduce the time and costs involved in UMTS deployment and optimization. Rahnema includes detailed coverage from both a theoretical and practical perspective on the planning and optimization aspects of UMTS, and a number of other new techniques to help operators get the most out of their networks. Provides an end-to-end perspective, from network design to optimizationIncorporates the hands-on experiences of numerous researchersSingle
Optimizing Aircraft Utilization for Retrograde Operations
2012-06-15
shortages. Coyle et al. (2011) contend commercial carriers will often adopt a loss minimization strategy. This occurs when the market will not support...accordance with market demands to minimize its losses. The other way carriers may choose to look at backhaul efficiency is by considering wages and...Edmonson, R.G. (2009). Senators Take Up Transport Policy. The Journal of Commerce, 10(21), 16-18. Retrieved from EBSCOhost . General Accounting Office
Verheyleweghen, Adriaen; Jaeschke, Johannes
2017-01-01
The efficient and safe operation of subsea gas and oil production systems sets strict requirements to equipment reliability to avoid unplanned breakdowns and costly maintenance interventions. Because of this, condition monitoring is employed to assess the status of the system in real-time. However, the condition of the system is usually not considered explicitly when finding the optimal operation strategy. Instead, operational constraints on flow rates, pressures etc., based on worst-case sce...
A proposal of optimal sampling design using a modularity strategy
Simone, A.; Giustolisi, O.; Laucelli, D. B.
2016-08-01
In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.
Systematic Methodology for Reproducible Optimizing Batch Operation
DEFF Research Database (Denmark)
Bonné, Dennis; Jørgensen, Sten Bay
2006-01-01
This contribution presents a systematic methodology for rapid acquirement of discrete-time state space model representations of batch processes based on their historical operation data. These state space models are parsimoniously parameterized as a set of local, interdependent models. The present...
Optimal reactor strategy for commercializing fast breeder reactors
International Nuclear Information System (INIS)
Yamaji, Kenji; Nagano, Koji
1988-01-01
In this paper, a fuel cycle optimization model developed for analyzing the condition of selecting fast breeder reactors in the optimal reactor strategy is described. By dividing the period of planning, 1966-2055, into nine ten-year periods, the model was formulated as a compact linear programming model. With the model, the best mix of reactor types as well as the optimal timing of reprocessing spent fuel from LWRs to minimize the total cost were found. The results of the analysis are summarized as follows. Fast breeder reactors could be introduced in the optimal strategy when they can economically compete with LWRs with 30 year storage of spent fuel. In order that fast breeder reactors monopolize the new reactor market after the achievement of their technical availability, their capital cost should be less than 0.9 times as much as that of LWRs. When a certain amount of reprocessing commitment is assumed, the condition of employing fast breeder reactors in the optimal strategy is mitigated. In the optimal strategy, reprocessing is done just to meet plutonium demand, and the storage of spent fuel is selected to adjust the mismatch of plutonium production and utilization. The price hike of uranium ore facilitates the commercial adoption of fast breeder reactors. (Kako, I.)
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Directory of Open Access Journals (Sweden)
Xiaojian Yu
2014-01-01
Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
Severe accident management. Optimized guidelines and strategies
International Nuclear Information System (INIS)
Braun, Matthias; Löffler, Micha; Plank, Hermann; Asse, Dietmar; Dimmelmeier, Harald
2014-01-01
The highest priority for mitigating the consequences of a severe accident with core melt lies in securing containment integrity, as this represents the last barrier against fission product release to the environment. Containment integrity is endangered by several physical phenomena, especially highly transient phenomena following high-pressure reactor pressure vessel failure (like direct containment heating or steam explosions which can lead to early containment failure), hydrogen combustion, quasi-static over-pressure, temperature failure of penetrations, and basemat penetration by core melt. Each of these challenges can be counteracted by dedicated severe accident mitigation hardware, like dedicated primary circuit depressurization valves, hydrogen recombiners or igniters, filtered containment venting, containment cooling systems, and core melt stabilization systems (if available). However, besides their main safety function these systems often have also secondary effects that need to be considered. Filtered containment venting causes (though limited) fission product release into the environment, primary circuit depressurization leads to loss of coolant, and an ex-vessel core melt stabilization system as well as hydrogen igniters can generate high pressure and temperature loads on the containment. To ensure that during a severe accident any available systems are used to their full beneficial extent while minimizing their potential negative impact, AREVA has implemented a severe accident management for German nuclear power plants. This concept makes use of extensive numerical simulations of the entire plant, quantifying the impact of system activations (operational systems, safety systems, as well as dedicated severe accident systems) on the accident progression for various scenarios. Based on the knowledge gained, a handbook has been developed, allowing the plant operators to understand the current state of the plant (supported by computational aids), to predict
Optimal Protection Coordination for Microgrid under Different Operating Modes
Directory of Open Access Journals (Sweden)
Ming-Ta Yang
2013-01-01
Full Text Available Significant consequences result when a microgrid is connected to a distribution system. This study discusses the impacts of bolted three-phase faults and bolted single line-to-ground faults on the protection coordination of a distribution system connected by a microgrid which operates in utility-only mode or in grid-connected mode. The power system simulation software is used to build the test system. The linear programming method is applied to optimize the coordination of relays, and the relays coordination simulation software is used to verify if the coordination time intervals (CTIs of the primary/backup relay pairs are adequate. In addition, this study also proposes a relays protection coordination strategy when the microgrid operates in islanding mode during a utility power outage. Because conventional CO/LCO relays are not capable of detecting high impedance fault, intelligent electrical device (IED combined with wavelet transformer and neural network is proposed to accurately detect high impedance fault and identify the fault phase.
SIMULTANEOUS SCHEDULING AND OPERATIONAL OPTIMIZATION OF MULTIPRODUCT, CYCLIC CONTINUOUS PLANTS
Directory of Open Access Journals (Sweden)
A. Alle
2002-03-01
Full Text Available The problems of scheduling and optimization of operational conditions in multistage, multiproduct continuous plants with intermediate storage are simultaneously addressed. An MINLP model, called TSPFLOW, which is based on the TSP formulation for product sequencing, is proposed to schedule the operation of such plants. TSPFLOW yields a one-order-of-magnitude CPU time reduction as well as the solution of instances larger than those formerly reported (Pinto and Grossmann, 1994. Secondly, processing rates and yields are introduced as additional optimization variables in order to state the simultaneous problem of scheduling with operational optimization. Results show that trade-offs are very complex and that the development of a straightforward (rule of thumb method to optimally schedule the operation is less effective than the proposed approach.
SIMULTANEOUS SCHEDULING AND OPERATIONAL OPTIMIZATION OF MULTIPRODUCT, CYCLIC CONTINUOUS PLANTS
Directory of Open Access Journals (Sweden)
Alle A.
2002-01-01
Full Text Available The problems of scheduling and optimization of operational conditions in multistage, multiproduct continuous plants with intermediate storage are simultaneously addressed. An MINLP model, called TSPFLOW, which is based on the TSP formulation for product sequencing, is proposed to schedule the operation of such plants. TSPFLOW yields a one-order-of-magnitude CPU time reduction as well as the solution of instances larger than those formerly reported (Pinto and Grossmann, 1994. Secondly, processing rates and yields are introduced as additional optimization variables in order to state the simultaneous problem of scheduling with operational optimization. Results show that trade-offs are very complex and that the development of a straightforward (rule of thumb method to optimally schedule the operation is less effective than the proposed approach.
Optimal scope of supply chain network & operations design
Ma, N.
2014-01-01
The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are
Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms
Cao, Ming; Lu, Ming; Zhang, Jian-Ping
2004-01-01
This work presents a new approach for concrete plant operations optimization by combining a ready mixed concrete (RMC) production simulation tool (called HKCONSIM) with a genetic algorithm (GA) based optimization procedure. A revamped HKCONSIM computer system can be used to automate the simulation
Synergy optimization and operation management on syndicate complementary knowledge cooperation
Tu, Kai-Jan
2014-10-01
The number of multi enterprises knowledge cooperation has grown steadily, as a result of global innovation competitions. I have conducted research based on optimization and operation studies in this article, and gained the conclusion that synergy management is effective means to break through various management barriers and solve cooperation's chaotic systems. Enterprises must communicate system vision and access complementary knowledge. These are crucial considerations for enterprises to exert their optimization and operation knowledge cooperation synergy to meet global marketing challenges.
Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming
DEFF Research Database (Denmark)
Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano
2018-01-01
An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...
Application of optimal interation strategies to diffusion theory calculations
International Nuclear Information System (INIS)
Jones, R.B.
1978-01-01
The geometric interpretation of optimal (minimum computational time) iteration strategies is applied to one- and two-group, two-dimensional diffusion-theory calculations. The method is a ''spectral/time balance'' technique which weighs the convergence enhancement of the inner iteration procedure with that of the outer iteration loop and the time required to reconstruct the source. The diffusion-theory option of the discrete-ordinates transport code DOT3.5 was altered to incorporate the theoretical inner/outer decision logic. For the two-dimensional configuration considered, the optimal strategies reduced the total number of iterations performed for a given error criterion
Optimization Under Uncertainty for Wake Steering Strategies: Preprint
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-05-01
Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.
Core design and operation optimization methods based on time-dependent perturbation theory
International Nuclear Information System (INIS)
Greenspan, E.
1983-08-01
A general approach for the optimization of nuclear reactor core design and operation is outlined; it is based on two cornerstones: a newly developed time-dependent (or burnup-dependent) perturbation theory for nonlinear problems and a succesive iteration technique. The resulting approach is capable of handling realistic reactor models using computational methods of any degree of sophistication desired, while accounting for all the constraints imposed. Three general optimization strategies, different in the way for handling the constraints, are formulated. (author)
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Dragicevic, Tomislav; Meng, Lexuan
2016-01-01
Next generation power management at all scales is highly relying on the efficient scheduling and operation of different energy sources to maximize efficiency and utility. The ability to schedule and modulate the energy storage options within energy systems can also lead to more efficient use...... of the generating units. This optimal planning and operation management strategy becomes increasingly important for off-grid systems that operate independently of the main utility, such as microgrids or power systems on marine vessels. This work extends the principles of optimal planning and economic dispatch...... for the proposed plan is derived based on the solution from a mixed-integer nonlinear programming (MINLP) problem. Simulation results showed that including well-sized energy storage options together with optimal operation management of generating units can improve the economic operation of the test system while...
Optimal football strategies: AC Milan versus FC Barcelona
Papahristodoulou, Christos
2012-01-01
In a recent UEFA Champions League game between AC Milan and FC Barcelona, played in Italy (final score 2-3), the collected match statistics, classified into four offensive and two defensive strategies, were in favour of FC Barcelona (by 13 versus 8 points). The aim of this paper is to examine to what extent the optimal game strategies derived from some deterministic, possibilistic, stochastic and fuzzy LP models would improve the payoff of AC Milan at the cost of FC Barcelona.
Optimal sizing and operation of energy storage systems considering long term assessment
Directory of Open Access Journals (Sweden)
Gerardo Guerra
2018-01-01
Full Text Available This paper proposes a procedure for estimating the optimal sizing of Photovoltaic Generators and Energy Storage units when they are operated from the utility’s perspective. The goal is to explore the potential improvement on the overall operating conditions of the distribution system to which the Generators and Storage units will be connected. Optimization is conducted by means of a General Parallel Genetic Algorithm that seeks to maximize the technical benefits for the distribution system. The paper proposes an operation strategy for Energy Storage units based on the daily variation of load and generation; the operation strategy is optimized for an evaluation period of one year using hourly power curves. The construction of the yearly Storage operation curve results in a high-dimension optimization problem; as a result, different day-classification methods are applied in order to reduce the dimension of the optimization. Results show that the proposed approach is capable of producing significant improvements in system operating conditions and that the best performance is obtained when the day-classification is based on the similarity among daily power curves.
Optimal hysteretic control for a BMAP/SM/1/N queue with two operation modes
Directory of Open Access Journals (Sweden)
Alexander N. Dudin
2000-01-01
Full Text Available We consider BMAP/SM/1 type queueing system with finite buffer of size N. The system has two operation modes, which are characterized by the matrix generating function of BMAP-input, the kernel of the semi-Markovian service process, and utilization cost. An algorithm for determining the optimal hysteresis strategy is presented.
Hydrocarbon control strategies for gasoline marketing operations
Energy Technology Data Exchange (ETDEWEB)
Norton, R.L.; Sakaida, R.R.; Yamada, M.M.
1978-05-01
This informational document provides basic and current descriptions of gasoline marketing operations and methods that are available to control hydrocarbon emissions from these operations. The three types of facilities that are described are terminals, bulk plants, and service stations. Operational and business trends are also discussed. The potential emissions from typical facilities, including transport trucks, are given. The operations which lead to emissions from these facilities include (1) gasoline storage, (2) gasoline loading at terminals and bulk plants, (3) gasoline delivery to bulk plants and service stations, and (4) the refueling of vehicles at service stations. Available and possible methods for controlling emissions are described with their estimated control efficiencies and costs. This report also includes a bibliography of references cited in the text, and supplementary sources of information.
Optimal decentralized valley-filling charging strategy for electric vehicles
International Nuclear Information System (INIS)
Zhang, Kangkang; Xu, Liangfei; Ouyang, Minggao; Wang, Hewu; Lu, Languang; Li, Jianqiu; Li, Zhe
2014-01-01
Highlights: • An implementable charging strategy is developed for electric vehicles connected to a grid. • A two-dimensional pricing scheme is proposed to coordinate charging behaviors. • The strategy effectively works in decentralized way but achieves the systematic valley filling. • The strategy allows device-level charging autonomy, and does not require a bidirectional communication/control network. • The strategy can self-correct when confronted with adverse factors. - Abstract: Uncoordinated charging load of electric vehicles (EVs) increases the peak load of the power grid, thereby increasing the cost of electricity generation. The valley-filling charging scenario offers a cheaper alternative. This study proposes a novel decentralized valley-filling charging strategy, in which a day-ahead pricing scheme is designed by solving a minimum-cost optimization problem. The pricing scheme can be broadcasted to EV owners, and the individual charging behaviors can be indirectly coordinated. EV owners respond to the pricing scheme by autonomously optimizing their individual charge patterns. This device-level response induces a valley-filling effect in the grid at the system level. The proposed strategy offers three advantages: coordination (by the valley-filling effect), practicality (no requirement for a bidirectional communication/control network between the grid and EV owners), and autonomy (user control of EV charge patterns). The proposed strategy is validated in simulations of typical scenarios in Beijing, China. According to the results, the strategy (1) effectively achieves the valley-filling charging effect at 28% less generation cost than the uncoordinated charging strategy, (2) is robust to several potential affecters of the valley-filling effect, such as (system-level) inaccurate parameter estimation and (device-level) response capability and willingness (which cause less than 2% deviation in the minimal generation cost), and (3) is compatible with
Energy evaluation of optimal control strategies for central VWV chiller systems
International Nuclear Information System (INIS)
Jin Xinqiao; Du Zhimin; Xiao Xiaokun
2007-01-01
Under various conditions, the actual load of the heating, ventilation and air conditioning (HVAC) systems is less than it is originally designed in most operation periods. To save energy and to optimize the controls for chilling systems, the performance of variable water volume (VWV) systems and characteristics of control systems are analyzed, and three strategies are presented and tested based on simulation in this paper. Energy evaluation for the three strategies shows that they can save energy to some extent, and there is potential remained. To minimize the energy consumption of chilling system, the setpoints of controls of supply chilled water temperature and supply head of secondary pump should be optimized simultaneously
Coordinating decentralized optimization of truck and shovel mining operations
Energy Technology Data Exchange (ETDEWEB)
Cheng, R.; Fraser Forbes, J. [Alberta Univ., Edmonton, AB (Canada). Dept. of Chemical and Materials Engineering; San Yip, W. [Suncor Energy, Fort McMurray, AB (Canada)
2006-07-01
Canada's oil sands contain the largest known reserve of oil in the world. Oil sands mining uses 3 functional processes, ore hauling, overburden removal and mechanical maintenance. The industry relies mainly on truck-and-shovel technology in its open-pit mining operations which contributes greatly to the overall mining operation cost. Coordination between operating units is crucial for achieving an enterprise-wide optimal operation level. Some of the challenges facing the industry include multiple or conflicting objectives such as minimizing the use of raw materials and energy while maximizing production. The large sets of constraints that define the feasible domain pose as challenge, as does the uncertainty in system parameters. One solution lies in assigning truck resources to various activities. This fully decentralized approach would treat the optimization of ore production, waste removal and equipment maintenance independently. It was emphasized that mine-wide optimal operation can only be achieved by coordinating ore hauling and overburden removal processes. For that reason, this presentation proposed a coordination approach for a decentralized optimization system. The approach is based on the Dantzig-Wolfe decomposition and auction-based methods that have been previously used to decompose large-scale optimization problems. The treatment of discrete variables and coordinator design was described and the method was illustrated with a simple truck and shovel mining simulation study. The approach can be applied to a wide range of applications such as coordinating decentralized optimal control systems and scheduling. 16 refs., 3 tabs., 2 figs.
Analysis of Optimal Operation of an Energy Integrated Distillation Plant
DEFF Research Database (Denmark)
Li, Hong Wen; Hansen, C.A.; Gani, Rafiqul
2003-01-01
The efficiency of manufacturing systems can be significantly increased through diligent application of control based on mathematical models thereby enabling more tight integration of decision making with systems operation. In the present paper analysis of optimal operation of an energy integrated...
Nickel-Cadmium Battery Operation Management Optimization Using Robust Design
Blosiu, Julian O.; Deligiannis, Frank; DiStefano, Salvador
1996-01-01
In recent years following several spacecraft battery anomalies, it was determined that managing the operational factors of NASA flight NiCd rechargeable battery was very important in order to maintain space flight battery nominal performance. The optimization of existing flight battery operational performance was viewed as something new for a Taguchi Methods application.
Development of Optimal Stressor Scenarios for New Operational Energy Systems
2017-12-01
OPTIMAL STRESSOR SCENARIOS FOR NEW OPERATIONAL ENERGY SYSTEMS by Geoffrey E. Fastabend December 2017 Thesis Advisor: Alejandro S... ENERGY SYSTEMS 5. FUNDING NUMBERS 6. AUTHOR(S) Geoffrey E. Fastabend 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School...developed and tested simulation model for operational energy related systems in order to develop better stressor scenarios for acceptance testing
International Nuclear Information System (INIS)
Jamalipour, Mostafa; Sayareh, Reza; Gharib, Morteza; Khoshahval, Farrokh; Karimi, Mahmood Reza
2013-01-01
Highlights: ► A new method called QPSO-DM is applied to BNPP in-core fuel management optimization. ► It is found that QPSO-DM performs better than PSO and QPSO. ► This method provides a permissible arrangement for optimum loading pattern. - Abstract: This paper presents a new method using Quantum Particle Swarm Optimization with Differential Mutation operator (QPSO-DM) for optimizing WWER-1000 core fuel management. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have shown good performance on in-core fuel management optimization (ICFMO). The objective of this paper is to show that QPSO-DM performs very well and is comparable to PSO and Quantum Particle Swarm Optimization (QPSO). Most of the strategies for ICFMO are based on maximizing multiplication factor (k eff ) to increase cycle length and minimizing power peaking factor (P q ) in order to improve fuel integrity. PSO, QPSO and QPSO-DM have been implemented to fulfill these requirements for the first operating cycle of WWER-1000 Bushehr Nuclear Power Plant (BNPP). The results show that QPSO-DM performs better than the others. A program has been written in MATLAB to map PSO, QPSO and QPSO-DM for loading pattern optimization. WIMS and CITATION have been used to simulate reactor core for neutronic calculations
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
Optimal portfolio strategies under a shortfall constraint | Akume ...
African Journals Online (AJOL)
We impose dynamically, a shortfall constraint in terms of Tail Conditional Expectation on the portfolio selection problem in continuous time, in order to obtain optimal strategies. The nancial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange ...
Validation of optimization strategies using the linear structured production chains
Kusiak, Jan; Morkisz, Paweł; Oprocha, Piotr; Pietrucha, Wojciech; Sztangret, Łukasz
2017-06-01
Different optimization strategies applied to sequence of several stages of production chains were validated in this paper. Two benchmark problems described by ordinary differential equations (ODEs) were considered. A water tank and a passive CR-RC filter were used as the exemplary objects described by the first and the second order differential equations, respectively. Considered in the work optimization problems serve as the validators of strategies elaborated by the Authors. However, the main goal of research is selection of the best strategy for optimization of two real metallurgical processes which will be investigated in an on-going projects. The first problem will be the oxidizing roasting process of zinc sulphide concentrate where the sulphur from the input concentrate should be eliminated and the minimal concentration of sulphide sulphur in the roasted products has to be achieved. Second problem will be the lead refining process consisting of three stages: roasting to the oxide, oxide reduction to metal and the oxidizing refining. Strategies, which appear the most effective in considered benchmark problems will be candidates for optimization of the mentioned above industrial processes.
Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Yuan Zou
2013-01-01
Full Text Available A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.
Hierarchical Control for Optimal and Distributed Operation of Microgrid Systems
DEFF Research Database (Denmark)
Meng, Lexuan
manages the power flow with external grids, while the economic and optimal operation of MGs is not guaranteed by applying the existing schemes. Accordingly, this project dedicates to the study of real-time optimization methods for MGs, including the review of optimization algorithms, system level...... mathematical modeling, and the implementation of real-time optimization into existing hierarchical control schemes. Efficiency enhancement in DC MGs and optimal unbalance compensation in AC MGs are taken as the optimization objectives in this project. Necessary system dynamic modeling and stability analysis......, a discrete-time domain modeling method is proposed to establish an accurate system level model. Taking into account the different sampling times of real world plant, digital controller and communication devices, the system is modeled with these three parts separately, and with full consideration...
International Nuclear Information System (INIS)
Porteus, E.
1982-01-01
The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained
Development of an evaluation method for optimization of maintenance strategy in commercial plant
International Nuclear Information System (INIS)
Ito, Satoshi; Shiraishi, Natsuki; Yuki, Kazuhisa; Hashizume, Hidetoshi
2006-01-01
In this study, a new simulation method is developed for optimization of maintenance strategy in NPP as a multiple-objective optimization problem (MOP). The result of operation is evaluated as the average of the following three measures in 3,000 trials: Cost of Electricity (COE) as economic risk, Frequency of unplanned shutdown as plant reliability, and Unavailability of Regular Service System (RSS) and Engineering Safety Features (ESF) as safety measures. The following maintenance parameters are considered to evaluate several risk in plant operation by changing maintenance strategy: planned outage cycle, surveillance cycle, major inspection cycle, and surveillance cycle depending on the value of Fussel-Vesely importance measure. By using the Decision-Making method based on AHP, there are individual tendencies depending on individual decision-maker. Therefore this study could be useful for resolving the problem of maintenance optimization as a MOP. (author)
Growth or reproduction: emergence of an evolutionary optimal strategy
International Nuclear Information System (INIS)
Grilli, J; Suweis, S; Maritan, A
2013-01-01
Modern ecology has re-emphasized the need for a quantitative understanding of the original ‘survival of the fittest theme’ based on analysis of the intricate trade-offs between competing evolutionary strategies that characterize the evolution of life. This is key to the understanding of species coexistence and ecosystem diversity under the omnipresent constraint of limited resources. In this work we propose an agent-based model replicating a community of interacting individuals, e.g. plants in a forest, where all are competing for the same finite amount of resources and each competitor is characterized by a specific growth–reproduction strategy. We show that such an evolution dynamics drives the system towards a stationary state characterized by an emergent optimal strategy, which in turn depends on the amount of available resources the ecosystem can rely on. We find that the share of resources used by individuals is power-law distributed with an exponent directly related to the optimal strategy. The model can be further generalized to devise optimal strategies in social and economical interacting systems dynamics. (paper)
Operation strategy analysis of a geothermal step utilization heating system
International Nuclear Information System (INIS)
Zheng, Guozhong; Li, Feng; Tian, Zhe; Zhu, Neng; Li, Qianru; Zhu, Han
2012-01-01
Geothermal energy has been successfully applied in many district heating systems. In order to promote better use of geothermal energy, it is important to analyze the operation strategy of geothermal heating system. This study proposes a comprehensive and systematic operation strategy for a geothermal step utilization heating system (GSUHS). Calculation models of radiator heating system (RHS), radiant floor heating system (RFHS), heat pump (HP), gas boiler (GB), plate heat exchanger (PHE) and pump are first established. Then the operation strategy of the GSUHS is analyzed with the aim to substantially reduce the conventional energy consumption of the whole system. Finally, the energy efficiency and geothermal tail water temperature are analyzed. With the operation strategy in this study, the geothermal energy provides the main heating amount for the system. The heating seasonal performance factor is 15.93. Compared with coal-fired heating, 75.1% of the standard coal equivalent can be saved. The results provide scientific guidance for the application of an operation strategy for a geothermal step utilization heating system. -- Highlights: ► We establish calculation models for the geothermal step utilization heating system. ► We adopt minimal conventional energy consumption to determine the operation strategy. ► The geothermal energy dominates the heating quantity of the whole system. ► The utilization efficiency of the geothermal energy is high. ► The results provide guidance to conduct operation strategy for scientific operation.
Online gaming for learning optimal team strategies in real time
Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.
2010-04-01
This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.
Artificial root foraging optimizer algorithm with hybrid strategies
Directory of Open Access Journals (Sweden)
Yang Liu
2017-02-01
Full Text Available In this work, a new plant-inspired optimization algorithm namely the hybrid artificial root foraging optimizion (HARFO is proposed, which mimics the iterative root foraging behaviors for complex optimization. In HARFO model, two innovative strategies were developed: one is the root-to-root communication strategy, which enables the individual exchange information with each other in different efficient topologies that can essentially improve the exploration ability; the other is co-evolution strategy, which can structure the hierarchical spatial population driven by evolutionary pressure of multiple sub-populations that ensure the diversity of root population to be well maintained. The proposed algorithm is benchmarked against four classical evolutionary algorithms on well-designed test function suites including both classical and composition test functions. Through the rigorous performance analysis that of all these tests highlight the significant performance improvement, and the comparative results show the superiority of the proposed algorithm.
Strategies to improve sleep during extended search and rescue operations.
Jenkins, Jennifer Lee; Fredericksen, Kim; Stone, Roger; Tang, Nelson
2007-01-01
This study investigated strategies to improve sleeping conditions during search and rescue operations during disaster response. Forty members of the Montgomery County (Maryland) Urban Search and Rescue Team were surveyed for individual sleep habits and sleeping aids used during extended deployments. Team members were also asked to suggest methods to improve sleep on future deployments. The average amount of sleep during field operations was 5.4 hours with a range of 4-8 hours. Eight percent surveyed would prefer another schedule besides the 12-hour work day, all of whom proposed three 8-hour shifts. Fifteen percent of participants were interested in a pharmacological sleeping aid. Fifty percent of search and rescue members interviewed would consider using nonpharmacological sleeping aids. Furthermore, 40% of participants stated they had successfully devised self-employed methods of sleep aids for previous deployments, such as ear plugs, massage, mental imagery, personal routines, music and headphones, reading, and blindfolds. This study suggests that availability of both pharmacological and nonpharmacological sleeping aids to search and rescue workers via the team cache could impact the quantity of sleep. Further investigation into methods of optimizing sleep during field missions could theoretically show enhanced performance through various aspects of missions including mitigation of errors, improved productivity, and improved overall physiological and emotional well-being of search and rescue personnel.
Fuzzy multiobjective models for optimal operation of a hydropower system
Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.
2013-06-01
Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.
A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy
Directory of Open Access Journals (Sweden)
Guohua Wu
2014-01-01
Full Text Available Although Particle Swarm Optimization (PSO has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.
Reservoir Operating Rule Optimization for California's Sacramento Valley
Directory of Open Access Journals (Sweden)
Timothy Nelson
2016-03-01
Full Text Available doi: http://dx.doi.org/10.15447/sfews.2016v14iss1art6Reservoir operating rules for water resource systems are typically developed by combining intuition, professional discussion, and simulation modeling. This paper describes a joint optimization–simulation approach to develop preliminary economically-based operating rules for major reservoirs in California’s Sacramento Valley, based on optimized results from CALVIN, a hydro-economic optimization model. We infer strategic operating rules from the optimization model results, including storage allocation rules to balance storage among multiple reservoirs, and reservoir release rules to determine monthly release for individual reservoirs. Results show the potential utility of considering previous year type on water availability and various system and sub-system storage conditions, in addition to normal consideration of local reservoir storage, season, and current inflows. We create a simple simulation to further refine and test the derived operating rules. Optimization model results show particular insights for balancing the allocation of water storage among Shasta, Trinity, and Oroville reservoirs over drawdown and refill seasons, as well as some insights for release rules at major reservoirs in the Sacramento Valley. We also discuss the applicability and limitations of developing reservoir operation rules from optimization model results.
Operation optimization of distributed generation using artificial intelligent techniques
Directory of Open Access Journals (Sweden)
Mahmoud H. Elkazaz
2016-06-01
Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.
Verification and synthesis of optimal decision strategies for complex systems
Energy Technology Data Exchange (ETDEWEB)
Summers, S. J.
2013-07-01
that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an obstacle set during each time step preceding the target hitting time. In contrast with the general reach-avoid formulation, which assumes that the target and obstacle sets are constant and deterministic, we allow these sets to be both time-varying and probabilistic. An optimal reach-avoid control policy is derived as the solution to an optimal control problem via dynamic programming. A framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents follows. We consider a zero sum game formulation of the probabilistic reach-avoid problem, in which the control objective is to maximize the probability of reaching a desired subset of the hybrid state space, while avoiding an unsafe set, subject to the worst case behavior of a rational adversary. Theoretical results are provided on a dynamic programming algorithm for computing the maximal reach-avoid probability under the worst-case adversary strategy, as well as the existence of a maxmin control policy that achieves this probability. Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic that has become a standard for expressing temporal properties of finite state Markov chains in the context of automated model checking. Here we consider PCTL for non countable-space Markov chains, and we show that there is a substantial affinity between certain of its operators and problems of dynamic programming. We prove some basic properties of the solutions to the latter. The dissertation concludes with a collection of computational examples in the areas of ecology, robotics, aerospace, and finance. (author)
Verification and synthesis of optimal decision strategies for complex systems
International Nuclear Information System (INIS)
Summers, S. J.
2013-01-01
that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an obstacle set during each time step preceding the target hitting time. In contrast with the general reach-avoid formulation, which assumes that the target and obstacle sets are constant and deterministic, we allow these sets to be both time-varying and probabilistic. An optimal reach-avoid control policy is derived as the solution to an optimal control problem via dynamic programming. A framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents follows. We consider a zero sum game formulation of the probabilistic reach-avoid problem, in which the control objective is to maximize the probability of reaching a desired subset of the hybrid state space, while avoiding an unsafe set, subject to the worst case behavior of a rational adversary. Theoretical results are provided on a dynamic programming algorithm for computing the maximal reach-avoid probability under the worst-case adversary strategy, as well as the existence of a maxmin control policy that achieves this probability. Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic that has become a standard for expressing temporal properties of finite state Markov chains in the context of automated model checking. Here we consider PCTL for non countable-space Markov chains, and we show that there is a substantial affinity between certain of its operators and problems of dynamic programming. We prove some basic properties of the solutions to the latter. The dissertation concludes with a collection of computational examples in the areas of ecology, robotics, aerospace, and finance. (author)
DEFF Research Database (Denmark)
Liu, Zhou; Chen, Zhe; Sun, Haishun Sun
2012-01-01
the runtime emergent states of related system component. Based on sensitivity analysis between the relay operation margin and power system state variables, an optimal load shedding strategy is applied to adjust the emergent states timely before the unwanted relay operation. Load dynamics is also taken...... into account to compensate load shedding amount calculation. And the multi-agent technology is applied for the whole strategy implementation. A test system is built in real time digital simulator (RTDS) and has demonstrated the effectiveness of the proposed strategy.......In order to prevent long term voltage instability and induced cascading events, a load shedding strategy based on the sensitivity of relay operation margin to load powers is discussed and proposed in this paper. The operation margin of critical impedance backup relay is defined to identify...
Comparison of operation optimization methods in energy system modelling
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2013-01-01
In areas with large shares of Combined Heat and Power (CHP) production, significant introduction of intermittent renewable power production may lead to an increased number of operational constraints. As the operation pattern of each utility plant is determined by optimization of economics......, possibilities for decoupling production constraints may be valuable. Introduction of heat pumps in the district heating network may pose this ability. In order to evaluate if the introduction of heat pumps is economically viable, we develop calculation methods for the operation patterns of each of the used...... energy technologies. In the paper, three frequently used operation optimization methods are examined with respect to their impact on operation management of the combined technologies. One of the investigated approaches utilises linear programming for optimisation, one uses linear programming with binary...
On the robust optimization to the uncertain vaccination strategy problem
International Nuclear Information System (INIS)
Chaerani, D.; Anggriani, N.; Firdaniza
2014-01-01
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented
On the robust optimization to the uncertain vaccination strategy problem
Energy Technology Data Exchange (ETDEWEB)
Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id [Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Padjadjaran Indonesia, Jalan Raya Bandung Sumedang KM 21 Jatinangor Sumedang 45363 (Indonesia)
2014-02-21
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.
Generating optimized stochastic power management strategies for electric car components
Energy Technology Data Exchange (ETDEWEB)
Fruth, Matthias [TraceTronic GmbH, Dresden (Germany); Bastian, Steve [Technische Univ. Dresden (Germany)
2012-11-01
With the increasing prevalence of electric vehicles, reducing the power consumption of car components becomes a necessity. For the example of a novel traffic-light assistance system, which makes speed recommendations based on the expected length of red-light phases, power-management strategies are used to control under which conditions radio communication, positioning systems and other components are switched to low-power (e.g. sleep) or high-power (e.g. idle/busy) states. We apply dynamic power management, an optimization technique well-known from other domains, in order to compute energy-optimal power-management strategies, sometimes resulting in these strategies being stochastic. On the example of the traffic-light assistant, we present a MATLAB/Simulink-implemented framework for the generation, simulation and formal analysis of optimized power-management strategies, which is based on this technique. We study capabilities and limitations of this approach and sketch further applications in the automotive domain. (orig.)
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Examples of radiation protection optimization in design and operation
International Nuclear Information System (INIS)
Gonzalez, A.J.; Palacios, E.; Curti, A.; Agatiello, O.; Majchrzak, J.
1982-01-01
The practical use of the requirement of optimization of radiological protection is presented. Application examples for designing ventilation systems and for maintenance operations of nuclear plants are given. A method is developed for the application of the optimization requirement to the design of ventilation systems in contaminated environments. Representative values of the main parameters are presented and their relevant features are discussed. A practical example shows actual results for a radioisotope production plant. Causes influencing collective doses incurred by the workers during maintenance operations are analyzed. A method is presented for the optimization of both the level of training of personnel and the apportionment of individual doses. As an example, this methodology is applied to the maintenance operations in a nuclear power plant. (author)
Operational optimization in the downstream; Otimizacao operacional no downstream
Energy Technology Data Exchange (ETDEWEB)
Silberman, Luis; Cunha, Filipe Silveira Ramos da [Petroleo Ipiranga, Porto Alegre, RS (Brazil)
2004-07-01
On the present competitive down stream's market, there is a great necessity of optimization aiming to guarantee the best price and quality of our clients. Our goal is to attend these expectations while we guarantee an efficient operation. The greatest question is how far we are from the ideal model. This way, a lot of projects have been executed during the last years aiming the operational optimization of all our activities. We divide the projects in 4 areas: Logistic (new modals distribution), Transport (transport optimization - quality and more deliveries with less trucks), Client Support (Internet Ipiranga and Support Center), Distribution Terminals Productivity (automation and environment). This work intend to present our ideal, perfect and complete Downstream Operation model. We will talk about how close we are of this ideal model and we will present the projects that we had already developed and implanted on the automation of the terminals and the logistics area. (author)
An optimization strategy for a biokinetic model of inhaled radionuclides
International Nuclear Information System (INIS)
Shyr, L.J.; Griffith, W.C.; Boecker, B.B.
1991-01-01
Models for material disposition and dosimetry involve predictions of the biokinetics of the material among compartments representing organs and tissues in the body. Because of a lack of human data for most toxicants, many of the basic data are derived by modeling the results obtained from studies using laboratory animals. Such a biomathematical model is usually developed by adjusting the model parameters to make the model predictions match the measured retention and excretion data visually. The fitting process can be very time-consuming for a complicated model, and visual model selections may be subjective and easily biased by the scale or the data used. Due to the development of computerized optimization methods, manual fitting could benefit from an automated process. However, for a complicated model, an automated process without an optimization strategy will not be efficient, and may not produce fruitful results. In this paper, procedures for, and implementation of, an optimization strategy for a complicated mathematical model is demonstrated by optimizing a biokinetic model for 144Ce in fused aluminosilicate particles inhaled by beagle dogs. The optimized results using SimuSolv were compared to manual fitting results obtained previously using the model simulation software GASP. Also, statistical criteria provided by SimuSolv, such as likelihood function values, were used to help or verify visual model selections
Optimal synthesis and operation of advanced energy supply systems for standard and domotic home
International Nuclear Information System (INIS)
Buoro, Dario; Casisi, Melchiorre; Pinamonti, Piero; Reini, Mauro
2012-01-01
Highlights: ► Definition of an optimization model for a home energy supply system. ► Optimization of the energy supply system for standard and domotic home. ► Strong improvement can be achieved adopting the optimal system in standard and domotic home. ► The improvements are consistent if supply side and demand side strategies are applied together. ► Solutions with internal combustion engines are less sensible to market price of electricity and gas. - Abstract: The paper deals with the optimization of an advanced energy supply systems for two dwellings: a standard home and an advanced domotic home, where some demand side energy saving strategies have been implemented. In both cases the optimal synthesis, design and operation of the whole energy supply system have been obtained and a sensitivity analysis has been performed, by introducing different economic constraints. The optimization model is based on a Mixed Integer Linear Program (MILP) and includes different kinds of small-scale cogenerators, geothermal heat pumps, boilers, heat storages, solar thermal and photovoltaic panels. In addition, absorption machines, supplied with cogenerated heat, can be used instead of conventional electrical chiller to face the cooling demand. The aim of the analysis is to address the question if advanced demand strategies and supply strategies have to be regarded as alternatives, or if they have to be simultaneously applied, in order to obtain the maximum energy and economic benefit.
Operating cycle optimization for a Magnus effect-based airborne wind energy system
International Nuclear Information System (INIS)
Milutinović, Milan; Čorić, Mirko; Deur, Joško
2015-01-01
Highlights: • Operating cycle of a Magnus effect-based AWE system has been optimized. • The cycle trajectory should be vertical and far from the ground based generator. • Vertical trajectory provides high pulling force that drives the generator. • Large distance from the generator is required for the feasibility of the cycle. - Abstract: The paper presents a control variables optimization study for an airborne wind energy production system. The system comprises an airborne module in the form of a buoyant, rotating cylinder, whose rotation in a wind stream induces the Magnus effect-based aerodynamic lift. Through a tether, the airborne module first drives the generator fixed on the ground, and then the generator becomes a motor that lowers the airborne module. The optimization is aimed at maximizing the average power produced at the generator during a continuously repeatable operating cycle. The control variables are the generator-side rope force and the cylinder rotation speed. The optimization is based on a multi-phase problem formulation, where operation is divided into ascending and descending phases, with free boundary conditions and free cycle duration. The presented simulation results show that significant power increase can be achieved by using the obtained optimal operating cycle instead of the initial, empirically based operation control strategy. A brief analysis is also given to provide a physical interpretation of the optimal cycle results
Automatic CT simulation optimization for radiation therapy: A general strategy.
Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa
2014-03-01
In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes
Automatic CT simulation optimization for radiation therapy: A general strategy
Energy Technology Data Exchange (ETDEWEB)
Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M.; Mutic, Sasa [Department of Radiation Oncology, Washington University, St. Louis, Missouri 63110 (United States); Yu, Lifeng [Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 (United States); Anastasio, Mark A. [Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63110 (United States); Low, Daniel A. [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States)
2014-03-15
Purpose: In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. Methods: The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Results: Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube
Economic Optimization Analysis of Chengdu Electric Community Bus Operation
Yidong, Wang; Yun, Cai; Zhengping, Tan; Xiong, Wan
2018-03-01
In recent years, the government has strongly supported and promoted electric vehicles and has given priority to demonstration and popularization in the field of public transport. The economy of public transport operations has drawn increasing attention. In this paper, Chengdu wireless charging pure electric community bus is used as the research object, the battery, air conditioning, driver’s driving behavior and other economic influence factors were analyzed, and optimizing the operation plan through case data analysis, through the reasonable battery matching and mode of operation to help businesses effectively save operating costs and enhance economic efficiency.
Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation
Janahiraman, Tiagrajah V.; Ahmad, Nooraziah; Hani Nordin, Farah
2018-04-01
The CNC machine is controlled by manipulating cutting parameters that could directly influence the process performance. Many optimization methods has been applied to obtain the optimal cutting parameters for the desired performance function. Nonetheless, the industry still uses the traditional technique to obtain those values. Lack of knowledge on optimization techniques is the main reason for this issue to be prolonged. Therefore, the simple yet easy to implement, Optimal Cutting Parameters Selection System is introduced to help the manufacturer to easily understand and determine the best optimal parameters for their turning operation. This new system consists of two stages which are modelling and optimization. In modelling of input-output and in-process parameters, the hybrid of Extreme Learning Machine and Particle Swarm Optimization is applied. This modelling technique tend to converge faster than other artificial intelligent technique and give accurate result. For the optimization stage, again the Particle Swarm Optimization is used to get the optimal cutting parameters based on the performance function preferred by the manufacturer. Overall, the system can reduce the gap between academic world and the industry by introducing a simple yet easy to implement optimization technique. This novel optimization technique can give accurate result besides being the fastest technique.
Strategies towards an optimized use of the shallow geothermal potential
Schelenz, S.; Firmbach, L.; Kalbacher, T.; Goerke, U.; Kolditz, O.; Dietrich, P.; Vienken, T.
2013-12-01
Thermal use of the shallow subsurface for heat generation, cooling and thermal energy storage is increasingly gaining importance in reconsideration of future energy supplies, e.g. in the course of German energy transition, with application shifting from isolated to intensive use. The planning and dimensioning of (geo-)thermal applications is strongly influenced by the availability of exploration data. Hence, reliable site-specific dimensioning of systems for the thermal use of the shallow subsurface will contribute to an increase in resource efficiency, cost reduction during installation and operation, as well as reduction of environmental impacts and prevention of resource over-exploitation. Despite large cumulative investments that are being made for the utilization of the shallow thermal potential, thermal energy is in many cases exploited without prior on-site exploration and investigation of the local geothermal potential, due to the lack of adequate and cost-efficient exploration techniques. We will present new strategies for an optimized utilization of urban thermal potential, showcased at a currently developed residential neighborhood with high demand for shallow geothermal applications, based on a) enhanced site characterization and b) simulation of different site specific application scenarios. For enhanced site characterization, surface geophysics and vertical high resolution direct push-profiling were combined for reliable determination of aquifer structure and aquifer parameterization. Based on the site characterization, different site specific geothermal application scenarios, including different system types and system configurations, were simulated using OpenGeoSys to guarantee an environmental and economic sustainable thermal use of the shallow subsurface.
Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System
Directory of Open Access Journals (Sweden)
Van-Hai Bui
2017-07-01
Full Text Available In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have implemented the consensus method, however, convergence time of the consensus method is quite long, while diffusion strategy includes a stochastic gradient term and can reach convergence much faster compared with consensus method. Therefore, in this paper, a diffusion strategy-based distributed operation of microgrids (MGs is proposed using multiagent system for both normal and emergency operation modes. In normal operation, the MG system is operated by a central controller instead of the distributed controller to minimize the operation cost. If any event (fault occurs in the system, MG system can be divided into two parts to isolate the faulty region. In this case, the MG system is changed to emergency operation mode. The normal part is rescheduled by the central controller while the isolated part schedules its resources in a distributed manner. The isolated part carries out distributed communication using diffusion between neighboring agents for optimal operation of this part. The proposed method enables peer-to-peer communication among the agents without the necessity of a centralized controller, and simultaneously performs resource optimization. Simulation results show that the system can be operated in an economic way in both normal operation and emergency operation modes.
Operative strategy based in low rate
International Nuclear Information System (INIS)
Mejia S, D.M.; Torres A, C.
2004-01-01
This work describes the possibility of the reactor operation of the unit 1 of the Laguna Verde Nuclear Power plant (CNLV) with a low flow, compared with the Cycle 10 that it was called Cycle 10 similar for this work. The main objective is to analyze the advantages or disadvantages that are obtained when going down the flow from the reactor to an interval that varies, from 81% to 106%, being a flow window but big of the one that it was used that is from 93.1% to 100.8%. It is found that making this type of changes, a favorable response is obtained, without any possibility of fault of the reactor. (Author)
Advanced operation strategy for feed-and-bleed operation in an OPR1000
International Nuclear Information System (INIS)
Kim, Bo Gyung; Yoon, Ho Joon; Kim, Jaewhan; Kang, Hyun Gook
2016-01-01
Highlights: • Advanced operating strategy covers all necessary conditions for F&B operation. • Advanced operating strategy identifies the urgency of F&B operation. • An advanced operating strategy for F&B operation is developed using a decision tree. • Human error probability is re-estimated based on a thermohydraulic analysis and K-HRA method. • An advanced operation strategy provides indications under various plant situations. - Abstract: When the secondary side is unavailable in a pressurized water reactor (PWR), heat from the core will accumulate in the primary side causing core damage. In this situation a heat removal mechanism called feed-and-bleed operation (F&B operation) must be used, which is a process of directly cooling the primary reactor cooling system (RCS). However, conventional operation strategy in emergency operating procedures (EOPs) does not cover all possible conditions to initiate F&B operation. If the EOP informs on the urgency of F&B operation, operators will be able to more clearly make decisions regarding F&B operation initiation. In order to cover all possible scenarios for F&B operation and systematically inform its urgency, an advanced operating strategy using a decision tree is developed in this study. The plant condition can be classified according to failure of secondary side, RCS pressure condition, injectable inventory to RCS, and remaining core inventory. RCS pressure, core level, and RCS temperature are representative indicators which provide information regarding the initiation of F&B operation. Indicators can be selected based on their detectability and quantification, and a decision tree is developed according to combinations of indicators. To estimate the effects of the advanced operation strategy, human error probability (HEP) of F&B operation is re-estimated based on a thermohydraulic analysis. The available time for operators to initiate F&B operation is also re-estimated to obtain more realistic data. This
Optimal Control Strategy Search Using a Simplest 3-D PWR Xenon Oscillation Simulator
International Nuclear Information System (INIS)
Yoichiro, Shimazu
2004-01-01
Power spatial oscillations due to the transient xenon spatial distribution are well known as xenon oscillation in large PWRs. When the reactor size becomes larger than the current design, then even radial oscillations can be also divergent. Even if the radial oscillation is convergent, when some control rods malfunction occurs, it is necessary to suppress the oscillation in as short time as possible. In such cases, optimal control strategy is required. Generally speaking the optimality search based on the modern control theory requires a lot of calculation for the evaluation of state variables. In the case of control rod malfunctions the xenon oscillation could be three dimensional. In such case, direct core calculations would be inevitable. From this point of view a very simple model, only four point reactor model, has been developed and verified. In this paper, an example of a procedure and the results for optimal control strategy search are presented. It is shown that we have only one optimal strategy within a half cycle of the oscillation with fixed control strength. It is also shown that a 3-D xenon oscillation introduced by a control rod malfunction can not be controlled by only one control step as can be done for axial oscillations. They might be quite strong limitations to the operators. Thus it is recommended that a strategy generator, which is quick in analyzing and easy to use, might be installed in a monitoring system or operator guiding system. (author)
Transitions in optimal adaptive strategies for populations in fluctuating environments
Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.
2017-09-01
Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
Optimizing Reservoir Operation to Adapt to the Climate Change
Madadgar, S.; Jung, I.; Moradkhani, H.
2010-12-01
Climate change and upcoming variation in flood timing necessitates the adaptation of current rule curves developed for operation of water reservoirs as to reduce the potential damage from either flood or draught events. This study attempts to optimize the current rule curves of Cougar Dam on McKenzie River in Oregon addressing some possible climate conditions in 21th century. The objective is to minimize the failure of operation to meet either designated demands or flood limit at a downstream checkpoint. A simulation/optimization model including the standard operation policy and a global optimization method, tunes the current rule curve upon 8 GCMs and 2 greenhouse gases emission scenarios. The Precipitation Runoff Modeling System (PRMS) is used as the hydrology model to project the streamflow for the period of 2000-2100 using downscaled precipitation and temperature forcing from 8 GCMs and two emission scenarios. An ensemble of rule curves, each associated with an individual scenario, is obtained by optimizing the reservoir operation. The simulation of reservoir operation, for all the scenarios and the expected value of the ensemble, is conducted and performance assessment using statistical indices including reliability, resilience, vulnerability and sustainability is made.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning.
Vendetti, Michael S; Starr, Ariel; Johnson, Elizabeth L; Modavi, Kiana; Bunge, Silvia A
2017-01-01
Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D). We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning
Directory of Open Access Journals (Sweden)
Michael S. Vendetti
2017-06-01
Full Text Available Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D. We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Strategies of operation cycles in BWR type reactors
International Nuclear Information System (INIS)
Molina, D.; Sendino, F.
1996-01-01
The article analyzes the operation cycles in BWR type reactors. The cycle size of operation is the consequence on the optimization process of the costs with the technical characteristics of nuclear fuel and the characteristics of demand and production. The authors analyze the cases of Garona NP and Cofrentes NP, both with BWR reactors. (Author)
Optimal intervention strategies for cholera outbreak by education and chlorination
Bakhtiar, Toni
2016-01-01
This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.
Optimal operation of a micro-combined cooling, heating and power system driven by a gas engine
International Nuclear Information System (INIS)
Kong, X.Q.; Wang, R.Z.; Li, Y.; Huang, X.H.
2009-01-01
The objective of this paper is to investigate the problem of energy management and optimal operation of cogeneration system for micro-combined cooling, heating and power production (CCHP). The energy system mainly consists of a gas engine, an adsorption chiller, a gas boiler, a heat exchanger and an electric chiller. On the basis of an earlier experimental research of the micro-CCHP system, a non-linear-programming cost-minimization optimization model is presented to determine the optimum operational strategies for the system. It is shown that energy management and optimal operation of the micro-CCHP system is dependent upon load conditions to be satisfied and energy cost. In view of energy cost, it would not be optimal to operate the gas engine when the electric-to-gas cost ratio (EGCR) is very low. With higher EGCR, the optimum operational strategy of the micro-CCHP system is independent of energy cost
Long-term damage management strategies for optimizing steam generator performance
International Nuclear Information System (INIS)
Egan, G.R.; Besuner, P.M.; Fox, J.H.; Merrick, E.A.
1991-01-01
Minimizing long-term impact of steam generator operating, maintenance, outage, and replacement costs is the goal of all pressurized water reactor utilities. Recent research results have led to deterministic controls that may be implemented to optimize steam generator performance and to minimize damage accumulation. The real dilemma that utilities encounter is the decision process that needs to be made in the face of uncertain data. Some of these decisions involve the frequency and extent of steam generator eddy current tube inspections; the definition of operating conditions to minimize the rate of corrosion reactions (T (hot) , T (cold) ; and the imposition of strict water quality management guidelines. With finite resources, how can a utility decide which damage management strategy provides the most return for its investment? Aptech Engineering Services, Inc. (APTECH) developed a damage management strategy that starts from a deterministic analysis of a current problem- primary water stress corrosion cracking (PWSCC). The strategy involves a probabilistic treatment that results in long-term performance optimization. By optimization, we refer to minimizing the total cost of operating the steam generator. This total includes the present value costs of operations, maintenance, outages, and replacements. An example of the application of this methodology is presented. (author)
The topography of the environment alters the optimal search strategy for active particles
Volpe, Giorgio; Volpe, Giovanni
2017-10-01
In environments with scarce resources, adopting the right search strategy can make the difference between succeeding and failing, even between life and death. At different scales, this applies to molecular encounters in the cell cytoplasm, to animals looking for food or mates in natural landscapes, to rescuers during search and rescue operations in disaster zones, and to genetic computer algorithms exploring parameter spaces. When looking for sparse targets in a homogeneous environment, a combination of ballistic and diffusive steps is considered optimal; in particular, more ballistic Lévy flights with exponent α≤1 are generally believed to optimize the search process. However, most search spaces present complex topographies. What is the best search strategy in these more realistic scenarios? Here, we show that the topography of the environment significantly alters the optimal search strategy toward less ballistic and more Brownian strategies. We consider an active particle performing a blind cruise search for nonregenerating sparse targets in a 2D space with steps drawn from a Lévy distribution with the exponent varying from α=1 to α=2 (Brownian). We show that, when boundaries, barriers, and obstacles are present, the optimal search strategy depends on the topography of the environment, with α assuming intermediate values in the whole range under consideration. We interpret these findings using simple scaling arguments and discuss their robustness to varying searcher's size. Our results are relevant for search problems at different length scales from animal and human foraging to microswimmers' taxis to biochemical rates of reaction.
Formulation of Higher Education Institutional Strategy Using Operational Research Approaches
Labib, Ashraf; Read, Martin; Gladstone-Millar, Charlotte; Tonge, Richard; Smith, David
2014-01-01
In this paper a framework is proposed for the formulation of a higher education institutional (HEI) strategy. This work provides a practical example, through a case study, to demonstrate how the proposed framework can be applied to the issue of formulation of HEI strategy. The proposed hybrid model is based on two operational research…
Integrated testing strategies can be optimal for chemical risk classification.
Raseta, Marko; Pitchford, Jon; Cussens, James; Doe, John
2017-08-01
There is an urgent need to refine strategies for testing the safety of chemical compounds. This need arises both from the financial and ethical costs of animal tests, but also from the opportunities presented by new in-vitro and in-silico alternatives. Here we explore the mathematical theory underpinning the formulation of optimal testing strategies in toxicology. We show how the costs and imprecisions of the various tests, and the variability in exposures and responses of individuals, can be assembled rationally to form a Markov Decision Problem. We compute the corresponding optimal policies using well developed theory based on Dynamic Programming, thereby identifying and overcoming some methodological and logical inconsistencies which may exist in the current toxicological testing. By illustrating our methods for two simple but readily generalisable examples we show how so-called integrated testing strategies, where information of different precisions from different sources is combined and where different initial test outcomes lead to different sets of future tests, can arise naturally as optimal policies. Copyright © 2017 Elsevier Inc. All rights reserved.
Optimal sampling strategies for detecting zoonotic disease epidemics.
Directory of Open Access Journals (Sweden)
Jake M Ferguson
2014-06-01
Full Text Available The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Optimal sampling strategies for detecting zoonotic disease epidemics.
Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W
2014-06-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
International Nuclear Information System (INIS)
Connolly, D.; Lund, H.; Finn, P.; Mathiesen, B.V.; Leahy, M.
2011-01-01
In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360 MW pump, 300 MW turbine, and a 2 GWh storage utilising price arbitrage on 13 electricity spot markets. The results indicate that almost all (∼97%) of the profits can be obtained by a PHES facility when it is optimised using the 24Optimal strategy developed, which optimises the energy storage based on the day-ahead electricity prices. However, to maximise profits with the 24Optimal strategy, the day-ahead electricity prices must be the actual prices which the PHES facility is charged or the PHES operator must have very accurate price predictions. Otherwise, the predicted profit could be significantly reduced and even become a loss. Finally, using the 24Optimal strategy, the PHES profit can surpass the annual investment repayments required. However, over the 5-year period investigated (2005-2009) the annual profit from the PHES facility varied by more than 50% on five out of six electricity markets considered. Considering the 40-year lifetime of PHES, even with low investment costs, a low interest rate, and a suitable electricity market, PHES is a risky investment without a more predictable profit. - Highlights: → Electricity generators typically operate on a market, including energy storage. → This paper assesses how energy storage can maximise its profits on a market. → Four operating strategies are assessed on 13 markets using a case study.→ One operating strategy achieves 97% of the profits feasible.→ However, the profit varies a lot depending on the market and capital costs.
Kim, U.; Parker, J.; Borden, R. C.
2014-12-01
In-situ chemical oxidation (ISCO) has been applied at many dense non-aqueous phase liquid (DNAPL) contaminated sites. A stirred reactor-type model was developed that considers DNAPL dissolution using a field-scale mass transfer function, instantaneous reaction of oxidant with aqueous and adsorbed contaminant and with readily oxidizable natural oxygen demand ("fast NOD"), and second-order kinetic reactions with "slow NOD." DNAPL dissolution enhancement as a function of oxidant concentration and inhibition due to manganese dioxide precipitation during permanganate injection are included in the model. The DNAPL source area is divided into multiple treatment zones with different areas, depths, and contaminant masses based on site characterization data. The performance model is coupled with a cost module that involves a set of unit costs representing specific fixed and operating costs. Monitoring of groundwater and/or soil concentrations in each treatment zone is employed to assess ISCO performance and make real-time decisions on oxidant reinjection or ISCO termination. Key ISCO design variables include the oxidant concentration to be injected, time to begin performance monitoring, groundwater and/or soil contaminant concentrations to trigger reinjection or terminate ISCO, number of monitoring wells or geoprobe locations per treatment zone, number of samples per sampling event and location, and monitoring frequency. Design variables for each treatment zone may be optimized to minimize expected cost over a set of Monte Carlo simulations that consider uncertainty in site parameters. The model is incorporated in the Stochastic Cost Optimization Toolkit (SCOToolkit) program, which couples the ISCO model with a dissolved plume transport model and with modules for other remediation strategies. An example problem is presented that illustrates design tradeoffs required to deal with characterization and monitoring uncertainty. Monitoring soil concentration changes during ISCO
Simulation and OR (operations research) in combination for practical optimization
van Dijk, N.; van der Sluis, E.; Haijema, R.; Al-Ibrahim, A.; van der Wal, J.; Kuhl, M.E.; Steiger, N.M.; Armstrong, F.B.; Joines, J.A.
2005-01-01
Should we pool capacities or not? This is a question that one can regularly be confronted with in operations and service management. It is a question that necessarily requires a combination of queueing (as OR discipline) and simulation (as evaluative tool) and further steps for optimization. It will
Optimization Methods in Operations Research and Systems Analysis
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 6. Optimization Methods in Operations Research and Systems Analysis. V G Tikekar. Book Review Volume 2 Issue 6 June 1997 pp 91-92. Fulltext. Click here to view fulltext PDF. Permanent link:
Positive-operator-valued measure optimization of classical correlations
Hamieh, S; Kobes, R; Zaraket, H
We study the problem of optimization over positive-operator-valued measures to extract classical correlation in a bipartite quantum system. The proposed method is applied to binary states only. Moreover, to illustrate this method, an explicit example is studied in detail.
Operator support through modern optimal estimation and control
International Nuclear Information System (INIS)
Burdick, G.R.
1980-01-01
Applications of Modern Optimal Estimation and Control Theories are late in coming to the nuclear industry. Some features of the theories that might be exploited in nuclear systems applications are described. Activities at the Idaho National Engineering Laboratory relating to operator support using those theories are identified and some implementation challenges are discussed
International Nuclear Information System (INIS)
Jing, Z.X.; Jiang, X.S.; Wu, Q.H.; Tang, W.H.; Hua, B.
2014-01-01
This paper presents a comprehensive model of a small-scale integrated energy based district heating and cooling (DHC) system located in a residential area of hot-summer and cold-winter zone, which makes joint use of wind energy, solar energy, natural gas and electric energy. The model includes an off-grid wind turbine generator, heat producers, chillers, a water supply network and terminal loads. This research also investigates an optimal operating strategy based on Group Search Optimizer (GSO), through which the daily running cost of the system is optimized in both the heating and cooling modes. The strategy can be used to find the optimal number of operating chillers, optimal outlet water temperature set points of boilers and optimal water flow set points of pumps, taking into account cost functions and various operating constraints. In order to verify the model and the optimal operating strategy, performance tests have been undertaken using MATLAB. The simulation results prove the validity of the model and show that the strategy is able to minimize the system operation cost. The proposed system is evaluated in comparison with a conventional separation production (SP) system. The feasibility of investment for the DHC system is also discussed. The comparative results demonstrate the investment feasibility, the significant energy saving and the cost reduction, achieved in daily operation in an environment, where there are varying heating loads, cooling loads, wind speeds, solar radiations and electricity prices. - Highlights: • A model of a small-scale integrated energy based DHC system is presented. • An off-grid wind generator used for water heating is embedded in the model. • An optimal control strategy is studied to optimize the running cost of the system. • The designed system is proved to be energy efficient and cost effective in operation
Directory of Open Access Journals (Sweden)
Narinder Singh
2018-03-01
Full Text Available The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO and Whale Optimizer Algorithm (WOA. We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO algorithm: (i firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.
Optimal Design and Operation of Permanent Irrigation Systems
Oron, Gideon; Walker, Wynn R.
1981-01-01
Solid-set pressurized irrigation system design and operation are studied with optimization techniques to determine the minimum cost distribution system. The principle of the analysis is to divide the irrigation system into subunits in such a manner that the trade-offs among energy, piping, and equipment costs are selected at the minimum cost point. The optimization procedure involves a nonlinear, mixed integer approach capable of achieving a variety of optimal solutions leading to significant conclusions with regard to the design and operation of the system. Factors investigated include field geometry, the effect of the pressure head, consumptive use rates, a smaller flow rate in the pipe system, and outlet (sprinkler or emitter) discharge.
Optimal operation of cogeneration units. State of art and perspective
International Nuclear Information System (INIS)
Polimeni, S.
2001-01-01
Optimal operation of cogeneration plants and of power plant fueling waste products is a complex challenge as they have to fulfill, beyond the contractual obligation of electric power supply, the constraints of supplying the required thermal energy to the user (for cogeneration units) or to burn completely the by-products of the industrial complex where they are integrated. Electrical power market evolution is pushing such units to a more and more volatile operation caused by uncertain selling price levels. This work intends to pinpoint the state of art in the optimization of these units outlining the important differences among the different size and cycles. The effect of the market liberalization on the automation systems and the optimization algorithms will be discussed [it
VI International Workshop on Nature Inspired Cooperative Strategies for Optimization
Otero, Fernando; Masegosa, Antonio
2014-01-01
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...
International Nuclear Information System (INIS)
Oliver, Mike; Jensen, Michael; Chen, Jeff; Wong, Eugene
2009-01-01
Intensity-modulated arc therapy (IMAT) is a rotational variant of intensity-modulated radiation therapy (IMRT) that can be implemented with or without angular dose rate variation. The purpose of this study is to assess optimization strategies and initial conditions using a leaf position optimization (LPO) algorithm altered for variable dose rate IMAT. A concave planning target volume (PTV) with a central cylindrical organ at risk (OAR) was used in this study. The initial IMAT arcs were approximated by multiple static beams at 5 deg. angular increments where multi-leaf collimator (MLC) leaf positions were determined from the beam's eye view to irradiate the PTV but avoid the OAR. For the optimization strategy, two arcs with arc ranges of 280 deg. and 150 deg. were employed and plans were created using LPO alone, variable dose rate optimization (VDRO) alone, simultaneous LPO and VDRO and sequential combinations of these strategies. To assess the MLC initialization effect, three single 360 deg. arc plans with different initial MLC configurations were generated using the simultaneous LPO and VDRO. The effect of changing optimization degrees of freedom was investigated by employing 3 deg., 5 deg. and 10 deg. angular sampling intervals for the two 280 deg., two 150 deg. and single arc plans using LPO and VDRO. The objective function value, a conformity index, a dose homogeneity index, mean dose to OAR and normal tissues were computed and used to evaluate the treatment plans. This study shows that the best optimization strategy for a concave target is to use simultaneous MLC LPO and VDRO. We found that the optimization result is sensitive to the choice of initial MLC aperture shapes suggesting that an LPO-based IMAT plan may not be able to overcome local minima for this geometry. In conclusion, simultaneous MLC leaf position and VDRO are needed with the most appropriate initial conditions (MLC positions, arc ranges and number of arcs) for IMAT.
Control and operation cost optimization of the HISS cryogenic system
International Nuclear Information System (INIS)
Porter, J.; Anderson, D.; Bieser, F.
1984-01-01
This chapter describes a control strategy for the Heavy Ion Spectrometer System (HISS), which relies upon superconducting coils of cryostable design to provide a particle bending field of 3 tesla. The control strategy has allowed full time unattended operation and significant operating cost reductions. Microprocessor control of flash boiling style LIN circuits has been successful. It is determined that the overall operating cost of most cryogenic systems using closed loop helium systems can be minimized by properly balancing the total heat load between the helium and nitrogen circuits to take advantage of the non-linearity which exists in the power input to 4K refrigeration characteristic. Variable throughput compressors have the advantage of turndown capability at steady state. It is concluded that a hybrid system using digital and analog input for control, data display and alarms enables full time unattended operation
Design and modeling of reservoir operation strategies for sediment management
Sloff, C.J.; Omer, A.Y.A.; Heynert, K.V.; Mohamed, Y.A.
2015-01-01
Appropriate operation strategies that allow for sediment flushing and sluicing (sediment routing) can reduce rapid storage losses of (hydropower and water-supply) reservoirs. In this study we have shown, using field observations and computational models, that the efficiency of these operations
Data reconciliation and optimal operation of a Catalytic naphtha reformer
Directory of Open Access Journals (Sweden)
Tore Lid
2008-10-01
Full Text Available The naphtha reforming process converts low-octane gasoline blending components to high-octane components for use in high-performance gasoline fuels. The reformer also has an important function as the producer of hydrogen to the refinery hydrotreaters. A process model based on a unit model structure, is used for estimation of the process condition using data reconciliation. Measurements are classified as redundant or non redundant and the model variables are classified as observable, barely observable or unobservable. The computed uncertainty of the measured and unmeasured variables shows that even if a variable is observable it may have a very large uncertainty and may thereby be practically unobservable. The process condition at 21 data points, sampled from two years of operation, was reconciled and used to optimize the process operation. There are large seasonal variations in the reformer product price and two operational cases are studied. In case 1, the product price is high and throughput is maximized with respect to process and product quality constraints. In case 2, the product price is low and the throughput is minimized with respect to a low constraint on the hydrogen production. Based on the characteristics of the optimal operation, a "self optimizing" control structure is suggested for each of the two operational cases.
Activity-Based Information Integrating the operations strategy
Directory of Open Access Journals (Sweden)
José Augusto da Rocha de Araujo
2005-12-01
Full Text Available In the globalized world, companies seek for new operations strategies to ensure world corporate success. This article analyzes how the cost management models – both traditional and activity-based, aid the planning and management of corporate globalized operations. The efficacy of the models application depends on their alignment with the competitive strategy. Companies must evaluate the nature of the competition and its competitive priorities; they should then define the necessary and sufficient dependence level on costs information. In this article, three dependence levels are presented: operational, decision support and strategic control. The result of the research shows the importance of alignment between the cost management model and the competitive strategy for corporate success, and confirms the adequacy of the activity-based costing model as a supporting tool for decision taking in a global strategy. Case studies in world class companies in Brazil are presented.
Perfect commuting-operator strategies for linear system games
Cleve, Richard; Liu, Li; Slofstra, William
2017-01-01
Linear system games are a generalization of Mermin's magic square game introduced by Cleve and Mittal. They show that perfect strategies for linear system games in the tensor-product model of entanglement correspond to finite-dimensional operator solutions of a certain set of non-commutative equations. We investigate linear system games in the commuting-operator model of entanglement, where Alice and Bob's measurement operators act on a joint Hilbert space, and Alice's operators must commute with Bob's operators. We show that perfect strategies in this model correspond to possibly infinite-dimensional operator solutions of the non-commutative equations. The proof is based around a finitely presented group associated with the linear system which arises from the non-commutative equations.
Optimal Operations and Resilient Investments in Steam Networks
Energy Technology Data Exchange (ETDEWEB)
Bungener, Stéphane L., E-mail: stephane.bungener@a3.epfl.ch [Industrial Process and Energy Systems Engineering, École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); Van Eetvelde, Greet [Environmental and Spatial Management, Faculty of Engineering and Architecture, Ghent University, Ghent (Belgium); Maréchal, François [Industrial Process and Energy Systems Engineering, École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland)
2016-01-20
Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience.
Optimal Operations and Resilient Investments in Steam Networks
International Nuclear Information System (INIS)
Bungener, Stéphane L.; Van Eetvelde, Greet; Maréchal, François
2016-01-01
Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience.
Site utility system optimization with operation adjustment under uncertainty
International Nuclear Information System (INIS)
Sun, Li; Gai, Limei; Smith, Robin
2017-01-01
Highlights: • Uncertainties are classified into time-based and probability-based uncertain factors. • Multi-period operation and recourses deal with uncertainty implementation. • Operation scheduling are specified at the design stage to deal with uncertainties. • Steam mains superheating affects steam distribution and power generation in the system. - Abstract: Utility systems must satisfy process energy and power demands under varying conditions. The system performance is decided by the system configuration and individual equipment operating load for boilers, gas turbines, steam turbines, condensers, and let down valves. Steam mains conditions in terms of steam pressures and steam superheating also play important roles on steam distribution in the system and power generation by steam expansion in steam turbines, and should be included in the system optimization. Uncertainties such as process steam power demand changes and electricity price fluctuations should be included in the system optimization to eliminate as much as possible the production loss caused by steam power deficits due to uncertainties. In this paper, uncertain factors are classified into time-based and probability-based uncertain factors, and operation scheduling containing multi-period equipment load sharing, redundant equipment start up, and electricity import to compensate for power deficits, have been presented to deal with the happens of uncertainties, and are formulated as a multi-period item and a recourse item in the optimization model. There are two case studies in this paper. One case illustrates the system design to determine system configuration, equipment selection, and system operation scheduling at the design stage to deal with uncertainties. The other case provides operational optimization scenarios for an existing system, especially when the steam superheating varies. The proposed method can provide practical guidance to system energy efficiency improvement.
Numerical simulation of energy efficiency measures: control and operational strategies
International Nuclear Information System (INIS)
Ardehali, M. M.
2006-01-01
The inherent limitation in performance of building envelop components and heating ventilating and air conditioning (HVAC) equipment necessitates the examination of operational strategies for improvement in energy-efficient operation of buildings. Due to the ease of installation and increasing availability of electronic controllers, operational strategies that could be programmed are of particular interest. The Iowa Energy Center in the US has taken the initiative to conduct the necessary assessment of current HVAC technology and the commonly-used operational strategies for commercial and industrial buildings, as applied to the midwestern part of the country, with weather and energy cost data for Des Moines, Iowa. The first part of this study focused on the energy consumption and cost effectiveness of HVAC systems. The objectives of the second part is concerned with examination of various operational strategies, namely, night purge (NP), fan optimum start and stop (OSS), condenser water reset (CWR), and chilled water reset (CHWR) applied to order and newer-type commercial office buildings. The indoor air quality requirement are met and the latest applicable energy rates from local utility companies are used. The results show that, in general, NP is not an effective strategy in buildings with low thermal mass storage, OSS reduced fan energy, and CWR and CHWR could be effective and require chillers with multi-stage unloading characteristics. The most operationally efficient strategies are the combination of OSS, CWR, and CHWR for the older-type building, and OSS for the newer-type building. Economically, the most effective is the OSS strategy for the older-type building and the CHWR strategy for the newer-type building.(Author)
The effect of pre-operative optimization on post-operative outcome in Crohn's disease resections
DEFF Research Database (Denmark)
El-Hussuna, Alaa; Iesalnieks, Igors; Horesh, Nir
2017-01-01
BACKGROUND: The timing of surgical intervention in Crohn's disease (CD) may depend on pre-operative optimization (PO) which includes different interventions to decrease the risk for unfavourable post-operative outcome. The objective of this study was to investigate the effect of multi-model PO on...
Optimal Operation of Energy Storage in Power Transmission and Distribution
Akhavan Hejazi, Seyed Hossein
In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider
OPF-Based Optimal Location of Two Systems Two Terminal HVDC to Power System Optimal Operation
Directory of Open Access Journals (Sweden)
Mehdi Abolfazli
2013-04-01
Full Text Available In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC-based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore, two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.
Neuro-optimal operation of a variable air volume HVAC and R system
International Nuclear Information System (INIS)
Ning Min; Zaheeruddin, M.
2010-01-01
Low operational efficiency especially under partial load conditions and poor control are some reasons for high energy consumption of heating, ventilation, air conditioning and refrigeration (HVAC and R) systems. To improve energy efficiency, HVAC and R systems should be efficiently operated to maintain a desired indoor environment under dynamic ambient and indoor conditions. This study proposes a neural network based optimal supervisory operation strategy to find the optimal set points for chilled water supply temperature, discharge air temperature and VAV system fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.
Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading
Ward, Brian
In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal
Maintenance and test strategies to optimize NPP equipment performance
International Nuclear Information System (INIS)
Mayer, S.; Tomic, B.
2000-01-01
This paper proposes an approach to maintenance optimization of nuclear power plant components, which can help to increase both safety and availability. In order to evaluate the benefits of preventive maintenance on a quantitative basis, a software code has been developed for component performance and reliability simulation of safety related nuclear power plant equipment. A three state Markov model will be introduced, considering a degraded state in addition to an operational state and a failed state. (author)
Optimal Input Strategy for Plug and Play Process Control Systems
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined pa...... the performance of the plant. The results are applied to a coal fired power plant where an additional new fuel system, gas, becomes available....
Operation optimization of a distributed energy system considering energy costs and exergy efficiency
International Nuclear Information System (INIS)
Di Somma, M.; Yan, B.; Bianco, N.; Graditi, G.; Luh, P.B.; Mongibello, L.; Naso, V.
2015-01-01
Highlights: • Operation optimization model of a Distributed Energy System (DES). • Multi-objective strategy to optimize energy cost and exergy efficiency. • Exergy analysis in building energy supply systems. - Abstract: With the growing demand of energy on a worldwide scale, improving the efficiency of energy resource use has become one of the key challenges. Application of exergy principles in the context of building energy supply systems can achieve rational use of energy resources by taking into account the different quality levels of energy resources as well as those of building demands. This paper is on the operation optimization of a Distributed Energy System (DES). The model involves multiple energy devices that convert a set of primary energy carriers with different energy quality levels to meet given time-varying user demands at different energy quality levels. By promoting the usage of low-temperature energy sources to satisfy low-quality thermal energy demands, the waste of high-quality energy resources can be reduced, thereby improving the overall exergy efficiency. To consider the economic factor as well, a multi-objective linear programming problem is formulated. The Pareto frontier, including the best possible trade-offs between the economic and exergetic objectives, is obtained by minimizing a weighted sum of the total energy cost and total primary exergy input using branch-and-cut. The operation strategies of the DES under different weights for the two objectives are discussed. The operators of DESs can choose the operation strategy from the Pareto frontier based on costs, essential in the short run, and sustainability, crucial in the long run. The contribution of each energy device in reducing energy costs and the total exergy input is also analyzed. In addition, results show that the energy cost can be much reduced and the overall exergy efficiency can be significantly improved by the optimized operation of the DES as compared with the
Cost-effectiveness analysis of optimal strategy for tumor treatment
International Nuclear Information System (INIS)
Pang, Liuyong; Zhao, Zhong; Song, Xinyu
2016-01-01
We propose and analyze an antitumor model with combined immunotherapy and chemotherapy. Firstly, we explore the treatment effects of single immunotherapy and single chemotherapy, respectively. Results indicate that neither immunotherapy nor chemotherapy alone are adequate to cure a tumor. Hence, we apply optimal theory to investigate how the combination of immunotherapy and chemotherapy should be implemented, for a certain time period, in order to reduce the number of tumor cells, while minimizing the implementation cost of the treatment strategy. Secondly, we establish the existence of the optimality system and use Pontryagin’s Maximum Principle to characterize the optimal levels of the two treatment measures. Furthermore, we calculate the incremental cost-effectiveness ratios to analyze the cost-effectiveness of all possible combinations of the two treatment measures. Finally, numerical results show that the combination of immunotherapy and chemotherapy is the most cost-effective strategy for tumor treatment, and able to eliminate the entire tumor with size 4.470 × 10"8 in a year.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Optimization of the Brillouin operator on the KNL architecture
Dürr, Stephan
2018-03-01
Experiences with optimizing the matrix-times-vector application of the Brillouin operator on the Intel KNL processor are reported. Without adjustments to the memory layout, performance figures of 360 Gflop/s in single and 270 Gflop/s in double precision are observed. This is with Nc = 3 colors, Nv = 12 right-hand-sides, Nthr = 256 threads, on lattices of size 323 × 64, using exclusively OMP pragmas. Interestingly, the same routine performs quite well on Intel Core i7 architectures, too. Some observations on the much harderWilson fermion matrix-times-vector optimization problem are added.
Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.
Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen
2017-02-01
Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.
A characteristic study of CCF modeling techniques and optimization of CCF defense strategies
International Nuclear Information System (INIS)
Kim, Min Chull
2000-02-01
Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective
Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Linhui Li
2014-01-01
Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.
A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles
Directory of Open Access Journals (Sweden)
Jun Yang
2016-08-01
Full Text Available With the popularization of electric vehicles (EVs, the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU electricity price.
An Optimal Portfolio and Capital Management Strategy for Basel III Compliant Commercial Banks
Directory of Open Access Journals (Sweden)
Grant E. Muller
2014-01-01
Full Text Available We model a Basel III compliant commercial bank that operates in a financial market consisting of a treasury security, a marketable security, and a loan and we regard the interest rate in the market as being stochastic. We find the investment strategy that maximizes an expected utility of the bank’s asset portfolio at a future date. This entails obtaining formulas for the optimal amounts of bank capital invested in different assets. Based on the optimal investment strategy, we derive a model for the Capital Adequacy Ratio (CAR, which the Basel Committee on Banking Supervision (BCBS introduced as a measure against banks’ susceptibility to failure. Furthermore, we consider the optimal investment strategy subject to a constant CAR at the minimum prescribed level. We derive a formula for the bank’s asset portfolio at constant (minimum CAR value and present numerical simulations on different scenarios. Under the optimal investment strategy, the CAR is above the minimum prescribed level. The value of the asset portfolio is improved if the CAR is at its (constant minimum value.
Optimizing capital and time expenditures for drilling service operations
Energy Technology Data Exchange (ETDEWEB)
Zazovskiy, F Ya; Soltysyak, T I
1980-01-01
The operational efficiency of drilling services operations management are examined. The structure of time expenditure is analyzed for repair operations according to equipment type employed by the Ivano-Frankovsk Drilling Management under the Ukrneft' enterprise during 1977. The results of this analysis are weighed against a series of service operations carried out at industrial enterprises and connected with technical disruptions. Some of the cases examined include service competion operations outside of the industrial units when technical processes are disrupted only for the change of equipment which has outlived its usefulness and is no longer in series production. First of all, time expended for repair work can be reduced to zero during the drilling of shallow wells which do not require extensive drilling time. The actual savings, both in time and money, as far as repair work is concerned, hinges on the actual time factor for total oil depetion. An equation is provided for optimal time expenditure necessary for repair work and equipment replacement. An actual example is given from the Dolinsk UBR (Drillin Management) under the Ukrneft' enterprise where time spent on actual service operations has appeared to be less than the optimal figure cited in the above material. This is possible because of increased capital expenditures.
Multiobjective Optimization Modeling Approach for Multipurpose Single Reservoir Operation
Directory of Open Access Journals (Sweden)
Iosvany Recio Villa
2018-04-01
Full Text Available The water resources planning and management discipline recognizes the importance of a reservoir’s carryover storage. However, mathematical models for reservoir operation that include carryover storage are scarce. This paper presents a novel multiobjective optimization modeling framework that uses the constraint-ε method and genetic algorithms as optimization techniques for the operation of multipurpose simple reservoirs, including carryover storage. The carryover storage was conceived by modifying Kritsky and Menkel’s method for reservoir design at the operational stage. The main objective function minimizes the cost of the total annual water shortage for irrigation areas connected to a reservoir, while the secondary one maximizes its energy production. The model includes operational constraints for the reservoir, Kritsky and Menkel’s method, irrigation areas, and the hydropower plant. The study is applied to Carlos Manuel de Céspedes reservoir, establishing a 12-month planning horizon and an annual reliability of 75%. The results highly demonstrate the applicability of the model, obtaining monthly releases from the reservoir that include the carryover storage, degree of reservoir inflow regulation, water shortages in irrigation areas, and the energy generated by the hydroelectric plant. The main product is an operational graph that includes zones as well as rule and guide curves, which are used as triggers for long-term reservoir operation.
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
Directory of Open Access Journals (Sweden)
Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
Development of Operation Strategy for Hybrid-SIT in SBO
International Nuclear Information System (INIS)
Jeon, In Seop; Kang, Hyun Gook
2015-01-01
The Fukushima accident was not managed properly due to a lack of effective mitigation systems against Station Black Out (SBO) accident. For this reason, development of passive system is suggested as an alternative way for active system because passive system doesn't need external energy source and passive system can also increase the diversity of mitigation technique of Nuclear Power Plant (NPP). H-SIT is a passive injection system that is newly planned to adjust into the Advanced Power Reactor plus (APR+). This system is specialized for mitigation of SBO scenarios because it is passive system and it can inject coolant even in high pressure condition. Main function of H-SIT is injection of coolant to the Reactor Coolant System (RCS) in a passive way. The H-SIT system can inject water using the pressure from nitrogen gas as a normal SIT in low pressure accidents such as large and medium break loss-of-coolant accidents. This operation strategy is divided according to numbers of PAFS which can be used. When one H-SIT is used, H-SIT is recommended to use operation strategy which is explained as follow. In case of operation number, 1+1+1+1 strategy is the best and first operation timing, the time when upper plenum level is 5% is the best and next operation timing, the time when water level of H-SIT which is operated in previous round is 5% and operation order, 4-3-2-1 is the best. Even if one PAFS can be used, the minimum flow of H-SIT can maintain core in normal condition before H-SIT dried out thus if two PAFS can be used, the strategy which is used in the condition one PAFS can be operated is also used as a best operation strategy
Inner strategies of coping with operational work amongst SAPS officers
Directory of Open Access Journals (Sweden)
Masefako A. Gumani
2013-11-01
Research purpose: The objective of this study was to describe inner coping strategies used by officers in the Vhembe district (South Africa to reconstruct stressful and traumatic experiences at work. Motivation for the study: Most studies on coping amongst SAPS officers focus on organisational stress and not on the impact of the officers’ operational work. Research design, approach and method: An exploratory design was used and 20 SAPS officers were selected through purposive sampling. In-depth face-to-face and telephone interviews, as well as diaries were used to collect data, which were analysed using content thematic data analysis. Main findings: The results showed that the main categories of coping strategies that led to management of the impact of operational work amongst the selected sample were centred around problem-focused and emotion-focused strategies, with some use of reappraisal and minimal use of avoidance. Considering the context of the officers’ work, the list of dimensions of inner coping strategies amongst SAPS officers should be extended. Practical/managerial implications: Intervention programmes designed for the SAPS, including critical incident stress debriefing, should take the operational officers’ inner strategies into account to improve the management of the impact of their work. Contribution/value-add: This study contributes to the body of knowledge on the inner coping strategies amongst SAPS officers, with special reference to operational work in a specific setting.
Energy Technology Data Exchange (ETDEWEB)
Yoon, Duk-Joo; Lee, Seung-Chan; Sung, Je-Joong; Ha, Sang-Jun [KHNP CRI, Daejeon (Korea, Republic of); Hwang, Su-Hyun [FNC Tech. Co., Yongin (Korea, Republic of)
2016-10-15
Loss of all AC power is classified as one of multiple failure accident by regulatory guide of Korean accident management program. Therefore we need develop strategies for the abnormal operating procedure both of power operating and shutdown mode. This paper developed abnormal operating guideline for loss of all AC power by analysis of accident scenario in pressurized water reactor. This paper analyzed the loss of ultimate heat sink (LOUHS) in shutdown operating mode and developed the operating strategy of the abnormal procedure. Also we performed the analysis of limiting scenarios that operator actions are not taken in shutdown LOUHS. Therefore, we verified the plant behavior and decided operator action to taken in time in order to protect the fuel of core with safety. From the analysis results of LOUHS, the fuel of core maintained without core uncovery for 73 minutes respectively for opened RCS states after the SBO occurred. Therefore, operator action for the emergency are required to take in 73 minutes for opened RCS state. Strategy is to cooldown by using spent fuel pool cooling system. This method required to change the plant design in some plant. In RCS boundary closed state, first abnormal operating strategy in shutdown LOUHS is first abnormal operating strategy in shutdown LOUHS is to remove the residual heat of core by steam dump flow and auxiliary feedwater of SG.
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Chen, Zhe
2015-01-01
in the stochastic optimization to deal with the uncertainty of the up regulation price and the up regulation activation of the power system.The Danish short-term electricity market and a wind farm in western Denmark are chosen to evaluate the effect of the proposed strategy. Simulation results showthe proposed......As modern wind farmshave the ability to provideregulation service for the power system, wind power plant operators may be motivated to participate in the regulating market to maximize their profit.In this paper, anoptimal regulation servicestrategy for a wind farm to participate...... strategy can increase the revenue of wind farms by leavinga certain amount of wind powerfor regulation service....
International Nuclear Information System (INIS)
Esselman, Thomas; Bruck, Paul; Mengers, Charles
2012-01-01
Nuclear plant operators are studying the possibility of extending their existing generating facilities operating lifetime to 60 years and beyond. Many nuclear plants have been granted licenses to operate their facilities beyond the original 40 year term; however, in order to optimize the long term operating strategies, plant decision-makers need a consistent approach to support their options. This paper proposes a standard methodology to support effective decision-making for the long-term management of selected station assets. Methods detailed are intended to be used by nuclear plant site management, equipment reliability personnel, long term planners, capital asset planners, license renewal staff, and others that intend to look at operation between the current time and the end of operation. This methodology, named Integrated Life Cycle Management (ILCM), will provide a technical basis to assist decision makers regarding the timing of large capital investments required to get to the end of operation safely and with high plant reliability. ILCM seeks to identify end of life cycle failure probabilities for individual plant large capital assets and attendant costs associated with their refurbishment or replacement. It will provide a standard basis for evaluation of replacement and refurbishment options for these components. ILCM will also develop methods to integrate the individual assets over the entire plant thus assisting nuclear plant decision-makers in their facility long term operating strategies. (author)
Data driven approaches for diagnostics and optimization of NPP operation
International Nuclear Information System (INIS)
Pliska, J.; Machat, Z.
2014-01-01
The efficiency and heat rate is an important indicator of both the health of the power plant equipment and the quality of power plant operation. To achieve this challenges powerful tool is a statistical data processing of large data sets which are stored in data historians. These large data sets contain useful information about process quality and equipment and sensor health. The paper discusses data-driven approaches for model building of main power plant equipment such as condenser, cooling tower and the overall thermal cycle as well using multivariate regression techniques based on so called a regression triplet - data, model and method. Regression models comprise a base for diagnostics and optimization tasks. Diagnostics and optimization tasks are demonstrated on practical cases - diagnostics of main power plant equipment to early identify equipment fault, and optimization task of cooling circuit by cooling water flow control to achieve for a given boundary conditions the highest power output. (authors)
Optimal Pricing Strategy for Wireless Social Community Networks
Mazloumian, Amin; Manshaei, Mohammad Hossein; Felegyhazi, Mark; Hubaux, Jean-Pierre
2008-01-01
The increasing number of mobile applications fuels the demand for affordable and ubiquitous wireless access. The traditional wireless network technologies such as EV-DO or WiMAX provide this service but require a huge upfront investment in infrastructure and spectrum. On the contrary, as they do not have to face such an investment, social community operators rely on subscribers who constitute a community of users. The pricing strategy of the provided wireless access is an open problem for thi...
Development of Inventory Optimization System for Operation Nuclear Plants
Energy Technology Data Exchange (ETDEWEB)
Jang, Se-Jin; Park, Jong-Hyuk; Yoo, Sung-Soo; Lee, Sang-Guk [Korea Electric Power Research Institutes, Taejon (Korea, Republic of)
2006-07-01
Inventory control of spare parts plays an increasingly important role in operation management. This is why inventory management systems such as manufacturing resources planning(MRP) and enterprise resource planning(ERP) have been added. However, most of these contributions have similar theoretical background. This means the concepts and techniques are mainly based on mathematical assumptions and modeling inventory of spare parts situations. Nuclear utilities in Korea have several problems to manage the optimum level of spare parts though they used MRP System. Because most of items have long lead time and they are imported from United States, Canada, France and so on. We developed the inventory optimization system for Operation Nuclear Plants to resolve these problems. In this paper, we report a data flow process, data load and inventory calculation process. The main contribution of this paper is development of inventory optimization system which can be used in domestic power plants.
A database structure for radiological optimization analyses of decommissioning operations
International Nuclear Information System (INIS)
Zeevaert, T.; Van de Walle, B.
1995-09-01
The structure of a database for decommissioning experiences is described. Radiological optimization is a major radiation protection principle in practices and interventions, involving radiological protection factors, economic costs, social factors. An important lack of knowledge with respect to these factors exists in the domain of the decommissioning of nuclear power plants, due to the low number of decommissioning operations already performed. Moreover, decommissioning takes place only once for a installation. Tasks, techniques, and procedures are in most cases rather specific, limiting the use of past experiences in the radiological optimization analyses of new decommissioning operations. Therefore, it is important that relevant data or information be acquired from decommissioning experiences. These data have to be stored in a database in a way they can be used efficiently in ALARA analyses of future decommissioning activities
Development of Inventory Optimization System for Operation Nuclear Plants
International Nuclear Information System (INIS)
Jang, Se-Jin; Park, Jong-Hyuk; Yoo, Sung-Soo; Lee, Sang-Guk
2006-01-01
Inventory control of spare parts plays an increasingly important role in operation management. This is why inventory management systems such as manufacturing resources planning(MRP) and enterprise resource planning(ERP) have been added. However, most of these contributions have similar theoretical background. This means the concepts and techniques are mainly based on mathematical assumptions and modeling inventory of spare parts situations. Nuclear utilities in Korea have several problems to manage the optimum level of spare parts though they used MRP System. Because most of items have long lead time and they are imported from United States, Canada, France and so on. We developed the inventory optimization system for Operation Nuclear Plants to resolve these problems. In this paper, we report a data flow process, data load and inventory calculation process. The main contribution of this paper is development of inventory optimization system which can be used in domestic power plants
Optimizing noise control strategy in a forging workshop.
Razavi, Hamideh; Ramazanifar, Ehsan; Bagherzadeh, Jalal
2014-01-01
In this paper, a computer program based on a genetic algorithm is developed to find an economic solution for noise control in a forging workshop. Initially, input data, including characteristics of sound sources, human exposure, abatement techniques, and production plans are inserted into the model. Using sound pressure levels at working locations, the operators who are at higher risk are identified and picked out for the next step. The program is devised in MATLAB such that the parameters can be easily defined and changed for comparison. The final results are structured into 4 sections that specify an appropriate abatement method for each operator and machine, minimum allowance time for high-risk operators, required damping material for enclosures, and minimum total cost of these treatments. The validity of input data in addition to proper settings in the optimization model ensures the final solution is practical and economically reasonable.
Optimal Operation of a Josephson Parametric Amplifier for Vacuum Squeezing
Malnou, M.; Palken, D. A.; Vale, Leila R.; Hilton, Gene C.; Lehnert, K. W.
2018-04-01
A Josephson parametric amplifier (JPA) can create squeezed states of microwave light, lowering the noise associated with certain quantum measurements. We experimentally study how the JPA's pump influences the phase-sensitive amplification and deamplification of a coherent tone's amplitude when that amplitude is commensurate with vacuum fluctuations. We predict and demonstrate that, by operating the JPA with a single current pump whose power is greater than the value that maximizes gain, the amplifier distortion is reduced and, consequently, squeezing is improved. Optimizing the singly pumped JPA's operation in this fashion, we directly observe 3.87 ±0.03 dB of vacuum squeezing over a bandwidth of 30 MHz.
Optimization of operation cycles in BWRs using neural networks
International Nuclear Information System (INIS)
Ortiz S, J. J.; Castillo, A.; Alejandro P, D.
2011-11-01
The first results of a system for the optimization of operation cycles in boiling water reactors by means of a multi state recurrent neural network are present in this work. The neural network finds the best combination of fuel cells; fuel reloads and control bars patterns previously designed, according to an energy function that qualifies the performance of the three partial solutions for the solution of the whole problem. The partial solutions are designed by means of optimization systems non couple among them and that can use any optimization technique. The phase of the fuel axial design is not made and the size of the axial areas is fixed during the optimization process. The methodology was applied to design a balance cycle of 18 months for the reactors of the nuclear power station of Laguna Verde. The results show that is possible to find combinations of partial solutions that in set represent good solutions to the complete design problem of an operation cycle of a nuclear reactor. The results are compared with others obtained previously by other techniques. This system was developed in platform Li nux and programmed in Fortran 95 taking advantage of the 8 nuclei of a work station Dell Precision T7400. (Author)
Optimal recovery of linear operators in non-Euclidean metrics
Energy Technology Data Exchange (ETDEWEB)
Osipenko, K Yu [Moscow State Aviation Technological University, Moscow (Russian Federation)
2014-10-31
The paper looks at problems concerning the recovery of operators from noisy information in non-Euclidean metrics. A number of general theorems are proved and applied to recovery problems for functions and their derivatives from the noisy Fourier transform. In some cases, a family of optimal methods is found, from which the methods requiring the least amount of original information are singled out. Bibliography: 25 titles.
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
Energy Technology Data Exchange (ETDEWEB)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T., E-mail: rsayre@newmexicoconsortium.org [Los Alamos National Laboratory, New Mexico Consortium, Los Alamos, NM (United States)
2015-02-02
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
International Nuclear Information System (INIS)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T.
2015-01-01
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Operations Strategy and –Innovation? -A Contractor Implementing Lean
DEFF Research Database (Denmark)
Koch, Christian; Simonsen, Rolf
2006-01-01
Traditional strategic management and operations strategy wants us to believe that the implementation of management concepts is a simple strategic choice made by top managers. In this paper we introduce the story of Lean Construction entering into the organisation of a Danish contractor. Lean...... concepts. The paper presents findings from empirical work in collaboration with a large Danish contractor. The case is analysed from the perspective of operation strategy and political process. It is observed how the management concept is socially constructed and negotiated through political action of key...
Vesna Tornjanski; Sanja Marinković; Željka Jančić
2017-01-01
This paper sets out to extend and deepen the understanding the ways toward economic sustainability through efficient and effective growth operations strategies, quality management and operational excellence in banking. In this study we define new quality management practices based on developed conceptual architecture of digital platform for operations function in banking. Additionally, we employ decision making framework consisted of two parts: introduction of new operations services using To...
Optimal Intermittent Operation of Water Distribution Networks under Water Shortage
Directory of Open Access Journals (Sweden)
mohamad Solgi
2017-07-01
Full Text Available Under water shortage conditions, it is necessary to exercise water consumption management practices in water distribution networks (WDN. Intermittent supply of water is one such practice that makes it possible to supply consumption nodal demands with the required pressure via water cutoff to some consumers during certain hours of the day. One of the most important issues that must be observed in this management practice is the equitable and uniform water distribution among the consumers. In the present study, uniformity in water distribution and minimum supply of water to all consumers are defined as justice and equity, respectively. Also, an optimization model has been developed to find an optimal intermittent supply schedule that ensures maximum number of demand nodes are supplied with water while the constraints on the operation of water distribution networks are also observed. To show the efficiency of the proposed model, it has been used in the Two-Loop distribution network under several different scenarios of water shortage. The optimization model has been solved using the honey bee mating optimization algorithm (HBMO linked to the hydraulic simulator EPANET. The results obtained confirm the efficiency of the proposed model in achieving an optimal intermittent supply schedule. Moreover, the model is found capable of distributing the available water in an equitable and just manner among all the consumers even under severe water shoratges.
International Nuclear Information System (INIS)
Wu, Xia; Wu, Genhua
2014-01-01
Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag 61 cluster with stacking-fault face-centered cubic motif is found. - Abstract: Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag 61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron
Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach
Directory of Open Access Journals (Sweden)
Wei Wei
2014-04-01
Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.
Hopmann, Ch.; Windeck, C.; Kurth, K.; Behr, M.; Siegbert, R.; Elgeti, S.
2014-05-01
The rheological design of profile extrusion dies is one of the most challenging tasks in die design. As no analytical solution is available, the quality and the development time for a new design highly depend on the empirical knowledge of the die manufacturer. Usually, prior to start production several time-consuming, iterative running-in trials need to be performed to check the profile accuracy and the die geometry is reworked. An alternative are numerical flow simulations. These simulations enable to calculate the melt flow through a die so that the quality of the flow distribution can be analyzed. The objective of a current research project is to improve the automated optimization of profile extrusion dies. Special emphasis is put on choosing a convenient starting geometry and parameterization, which enable for possible deformations. In this work, three commonly used design features are examined with regard to their influence on the optimization results. Based on the results, a strategy is derived to select the most relevant areas of the flow channels for the optimization. For these characteristic areas recommendations are given concerning an efficient parameterization setup that still enables adequate deformations of the flow channel geometry. Exemplarily, this approach is applied to a L-shaped profile with different wall thicknesses. The die is optimized automatically and simulation results are qualitatively compared with experimental results. Furthermore, the strategy is applied to a complex extrusion die of a floor skirting profile to prove the universal adaptability.
Optimization of advanced plants operation: The Escrime project
International Nuclear Information System (INIS)
Fiche, C.; Papin, B.
1994-01-01
The Escrime program aims at defining the optimal share of tasks between humans and computers under normal or accidental plant operation. Basic principles we keep in mind are the following: human operators are likely to be necessary in the operation of future plants because we cannot demonstrate that plant design is error free, so unexpected situation can still happen; automation must not release the operators from their decisional role but only help them avoiding situations of cognitive overload which can lead to increase the risk of errors; the optimum share of tasks between human and automatic systems must be based on a critical analysis of the tasks and of the way they are handled. The last point appeared to be of major importance. The corresponding analysis of the French PWR's operating procedures enabled us to define a unified scheme for plant operation under the form of a hierarchy of goals and means. Beyond this analysis, development of a specific testing facility is under way to check the relevance of the proposed plant operation organization and to test the human-machine cooperation in different situations for various levels of automation. 7 refs, 4 figs
Optimization of fuel cycle strategies with constraints on uranium availability
International Nuclear Information System (INIS)
Silvennoinen, P.; Vira, J.; Westerberg, R.
1982-01-01
Optimization of nuclear reactor and fuel cycle strategies is studied under the influence of reduced availability of uranium. The analysis is separated in two distinct steps. First, the global situation is considered within given high and low projections of the installed capacity up to the year 2025. Uranium is regarded as an exhaustible resource whose production cost would increase proportionally to increasing cumulative exploitation. Based on the estimates obtained for the uranium cost, a global strategy is derived by splitting the installed capacity between light water reactor (LWR) once-through, LWR recycle, and fast breeder reactor (FBR) alternatives. In the second phase, the nuclear program of an individual utility is optimized within the constraints imposed from the global scenario. Results from the global scenarios indicate that in a reference case the uranium price would triple by the year 2000, and the price escalation would continue throughout the planning period. In a pessimistic growth scenario where the global nuclear capacity would not exceed 600 GW(electric) in 2025, the uranium price would almost double by 2000. In both global scenarios, FBRs would be introduced, in the reference case after 2000 and in the pessimistic case after 2010. In spite of the increases in the uranium prices, the levelized power production cost would increase only by 45% up to 2025 in the utility case provided that the plutonium is incinerated as a substitute fuel
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Integrated approach to optimize operation and maintenance costs for operating nuclear power plants
International Nuclear Information System (INIS)
2006-06-01
In the context of increasingly open electricity markets and the 'unbundling' of generating companies from former utility monopolies, an area of major concern is the economic performance of the existing fleet of nuclear power plants. Nuclear power, inevitably, must compete directly with other electricity generation sources. Coping with this competitive pressure is a challenge that the nuclear industry should meet if the nuclear option is to remain a viable one. This competitive environment has significant implications for nuclear plant operations, including, among others, the need for the more cost effective management of plant activities, and the greater use of analytical tools to balance the costs and benefits of proposed activities, in order to optimize operation and maintenance costs, and thus insure the economic competitiveness of existing nuclear power plants. In the framework of the activities on Nuclear Economic Performance Information System (NEPIS), the IAEA embarked in developing guidance on optimization of operation and maintenance costs for nuclear power plants. The report was prepared building on the fundamental that optimization of operation and maintenance costs of a nuclear power plant is a key component of a broader integrated business strategic planning process, having as overall result achievement of organization's business objectives. It provides advice on optimization of O and M costs in the framework of strategic business planning, with additional details on operational planning and controlling. This TECDOC was elaborated in 2004-2005 in the framework of the IAEA's programme on Nuclear Power Plant Operating Performance and Life Cycle Management, with the support of two consultants meetings and one technical meeting and based on contributions provided by participants. It can serve as a useful reference for the management and operation staff within utilities, nuclear power plant operators and regulators and other organizations involved in
Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries
Directory of Open Access Journals (Sweden)
Yan Li
2016-01-01
Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.
Optimal reservoir operation policies using novel nested algorithms
Delipetrev, Blagoj; Jonoski, Andreja; Solomatine, Dimitri
2015-04-01
Historically, the two most widely practiced methods for optimal reservoir operation have been dynamic programming (DP) and stochastic dynamic programming (SDP). These two methods suffer from the so called "dual curse" which prevents them to be used in reasonably complex water systems. The first one is the "curse of dimensionality" that denotes an exponential growth of the computational complexity with the state - decision space dimension. The second one is the "curse of modelling" that requires an explicit model of each component of the water system to anticipate the effect of each system's transition. We address the problem of optimal reservoir operation concerning multiple objectives that are related to 1) reservoir releases to satisfy several downstream users competing for water with dynamically varying demands, 2) deviations from the target minimum and maximum reservoir water levels and 3) hydropower production that is a combination of the reservoir water level and the reservoir releases. Addressing such a problem with classical methods (DP and SDP) requires a reasonably high level of discretization of the reservoir storage volume, which in combination with the required releases discretization for meeting the demands of downstream users leads to computationally expensive formulations and causes the curse of dimensionality. We present a novel approach, named "nested" that is implemented in DP, SDP and reinforcement learning (RL) and correspondingly three new algorithms are developed named nested DP (nDP), nested SDP (nSDP) and nested RL (nRL). The nested algorithms are composed from two algorithms: 1) DP, SDP or RL and 2) nested optimization algorithm. Depending on the way we formulate the objective function related to deficits in the allocation problem in the nested optimization, two methods are implemented: 1) Simplex for linear allocation problems, and 2) quadratic Knapsack method in the case of nonlinear problems. The novel idea is to include the nested
Directory of Open Access Journals (Sweden)
Carmen Fullana-Belda
2013-10-01
Full Text Available Traditional uneven-aged forest management seeks a balance between equilibrium stand structure and economic profitability, which often leads to harvesting strategies concentrated in the larger diameter classes. The sustainability (i.e., population persistence over time and influence of such economically optimal strategies on the equilibrium position of a stand (given by the stable diameter distribution have not been sufficiently investigated in prior forest literature. This article therefore proposes a discrete optimal control model to analyze the sustainability and stability of the economically optimal harvesting strategies of uneven-aged Pinus nigra stands. For this model, we rely on an objective function that integrates financial data of harvesting operations with a projection matrix model that can describe the population dynamics. The model solution reveals the optimal management schedules for a wide variety of scenarios. To measure the distance between the stable diameter distribution and the economically optimal harvesting strategy distribution, the model uses Keyfitz’s delta, which returns high values for all the scenarios and, thus, suggests that those economically optimal harvesting strategies have an unstabilizing influence on the equilibrium positions. Moreover, the economically optimal harvesting strategies were unsustainable for all the scenarios.
Tsai, Wen-Ping; Chang, Fi-John; Chang, Li-Chiu; Herricks, Edwin E.
2015-11-01
Flow regime is the key driver of the riverine ecology. This study proposes a novel hybrid methodology based on artificial intelligence (AI) techniques for quantifying riverine ecosystems requirements and delivering suitable flow regimes that sustain river and floodplain ecology through optimizing reservoir operation. This approach addresses issues to better fit riverine ecosystem requirements with existing human demands. We first explored and characterized the relationship between flow regimes and fish communities through a hybrid artificial neural network (ANN). Then the non-dominated sorting genetic algorithm II (NSGA-II) was established for river flow management over the Shihmen Reservoir in northern Taiwan. The ecosystem requirement took the form of maximizing fish diversity, which could be estimated by the hybrid ANN. The human requirement was to provide a higher satisfaction degree of water supply. The results demonstrated that the proposed methodology could offer a number of diversified alternative strategies for reservoir operation and improve reservoir operational strategies producing downstream flows that could meet both human and ecosystem needs. Applications that make this methodology attractive to water resources managers benefit from the wide spread of Pareto-front (optimal) solutions allowing decision makers to easily determine the best compromise through the trade-off between reservoir operational strategies for human and ecosystem needs.
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.
Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.
Survey Strategy Optimization for the Atacama Cosmology Telescope
De Bernardis, F.; Stevens, J. R.; Hasselfield, M.; Alonso, D.; Bond, J. R.; Calabrese, E.; Choi, S. K.; Crowley, K. T.; Devlin, M.; Wollack, E. J.
2016-01-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over approximately 2000 square degrees. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24-hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
International Nuclear Information System (INIS)
Romero, Alberto; Millar, Dean; Carvalho, Monica; Maestre, José M.; Camacho, Eduardo F.
2015-01-01
Mine dewatering can represent up to 5% of the total energy demand of a mine, and is one of the mine systems that aim to guarantee safe operating conditions. As mines go deeper, dewatering pumping heads become bigger, potentially involving several lift stages. Greater depth does not only mean greater dewatering cost, but more complex systems that require more sophisticated control systems, especially if mine operators wish to gain benefits from demand response incentives that are becoming a routine part of electricity tariffs. This work explores a two stage economic optimization procedure of an underground mine dewatering system, comprising two lifting stages, each one including a pump station and a water reservoir. First, the system design is optimized considering hourly characteristic dewatering demands for twelve days, one day representing each month of the year to account for seasonal dewatering demand variations. This design optimization minimizes the annualized cost of the system, and therefore includes the investment costs in underground reservoirs. Reservoir size, as well as an hourly pumping operation plan are calculated for specific operating environments, defined by characteristic hourly electricity prices and water inflows (seepage and water use from production activities), at best known through historical observations for the previous year. There is no guarantee that the system design will remain optimal when it faces the water inflows and market determined electricity prices of the year ahead, or subsequent years ahead, because these remain unknown at design time. Consequently, the dewatering optimized system design is adopted subsequently as part of a Model Predictive Control (MPC) strategy that adaptively maintains optimality during the operations phase. Centralized, distributed and non-centralized MPC strategies are explored. Results show that the system can be reliably controlled using any of these control strategies proposed. Under the operating
Optimization strategies for cask design and container loading in long term spent fuel storage
International Nuclear Information System (INIS)
2006-12-01
As delays are incurred in implementing reprocessing and in planning for geologic repositories, storage of increasing quantities of spent fuel for extended durations is becoming a growing reality. Accordingly, effective management of spent fuel continues to be a priority topic. In response, the IAEA has organized a series of meetings to identify cask loading optimisation issues in preparation for a technical publication on Optimization Strategies for Cask/Container Loading in Long Term Spent Fuel Storage. This publication outlines the optimisation process for cask design, licensing and utilization, describing three principal groups of optimization activities in terms of relevant technical considerations such as criticality, shielding, structural design, operations, maintenance and retrievability. The optimization process for cask design, licensing, and utilization is outlined. The general objectives for the design of storage casks, including storage casks that are intended to be transportable, are summarized. The nature of optimization within the design process is described. The typical regulatory and licensing process is outlined, focusing on the roles of safety regulations, the regulator, and the designer/applicant in the optimization process. Based on the foregoing, a description of the three principal groups of optimization activities is provided. The subsequent chapters of this document then describe the specific optimization activities within these three activity groups, in each of the several design disciplines
International Nuclear Information System (INIS)
Cox, G.; Beresford, N.A.; Alvarez-Farizo, B.; Oughton, D.; Kis, Z.; Eged, K.; Thorring, H.; Hunt, J.; Wright, S.; Barnett, C.L.; Gil, J.M.; Howard, B.J.; Crout, N.M.J.
2005-01-01
A spatially implemented model designed to assist the identification of optimal countermeasure strategies for radioactively contaminated regions is described. Collective and individual ingestion doses for people within the affected area are estimated together with collective exported ingestion dose. A range of countermeasures are incorporated within the model, and environmental restrictions have been included as appropriate. The model evaluates the effectiveness of a given combination of countermeasures through a cost function which balances the benefit obtained through the reduction in dose with the cost of implementation. The optimal countermeasure strategy is the combination of individual countermeasures (and when and where they are implemented) which gives the lowest value of the cost function. The model outputs should not be considered as definitive solutions, rather as interactive inputs to the decision making process. As a demonstration the model has been applied to a hypothetical scenario in Cumbria (UK). This scenario considered a published nuclear power plant accident scenario with a total deposition of 1.7 x 10 14 , 1.2 x 10 13 , 2.8 x 10 10 and 5.3 x 10 9 Bq for Cs-137, Sr-90, Pu-239/240 and Am-241, respectively. The model predicts that if no remediation measures were implemented the resulting collective dose would be approximately 36 000 person-Sv (predominantly from 137 Cs) over a 10-year period post-deposition. The optimal countermeasure strategy is predicted to avert approximately 33 000 person-Sv at a cost of approximately pound 160 million. The optimal strategy comprises a mixture of ploughing, AFCF (ammonium-ferric hexacyano-ferrate) administration, potassium fertiliser application, clean feeding of livestock and food restrictions. The model recommends specific areas within the contaminated area and time periods where these measures should be implemented
International Nuclear Information System (INIS)
Boonchuay, Chanwit; Ongsakul, Weerakorn
2011-01-01
In this paper, an optimal risky bidding strategy for a generating company (GenCo) by self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC) is proposed. A significant risk index based on mean-standard deviation ratio (MSR) is maximised to provide the optimal bid prices and quantities. The Monte Carlo (MC) method is employed to simulate rivals' behaviour in competitive environment. Non-convex operating cost functions of thermal generating units and minimum up/down time constraints are taken into account. The proposed bidding strategy is implemented in a multi-hourly trading in a uniform price spot market and compared to other particle swarm optimisation (PSO). Test results indicate that the proposed SPSO-TVAC approach can provide a higher MSR than the other PSO methods. It is potentially applicable to risk management of profit variation of GenCo in spot market.
Optimal economic and environment operation of micro-grid power systems
International Nuclear Information System (INIS)
Elsied, Moataz; Oukaour, Amrane; Gualous, Hamid; Lo Brutto, Ottavio A.
2016-01-01
Highlights: • Real-time energy management system for Micro-Grid power systems is introduced. • The management system considered cost objective function and emission constraints. • The optimization problem is solved using Binary Particle Swarm Algorithm. • Advanced real-time interface libraries are used to run the optimization code. - Abstract: In this paper, an advanced real-time energy management system is proposed in order to optimize micro-grid performance in a real-time operation. The proposed strategy of the management system capitalizes on the power of binary particle swarm optimization algorithm to minimize the energy cost and carbon dioxide and pollutant emissions while maximizing the power of the available renewable energy resources. Advanced real-time interface libraries are used to run the optimization code. The simulation results are considered for three different scenarios considering the complexity of the proposed problem. The proposed management system along with its control system is experimentally tested to validate the simulation results obtained from the optimization algorithm. The experimental results highlight the effectiveness of the proposed management system for micro-grids operation.
Integrated Bidding and Operating Strategies for Wind-Storage Systems
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2016-01-01
Due to their flexible charging and discharging capabilities, energy storage systems (ESS) are considered a promising complement to wind farms (WFs) participating in electricity markets. This paper presents integrated day-ahead bidding and real-time operation strategies for a wind-storage system...
A systemic approach for optimal cooling tower operation
International Nuclear Information System (INIS)
Cortinovis, Giorgia F.; Paiva, Jose L.; Song, Tah W.; Pinto, Jose M.
2009-01-01
The thermal performance of a cooling tower and its cooling water system is critical for industrial plants, and small deviations from the design conditions may cause severe instability in the operation and economics of the process. External disturbances such as variation in the thermal demand of the process or oscillations in atmospheric conditions may be suppressed in multiple ways. Nevertheless, such alternatives are hardly ever implemented in the industrial operation due to the poor coordination between the utility and process sectors. The complexity of the operation increases because of the strong interaction among the process variables. In the present work, an integrated model for the minimization of the operating costs of a cooling water system is developed. The system is composed of a cooling tower as well as a network of heat exchangers. After the model is verified, several cases are studied with the objective of determining the optimal operation. It is observed that the most important operational resources to mitigate disturbances in the thermal demand of the process are, in this order: the increase in recycle water flow rate, the increase in air flow rate and finally the forced removal of a portion of the water flow rate that enters the cooling tower with the corresponding make-up flow rate.
Directory of Open Access Journals (Sweden)
Jun Yang
2015-08-01
Full Text Available The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.
Robust approximate optimal guidance strategies for aeroassisted orbital transfer missions
Ilgen, Marc R.
This thesis presents the application of game theoretic and regular perturbation methods to the problem of determining robust approximate optimal guidance laws for aeroassisted orbital transfer missions with atmospheric density and navigated state uncertainties. The optimal guidance problem is reformulated as a differential game problem with the guidance law designer and Nature as opposing players. The resulting equations comprise the necessary conditions for the optimal closed loop guidance strategy in the presence of worst case parameter variations. While these equations are nonlinear and cannot be solved analytically, the presence of a small parameter in the equations of motion allows the method of regular perturbations to be used to solve the equations approximately. This thesis is divided into five parts. The first part introduces the class of problems to be considered and presents results of previous research. The second part then presents explicit semianalytical guidance law techniques for the aerodynamically dominated region of flight. These guidance techniques are applied to unconstrained and control constrained aeroassisted plane change missions and Mars aerocapture missions, all subject to significant atmospheric density variations. The third part presents a guidance technique for aeroassisted orbital transfer problems in the gravitationally dominated region of flight. Regular perturbations are used to design an implicit guidance technique similar to the second variation technique but that removes the need for numerically computing an optimal trajectory prior to flight. This methodology is then applied to a set of aeroassisted inclination change missions. In the fourth part, the explicit regular perturbation solution technique is extended to include the class of guidance laws with partial state information. This methodology is then applied to an aeroassisted plane change mission using inertial measurements and subject to uncertainties in the initial value
Optimization of operating regime of mass-diffusion cascades
International Nuclear Information System (INIS)
Chuzhinov, V.A.; Laguntsov, N.I.; Nikolaev, B.I.; Sulaberidze, G.A.
1975-01-01
This work deals with questions of the optimization of mass diffusion elements (columns or pumps) in cascades. Since the establishment and operation of real diffusion plants involves substantial outlays of material resources and energy, cascade optimization should be conducted in accordance with the criterion of the possibility of realizing further economies on the method and diffusion process. One of these indicators is the cost of the end product. Formulas are given for calculating the basic expenditures required for the production of an isotope in a cascade, and an analytical formula is obtained for assessing the cost of an enriched isotope mixture. Calculations are made of the influence of the steam flow rate on the cost of 99% 13 CH 4 and its constitutents, taking into account capital and power outlay on the construction and operation of the installation. It is demonstrated that as the result of a discrepancy between optimum power and capital outlays, the steam flow rate corresponding to the minimum cost is less than that corresponding to the maximum fractionating capacity of the column. In each specific case, optimization parameters should be selected having regard to the special features of the fractionating method and the fractionating apparatus. The results may be used in calculations of mass-diffusion fractionating installations, and also in comparisons of the effectiveness of the various methods used in the separation of these and other isotopes. (author)
Optimizing Environmental Flow Operation Rules based on Explicit IHA Constraints
Dongnan, L.; Wan, W.; Zhao, J.
2017-12-01
Multi-objective operation of reservoirs are increasingly asked to consider the environmental flow to support ecosystem health. Indicators of Hydrologic Alteration (IHA) is widely used to describe environmental flow regimes, but few studies have explicitly formulated it into optimization models and thus is difficult to direct reservoir release. In an attempt to incorporate the benefit of environmental flow into economic achievement, a two-objective reservoir optimization model is developed and all 33 hydrologic parameters of IHA are explicitly formulated into constraints. The benefit of economic is defined by Hydropower Production (HP) while the benefit of environmental flow is transformed into Eco-Index (EI) that combined 5 of the 33 IHA parameters chosen by principal component analysis method. Five scenarios (A to E) with different constraints are tested and solved by nonlinear programming. The case study of Jing Hong reservoir, located in the upstream of Mekong basin, China, shows: 1. A Pareto frontier is formed by maximizing on only HP objective in scenario A and on only EI objective in scenario B. 2. Scenario D using IHA parameters as constraints obtains the optimal benefits of both economic and ecological. 3. A sensitive weight coefficient is found in scenario E, but the trade-offs between HP and EI objectives are not within the Pareto frontier. 4. When the fraction of reservoir utilizable capacity reaches 0.8, both HP and EI capture acceptable values. At last, to make this modelmore conveniently applied to everyday practice, a simplified operation rule curve is extracted.
Nonlinear Burn Control and Operating Point Optimization in ITER
Boyer, Mark; Schuster, Eugenio
2013-10-01
Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).
Formation of strategy and policy of banking credit operations management
Directory of Open Access Journals (Sweden)
O.V. Lysenok
2016-03-01
Full Text Available The article examines the strategic management of credit operations as the activities on credit strategies of banking institutions, the formation of goals, objectives, and the choice of methods to achieve them. The basis of this is the strategic management analysis of the factors affecting the lending operations, strategic planning, communication mechanisms of strategic and tactical decisions, monitoring the implementation of the strategy and timely adjustments. For the purpose of effective implementation of the developed strategy, the article argues that banks in modern conditions should develop their own internal credit policy which should cover the essential elements and principles of credit at these banks. The study determines that the credit policy is based on the factors determined by the amount of capital assets and loan portfolio, the structure of its clientele, specialization, location, presence of branch network, the situation in the money market.
Energy Technology Data Exchange (ETDEWEB)
Kim, Do Yeon; Yang, Dae Ryook [Korea University, Seoul (Korea, Republic of)
2015-07-15
To improve the filterability of hydroxybenzophenone crystal, a cooling strategy for the cooling crystallization process is investigated by examining the solubility and growth kinetics of hydroxybenzophenone. The operating strategy is divided into two steps. The first step is to generate the seed by dissolving the raw material and by changing operating conditions. The second step is to grow seeds to the product with desired crystal size distribution. For each part, an operating strategy has been proposed based on the solid-liquid phase equilibrium data in a ternary system and growth kinetic experimental results. The strategy for the first step is experimentally determined under various operating conditions, and the second one is determined by theoretical modeling and model-based optimization. The average crystal size resulting from the proposed strategy has been improved and the filterability has been enhanced compared to an existing strategy used in the industry.
International Nuclear Information System (INIS)
Kim, Do Yeon; Yang, Dae Ryook
2015-01-01
To improve the filterability of hydroxybenzophenone crystal, a cooling strategy for the cooling crystallization process is investigated by examining the solubility and growth kinetics of hydroxybenzophenone. The operating strategy is divided into two steps. The first step is to generate the seed by dissolving the raw material and by changing operating conditions. The second step is to grow seeds to the product with desired crystal size distribution. For each part, an operating strategy has been proposed based on the solid-liquid phase equilibrium data in a ternary system and growth kinetic experimental results. The strategy for the first step is experimentally determined under various operating conditions, and the second one is determined by theoretical modeling and model-based optimization. The average crystal size resulting from the proposed strategy has been improved and the filterability has been enhanced compared to an existing strategy used in the industry
Directory of Open Access Journals (Sweden)
Elahe Fallah Mehdipour
2012-12-01
Full Text Available Optimal operation of multipurpose reservoirs is one of the complex and sometimes nonlinear problems in the field of multi-objective optimization. Evolutionary algorithms are optimization tools that search decision space using simulation of natural biological evolution and present a set of points as the optimum solutions of problem. In this research, application of multi-objective particle swarm optimization (MOPSO in optimal operation of Bazoft reservoir with different objectives, including generating hydropower energy, supplying downstream demands (drinking, industry and agriculture, recreation and flood control have been considered. In this regard, solution sets of the MOPSO algorithm in bi-combination of objectives and compromise programming (CP using different weighting and power coefficients have been first compared that the MOPSO algorithm in all combinations of objectives is more capable than the CP to find solution with appropriate distribution and these solutions have dominated the CP solutions. Then, ending points of solution set from the MOPSO algorithm and nonlinear programming (NLP results have been compared. Results showed that the MOPSO algorithm with 0.3 percent difference from the NLP results has more capability to present optimum solutions in the ending points of solution set.
Sobh, Tarek M.; Tibrewal, Abhilasha
2006-01-01
Operating systems theory primarily concentrates on the optimal use of computing resources. This paper presents an alternative approach to teaching and studying operating systems design and concepts by way of parametrically optimizing critical operating system functions. Detailed examples of two critical operating systems functions using the…
Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub
International Nuclear Information System (INIS)
Ma, Tengfei; Wu, Junyong; Hao, Liangliang
2017-01-01
Highlights: • Design a novel architecture for energy hub integrating power hub, cooling hub and heating hub. • The micro energy grid based on energy hub is introduced and its advantages are discussed. • Propose a generic modeling method for the energy flow of micro energy grid. • Propose an optimal operation model for micro energy grid with considering demand response. • The roles of renewable energy, energy storage devices and demand response are discussed separately. - Abstract: The energy security and environmental problems impel people to explore a more efficient, environment friendly and economical energy utilization pattern. In this paper, the coordinated operation and optimal dispatch strategies for multiple energy system are studied at the whole Micro Energy Grid level. To augment the operation flexibility of energy hub, the innovation sub-energy hub structure including power hub, heating hub and cooling hub is put forward. Basing on it, a generic energy hub architecture integrating renewable energy, combined cooling heating and power, and energy storage devices is developed. Moreover, a generic modeling method for the energy flow of micro energy grid is proposed. To minimize the daily operation cost, a day-ahead dynamic optimal operation model is formulated as a mixed integer linear programming optimization problem with considering the demand response. Case studies are undertaken on a community Micro Energy Grid in four different scenarios on a typical summer day and the roles of renewable energy, energy storage devices and demand response are discussed separately. Numerical simulation results indicate that the proposed energy flow modeling and optimal operation method are universal and effective over the entire energy dispatching horizon.
Braun, Robert Joseph
The advent of maturing fuel cell technologies presents an opportunity to achieve significant improvements in energy conversion efficiencies at many scales; thereby, simultaneously extending our finite resources and reducing "harmful" energy-related emissions to levels well below that of near-future regulatory standards. However, before realization of the advantages of fuel cells can take place, systems-level design issues regarding their application must be addressed. Using modeling and simulation, the present work offers optimal system design and operation strategies for stationary solid oxide fuel cell systems applied to single-family detached dwellings. A one-dimensional, steady-state finite-difference model of a solid oxide fuel cell (SOFC) is generated and verified against other mathematical SOFC models in the literature. Fuel cell system balance-of-plant components and costs are also modeled and used to provide an estimate of system capital and life cycle costs. The models are used to evaluate optimal cell-stack power output, the impact of cell operating and design parameters, fuel type, thermal energy recovery, system process design, and operating strategy on overall system energetic and economic performance. Optimal cell design voltage, fuel utilization, and operating temperature parameters are found using minimization of the life cycle costs. System design evaluations reveal that hydrogen-fueled SOFC systems demonstrate lower system efficiencies than methane-fueled systems. The use of recycled cell exhaust gases in process design in the stack periphery are found to produce the highest system electric and cogeneration efficiencies while achieving the lowest capital costs. Annual simulations reveal that efficiencies of 45% electric (LHV basis), 85% cogenerative, and simple economic paybacks of 5--8 years are feasible for 1--2 kW SOFC systems in residential-scale applications. Design guidelines that offer additional suggestions related to fuel cell
Optimization of PHEV Power Split Gear Ratio to Minimize Fuel Consumption and Operation Cost
Li, Yanhe
A Plug-in Hybrid Electric Vehicle (PHEV) is a vehicle powered by a combination of an internal combustion engine and an electric motor with a battery pack. The battery pack can be charged by plugging the vehicle to the electric grid and from using excess engine power. The research activity performed in this thesis focused on the development of an innovative optimization approach of PHEV Power Split Device (PSD) gear ratio with the aim to minimize the vehicle operation costs. Three research activity lines have been followed: • Activity 1: The PHEV control strategy optimization by using the Dynamic Programming (DP) and the development of PHEV rule-based control strategy based on the DP results. • Activity 2: The PHEV rule-based control strategy parameter optimization by using the Non-dominated Sorting Genetic Algorithm (NSGA-II). • Activity 3: The comprehensive analysis of the single mode PHEV architecture to offer the innovative approach to optimize the PHEV PSD gear ratio.
Optimal Constant DC Link Voltage Operation of aWave Energy Converter
Directory of Open Access Journals (Sweden)
Mats Leijon
2013-04-01
Full Text Available This article proposes a simple and reliable damping strategy for wave powerfarm operation of small-scale point-absorber converters. The strategy is based on passiverectification onto a constant DC-link, making it very suitable for grid integration of the farm.A complete model of the system has been developed in Matlab Simulink, and uses real sitedata as input. The optimal constant DC-voltage is evaluated as a function of the significantwave height and energy period of the waves. The total energy output of the WEC is derivedfor one year of experimental site data. The energy output is compared for two cases, onewhere the optimal DC-voltage is determined and held constant at half-hour basis throughoutthe year, and one where a selected value of the DC-voltage is kept constant throughout theyear regardless of sea state.
[Numerical simulation and operation optimization of biological filter].
Zou, Zong-Sen; Shi, Han-Chang; Chen, Xiang-Qiang; Xie, Xiao-Qing
2014-12-01
BioWin software and two sensitivity analysis methods were used to simulate the Denitrification Biological Filter (DNBF) + Biological Aerated Filter (BAF) process in Yuandang Wastewater Treatment Plant. Based on the BioWin model of DNBF + BAF process, the operation data of September 2013 were used for sensitivity analysis and model calibration, and the operation data of October 2013 were used for model validation. The results indicated that the calibrated model could accurately simulate practical DNBF + BAF processes, and the most sensitive parameters were the parameters related to biofilm, OHOs and aeration. After the validation and calibration of model, it was used for process optimization with simulating operation results under different conditions. The results showed that, the best operation condition for discharge standard B was: reflux ratio = 50%, ceasing methanol addition, influent C/N = 4.43; while the best operation condition for discharge standard A was: reflux ratio = 50%, influent COD = 155 mg x L(-1) after methanol addition, influent C/N = 5.10.
International Nuclear Information System (INIS)
Franco, Alessandro; Versace, Michele
2017-01-01
Highlights: • Combined Heat and Power plants and civil/residential energy uses. • CHP plant supported by auxiliary boilers and thermal energy storage. • Definition of optimal operational strategies for cogeneration plants for District Heating. • Optimal-sized Thermal Energy Storage and a hybrid operational strategy. • Maximization of cogeneration share and reduction of time of operation of auxiliary boilers. - Abstract: The aim of the paper is to define optimal operational strategies for Combined Heat and Power plants connected to civil/residential District Heating Networks. The role of a reduced number of design variables, including a Thermal Energy Storage system and a hybrid operational strategy dependent on the storage level, is considered. The basic principle is to reach maximum efficiency of the system operation through the utilization of an optimal-sized Thermal Energy Storage. Objective functions of both energetic and combined energetic and economic can be considered. In particular, First and Second Law Efficiency, thermal losses of the storage, number of starts and stops of the combined heat and power unit are considered. Constraints are imposed to nullify the waste of heat and to operate the unit at its maximum efficiency for the highest possible number of consecutive operating hours, until the thermal tank cannot store more energy. The methodology is applied to a detailed case study: a medium size district heating system, in an urban context in the northern Italy, powered by a combined heat and power plant supported by conventional auxiliary boilers. The issues involving this type of thermal loads are also widely investigated in the paper. An increase of Second Law Efficiency of the system of 26% (from 0.35 to 0.44) can be evidenced, while the First Law Efficiency shifts from about 0.74 to 0.84. The optimization strategy permits of combining the economic benefit of cogeneration with the idea of reducing the energy waste and exergy losses.
Optimal operation of integrated processes. Studies on heat recovery systems
Energy Technology Data Exchange (ETDEWEB)
Glemmestad, Bjoern
1997-12-31
Separators, reactors and a heat exchanger network (HEN) for heat recovery are important parts of an integrated plant. This thesis deals with the operation of HENs, in particular, optimal operation. The purpose of heat integration is to save energy, but the HEN also introduces new interactions and feedback into the overall plant. A prerequisite for optimisation is that there are extra degrees of freedom left after regulatory control is implemented. It is shown that extra degrees of freedom may not always be utilized for energy optimisation, and a quantitative expression for the degrees of freedom that can be so utilized are presented. A simplified expression that is often valid is also deduced. The thesis presents some improvements and generalisations of a structure based method that has been proposed earlier. Structural information is used to divide possible manipulations into three categories depending on how each manipulation affects the utility consumption. By means of these categories and two heuristic rules for operability, the possible manipulations are ordered in a priority table. This table is used to determine which manipulation should be preferred and which manipulation should be selected if an active manipulation is saturated. It is shown that the method may correspond to split-range control. A method that uses parametric information in addition to structural information is proposed. In this method, the optimal control structure is found through solving an integer programming problem. The thesis also proposes a method that combines the use of steady state optimisation and optimal selection of measurements. 86 refs., 46 figs., 8 tabs.
Optimal operating conditions for maximum biogas production in anaerobic bioreactors
International Nuclear Information System (INIS)
Balmant, W.; Oliveira, B.H.; Mitchell, D.A.; Vargas, J.V.C.; Ordonez, J.C.
2014-01-01
The objective of this paper is to demonstrate the existence of optimal residence time and substrate inlet mass flow rate for maximum methane production through numerical simulations performed with a general transient mathematical model of an anaerobic biodigester introduced in this study. It is herein suggested a simplified model with only the most important reaction steps which are carried out by a single type of microorganisms following Monod kinetics. The mathematical model was developed for a well mixed reactor (CSTR – Continuous Stirred-Tank Reactor), considering three main reaction steps: acidogenesis, with a μ max of 8.64 day −1 and a K S of 250 mg/L, acetogenesis, with a μ max of 2.64 day −1 and a K S of 32 mg/L, and methanogenesis, with a μ max of 1.392 day −1 and a K S of 100 mg/L. The yield coefficients were 0.1-g-dry-cells/g-pollymeric compound for acidogenesis, 0.1-g-dry-cells/g-propionic acid and 0.1-g-dry-cells/g-butyric acid for acetogenesis and 0.1 g-dry-cells/g-acetic acid for methanogenesis. The model describes both the transient and the steady-state regime for several different biodigester design and operating conditions. After model experimental validation, a parametric analysis was performed. It was found that biogas production is strongly dependent on the input polymeric substrate and fermentable monomer concentrations, but fairly independent of the input propionic, acetic and butyric acid concentrations. An optimisation study was then conducted and optimal residence time and substrate inlet mass flow rate were found for maximum methane production. The optima found were very sharp, showing a sudden drop of methane mass flow rate variation from the observed maximum to zero, within a 20% range around the optimal operating parameters, which stresses the importance of their identification, no matter how complex the actual bioreactor design may be. The model is therefore expected to be a useful tool for simulation, design, control and
Gradient Material Strategies for Hydrogel Optimization in Tissue Engineering Applications
2018-01-01
Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell–hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell–hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior. PMID:29485612
Optimal Strategies for Probing Terrestrial Exoplanet Atmospheres with JWST
Batalha, Natasha E.; Lewis, Nikole K.; Line, Michael
2018-01-01
It is imperative that the exoplanet community determines the feasibility and the resources needed to yield high fidelity atmospheric compositions from terrestrial exoplanets. In particular, LHS 1140b and the TRAPPIST-1 system, already slated for observations by JWST’s Guaranteed Time Observers, will be the first two terrestrial planets observed by JWST. I will discuss optimal observing strategies for observing these two systems, focusing on the NIRSpec Prism (1-5μm) and the combination of NIRISS SOSS (1-2.7μm) and NIRSpec G395H (3-5μm). I will also introduce currently unsupported JWST readmodes that have the potential to greatly increase the precision on our atmospheric spectra. Lastly, I will use information content theory to compute the expected confidence interval on the retrieved abundances of key molecular species and temperature profiles as a function of JWST observing cycles.
Optimal Inspection and Repair Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.; Nowak, A. S.; Thoft-Christensen, Palle
1992-01-01
and a design variable as optimization variables. A model for estimating the total expected costs for structural systems is given including the costs associated with the loss of individual structural members as well as the costs associated with the loss of at least one element of a particular group......A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... of structural members and the costs associated with the simultaneous loss of all members of a specific group of structural members. The approach is based on the pre-posteriori analysis from the classical decision theory. Special emphasis is given to the problem of selecting the number of points in the structure...
Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang
2008-12-01
Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.
Optimal Bidding of a Microgrid Based on Probabilistic Analysis of Island Operation
Directory of Open Access Journals (Sweden)
Siyoung Lee
2016-10-01
Full Text Available Island operation of a microgrid increases operation survivability and reliability when there is a large accident in a main grid. However, because a microgrid typically has limited generation capability, a microgrid operator (MGO has to take the risk of island operation into account in its market participation and generation scheduling to ensure efficient operation. In this paper, a microgrid islanding event is interpreted as a trade suspension of a contract, and a set of islanding rules is presented in the form of a market rule. The risk of island operation is evaluated by modeling the microgrid islanding stochastically using an islanding probability function, which is defined in the form of a conditional probability to reflect the influence of outside conditions. An optimal bidding strategy is obtained for the MGO by formulating and solving an optimization problem to minimize the expected operating cost. The effectiveness of the proposed method was investigated by numerical simulations in which the proposed method and two other methods were applied to the same microgrid. Numerical sensitivity analyses of the coefficients of the islanding probability function were conducted to determine how an MGO copes with changes in outside conditions.
Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.
2011-10-01
This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.
Directory of Open Access Journals (Sweden)
Shuai Su
2016-02-01
Full Text Available Increasing attention is being paid to the energy efficiency in metro systems to reduce the operational cost and to advocate the sustainability of railway systems. Classical research has studied the energy-efficient operational strategy and the energy-efficient system design separately to reduce the traction energy consumption. This paper aims to combine the operational strategies and the system design by analyzing how the infrastructure and vehicle parameters of metro systems influence the operational traction energy consumption. Firstly, a solution approach to the optimal train control model is introduced, which is used to design the Optimal Train Control Simulator(OTCS. Then, based on the OTCS, the performance of some important energy-efficient system design strategies is investigated to reduce the trains’ traction energy consumption, including reduction of the train mass, improvement of the kinematic resistance, the design of the energy-saving gradient, increasing the maximum traction and braking forces, introducing regenerative braking and timetable optimization. As for these energy-efficient strategies, the performances are finally evaluated using the OTCS with the practical operational data of the Beijing Yizhuang metro line. The proposed approach gives an example to quantitatively analyze the energy reduction of different strategies in the system design procedure, which may help the decision makers to have an overview of the energy-efficient performances and then to make decisions by balancing the costs and the benefits.
Collins, Linda M
2018-01-01
This book presents a framework for development, optimization, and evaluation of behavioral, biobehavioral, and biomedical interventions. Behavioral, biobehavioral, and biomedical interventions are programs with the objective of improving and maintaining human health and well-being, broadly defined, in individuals, families, schools, organizations, or communities. These interventions may be aimed at, for example, preventing or treating disease, promoting physical and mental health, preventing violence, or improving academic achievement. This volume introduces the Multiphase Optimization Strategy (MOST), pioneered at The Methodology Center at the Pennsylvania State University, as an alternative to the classical approach of relying solely on the randomized controlled trial (RCT). MOST borrows heavily from perspectives taken and approaches used in engineering, and also integrates concepts from statistics and behavioral science, including the RCT. As described in detail in this book, MOST consists of ...
Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
Cooperative Optimal Operation of Wind-Storage Facilities
DEFF Research Database (Denmark)
Farashbashi-Astaneh, Seyed-Mostafa; Hu, Weihao; Chen, Zhe
2014-01-01
investment cost. We suggest benefitting the storage unit as a regulation service provider beside its normal operation for mitigating wind power imbalances. This idea comes from the fact that storage units have a fast ramping capability which is necessary to meet close to real-time regulation needs......As the penetration of wind power increases in power systems across the world, wind forecast errors become an emerging problem. Storage units are reliable tools to be used in cooperation with wind farms to mitigate imbalance penalties. Nevertheless they are not still economically viable due to huge....... In this paper a framework is proposed to formulate the optimal design of storage unit’s operation under different scenarios. These scenarios include whether the wind farm is actually generating more or less than the scheduled level submitted to day-ahead market. The results emphasize that the deployment...
Engineering to Control Noise, Loading, and Optimal Operating Points
International Nuclear Information System (INIS)
Mitchell R. Swartz
2000-01-01
Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems
Optimal Design and Operation Management of Battery-Based Energy Storage Systems (BESS) in Microgrids
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Dulout, Jeremy; Alonso, Corinne
2017-01-01
of energy storage units requires certain performance measures and constraints, which has to be well considered in design phase and embedded in control and management strategies. This chapter mainly focuses on these aspects and provides a general framework for optimal design and operation management......-scale integration of renewables into the grid environment. Energy storage options can also be used for economic operation of energy systems to cut down system’s operating cost. By utilizing ESSs, it is very possible to store energy in off-peak hours with lower cost and energize the grid during peak load intervals...... at supply/demand side which is helpful for load levelling or peak shaving purposes. Last but not least, ESSs can provide frequency regulation services in offgrid locations where there is a strong need to meet the power balance in different operating conditions. Each of the abovementioned applications...
Optimized green operation of LTE networks in the presence of multiple electricity providers
Ghazzai, Hakim
2012-12-01
Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.
Optimized green operation of LTE networks in the presence of multiple electricity providers
Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.
2012-01-01
Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.
Zhao, Zhongfan; Li, Yaoyu; Mu, Baojie; Salsbury, Timothy I.; House, John M.
2016-01-01
Chilled-water plants with multiple chillers account for a significant fraction of energy use in large commercial buildings. Real-time optimization and sequencing of such plants is thus critical for building energy efficiency. Due to the cost and complexity associated with calibrating a chiller plant model to field operation, model-free control has become an attractive solution. Recently, Mu et al. (2015) proposed a model-free real-time optimization and sequencing strategy based on extremum se...
Optimization of startup and shutdown operation of simulated moving bed chromatographic processes.
Li, Suzhou; Kawajiri, Yoshiaki; Raisch, Jörg; Seidel-Morgenstern, Andreas
2011-06-24
This paper presents new multistage optimal startup and shutdown strategies for simulated moving bed (SMB) chromatographic processes. The proposed concept allows to adjust transient operating conditions stage-wise, and provides capability to improve transient performance and to fulfill product quality specifications simultaneously. A specially tailored decomposition algorithm is developed to ensure computational tractability of the resulting dynamic optimization problems. By examining the transient operation of a literature separation example characterized by nonlinear competitive isotherm, the feasibility of the solution approach is demonstrated, and the performance of the conventional and multistage optimal transient regimes is evaluated systematically. The quantitative results clearly show that the optimal operating policies not only allow to significantly reduce both duration of the transient phase and desorbent consumption, but also enable on-spec production even during startup and shutdown periods. With the aid of the developed transient procedures, short-term separation campaigns with small batch sizes can be performed more flexibly and efficiently by SMB chromatography. Copyright © 2011 Elsevier B.V. All rights reserved.
Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization
Directory of Open Access Journals (Sweden)
Da Xie
2016-06-01
Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.
Optimal production of renewable hydrogen based on an efficient energy management strategy
International Nuclear Information System (INIS)
Ziogou, Chrysovalantou; Ipsakis, Dimitris; Seferlis, Panos; Bezergianni, Stella; Papadopoulou, Simira; Voutetakis, Spyros
2013-01-01
This work presents the development of a flexible energy management strategy (EMS) for a renewable hydrogen production unit through water electrolysis with solar power. The electricity flow of the unit is controlled by a smart microgrid and the overall unattended operation is achieved by a supervisory control system. The proposed approach formalizes the knowledge regarding the system operation using a finite-state machine (FSM) which is subsequently combined with a propositional-based logic to describe the transitions among various process states. The operating rules for the integrated system are derived by taking into account both the operating constraints and the interaction effects among the individual subsystems in a systematic way. Optimal control system parameter values are obtained so that a system performance criterion incorporating efficient and economic operation is satisfied. The resulted EMS has been deployed to the industrial automation system that monitors and controls a small-scale experimental solar hydrogen production unit. The overall performance of the proposed EMS in the experimental unit has been evaluated over short-term and long-term operating periods resulting in smooth and efficient hydrogen production. - Highlights: • Development of an energy management strategy based on a finite-state machine and propositional-based reasoning. • Deployment of the energy-aware algorithm to an autonomous renewable hydrogen production unit. • Supervisory control of the electricity flow by a smart microgrid using an industrial automation system. • Unattended operation and remote monitoring incorporating subsystem interactions in a systematic way. • Optimal hydrogen production regardless of the weather conditions through water electrolysis with solar power
Workforce Optimization for Bank Operation Centers: A Machine Learning Approach
Directory of Open Access Journals (Sweden)
Sefik Ilkin Serengil
2017-12-01
Full Text Available Online Banking Systems evolved and improved in recent years with the use of mobile and online technologies, performing money transfer transactions on these channels can be done without delay and human interaction, however commercial customers still tend to transfer money on bank branches due to several concerns. Bank Operation Centers serve to reduce the operational workload of branches. Centralized management also offers personalized service by appointed expert employees in these centers. Inherently, workload volume of money transfer transactions changes dramatically in hours. Therefore, work-force should be planned instantly or early to save labor force and increase operational efficiency. This paper introduces a hybrid multi stage approach for workforce planning in bank operation centers by the application of supervised and unsu-pervised learning algorithms. Expected workload would be predicted as supervised learning whereas employees are clus-tered into different skill groups as unsupervised learning to match transactions and proper employees. Finally, workforce optimization is analyzed for proposed approach on production data.
Operational characteristics optimization of human-computer system
Directory of Open Access Journals (Sweden)
Zulquernain Mallick
2010-09-01
Full Text Available Computer operational parameters are having vital influence on the operators efficiency from readability viewpoint. Four parameters namely font, text/background color, viewing angle and viewing distance are analyzed. The text reading task, in the form of English text, was presented on the computer screen to the participating subjects and their performance, measured in terms of number of words read per minute (NWRPM, was recorded. For the purpose of optimization, the Taguchi method is used to find the optimal parameters to maximize operators’ efficiency for performing readability task. Two levels of each parameter have been considered in this study. An orthogonal array, the signal-to-noise (S/N ratio and the analysis of variance (ANOVA were employed to investigate the operators’ performance/efficiency. Results showed that Times Roman font, black text on white background, 40 degree viewing angle and 60 cm viewing distance, the subjects were quite comfortable, efficient and read maximum number of words per minute. Text/background color was dominant parameter with a percentage contribution of 76.18% towards the laid down objective followed by font type at 18.17%, viewing distance 7.04% and viewing angle 0.58%. Experimental results are provided to confirm the effectiveness of this approach.
Optimization of wind farm power production using innovative control strategies
DEFF Research Database (Denmark)
Duc, Thomas
Wind energy has experienced a very significant growth and cost reduction over the past decade, and is now able to compete with conventional power generation sources. New concepts are currently investigated to decrease costs of production of electricity even further. Wind farm coordinated control...... deficit caused by the wake downstream, or yawing the turbine to deflect the wake away from the downwind turbine. Simulation results found in the literature indicate that an increase in overall power production can be obtained. However they underline the high sensitivity of these gains to incoming wind...... aligned wind turbines. The experimental results show that the scenarios implemented during the first measurement campaign did not achieve an increase in overall power production, which confirms the difficulty to realize wind farm power optimization in real operating conditions. In the curtailment field...
Improved operating strategies for uranium extraction: a stochastic simulation
International Nuclear Information System (INIS)
Broekman, B.R.
1986-01-01
Deterministic and stochastic simulations of a Western Transvaal uranium process are used in this research report to determine more profitable uranium plant operating strategies and to gauge the potential financial benefits of automatic process control. The deterministic simulation model was formulated using empirical and phenomenological process models. The model indicated that profitability increases significantly as the uranium leaching strategy becomes harsher. The stochastic simulation models use process variable distributions corresponding to manually and automatically controlled conditions to investigate the economic gains that may be obtained if a change is made from manual to automatic control of two important process variables. These lognormally distributed variables are the pachuca 1 sulphuric acid concentration and the ferric to ferrous ratio. The stochastic simulations show that automatic process control is justifiable in certain cases. Where the leaching strategy is relatively harsh, such as that in operation during January 1986, it is not possible to justify an automatic control system. Automatic control is, however, justifiable if a relatively mild leaching strategy is adopted. The stochastic and deterministic simulations represent two different approaches to uranium process modelling. This study has indicated the necessity for each approach to be applied in the correct context. It is contended that incorrect conclusions may have been drawn by other investigators in South Africa who failed to consider the two approaches separately
Optimal mission planning of GEO on-orbit refueling in mixed strategy
Chen, Xiao-qian; Yu, Jing
2017-04-01
The mission planning of GEO on-orbit refueling (OOR) in Mixed strategy is studied in this paper. Specifically, one SSc will be launched to an orbital slot near the depot when multiple GEO satellites are reaching their end of lives. The SSc replenishes fuel from the depot and then extends the lifespan of the target satellites via refueling. In the mixed scenario, only some of the target satellites could be served by the SSc, and the remaining ones will be fueled by Pseudo SScs (the target satellite which has already been refueled by the SSc and now has sufficient fuel for its operation as well as the fuel to refuel other target satellites is called Pseudo SSc here). The mission sequences and fuel mass of the SSc and Pseudo SScs, the dry mass of the SSc are used as design variables, whereas the economic benefit of the whole mission is used as design objective. The economic cost and benefit models are stated first, and then a mathematical optimization model is proposed. A comprehensive solution method involving enumeration, particle swarm optimization and modification is developed. Numerical examples are carried out to demonstrate the effectiveness of the model and solution method. Economic efficiencies of different OOR strategies are compared and discussed. The mixed strategy would perform better than the other strategies only when the target satellites satisfy some conditions. This paper presents an available mixed strategy scheme for users and analyzes its advantages and disadvantages by comparing with some other OOR strategies, providing helpful references to decision makers. The best strategy in practical applications depends on the specific demands and user preference.
Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System
Directory of Open Access Journals (Sweden)
Anh-Duc Nguyen
2018-06-01
Full Text Available The increased penetration of renewables is beneficial for power systems but it poses several challenges, i.e., uncertainty in power supply, power quality issues, and other technical problems. Backup generators or storage system have been proposed to solve this problem but there are limitations remaining due to high installation and maintenance cost. Furthermore, peak load is also an issue in the power distribution system. Due to the adjustable characteristics of loads, strategies on demand side such as demand response (DR are more appropriate in order to deal with these challenges. Therefore, this paper studies how DR programs influence the operation of the multi-microgrid (MMG. The implementation is executed based on a hierarchical energy management system (HiEMS including microgrid EMSs (MG-EMSs responsible for local optimization in each MG and community EMS (C-EMS responsible for community optimization in the MMG. Mixed integer linear programming (MILP-based mathematical models are built for MMG optimal operation. Five scenarios consisting of single DR programs and DR groups are tested in an MMG test system to evaluate their impact on MMG operation. Among the five scenarios, some DR programs apply curtailing strategies, resulting in a study about the influence of base load value and curtailable load percentage on the amount of curtailed load and shifted load as well as the operation cost of the MMG. Furthermore, the impact of DR programs on the amount of external and internal trading power in the MMG is also examined. In summary, each individual DR program or group could be handy in certain situations depending on the interest of the MMG such as external trading, self-sufficiency or operation cost minimization.
An Optimization of ASI Operation Band in KSNP
International Nuclear Information System (INIS)
Park, C.O.; Um, K.S.; Lee, J.I.; Choi, T.S.; Yoo, J.S.; Kim, J.S.; Kim, J.J.; Ryu, S.H.; Choi, J.D.; Kwon, J.T.; Lee, C.C.; Kim, J.I.; Suh, D.S.
2002-01-01
A power level dependent ASI LCO (Limiting Condition for Operation) is developed for the Korea Standard Nuclear Power Plant to improve the plant operability in the low power range and to gain the additional thermal margin in the high power range. The ASI LCO for COLSS (Core Operating Limit Supervisory System) in the low power range between 20% and 40% is relaxed to ±0.57 from ±0.27 so as to enhance the plant operability especially during the fast return-to-power maneuvering after trip. In contrast, the ASI LCO in the high power range between 80% and 100% is tightened to ±0.17 from ±0.27 to recover unnecessarily eroded thermal margin that could otherwise be easily utilized for enhancing capacity factor like the power up-rating. In addition to the COLSS ASI optimization, the CPC ASI range trip set point is expanded from ±0.5 to ±0.7 to allow the COLSS LCO change and to enhance the plant operability for power range below 20% by virtually eliminating the possibility of ASI range trip. Safety evaluations for the limiting accidents of concern have been carried out to demonstrate that the power dependent ASI LCO does not cause any un-compliance with safety criteria and provides considerable thermal margin gain in the high power range. Thermal margin evaluation to date indicates that ±0.1 ASI reduction near full power level can lead to ∼2% overpower margin gain and more than 85 K gain in LOCA PCT. (authors)
Operational Strategy of CBPs for load balancing of Operators in Advanced Main Control Room
International Nuclear Information System (INIS)
Kim, Seunghwan; Kim, Yochan; Jung, Wondea
2014-01-01
With the using of a computer-based control room in an APR1400 (Advanced Pressurized Reactor-1400), the operators' behaviors in the main control room had changed. However, though the working environment of operators has been changed a great deal, digitalized interfaces can also change the cognitive tasks or activities of operators. First, a shift supervisor (SS) can confirm/check the conduction of the procedures and the execution of actions of board operators (BOs) while confirming directly the operation variables without relying on the BOs. Second, all operators added to their work the use of a new CBP and Soft Controls, increasing their procedural workload. New operational control strategies of CBPs are necessary for load balancing of operator's task load in APR1400. In this paper, we compared the workloads of operators in an APR1400 who work with two different usages of the CBP. They are SS oriented usage and SS-BO collaborative usage. In this research, we evaluated the workloads of operators in an advanced main control room by the COCOA method. Two types of CBP usages were defined and the effects of these usages on the workloads were investigated. The obtained results showed that the workloads between operators in a control room can be balanced according to the CBP usages by assigning control authority to the operators
Operational Strategy of CBPs for load balancing of Operators in Advanced Main Control Room
Energy Technology Data Exchange (ETDEWEB)
Kim, Seunghwan; Kim, Yochan; Jung, Wondea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-05-15
With the using of a computer-based control room in an APR1400 (Advanced Pressurized Reactor-1400), the operators' behaviors in the main control room had changed. However, though the working environment of operators has been changed a great deal, digitalized interfaces can also change the cognitive tasks or activities of operators. First, a shift supervisor (SS) can confirm/check the conduction of the procedures and the execution of actions of board operators (BOs) while confirming directly the operation variables without relying on the BOs. Second, all operators added to their work the use of a new CBP and Soft Controls, increasing their procedural workload. New operational control strategies of CBPs are necessary for load balancing of operator's task load in APR1400. In this paper, we compared the workloads of operators in an APR1400 who work with two different usages of the CBP. They are SS oriented usage and SS-BO collaborative usage. In this research, we evaluated the workloads of operators in an advanced main control room by the COCOA method. Two types of CBP usages were defined and the effects of these usages on the workloads were investigated. The obtained results showed that the workloads between operators in a control room can be balanced according to the CBP usages by assigning control authority to the operators.
Exploring the Optimal Strategy to Predict Essential Genes in Microbes
Directory of Open Access Journals (Sweden)
Yao Lu
2011-12-01
Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.
Optimal integration strategies for a syngas fuelled SOFC and gas turbine hybrid
Zhao, Yingru; Sadhukhan, Jhuma; Lanzini, Andrea; Brandon, Nigel; Shah, Nilay
This article aims to develop a thermodynamic modelling and optimization framework for a thorough understanding of the optimal integration of fuel cell, gas turbine and other components in an ambient pressure SOFC-GT hybrid power plant. This method is based on the coupling of a syngas-fed SOFC model and an associated irreversible GT model, with an optimization algorithm developed using MATLAB to efficiently explore the range of possible operating conditions. Energy and entropy balance analysis has been carried out for the entire system to observe the irreversibility distribution within the plant and the contribution of different components. Based on the methodology developed, a comprehensive parametric analysis has been performed to explore the optimum system behavior, and predict the sensitivity of system performance to the variations in major design and operating parameters. The current density, operating temperature, fuel utilization and temperature gradient of the fuel cell, as well as the isentropic efficiencies and temperature ratio of the gas turbine cycle, together with three parameters related to the heat transfer between subsystems are all set to be controllable variables. Other factors affecting the hybrid efficiency have been further simulated and analysed. The model developed is able to predict the performance characteristics of a wide range of hybrid systems potentially sizing from 2000 to 2500 W m -2 with efficiencies varying between 50% and 60%. The analysis enables us to identify the system design tradeoffs, and therefore to determine better integration strategies for advanced SOFC-GT systems.
Optimizing strategies to improve interprofessional practice for veterans, part 1
Directory of Open Access Journals (Sweden)
Bhattacharya SB
2014-04-01
Full Text Available Shelley B Bhattacharya,1–3 Michelle I Rossi,1,2 Jennifer M Mentz11Geriatric Research Education and Clinical Center (GRECC, Veteran's Affairs Pittsburgh Healthcare System, 2University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 3Albert Schweitzer Fellowship Program, Pittsburgh, PA, USAIntroduction: Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran's Affairs (VA system initiated interprofessional practice (IPP models with their Geriatric Evaluation and Management (GEM programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.Methods: Three strategies were used: 1 a national GEM program survey; 2 a veteran/family satisfaction survey; and 3 an absentee assessment.Results: Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.Discussion: Maintaining the
International Nuclear Information System (INIS)
Zheng, Xiaoyu; Ishikawa, Jun; Sugiyama, Tomoyuki; Maryyama, Yu
2017-01-01
Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the “black-box” code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents
Energy Technology Data Exchange (ETDEWEB)
Zheng, Xiaoyu; Ishikawa, Jun; Sugiyama, Tomoyuki; Maryyama, Yu [Nuclear Safety Research Center, Japan Atomic Energy Agency, Ibaraki (Japan)
2017-03-15
Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the “black-box” code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.
Directory of Open Access Journals (Sweden)
B. Thamaraikannan
2014-01-01
Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.
Operational controlling - a tool of translating strategy into action
Directory of Open Access Journals (Sweden)
2011-03-01
Full Text Available . Enterprises have a lot of problems with realization their strategic aims in the fast changing and competitive business arena from many years. Effective execution of strategic plan needs its translating into action, task results and indicators of everyday activities. The success on the market is attainable by communicating strategic and operating goals on the each level of organizational structure and their connecting with budget of units or employee motivation. The scorecards balancing in finance, customer, process and development perspectives is very useful for pointing - what do we control with? or - what do we have to achieve? But doesn't answer to question about ways of enterprise managing. Main aim of the article is proving that operational controlling system is a essential tool for translating strategy into action. The Balanced Scorecard methodology should to take into consideration system and process connection of enterprise with procurement, co-operation or distribution supply chain also.
Operation and maintenance strategies for wave energy converters
DEFF Research Database (Denmark)
Ambühl, Simon; Marquis, Laurent; Kofoed, Jens Peter
2015-01-01
costs including costs due to lost electricity production are minimized. The risk-based approach is compared with an approach where only boats are used and another approach where the target is to minimize the downtime of the device. This article presents a dynamic approach for total operation......Inspection and maintenance costs are a significant contributor to the cost of energy for wave energy converters. There are different operation and maintenance strategies for wave energy converters. Maintenance can be performed after failure (corrective) or before a breakdown (preventive) occurs....... Furthermore, a helicopter and boats can be used to transport equipment and personnel to the device, or the whole device can be towed to a harbour for operation and maintenance actions. This article describes, among others, a risk-based inspection and maintenance planning approach where the overall repair...
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Directory of Open Access Journals (Sweden)
Vesna Tornjanski
2017-02-01
Full Text Available This paper sets out to extend and deepen the understanding the ways toward economic sustainability through efficient and effective growth operations strategies, quality management and operational excellence in banking. In this study we define new quality management practices based on developed conceptual architecture of digital platform for operations function in banking. Additionally, we employ decision making framework consisted of two parts: introduction of new operations services using Total Unduplicated Reach and Frequency (TURF statistical analysis and segregation of core from actual and augmented operations services utilizing Analytic Network Process (ANP method based on BOCR model. Proposed quality management practices were used for the first time in this paper for particular purposes and have the high potential to impact the excellence in banking business. The study can contribute to operations management, quality management, innovation management, IT management, business process management and decision making in service organizations.
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Electricity pricing: optimal operation and investment by industrial consumers
Energy Technology Data Exchange (ETDEWEB)
Outhred, H.R.; Kaye, R.J.; Sutanto, D.; Manimaran, R.; Bannister, C.H.; Lee, Y.B.
1988-08-01
Ongoing research in the areas of economically efficient electricity pricing and industrial consumer response is described. A new electricity pricing theory is described that incorporates future uncertainty and intertemporal linkages between decisions. It indicates that electricity prices should contain two terms - short-run marginal cost plus a term that reflects how each particular decision is likely to affect future global welfare. A practical implementation using spot prices and forward contracts plus financial instruments for risk sharing and decision coordination is explored, and a procedure for developing long-term pricing policy is considered. The operation of industrial plant has been investigated and models developed to optimize plant behaviour in response to spot prices and forward contracts for electricity. These models are described and results of simulation studies discussed. The economic efficiency and risk sharing advantages of this advanced tariff structure compared with a conventional time-of-use tariff are illustrated.
OPTIMIZATION OF OPERATION PARAMETERS OF 80-KEV ELECTRON GUN
Directory of Open Access Journals (Sweden)
JEONG DONG KIM
2014-06-01
As a first step, the electron generator of an 80-keV electron gun was manufactured. In order to produce the high beam power from electron linear accelerator, a proper beam current is required form the electron generator. In this study, the beam current was measured by evaluating the performance of the electron generator. The beam current was determined by five parameters: high voltage at the electron gun, cathode voltage, pulse width, pulse amplitude, and bias voltage at the grid. From the experimental results under optimal conditions, the high voltage was determined to be 80 kV, the pulse width was 500 ns, and the cathode voltage was from 4.2 V to 4.6 V. The beam current was measured as 1.9 A at maximum. These results satisfy the beam current required for the operation of an electron linear accelerator.
Optimizing wellfield operation in a variable power price regime
DEFF Research Database (Denmark)
Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus
Wellfield management is a multi-objective optimization problem. One important management objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m3). However, power systems in most countries are moving in the direction of deregulated power...... use itself. We estimated energy footprint as a function of wellfield pumping rate (EFP-Q relationship) for a wellfield in Denmark using a coupled well and pipe network model. This EFP-Q relationship was subsequently used in a stochastic dynamic programming framework to minimize total cost of operating...... the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include storage...
Optimizing Wellfield Operation in a Variable Power Price Regime
DEFF Research Database (Denmark)
Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus
2016-01-01
Wellfield management is a multiobjective optimization problem. One important objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m3). However, power systems in most countries are moving in the direction of deregulated markets and price...... itself. We estimated EFP of pumped water as a function of wellfield pumping rate (EFP-Q relationship) for a wellfield in Denmark using a coupled well and pipe network model. This EFP-Q relationship was subsequently used in a Stochastic Dynamic Programming (SDP) framework to minimize total cost...... of operating the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include...
Optimal Stochastic Advertising Strategies for the U.S. Beef Industry
Kun C. Lee; Stanley Schraufnagel; Earl O. Heady
1982-01-01
An important decision variable in the promotional strategy for the beef sector is the optimal level of advertising expenditures over time. Optimal stochastic and deterministic advertising expenditures are derived for the U.S. beef industry for the period `1966 through 1980. They are compared with historical levels and gains realized by optimal advertising strategies are measured. Finally, the optimal advertising expenditures in the future are forecasted.
Nanaeda, Kimihiro; Mueller, Fabian; Brouwer, Jacob; Samuelsen, Scott
Operating strategies of solid oxide fuel cell (SOFC) combined heat and power (CHP) systems are developed and evaluated from a utility, and end-user perspective using a fully integrated SOFC-CHP system dynamic model that resolves the physical states, thermal integration and overall efficiency of the system. The model can be modified for any SOFC-CHP system, but the present analysis is applied to a hotel in southern California based on measured electric and heating loads. Analysis indicates that combined heat and power systems can be operated to benefit both the end-users and the utility, providing more efficient electric generation as well as grid ancillary services, namely dispatchable urban power. Design and operating strategies considered in the paper include optimal sizing of the fuel cell, thermal energy storage to dispatch heat, and operating the fuel cell to provide flexible grid power. Analysis results indicate that with a 13.1% average increase in price-of-electricity (POE), the system can provide the grid with a 50% operating range of dispatchable urban power at an overall thermal efficiency of 80%. This grid-support operating mode increases the operational flexibility of the SOFC-CHP system, which may make the technology an important utility asset for accommodating the increased penetration of intermittent renewable power.
Installation and first operation of the negative ion optimization experiment
International Nuclear Information System (INIS)
De Muri, Michela; Cavenago, Marco; Serianni, Gianluigi; Veltri, Pierluigi; Bigi, Marco; Pasqualotto, Roberto; Barbisan, Marco; Recchia, Mauro; Zaniol, Barbara; Kulevoy, Timour; Petrenko, Sergey; Baseggio, Lucio; Cervaro, Vannino; Agostini, Fabio Degli; Franchin, Luca; Laterza, Bruno; Minarello, Alessandro; Rossetto, Federico; Sattin, Manuele; Zucchetti, Simone
2015-01-01
Highlights: • Negative ion sources are key components of the neutral beam injectors. • The NIO1 experiment is a RF ion source, 60 kV–135 mA hydrogen negative ion beam. • NIO1 can contribute to beam extraction and optics thanks to quick replacement and upgrading of parts. • This work presents installation, status and first experiments results of NIO1. - Abstract: Negative ion sources are key components of the neutral beam injectors for thermonuclear fusion experiments. The NIO1 experiment is a radio frequency ion source generating a 60 kV–135 mA hydrogen negative ion beam. The beam is composed of nine beamlets over an area of about 40 × 40 mm"2. This experiment is jointly developed by Consorzio RFX and INFN-LNL, with the purpose of providing and optimizing a test ion source, capable of working in continuous mode and in conditions similar to those foreseen for the larger ion sources of the ITER neutral beam injectors. At present research and development activities on these ion sources still address several important issues related to beam extraction and optics optimization, to which the NIO1 test facility can contribute thanks to its modular design, which allows for quick replacement and upgrading of components. This contribution presents the installation phases, the status of the test facility and the results of the first experiments, which have demonstrated that the source can operate in continuous mode.
Optimization of bridging agents size distribution for drilling operations
Energy Technology Data Exchange (ETDEWEB)
Waldmann, Alex; Andrade, Alex Rodrigues de; Pires Junior, Idvard Jose; Martins, Andre Leibsohn [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)]. E-mails: awaldmann@petrobras.com.br; andradear.gorceix@petrobras.com.br; idvard.gorceix@petrobras.com.br; aleibsohn@petrobras.com.br
2008-07-01
The conventional drilling technique is based on positive hydrostatic pressure against well walls to prevent inflows of native fluids into the well. Such inflows can cause security problems for the team well and to probe. As the differential pressure of the well to reservoir is always positive, the filtrate of the fluid tends to invade the reservoir rock. Minimize the invasion of drilling fluid is a relevant theme in the oil wells drilling operations. In the design of drilling fluid, a common practice in the industry is the addition of bridging agents in the composition of the fluid to form a cake of low permeability at well walls and hence restrict the invasive process. The choice of drilling fluid requires the optimization of the concentration, shape and size distribution of particles. The ability of the fluid to prevent the invasion is usually evaluated in laboratory tests through filtration in porous media consolidated. This paper presents a description of the methods available in the literature for optimization of the formulation of bridging agents to drill-in fluids, predicting the pore throat from data psychotherapy, and a sensitivity analysis of the main operational parameters. The analysis is based on experimental results of the impact of the size distribution and concentration of bridging agents in the filtration process of drill-in fluids through porous media submitted to various different differential of pressure. The final objective is to develop a software for use of PETROBRAS, which may relate different types and concentrations of bridging agents with the properties of the reservoir to minimize the invasion. (author)
International Nuclear Information System (INIS)
Gao, Jiajia; Huang, Gongsheng; Xu, Xinhua
2016-01-01
Highlights: • An optimization strategy for a small-scale air-conditioning system is developed. • The optimization strategy aims at optimizing the overall system energy consumption. • The strategy may guarantee the robust control of the space air temperature. • The performance of the optimization strategy was tested on a simulation platform. - Abstract: This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.
Noninfectious uveitis: strategies to optimize treatment compliance and adherence
Directory of Open Access Journals (Sweden)
Dolz-Marco R
2015-08-01
Full Text Available Rosa Dolz-Marco,1 Roberto Gallego-Pinazo,1 Manuel Díaz-Llopis,2 Emmett T Cunningham Jr,3–6 J Fernando Arévalo7,8 1Unit of Macula, Department of Ophthalmology, University and Polytechnic Hospital La Fe, 2Faculty of Medicine, University of Valencia, Spain; 3Department of Ophthalmology, California Pacific Medical Center, San Francisco, 4Department of Ophthalmology, Stanford University School of Medicine, Stanford, 5The Francis I Proctor Foundation, University of California San Francisco Medical Center, 6West Coast Retina Medical Group, San Francisco, CA, USA; 7Vitreoretina Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 8Retina Division, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Noninfectious uveitis includes a heterogenous group of sight-threatening ocular and systemic disorders. Significant progress has been made in the treatment of noninfectious uveitis in recent years, particularly with regard to the effective use of corticosteroids and non-corticosteroid immunosuppressive drugs, including biologic agents. All of these therapeutic approaches are limited, however, by any given patient’s ability to comply with and adhere to their prescribed treatment. In fact, compliance and adherence are among the most important patient-related determinants of treatment success. We discuss strategies to optimize compliance and adherence. Keywords: noninfectious uveitis, intraocular inflammation, immunosuppressive treatment, adherence, compliance, therapeutic failure
Optimal breast cancer screening strategies for older women: current perspectives
Directory of Open Access Journals (Sweden)
Braithwaite D
2016-02-01
Full Text Available Dejana Braithwaite,1 Joshua Demb,1 Louise M Henderson2 1Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 2Department of Radiology, University of North Carolina, Chapel Hill, NC, USA Abstract: Breast cancer is a major cause of cancer-related deaths among older women, aged 65 years or older. Screening mammography has been shown to be effective in reducing breast cancer mortality in women aged 50–74 years but not among those aged 75 years or older. Given the large heterogeneity in comorbidity status and life expectancy among older women, controversy remains over screening mammography in this population. Diminished life expectancy with aging may decrease the potential screening benefit and increase the risk of harms. In this review, we summarize the evidence on screening mammography utilization, performance, and outcomes and highlight evidence gaps. Optimizing the screening strategy will involve separating older women who will benefit from screening from those who will not benefit by using information on comorbidity status and life expectancy. This review has identified areas related to screening mammography in older women that warrant additional research, including the need to evaluate emerging screening technologies, such as tomosynthesis among older women and precision cancer screening. In the absence of randomized controlled trials, the benefits and harms of continued screening mammography in older women need to be estimated using both population-based cohort data and simulation models. Keywords: aging, breast cancer, precision cancer screening
An Optimal Investment Strategy for Insurers in Incomplete Markets
Directory of Open Access Journals (Sweden)
Mohamed Badaoui
2018-04-01
Full Text Available In this paper we consider the problem of an insurance company where the wealth of the insurer is described by a Cramér-Lundberg process. The insurer is allowed to invest in a risky asset with stochastic volatility subject to the influence of an economic factor and the remaining surplus in a bank account. The price of the risky asset and the economic factor are modeled by a system of correlated stochastic differential equations. In a finite horizon framework and assuming that the market is incomplete, we study the problem of maximizing the expected utility of terminal wealth. When the insurer’s preferences are exponential, an existence and uniqueness theorem is proven for the non-linear Hamilton-Jacobi-Bellman equation (HJB. The optimal strategy and the value function have been produced in closed form. In addition and in order to show the connection between the insurer’s decision and the correlation coefficient we present two numerical approaches: A Monte-Carlo method based on the stochastic representation of the solution of the insurer problem via Feynman-Kac’s formula, and a mixed Finite Difference Monte-Carlo one. Finally the results are presented in the case of Scott model.
Optimizing individual iron deficiency prevention strategies in physiological pregnancy
Directory of Open Access Journals (Sweden)
Kramarskiy V.A.
2018-04-01
Full Text Available Sideropenia by the end of pregnancy takes place in all mothers without exception. Moreover, the selective administration of iron preparations, in contrast to the routine, makes it possible to avoid hemochromatosis, frequency of which in the general population makes from 0.5 to 13 %. The aim of the study was to optimize the individual strategy for the prevention of iron deficiency in physiological pregnancy. A prospective pre-experimental study was conducted, the criterion of inclusion in which was the mother’s extragenital and obstetrical pathology during the first half of pregnancy, a burdened obstetric and gynecological anamnesis. The study group of 98 women with a physiological pregnancy in the period of 20 to 24 weeks was recruited by simple ran- dom selection. Serum ferritin, hemoglobin, and serum iron were used to estimate iron deficiency. In the latent stage of iron deficiency against a background of monthly correction with Fenules ® in a dose of 90 mg of elemental iron per day, there was a significant increase in ferritin and iron in the blood rotor. In healthy mothers, during the gestational period of 20–24 weeks, a regularity arises in the replenishment of iron status, especially in the case of repeated pregnancy, which is successfully satisfied during the month of Fenules ® intake in doses of 45 mg or 90 mg per day with a serum ferritin level of, respectively, 30 up to 70 μg/l or less than 30 μg/l.
Sue-Ann, Goh; Ponnambalam, S. G.
This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.
Directory of Open Access Journals (Sweden)
Liudong Zhang
2014-01-01
Full Text Available An uncertain monthly reservoirs operation and multicrop deficit irrigation model was proposed under conjunctive use of underground and surface water for water resources optimization management. The objective is to maximize the total crop yield of the entire irrigation districts. Meanwhile, ecological water remained for the downstream demand. Because of the shortage of water resources, the monthly crop water production function was adopted for multiperiod deficit irrigation management. The model reflects the characteristics of water resources repetitive transformation in typical inland rivers irrigation system. The model was used as an example for water resources optimization management in Shiyang River Basin, China. Uncertainties in reservoir management shown as fuzzy probability were treated through chance-constraint parameter for decision makers. Necessity of dominance (ND was used to analyse the advantages of the method. The optimization results including reservoirs real-time operation policy, deficit irrigation management, and the available water resource allocation could be used to provide decision support for local irrigation management. Besides, the strategies obtained could help with the risk analysis of reservoirs operation stochastically.
Operational strategy and marginal costs in simple trigeneration systems
International Nuclear Information System (INIS)
Lozano, M.A.; Carvalho, M.; Serra, L.M.
2009-01-01
As a direct result of economic pressures to cut expenses, as well as the legal obligation to reduce emissions, companies and businesses are seeking ways to use energy more efficiently. Trigeneration systems (CHCP: Combined Heating, Cooling and Power generation) allow greater operational flexibility at sites with a variable demand for energy in the form of heating and cooling. This is particularly relevant in buildings where the need for heating is restricted to a few winter months. In summer, the absorption chillers make use of the cogenerated heat to produce chilled water, avoiding waste heat discharge. The operation of a simple trigeneration system is analyzed in this paper. The system is interconnected to the electric utility grid, both to receive electricity and to deliver surplus electricity. For any given demand required by the users, a great number of operating conditions are possible. A linear programming model provides the operational mode with the lowest variable cost. A thermoeconomic analysis, based on marginal production costs, is used to obtain unit costs for internal energy flows and final products as well as to explain the best operational strategy as a function of the demand for energy services and the prices of the resources consumed. (author)
Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables
Pina, Jasson; Tilmant, Amaury; Côté, Pascal
2017-11-01
Stochastic dual dynamic programming (SDDP) is one of the few available algorithms to optimize the operating policies of large-scale hydropower systems. This paper presents a variant, called SDDPX, in which exogenous hydrologic variables, such as snow water equivalent and/or sea surface temperature, are included in the state space vector together with the traditional (endogenous) variables, i.e., past inflows. A reoptimization procedure is also proposed in which SDDPX-derived benefit-to-go functions are employed within a simulation carried out over the historical record of both the endogenous and exogenous hydrologic variables. In SDDPX, release policies are now a function of storages, past inflows, and relevant exogenous variables that potentially capture more complex hydrological processes than those found in traditional SDDP formulations. To illustrate the potential gain associated with the use of exogenous variables when operating a multireservoir system, the 3,137 MW hydropower system of Rio Tinto (RT) located in the Saguenay-Lac-St-Jean River Basin in Quebec (Canada) is used as a case study. The performance of the system is assessed for various combinations of hydrologic state variables, ranging from the simple lag-one autoregressive model to more complex formulations involving past inflows, snow water equivalent, and winter precipitation.
Optimal Wind Power Uncertainty Intervals for Electricity Market Operation
Energy Technology Data Exchange (ETDEWEB)
Wang, Ying; Zhou, Zhi; Botterud, Audun; Zhang, Kaifeng
2018-01-01
It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a twosettlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.
Control and operation cost optimization of the HISS cryogenic system
International Nuclear Information System (INIS)
Porter, J.; Bieser, F.; Anderson, D.
1983-08-01
The Heavy Ion Spectrometer System (HISS) relies upon superconducting coils of cryostable design to provide a maximum particle bending field of 3 tesla. A previous paper describes the cryogenic facility including helium refrigeration and gas management. This paper discusses a control strategy which has allowed full time unattended operation, along with significant nitrogen and power cost reductions. Reduction of liquid nitrogen consumption has been accomplished by making use of the sensible heat available in the cold exhaust gas. Measured nitrogen throughput agrees with calculations for sensible heat utilization of zero to 70%. Calculated consumption saving over this range is 40 liters per hour for conductive losses to the supports only. The measured throughput differential for the total system is higher
Optimal Corridor Selection for a Road Space Management Strategy: Methodology and Tool
Directory of Open Access Journals (Sweden)
Sushant Sharma
2017-01-01
Full Text Available Nationwide, there is a growing realization that there are valuable benefits to using the existing roadway facilities to their full potential rather than expanding capacity in a traditional way. Currently, state DOTs are looking for cost-effective transportation solutions to mitigate the growing congestion and increasing funding gaps. Innovative road space management strategies like narrowing of multiple lanes (three or more and shoulder width to add a lane enhance the utilization while eliminating the costs associated with constructing new lanes. Although this strategy (among many generally leads to better mobility, identifying optimal corridors is a challenge and may affect the benefits. Further, there is a likelihood that added capacity may provide localized benefits, at the expense of system level performance measures (travel time and crashes because of the relocation of traffic operational bottlenecks. This paper develops a novel transportation programming and investment decision method to identify optimal corridors for adding capacity in the network by leveraging lane widths. The methodology explicitly takes into consideration the system level benefits and safety. The programming compares two conflicting objectives of system travel time and safety benefits to find an optimal solution.
Optimizing Wind And Hydropower Generation Within Realistic Reservoir Operating Policy
Magee, T. M.; Clement, M. A.; Zagona, E. A.
2012-12-01
Previous studies have evaluated the benefits of utilizing the flexibility of hydropower systems to balance the variability and uncertainty of wind generation. However, previous hydropower and wind coordination studies have simplified non-power constraints on reservoir systems. For example, some studies have only included hydropower constraints on minimum and maximum storage volumes and minimum and maximum plant discharges. The methodology presented here utilizes the pre-emptive linear goal programming optimization solver in RiverWare to model hydropower operations with a set of prioritized policy constraints and objectives based on realistic policies that govern the operation of actual hydropower systems, including licensing constraints, environmental constraints, water management and power objectives. This approach accounts for the fact that not all policy constraints are of equal importance. For example target environmental flow levels may not be satisfied if it would require violating license minimum or maximum storages (pool elevations), but environmental flow constraints will be satisfied before optimizing power generation. Additionally, this work not only models the economic value of energy from the combined hydropower and wind system, it also captures the economic value of ancillary services provided by the hydropower resources. It is recognized that the increased variability and uncertainty inherent with increased wind penetration levels requires an increase in ancillary services. In regions with liberalized markets for ancillary services, a significant portion of hydropower revenue can result from providing ancillary services. Thus, ancillary services should be accounted for when determining the total value of a hydropower system integrated with wind generation. This research shows that the end value of integrated hydropower and wind generation is dependent on a number of factors that can vary by location. Wind factors include wind penetration level
International Nuclear Information System (INIS)
Godoy, E.; Benz, S.J.; Scenna, N.J.
2011-01-01
Optimal combined cycle gas turbine power plants characterized by minimum specific annual cost values are here determined for wide ranges of market conditions as given by the relative weights of capital investment and operative costs, by means of a non-linear mathematical programming model. On the other hand, as the technical optimization allows identifying trends in the system behavior and unveiling optimization opportunities, selected functional relationships are obtained as the thermodynamic optimal values of the decision variables are systematically linked to the ratio between the total heat transfer area and the net power production (here named as specific transfer area). A strategy for simplifying the resolution of the rigorous economic optimization problem of power plants is proposed based on the economic optima distinctive characteristics which describe the behavior of the decision variables of the power plant on its optima. Such approach results in a novel mathematical formulation shaped as a system of non-linear equations and additional constraints that is able to easily provide accurate estimations of the optimal values of the power plant design and operative variables. Research highlights: → We achieve relationships between power plants' economic and thermodynamic optima. → We achieve functionalities among thermodynamic optimal values of decision variables. → The rigorous optimization problem is reduced to a non-linear equations system. → Accurate estimations of power plants' design and operative variables are obtained.
Radio Access Sharing Strategies for Multiple Operators in Cellular Networks
DEFF Research Database (Denmark)
Popovska Avramova, Andrijana; Iversen, Villy Bæk
2015-01-01
deployments (required for coverage enhancement), increased base station utilization, and reduced overall power consumption. Today, network sharing in the radio access part is passive and limited to cell sites. With the introduction of Cloud Radio Access Network and Software Defined Networking adoption...... to the radio access network, the possibility for sharing baseband processing and radio spectrum becomes an important aspect of network sharing. This paper investigates strategies for active sharing of radio access among multiple operators, and analyses the individual benefits depending on the sharing degree...
Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.
Lorenz, Todd C
2012-05-22
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: • Set up reactions and thermal cycling
Combining two strategies to optimize biometric decisions against spoofing attacks
Li, Weifeng; Poh, Norman; Zhou, Yicong
2014-09-01
Spoof attack by replicating biometric traits represents a real threat to an automatic biometric verification/ authentication system. This is because the system, originally designed to distinguish between genuine users from impostors, simply cannot distinguish between a replicated biometric sample (replica) from a live sample. An effective solution is to obtain some measures that can indicate whether or not a biometric trait has been tempered with, e.g., liveness detection measures. These measures are referred to as evidence of spoofing or anti-spoofing measures. In order to make the final accept/rejection decision, a straightforward solution to define two thresholds: one for the anti-spoofing measure, and another for the verification score. We compared two variants of a method that relies on applying two thresholds - one to the verification (matching) score and another to the anti-spoofing measure. Our experiments carried out using a signature database as well as by simulation show that both the brute-force and its probabilistic variant turn out to be optimal under different operating conditions.
Factors affecting the optimal performance of a high-yield pulping operation
Energy Technology Data Exchange (ETDEWEB)
Broderick, G [Noranda Technology Centre, Pointe-Claire, PQ (Canada); Paris, J [Ecole Polytechnique, Montreal, PQ (Canada); Valada, J L [Quebec Univ., Trois-Rivieres, PQ (Canada)
1995-06-01
Strategies for operating a chemical-mechanical pulp mill were investigated from data based on process models from some one hundred pilot scale pulping runs. Optimal values for 55 process and pulp quality variables have been calculated by applying a genetic algorithm search to a fuzzy model of the overall system. Best pulp quality was achieved and maintained when the chemical pretreatment was conducted at moderately low temperatures using a high SO{sub 2} concentration, which produced high sulphonation and high yield at the same time. By characterizing the quality of the pulp at the fibre level, optimization results were said to be more easily transferable to other high yield pulping systems. 19 refs., 6 tabs.
International Nuclear Information System (INIS)
Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad
2015-01-01
Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.
Bacterial Quorum Sensing Stabilizes Cooperation by Optimizing Growth Strategies.
Bruger, Eric L; Waters, Christopher M
2016-11-15
Communication has been suggested as a mechanism to stabilize cooperation. In bacteria, chemical communication, termed quorum sensing (QS), has been hypothesized to fill this role, and extracellular public goods are often induced by QS at high cell densities. Here we show, with the bacterium Vibrio harveyi, that QS provides strong resistance against invasion of a QS defector strain by maximizing the cellular growth rate at low cell densities while achieving maximum productivity through protease upregulation at high cell densities. In contrast, QS mutants that act as defectors or unconditional cooperators maximize either the growth rate or the growth yield, respectively, and thus are less fit than the wild-type QS strain. Our findings provide experimental evidence that regulation mediated by microbial communication can optimize growth strategies and stabilize cooperative phenotypes by preventing defector invasion, even under well-mixed conditions. This effect is due to a combination of responsiveness to environmental conditions provided by QS, lowering of competitive costs when QS is not induced, and pleiotropic constraints imposed on defectors that do not perform QS. Cooperation is a fundamental problem for evolutionary biology to explain. Conditional participation through phenotypic plasticity driven by communication is a potential solution to this dilemma. Thus, among bacteria, QS has been proposed to be a proximate stabilizing mechanism for cooperative behaviors. Here, we empirically demonstrate that QS in V. harveyi prevents cheating and subsequent invasion by nonproducing defectors by maximizing the growth rate at low cell densities and the growth yield at high cell densities, whereas an unconditional cooperator is rapidly driven to extinction by defectors. Our findings provide experimental evidence that QS regulation prevents the invasion of cooperative populations by QS defectors even under unstructured conditions, and they strongly support the role of
International Nuclear Information System (INIS)
Peng, Xingjie; Wang, Kan; Li, Qing
2014-01-01
Highlights: • A new power mapping method based on Ordinary Kriging (OK) is proposed. • Measurements from DayaBay Unit 1 PWR are used to verify the OK method. • The OK method performs better than the CECOR method. • An optimal neutron detector location strategy based on ordinary kriging and simulated annealing is proposed. - Abstract: The Ordinary Kriging (OK) method is presented that is designed for a core power mapping calculation of pressurized water reactors (PWRs). Measurements from DayaBay Unit 1 PWR are used to verify the accuracy of the OK method. The root mean square (RMS) reconstruction errors are kept at less than 0.35%, and the maximum reconstruction relative errors (RE) are kept at less than 1.02% for the entire operating cycle. The reconstructed assembly power distribution results show that the OK method is fit for core power distribution monitoring. The quality of power distribution obtained by the OK method is partly determined by the neutron detector locations, and the OK method is also applied to solve the optimal neutron detector location problem. The spatially averaged ordinary kriging variance (AOKV) is minimized using simulated annealing, and then, the optimal in-core neutron detector locations are obtained. The result shows that the current neutron detector location of DayaBay Unit 1 reactor is near-optimal
International Nuclear Information System (INIS)
Neves, Diana; Silva, Carlos A.
2015-01-01
The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs
Design principles and operating principles: the yin and yang of optimal functioning.
Voit, Eberhard O
2003-03-01
Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.
Optimizing Wellfield Operation in a Variable Power Price Regime.
Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus
2016-01-01
Wellfield management is a multiobjective optimization problem. One important objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m(3) ). However, power systems in most countries are moving in the direction of deregulated markets and price variability is increasing in many markets because of increased penetration of intermittent renewable power sources. In this context the relevant management objective becomes minimizing the cost of electric energy used for pumping and distribution of groundwater from wells rather than minimizing energy use itself. We estimated EFP of pumped water as a function of wellfield pumping rate (EFP-Q relationship) for a wellfield in Denmark using a coupled well and pipe network model. This EFP-Q relationship was subsequently used in a Stochastic Dynamic Programming (SDP) framework to minimize total cost of operating the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include storage capacity and hourly water demand fulfilment. The SDP was solved for a baseline situation and for five scenario runs representing different EFP-Q relationships and different maximum wellfield pumping rates. Savings were quantified as differences in total cost between the scenario and a constant-rate pumping benchmark. Minor savings up to 10% were found in the baseline scenario, while the scenario with constant EFP and unlimited pumping rate resulted in savings up to 40%. Key factors determining potential cost savings obtained by flexible wellfield operation under a variable power price regime are the shape of the EFP-Q relationship, the maximum feasible pumping rate and the capacity of available storage facilities. © 2015 The Authors. Groundwater published by Wiley
Optimal strategy analysis based on robust predictive control for inventory system with random demand
Saputra, Aditya; Widowati, Sutrisno
2017-12-01
In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.
Studies on optimal design and operation of integrated distillation arrangements
Energy Technology Data Exchange (ETDEWEB)
Christiansen, Atle Christer
1997-12-31
During the last decades, there has been growing concern in the chemical engineering environment over the task of developing more cost- and energy efficient process equipment. This thesis discusses measures for improving the end-use energy efficiency of separation systems. It emphasises a certain class of integrated distillation arrangements, in particular it considers means for direct coupling of distillation columns so as to use the underlying physics to facilitate more energy efficient separations. The numerical methods discussed are well suited to solve models of distillation columns. A tear and grid method is proposed that to some extent exploits the sparsity, since the number of tear variables required for solving a distillation model usually is rather small. The parameter continuation method described is well suited for ill-conditioned problems. The analysis of integrated columns is extended beyond the scope of numerical simulations by means of analytical results that applies in certain limiting cases. The consept of preferred separation, which is important for prefractionator arrangements, is considered. From this analysis is derived information that is important for the practical operation of such columns. Finally, the proposed numerical methods are used to optimize Petlyuk arrangements for separating ternary and quaternary mixtures. 166 refs., 130 figs., 20 tabs.
Optimized operation of dielectric laser accelerators: Single bunch
Directory of Open Access Journals (Sweden)
Adi Hanuka
2018-05-01
Full Text Available We introduce a general approach to determine the optimal charge, efficiency and gradient for laser driven accelerators in a self-consistent way. We propose a way to enhance the operational gradient of dielectric laser accelerators by leverage of beam-loading effect. While the latter may be detrimental from the perspective of the effective gradient experienced by the particles, it can be beneficial as the effective field experienced by the accelerating structure, is weaker. As a result, the constraint imposed by the damage threshold fluence is accordingly weakened and our self-consistent approach predicts permissible gradients of ∼10 GV/m, one order of magnitude higher than previously reported experimental results—with unbunched pulse of electrons. Our approach leads to maximum efficiency to occur for higher gradients as compared with a scenario in which the beam-loading effect on the material is ignored. In any case, maximum gradient does not occur for the same conditions that maximum efficiency does—a trade-off set of parameters is suggested.
Energy Technology Data Exchange (ETDEWEB)
Cao, Cuiwen; Zhang, Yakun; Gu, Xingsheng [Ministry of Education, East China Univ. of Science and Technology, Shanghai (China). Key Lab. of Advanced Control and Optimization for Chemical Processes
2013-07-01
Optimizing operation parameters for Texaco coal-water slurry gasifier with the consideration of multiple objectives is a complicated nonlinear constrained problem concerning 3 BP neural networks. In this paper, multi-objective 3-layer mixed cultural differential evolution (MO-3LM-CDE) algorithms which comprise of 4 multi-objective strategies and a 3LM-CDE algorithm are firstly presented. Then they are tested in 6 benchmark functions. Finally, the MO-3LM-CDE algorithms are applied to optimize 3 control parameters of the Texaco coal-water slurry gasifier in methanol production of a real-world chemical plant. The simulation results show that multi-objective optimal results are better than the respective single-objective optimal operations.
A proposed strategy for power optimization of a wind energy conversion system connected to the grid
International Nuclear Information System (INIS)
Taraft, S.; Rekioua, D.; Aouzellag, D.; Bacha, S.
2015-01-01
Highlights: • Wind energy conversion based doubly fed induction generator controlled by matrix converter. • Operation at both sub and super-synchronous regions is possible with the proposed drive system. • Double the power generated by the DFIG at a twice of speed rated. • Sliding mode control is used to achieve active and reactive power control. - Abstract: Many strategies have been developed in last decade to optimize power extracted from wind energy conversion system where many of them can produce only 30% more than the rated power. With the considered strategy, the generated wind power can reach twice its nominal value using a fast and reliable fully rugged electrical control. Indeed, by employing a suitable control technique where the produced power in super-synchronous mode is derived from both the stator and the rotor. Also, the rotor provided power in this case grows up 100% comparing to stator rated power. However, this solution permits to maintain the wind energy conversion system operation in its stable area. The considered system consists of a double fed induction generator whose stator is connected directly to the grid and its rotor is supplied by matrix converter. In this paper, the sliding mode approach to achieve active and reactive power control is used. This latter is combined with de Perturbation and Observation Maximum Power Point Tracking used in the second operation zone. The obtained simulations results are assessed and carried out using Matlab/Simulink package and show the performance and the effectiveness of the proposed control
Optimization for a fuel cell/battery/capacity tram with equivalent consumption minimization strategy
International Nuclear Information System (INIS)
Zhang, Wenbin; Li, Jianqiu; Xu, Liangfei; Ouyang, Minggao
2017-01-01
Highlights: • The hybridization of the fuel cell with the energy storage systems is realized for the tram. • A protype tram is tested based on an operation mode switching method. • An equivalent consumption minimization strategy is proposed and verified for optimization. - Abstract: This paper describes a hybrid tram powered by a Proton Exchange Membrane (PEM) fuel cell (FC) stack supported by an energy storage system (ESS) composed of a Li-ion battery (LB) pack and an ultra-capacitor (UC) pack. This configuration allows the tram to operate without grid connection. The hybrid tram with its full load is tested in the CRRC Qingdao Sifang Co.; Ltd. It firstly works on the operation mode switching method (OPMS) without energy regenerative and proper power management. Therefore, an equivalent consumption minimization strategy (ECMS) aimed at minimizing the hydrogen consumption is proposed to improve the characteristics of the tram. The results show that the proposed control system enhances drivability and economy, and is effective for application to this hybrid system.
Implementation of an optimal control energy management strategy in a hybrid truck
Mullem, D. van; Keulen, T. van; Kessels, J.T.B.A.; Jager, B. de; Steinbuch, M.
2010-01-01
Energy Management Strategies for hybrid powertrains control the power split, between the engine and electric motor, of a hybrid vehicle, with fuel consumption or emission minimization as objective. Optimal control theory can be applied to rewrite the optimization problem to an optimization
Li, Rui
2009-01-01
The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of
Strategies of Yota (Scartel - 4G Operator in Russian Federation
Directory of Open Access Journals (Sweden)
Netra Pal Singh
2013-12-01
Full Text Available Russian Federation is one of the high growth markets for telecom services which are expected to reach $48.5 billion by 2013. With the granting of 4G LTE licenses, it is expected that 4G market in Russian Federation will be dominated by four cellular operators, i.e., MTS, Beeline, and MegaFon, Rostelecom along with two new startups, i.e., Osnova Telecom and Red Telecom (Iladi (2010. In addition, other companies such as Yota, Synterra, COMSTAR, Freshtel etc. are also operating in Russian WiMax & LTE telecom market to provide similar services. This paper is an attempt to analyze some of the parameters of LTE turn Yota WiMax Telecom Operator in Russian Federation. The paper covers current achievements of Yota, its reach in Russian Federation, its network size & technology, its services, expansion plans for future, strategies for survival (in question in a highly competitive market of big companies, and its ultimate fate.
Anodic Cyclization Reactions and the Mechanistic Strategies That Enable Optimization.
Feng, Ruozhu; Smith, Jake A; Moeller, Kevin D
2017-09-19
Oxidation reactions are powerful tools for synthesis because they allow us to reverse the polarity of electron-rich functional groups, generate highly reactive intermediates, and increase the functionality of molecules. For this reason, oxidation reactions have been and continue to be the subject of intense study. Central to these efforts is the development of mechanism-based strategies that allow us to think about the reactive intermediates that are frequently central to the success of the reactions and the mechanistic pathways that those intermediates trigger. For example, consider oxidative cyclization reactions that are triggered by the removal of an electron from an electron-rich olefin and lead to cyclic products that are functionalized for further elaboration. For these reactions to be successful, the radical cation intermediate must first be generated using conditions that limit its polymerization and then channeled down a productive desired pathway. Following the cyclization, a second oxidation step is necessary for product formation, after which the resulting cation must be quenched in a controlled fashion to avoid undesired elimination reactions. Problems can arise at any one or all of these steps, a fact that frequently complicates reaction optimization and can discourage the development of new transformations. Fortunately, anodic electrochemistry offers an outstanding opportunity to systematically probe the mechanism of oxidative cyclization reactions. The use of electrochemical methods allows for the generation of radical cations under neutral conditions in an environment that helps prevent polymerization of the intermediate. Once the intermediates have been generated, a series of "telltale indicators" can be used to diagnose which step in an oxidative cyclization is problematic for less successful transformation. A set of potential solutions to address each type of problem encountered has been developed. For example, problems with the initial
An optimal staggered harvesting strategy for herbaceous biomass energy crops
Energy Technology Data Exchange (ETDEWEB)
Bhat, M.G.; English, B.C. [Univ. of Tennessee, Knoxville, TN (United States)
1993-12-31
Biofuel research over the past two decades indicates lignocellulosic crops are a reliable source of feedstock for alternative energy. However, under the current technology of producing, harvesting and converting biomass crops, the cost of biofuel is not competitive with conventional biofuel. Cost of harvesting biomass feedstock is a single largest component of feedstock cost so there is a cost advantage in designing a biomass harvesting system. Traditional farmer-initiated harvesting operation causes over investment. This study develops a least-cost, time-distributed (staggered) harvesting system for example switch grass, that calls for an effective coordination between farmers, processing plant and a single third-party custom harvester. A linear programming model explicitly accounts for the trade-off between yield loss and benefit of reduced machinery overhead cost, associated with the staggered harvesting system. Total cost of producing and harvesting switch grass will decline by 17.94 percent from conventional non-staggered to proposed staggered harvesting strategy. Harvesting machinery cost alone experiences a significant reduction of 39.68 percent from moving from former to latter. The net return to farmers is estimated to increase by 160.40 percent. Per tonne and per hectare costs of feedstock production will decline by 17.94 percent and 24.78 percent, respectively. These results clearly lend support to the view that the traditional system of single period harvesting calls for over investment on agricultural machinery which escalates the feedstock cost. This social loss to the society in the form of escalated harvesting cost can be avoided if there is a proper coordination among farmers, processing plant and custom harvesters as to when and how biomass crop needs to be planted and harvested. Such an institutional arrangement benefits producers, processing plant and, in turn, end users of biofuels.
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors...... leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...... the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find...
Research on Operation and Control Strategy of 600MW PWR in Load Follow
Energy Technology Data Exchange (ETDEWEB)
Qu, Bing Yang; Cao, Xin Rong [Harbin Engineering University, Harbin (China); Li, Han Chen [China Nuclear Power Engineering Co., Beijing (China)
2014-08-15
600MW Pressurized Water Reactor (PWR) is designed to operate in Constant Axial Offset Control (CAOC) strategy with base load originally. By calculations over a typical load follow scenario '12-3-6-3 {sup (}100-50-100%FP) via the CASMO-4E and SIMULATE-3 package, values of core operating parameter have been examined. With the progress of the nuclear power industry, advanced reactors are considered to have a good performance in load follow, economy and flexibility. Under the premise of fuel loading and structural dimensions unchanged, two independent control rod groups M and AO are used in 600MW pressurized water reactor to provide fine control of both the core reactivity and axial power distribution, which is named ' Improved G strategy .' The influences of different control rod distributions, composition materials, and overlap steps had in power changes have been examined in a comparative study to choose the optimal one.Then we simulate a range of load follow scenarios of the redesigned 600MW core without adjusting soluble boron concentration in the begin, middle and end of first cycle. This paper additionally demonstrated the moderator temperature coefficient and shutdown margin values of the reactor in Improved G strategy to compare with the thermal safety design criteria. It's demonstrated that adequate adjustment of control rod groups enable the core to perform load follow through Improved G strategy in 80% of cycle and save a large volume of liquid effluent particularly toward the end of cycle.
Directory of Open Access Journals (Sweden)
Yongli Wang
2018-03-01
Full Text Available With the application of distributed generation and the development of smart grid technology, micro-grid, an economic and stable power grid, tends to play an important role in the demand side management. Because micro-grid technology and demand response have been widely applied, what Demand Response actions can realize the economic operation of micro-grid has become an important issue for utilities. In this proposed work, operation optimization modeling for micro-grid is done considering distributed generation, environmental factors and demand response. The main contribution of this model is to optimize the cost in the context of considering demand response and system operation. The presented optimization model can reduce the operation cost of micro-grid without bringing discomfort to the users, thus increasing the consumption of clean energy effectively. Then, to solve this operational optimization problem, genetic algorithm is used to implement objective function and DR scheduling strategy. In addition, to validate the proposed model, it is employed on a smart micro-grid from Tianjin. The obtained numerical results clearly indicate the impact of demand response on economic operation of micro-grid and development of distributed generation. Besides, a sensitivity analysis on the natural gas price is implemented according to the situation of China, and the result shows that the natural gas price has a great influence on the operation cost of the micro-grid and effect of demand response.
A systematic review on the composting of green waste: Feedstock quality and optimization strategies.
Reyes-Torres, M; Oviedo-Ocaña, E R; Dominguez, I; Komilis, D; Sánchez, A
2018-04-27
Green waste (GW) is an important fraction of municipal solid waste (MSW). The composting of lignocellulosic GW is challenging due to its low decomposition rate. Recently, an increasing number of studies that include strategies to optimize GW composting appeared in the literature. This literature review focuses on the physicochemical quality of GW and on the effect of strategies used to improve the process and product quality. A systematic search was carried out, using keywords, and 447 papers published between 2002 and 2018 were identified. After a screening process, 41 papers addressing feedstock quality and 32 papers on optimization strategies were selected to be reviewed and analyzed in detail. The GW composition is highly variable due to the diversity of the source materials, the type of vegetation, and climatic conditions. This variability limits a strict categorization of the GW physicochemical characteristics. However, this research established that the predominant features of GW are a C/N ratio higher than 25, a deficit in important nutrients, namely nitrogen (0.5-1.5% db), phosphorous (0.1-0.2% db) and potassium (0.4-0.8% db) and a high content of recalcitrant organic compounds (e.g. lignin). The promising strategies to improve composting of GW were: i) GW particle size reduction (e.g. shredding and separation of GW fractions); ii) addition of energy amendments (e.g. non-refined sugar, phosphate rock, food waste, volatile ashes), bulking materials (e.g. biocarbon, wood chips), or microbial inoculum (e.g. fungal consortia); and iii) variations in operating parameters (aeration, temperature, and two-phase composting). These alternatives have successfully led to the reduction of process length and have managed to transform recalcitrant substances to a high-quality end-product. Copyright © 2018 Elsevier Ltd. All rights reserved.
Cryogenic operation strategy for the SST-1 device
International Nuclear Information System (INIS)
Tanna, V.L.; Pradhan, S.
2013-01-01
The SST-1 has been operated since 2012 as part of its engineering commissioning and almost 5 experimental campaigns have been successfully completed. Before final assembling, cool-down and current excitation tests for the Toroidal field coils and PF 3 (Upper) coil were demonstrated successfully as part of validation under coils test program. These superconducting coils consist of a cable-in-conduit conductor, (CICC) is cooled by the forced-flow Two-phase flow as well as supercritical helium conditions. During the recent campaigns, hydraulic characteristics of whole superconducting magnets along with the TF case cooling were studied as an integral system. Based on the experimental observations, efforts have been made to cryo stable conditions of the SST-1 superconducting magnets system in order to produce steady state TF magnetic field of 1.5 T at the plasma center. Optimization of Helium plant related processes have been worked out and implemented to realize the successful SST-1 device operation over a week. In order to have long experimental campaign, an intermediate temperature cooling down philosophy has been adopted. The complete superconducting coils flow distribution among their cooling channels and pressure head requirements were studied from the measurements. In this paper, we will highlight the recent cool-down results, flow distribution and temperature uniformity aspects while cooling down the SST-1 magnets system. (author)
Finding optimal vaccination strategies for pandemic influenza using genetic algorithms.
Patel, Rajan; Longini, Ira M; Halloran, M Elizabeth
2005-05-21
In the event of pandemic influenza, only limited supplies of vaccine may be available. We use stochastic epidemic simulations, genetic algorithms (GA), and random mutation hill climbing (RMHC) to find optimal vaccine distributions to minimize the number of illnesses or deaths in the population, given limited quantities of vaccine. Due to the non-linearity, complexity and stochasticity of the epidemic process, it is not possible to solve for optimal vaccine distributions mathematically. However, we use GA and RMHC to find near optimal vaccine distributions. We model an influenza pandemic that has age-specific illness attack rates similar to the Asian pandemic in 1957-1958 caused by influenza A(H2N2), as well as a distribution similar to the Hong Kong pandemic in 1968-1969 caused by influenza A(H3N2). We find the optimal vaccine distributions given that the number of doses is limited over the range of 10-90% of the population. While GA and RMHC work well in finding optimal vaccine distributions, GA is significantly more efficient than RMHC. We show that the optimal vaccine distribution found by GA and RMHC is up to 84% more effective than random mass vaccination in the mid range of vaccine availability. GA is generalizable to the optimization of stochastic model parameters for other infectious diseases and population structures.
Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method
Chen, Xiaomin; Wang, Gang
2017-05-01
The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.
Optimal waste-to-energy strategy assisted by GIS For sustainable solid waste management
International Nuclear Information System (INIS)
Tan, S T; Hashim, H; Lee, C T; Lim, J S; Kanniah, K D
2014-01-01
Municipal solid waste (MSW) management has become more complex and costly with the rapid socio-economic development and increased volume of waste. Planning a sustainable regional waste management strategy is a critical step for the decision maker. There is a great potential for MSW to be used for the generation of renewable energy through waste incineration or landfilling with gas capture system. However, due to high processing cost and cost of resource transportation and distribution throughout the waste collection station and power plant, MSW is mostly disposed in the landfill. This paper presents an optimization model incorporated with GIS data inputs for MSW management. The model can design the multi-period waste-to-energy (WTE) strategy to illustrate the economic potential and tradeoffs for MSW management under different scenarios. The model is capable of predicting the optimal generation, capacity, type of WTE conversion technology and location for the operation and construction of new WTE power plants to satisfy the increased energy demand by 2025 in the most profitable way. Iskandar Malaysia region was chosen as the model city for this study
Optimal waste-to-energy strategy assisted by GIS For sustainable solid waste management
Tan, S. T.; Hashim, H.
2014-02-01
Municipal solid waste (MSW) management has become more complex and costly with the rapid socio-economic development and increased volume of waste. Planning a sustainable regional waste management strategy is a critical step for the decision maker. There is a great potential for MSW to be used for the generation of renewable energy through waste incineration or landfilling with gas capture system. However, due to high processing cost and cost of resource transportation and distribution throughout the waste collection station and power plant, MSW is mostly disposed in the landfill. This paper presents an optimization model incorporated with GIS data inputs for MSW management. The model can design the multi-period waste-to-energy (WTE) strategy to illustrate the economic potential and tradeoffs for MSW management under different scenarios. The model is capable of predicting the optimal generation, capacity, type of WTE conversion technology and location for the operation and construction of new WTE power plants to satisfy the increased energy demand by 2025 in the most profitable way. Iskandar Malaysia region was chosen as the model city for this study.
International Nuclear Information System (INIS)
Luo, Xianglong; Zhang, Bingjian; Chen, Ying; Mo, Songping
2013-01-01
Highlights: ► We develop a systematic programming methodology to address equipment failure. ► We classify different operation conditions into real periods and virtual periods. ► The formulated MILP models guarantee cost reduction and enough operation safety. ► The consideration of reserving operation redundancy is effective. - Abstract: One or more interconnected steam power plants (SPPs) are constructed in a petrochemical complex to supply utility energy to the process. To avoid large economic penalties or process shutdowns, these SPPs should be flexible and reliable enough to meet the process energy requirement under varying conditions. Unexpected utility equipment failure is inevitable and difficult to be predicted. Most of the conventional methods are based on the assumption that SPPs do not experience any kind of equipment failure. Unfortunately, a process shutdown cannot be avoided when equipment fails unexpectedly. In this paper, a systematic methodology is presented to minimize the total cost under normal conditions while reserving enough flexibility and safety for unexpected equipment failure conditions. The proposed method transforms the different conditions into real periods to indicate normal scenarios and virtual periods to indicate unexpected equipment failure scenarios. The optimization strategy incorporating various operation redundancy scheduling, the transition constraints from equipment failure conditions to normal conditions, and the boiler load increase behavior modeling are presented to save cost and guarantee operation safety. A detailed industrial case study shows that the proposed systematic methodology is effective and practical in coping with equipment failure conditions with only few additional cost penalties
Research on a Microgrid Subsidy Strategy Based on Operational Efficiency of the Industry Chain
Directory of Open Access Journals (Sweden)
Yong Long
2018-05-01
Full Text Available Government subsidy is a powerful tool to motivate the development of a new energy industry. At the early stage of microgrid development, for the sake of the cost and benefit issue, it is necessary for the government to subsidize so as to support and promote the development of microgrids. However, a big challenge in practice is how to optimize the operational efficiency of the microgrid industry chain with varying targets and methods of subsidy. In order to explore this problem, we construct a subsidy model based on the microgrid industry chain, involving government, investor, operator, equipment supplier, and user. Through calculation and solution of this model, we obtain price and return indicators of each microgrid industry chain participant when the subsidy target differs. Based on that, we contrast and compare the optimal subsidy strategy and influencing factors when operational efficiency indicators vary. Finally, we validate and analyze this model with numerical analysis and discuss the impact of development stage, technological level, and change in subsidy amount on the operational efficiency of the microgrid industry chain and on the returns of each participant. This result is of great significance to subsidy practice for microgrids and the development of microgrids.
Optimal Software Strategies in the Presence of Network Externalities
Liu, Yipeng
2009-01-01
Network externalities or alternatively termed network effects are pervasive in computer software markets. While software vendors consider pricing strategies, they must also take into account the impact of network externalities on their sales. My main interest in this research is to describe a firm's strategies and behaviors in the presence of…
Optimizing the stirring strategy for the vibrating intrinsic reverberation chamber
Serra, Ramiro; Serra, Ramiro; Leferink, Frank Bernardus Johannes
2010-01-01
This work describes the definition, application and assessment of a factorial plan with the aim of gaining insight on what kind of stirring strategy could work the best in a vibrating intrinsic reverberation chamber. Three different stirring strategies were defined as factors of a factorial
Enders, Philip; Adler, Werner; Schaub, Friederike; Hermann, Manuel M; Diestelhorst, Michael; Dietlein, Thomas; Cursiefen, Claus; Heindl, Ludwig M
2017-10-24
To compare a simultaneously optimized continuous minimum rim surface parameter between Bruch's membrane opening (BMO) and the internal limiting membrane to the standard sequential minimization used for calculating the BMO minimum rim area in spectral domain optical coherence tomography (SD-OCT). In this case-control, cross-sectional study, 704 eyes of 445 participants underwent SD-OCT of the optic nerve head (ONH), visual field testing, and clinical examination. Globally and clock-hour sector-wise optimized BMO-based minimum rim area was calculated independently. Outcome parameters included BMO-globally optimized minimum rim area (BMO-gMRA) and sector-wise optimized BMO-minimum rim area (BMO-MRA). BMO area was 1.89 ± 0.05 mm 2 . Mean global BMO-MRA was 0.97 ± 0.34 mm 2 , mean global BMO-gMRA was 1.01 ± 0.36 mm 2 . Both parameters correlated with r = 0.995 (P < 0.001); mean difference was 0.04 mm 2 (P < 0.001). In all sectors, parameters differed by 3.0-4.2%. In receiver operating characteristics, the calculated area under the curve (AUC) to differentiate glaucoma was 0.873 for BMO-MRA, compared to 0.866 for BMO-gMRA (P = 0.004). Among ONH sectors, the temporal inferior location showed the highest AUC. Optimization strategies to calculate BMO-based minimum rim area led to significantly different results. Imposing an additional adjacency constraint within calculation of BMO-MRA does not improve diagnostic power. Global and temporal inferior BMO-MRA performed best in differentiating glaucoma patients.
Cost related sensitivity analysis for optimal operation of a grid-parallel PEM fuel cell power plant
El-Sharkh, M. Y.; Tanrioven, M.; Rahman, A.; Alam, M. S.
Fuel cell power plants (FCPP) as a combined source of heat, power and hydrogen (CHP&H) can be considered as a potential option to supply both thermal and electrical loads. Hydrogen produced from the FCPP can be stored for future use of the FCPP or can be sold for profit. In such a system, tariff rates for purchasing or selling electricity, the fuel cost for the FCPP/thermal load, and hydrogen selling price are the main factors that affect the operational strategy. This paper presents a hybrid evolutionary programming and Hill-Climbing based approach to evaluate the impact of change of the above mentioned cost parameters on the optimal operational strategy of the FCPP. The optimal operational strategy of the FCPP for different tariffs is achieved through the estimation of the following: hourly generated power, the amount of thermal power recovered, power trade with the local grid, and the quantity of hydrogen that can be produced. Results show the importance of optimizing system cost parameters in order to minimize overall operating cost.
Optimal Pricing Strategies for New Products in Dynamic Oligopolies
Engelbert Dockner; Steffen Jørgensen
1988-01-01
This paper deals with the determination of optimal pricing policies for firms in oligopolistic markets. The problem is studied as a differential game and optimal pricing policies are established as Nash open-loop controls. Cost learning effects are assumed such that unit costs are decreasing with cumulative output. Discounting of future profits is also taken into consideration. Initially, the problem is addressed in a general framework, and we proceed to study some specific cases that are rel...
Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units
Directory of Open Access Journals (Sweden)
Jinjiao Hou
2018-05-01
Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.
Heinsch, Stephen C; Das, Siba R; Smanski, Michael J
2018-01-01
Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.
Maere, Thomas; Verrecht, Bart; Moerenhout, Stefanie; Judd, Simon; Nopens, Ingmar
2011-03-01
A benchmark simulation model for membrane bioreactors (BSM-MBR) was developed to evaluate operational and control strategies in terms of effluent quality and operational costs. The configuration of the existing BSM1 for conventional wastewater treatment plants was adapted using reactor volumes, pumped sludge flows and membrane filtration for the water-sludge separation. The BSM1 performance criteria were extended for an MBR taking into account additional pumping requirements for permeate production and aeration requirements for membrane fouling prevention. To incorporate the effects of elevated sludge concentrations on aeration efficiency and costs a dedicated aeration model was adopted. Steady-state and dynamic simulations revealed BSM-MBR, as expected, to out-perform BSM1 for effluent quality, mainly due to complete retention of solids and improved ammonium removal from extensive aeration combined with higher biomass levels. However, this was at the expense of significantly higher operational costs. A comparison with three large-scale MBRs showed BSM-MBR energy costs to be realistic. The membrane aeration costs for the open loop simulations were rather high, attributed to non-optimization of BSM-MBR. As proof of concept two closed loop simulations were run to demonstrate the usefulness of BSM-MBR for identifying control strategies to lower operational costs without compromising effluent quality. Copyright © 2011 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Lacerda, Antonio Ignacio de [Universidade Federal Fluminense, Niteroi, RJ (Brazil). Dept. de Engenharia Quimica]. E-mail: ailac@vm.uff.br; Araujo, Ofelia de Queiroz Fernandes; Medeiros, Jose Luiz de [Universidade Federal, Rio de Janeiro, RJ (Brazil). Escola de Quimica]. E-mail: ofelia@eq.ufrj.br; jlm@eq.ufrj.br
2004-12-01
The increasingly market competitiveness, the frequent changes in costs of raw materials and imposition of environmental restrictions require quick responses from the industries and better control of their production. The growing increase of the computational systems processing capacity and advances in analysis and instrumentation systems favor the formulation of new strategies geared to the operational optimization of industrial processes. The optimization of a process, within a more rigid context, assumes that it is made through the optimal control theory. In this aspect, comparative studies are carried out between some formulations of the problem in terms of optimal control and a new methodology of economic optimization. The study process was a pyrolysis oven for which an economic function was developed. Such function considers the effects of the oven operation on the other subsequent parts of the Ethylene Plant, taking into account their energy consumptions and their operational restrictions. A rigorous thermal-dynamic analysis was made in the development thereof involving major parts of the product separation system upstream the oven. The results obtained met the expectations and the new optimization criterion tested can be implemented in a relatively simple computational system using personal computers currently available. Although the work is oriented towards the pyrolysis of hydrocarbons the proposed structure may be applied to other types of chemical and petrochemical processes with the same topology: a reaction system and a separation system. (author)
Metering Plan: Intelligent Operational Strategies Through Enhanced Metering Systems
Energy Technology Data Exchange (ETDEWEB)
Pope, Jason E.
2016-07-27
The Sustainability Program at Pacific Northwest National Laboratory (PNNL) has adopted a “triple-bottom-line” approach of environmental stewardship, social responsibility, and economic prosperity to its operations. Metering at PNNL works in support of all three, specifically to measure and inform building energy use and greenhouse gas emissions and minimize water use. The foundation for metering at PNNL is a core goal set, which consists of four objectives: providing accurate data without interruption, analyzing data while it is still new, providing actionable recommendations to operations management, and ensuring PNNL’s compliance with contract metering requirements. These core objectives guide the decisions that we make during annual planning and as we operate throughout the year. This 2016 edition of the Metering Plan conveys the metering practices for and vision of the Sustainability Program. Changes in this plan from the 2015 edition include updated tables and an enhanced discussion on energy tracking systems used at PNNL. This plan also discusses updated benchmarking strategies using PNNL’s graphics and analytics tool, BuildingOS by Lucid Design Group. This plan presents our progress toward the metering goals shared by all federal agencies and highlights our successful completion of metering requirements. Currently, PNNL is fully compliant with the applicable legislative and Executive Order metering requirements. PNNL’s approach to the installation of new meters will be discussed. Perhaps most importantly, this plan details the analysis techniques utilized at PNNL that rely on the endless streams of data newly available as a result of increased meter deployment over the last several years. Previous Metering Plans have documented specific meter connection schemes as PNNL focused on deploying meters in a first step toward managing energy and water use. This plan serves not only to highlight PNNL’s successful completion of agency metering goals, but
Exposure assessment strategies for non-routine work operations (NORWO)
International Nuclear Information System (INIS)
Lew, V.; Cohen, J.; Chiusano, S.; McGann, C.; McLouth, L.
1993-09-01
The DOE Office of Health and Office of Safety and Health Oversight are collaborating to address special problems related to assessment of worker exposures associated with nonroutine work operations (NORWO), such as hazardous waste operations. Both off ices have formed a single working group of industrial hygiene specialists from the DOE, fts contractors, and other interested organizations which held its first meeting July 1993. The DOE Canter of Excellence for Exposure Assessment, maintained at Lawrence Livermore National Laboratory, is assisting in developing reasonable policies and guidance on exposure assessment strategies for NORWO. The DOE EA Center will research this subject to assist the DOE in formulating guidance documents for conduct of EA for NORWO that are consistent with the DOE draft EAS technical standard. This report presents an outline for a section on NORWO intended for inclusion in the DOE technical guidance documents for EAS and Hazardous Waste Operations Emergency Response (HAZWOPER) currently under development by the DOE Industrial Hygiene Division (EH-412), and EM-23. Also presented is a review of the July 21--23 meeting and a proposed workplan for developing NORWO exposure assessment procedures. Appendices include: (A) David Weitzman's memo on NORWO, (B) Draft annotated outline of the technical standard for the Assessment of Employee Exposure to Hazardous Chemical Agents, (C) ORC proposed EAS standard, (D) program for the October 31--November 3, 1993 ACGIH Conference on Occupational Exposure Databases, (E) agenda for the July 15, 1993 DOE meeting on NORWO, (F) viewgraphs used in formal presentations at this meeting, (G) Hanford Exposure Assessment Program Plan, and (H) a list of attendees and invitees to the July DOE -- NORWO meeting
Directory of Open Access Journals (Sweden)
Chanda Emmanuel
2013-01-01
Full Text Available Abstract Background While consensus on malaria vector control policy and strategy has stimulated unprecedented political-will, backed by international funding organizations and donors, vector control interventions are expansively being implemented based on assumptions with unequaled successes. This manuscript reports on the strategies, achievements and challenges of the past and contemporary malaria vector control efforts in Zambia. Case description All available information and accessible archived documentary records on malaria vector control in Zambia were reviewed. Retrospective analysis of routine surveillance data from the Health Management Information System (HMIS, data from population-based household surveys and various operations research reports was conducted to assess the status in implementing policies and strategies. Discussion and evaluation Empirical evidence is critical for informing policy decisions and tailoring interventions to local settings. Thus, the World Health Organization (WHO encourages the adoption of the integrated vector management (IVM strategy which is a rational decision making process for optimal use of available resources. One of the key features of IVM is capacity building at the operational level to plan, implement, monitor and evaluate vector control and its epidemiological and entomological impact. In Zambia, great progress has been made in implementing WHO-recommended vector control policies and strategies within the context of the IVM Global Strategic framework with strong adherence to its five key attributes. Conclusions The country has solid, consistent and coordinated policies, strategies and guidelines for malaria vector control. The Zambian experience demonstrates the significance of a coordinated multi-pronged IVM approach effectively operationalized within the context of a national health system.
International Nuclear Information System (INIS)
Han, In-Su; Park, Sang-Kyun; Chung, Chang-Bock
2016-01-01
Highlights: • A proton exchange membrane fuel cell system is operationally optimized. • A constrained optimization problem is formulated to maximize fuel cell efficiency. • Empirical and semi-empirical models for most system components are developed. • Sensitivity analysis is performed to elucidate the effects of major operating variables. • The optimization results are verified by comparison with actual operation data. - Abstract: This paper presents an operation optimization method and demonstrates its application to a proton exchange membrane fuel cell system. A constrained optimization problem was formulated to maximize the efficiency of a fuel cell system by incorporating practical models derived from actual operations of the system. Empirical and semi-empirical models for most of the system components were developed based on artificial neural networks and semi-empirical equations. Prior to system optimizations, the developed models were validated by comparing simulation results with the measured ones. Moreover, sensitivity analyses were performed to elucidate the effects of major operating variables on the system efficiency under practical operating constraints. Then, the optimal operating conditions were sought at various system power loads. The optimization results revealed that the efficiency gaps between the worst and best operation conditions of the system could reach 1.2–5.5% depending on the power output range. To verify the optimization results, the optimal operating conditions were applied to the fuel cell system, and the measured results were compared with the expected optimal values. The discrepancies between the measured and expected values were found to be trivial, indicating that the proposed operation optimization method was quite successful for a substantial increase in the efficiency of the fuel cell system.
Multi-Agent System-Based Microgrid Operation Strategy for Demand Response
Directory of Open Access Journals (Sweden)
Hee-Jun Cha
2015-12-01
Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.
Identification of strategy parameters for particle swarm optimizer through Taguchi method
Institute of Scientific and Technical Information of China (English)
KHOSLA Arun; KUMAR Shakti; AGGARWAL K.K.
2006-01-01
Particle swarm optimization (PSO), like other evolutionary algorithms is a population-based stochastic algorithm inspired from the metaphor of social interaction in birds, insects, wasps, etc. It has been used for finding promising solutions in complex search space through the interaction of particles in a swarm. It is a well recognized fact that the performance of evolutionary algorithms to a great extent depends on the choice of appropriate strategy/operating parameters like population size,crossover rate, mutation rate, crossover operator, etc. Generally, these parameters are selected through hit and trial process, which is very unsystematic and requires rigorous experimentation. This paper proposes a systematic based on Taguchi method reasoning scheme for rapidly identifying the strategy parameters for the PSO algorithm. The Taguchi method is a robust design approach using fractional factorial design to study a large number of parameters with small number of experiments. Computer simulations have been performed on two benchmark functions-Rosenbrock function and Griewank function-to validate the approach.
Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function
International Nuclear Information System (INIS)
Bogolubov, Nikolai N. Jr.; Kyshakevych, Bohdan Yu.; Blackmore, Denis; Prykarpatsky, Anatoliy K.
2010-12-01
A competing market model with a polyvariant profit function that assumes 'zeitnot' stock behavior of clients is formulated within the banking portfolio medium and then analyzed from the perspective of devising optimal strategies. An associated Markov process method for finding an optimal choice strategy for monovariant and bivariant profit functions is developed. Under certain conditions on the bank 'promotional' parameter with respect to the 'fee' for a missed share package transaction and at an asymptotically large enough portfolio volume, universal transcendental equations - determining the optimal share package choice among competing strategies with monovariant and bivariant profit functions - are obtained. (author)
Application of evolution strategy algorithm for optimization of a single-layer sound absorber
Directory of Open Access Journals (Sweden)
Morteza Gholamipoor
2014-12-01
Full Text Available Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process.
Optimal Demand Execution Strategy for the Defense Logistics Agency
2014-12-01
PLT Production Lead-Time PTO Paid Time Off FSC Federal Stock/Supply Class NIIN National Item Identification Number S & OP Sales and Operations...sales and operations planning ( S & OP ). The execution of S & OP involves a mix of inputs from management, sales, operations, finance, and product...four elements of a proper S & OP plan: supply, demand, volume, and mix. Supply in this context refers to the quantity available to meet the existing
Optimal sizing and control strategy of isolated grid with wind power and energy storage system
International Nuclear Information System (INIS)
Luo, Yi; Shi, Lin; Tu, Guangyu
2014-01-01
Highlights: • An energy storage sizing scheme for wind powered isolated grid is developed. • A bi-level control strategy for wind-battery isolated grid is proposed. • The energy storage type selection method for Nan’ao island grid is presented. • The sizing method and the control strategy are verified based on the Nan’ao island. • The wind-battery demonstration system has great benefit for remote areas. - Abstract: Integrating renewable energy and energy storage system provides a prospective way for power supply of remote areas. Focused on the isolated grids comprising renewable energy generation and energy storage, an energy storage sizing method for taking account of the reliability requirement and a bi-level control strategy of the isolated grids are presented in this paper. Based on comparative analysis of current energy storage characteristics and practicability, Sodium–sulfur battery is recommended for power balance control in the isolated grids. The optimal size of the energy storage system is determined by genetic algorithm and sequential simulation. The annualized cost considering the compensation cost of curtailed wind power and load is minimized when the reliability requirement can be satisfied. The sizing method emphasizes the tradeoff between energy storage size and reliability of power supply. The bi-level control strategy is designed as upper level wide area power balance control in dispatch timescale and lower level battery energy storage system V/f control in real-time range for isolated operation. The mixed timescale simulation results of Nan’ao Island grid verify the effectiveness of the proposed sizing method and control strategy
Scout or Cavalry? Optimal Discovery Strategies for GRBs
International Nuclear Information System (INIS)
Nemiroff, Robert J.
2004-01-01
Many present and past gamma-ray burst (GRB) detectors try to be not only a 'scout', discovering new GRBs, but also the 'cavalry', simultaneously optimizing on-board science return. Recently, however, most GRB science return has moved out from the gamma-ray energy bands where discovery usually occurs. Therefore a future gamma-ray instrument that is only a scout might best optimize future GRB science. Such a scout would specialize solely in the initial discovery of GRBs, determining only those properties that would allow an unambiguous handoff to waiting cavalry instruments. Preliminary general principles of scout design and cadence are discussed. Scouts could implement observing algorithms optimized for finding GRBs with specific attributes of duration, location, or energy. Scout sky-scanning algorithms utilizing a return cadence near to desired durations of short GRBs are suggested as a method of discovering GRBs in the unexplored short duration part of the GRB duration distribution
Directory of Open Access Journals (Sweden)
Yi Tang
2017-05-01
Full Text Available In a competitive electricity market with substantial involvement of renewable electricity, maximizing profits by optimizing bidding strategies is crucial to different power producers including conventional power plants and renewable ones. This paper proposes a game-theoretic bidding optimization method based on bi-level programming, where power producers are at the upper level and utility companies are at the lower level. The competition among the multiple power producers is formulated as a non-cooperative game in which bidding curves are their strategies, while uniform clearing pricing is considered for utility companies represented by an independent system operator. Consequently, based on the formulated game model, the bidding strategies for power producers are optimized for the day-ahead market and the intraday market with considering the properties of renewable energy; and the clearing pricing for the utility companies, with respect to the power quantity from different power producers, is optimized simultaneously. Furthermore, a distributed algorithm is provided to search the solution of the generalized Nash equilibrium. Finally, simulation results were performed and discussed to verify the feasibility and effectiveness of the proposed non-cooperative game-based bi-level optimization approach.
International Nuclear Information System (INIS)
Howard, B.; Modi, V.
2017-01-01
Highlights: • CHP attributable reductions, not viable by electric generation alone, are defined. • Simplified operating strategy heuristics are optimal under specific circumstances. • Phosphoric acid fuel cells yield the largest reductions except in the extremes. • Changes in baseline emissions affect the optimal system capacity and operating hours. - Abstract: This work aims to elucidate notions concerning the ideal operation and greenhouse gas (GHG) emissions benefits of combined heat and power (CHP) systems by investigating how various metrics change as a function of the GHG emissions from the underlying electricity source, building use type and climate. Additionally, a new term entitled “CHP Attributable” reductions is introduced to quantify the benefits from the simultaneous use of thermal and electric energy, removing benefits achieved solely from fuel switching and generating electricity more efficiently. The GHG emission benefits from implementing internal combustion engine, microturbines, and phosphoric acid (PA) fuel cell based CHP systems were evaluated through an optimization approach considering energy demands of prototypical hospital, office, and residential buildings in varied climates. To explore the effect of electric GHG emissions rates, the ideal operation of the CHP systems was evaluated under three scenarios: “High” GHG emissions rates, “Low” GHG emissions rates, and “Current” GHG emissions rate for a specific location. The analysis finds that PA fuel cells achieve the highest GHG emission reductions in most cases considered, though there are exceptions. Common heuristics, such as electric load following and thermal load following, are the optimal operating strategy under specific conditions. The optimal CHP capacity and operating hours both vary as a function of building type, climate and GHG emissions rates from grid electricity. GHG emissions reductions can be as high as 49% considering a PA fuel cell for a
Investment Strategies Optimization based on a SAX-GA Methodology
Canelas, António M L; Horta, Nuno C G
2013-01-01
This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
Mohammad Aghaei; Amin Asadollahi; Elham Vahedi; Mahdi Pirooz
2013-01-01
To maintain and achieve optimal growth, development and to be more competitive, organizations need a comprehensive and coherent plan compatible with their objectives and goals which is called strategic planning. This research aims to analyse strategically “Etka Chain Stores” and to propose optimal strategies by using SWOT model and based on fuzzy logic. The scope of this research is limited to “Etka Chain stores in Tehran”. As instrumentation, a questioner, consisting of 138 questions, was us...
Screening of natural substrates and optimization of operating ...
African Journals Online (AJOL)
STORAGESEVER
2009-02-18
Feb 18, 2009 ... 2Department of Chemical Engineering, Eritrea Institute of Technology, Eritrea, North-East Africa. ... The work involves optimizing various parameters like substrate ... of application in food industries (Brawman, 1981; Phutela.
Refrigerator Optimal Scheduling to Minimise the Cost of Operation
Directory of Open Access Journals (Sweden)
Bálint Roland
2016-12-01
Full Text Available The cost optimal scheduling of a household refrigerator is presented in this work. The fundamental approach is the model predictive control methodology applied to the piecewise affine model of the refrigerator.
Coordinated Optimal Operation Method of the Regional Energy Internet
Directory of Open Access Journals (Sweden)
Rishang Long
2017-05-01
Full Text Available The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized.
Optimizing torque vectoring strategies for an electric vehicle concept
van Boekel, J.J.P.; Besselink, I.J.M.; Nijmeijer, H.; Rauh, J.; Knorr, S.; Durnberger, J.
2013-01-01
As part of the internship project carried out at Daimler AG, this report describes the application and optimization of torque vectoring on a research vehicle based on the Mercedes- Benz SLS AMG E-CELL. A concise introduction is given regarding the MATLAB scripts and Simulink models that were used
An Optimal Stochastic Investment and Consumption Strategy with ...
African Journals Online (AJOL)
This paper considers a single investor who owns a production plant that generates units of consumption goods in a capitalist economy. The goal is to choose optimal investment and consumption policies that maximize the finite horizon expected discounted logarithmic utility of consumption and terminal wealth. A dynamical ...
Optimal detection and control strategies for invasive species management
Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette
2007-01-01
The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...
Energy Technology Data Exchange (ETDEWEB)
John, Oliver
2012-07-01
The author of the contribution under consideration reports on risk-based economic optimization of investment decisions of regulated power distribution system operators. The focus is the economically rational decision behavior of operators under certain regulatory requirements. Investments in power distribution systems form the items subject to decisions. Starting from a description of theoretical and practical regulatory approaches, their financial implications are quantified at first. On this basis, optimization strategies are derived with respect to the investment behavior. For this purpose, an optimization algorithm is developed and applied to exemplary companies. Finally, effects of uncertainties in regulatory systems are investigated. In this context, Monte Carlo simulations are used in conjunction with real options analysis.
Directory of Open Access Journals (Sweden)
Yuying Wang
2017-11-01
Full Text Available This paper presents an energy management strategy for plug-in hybrid electric vehicles (PHEVs that not only tries to minimize the energy consumption, but also considers the battery health. First, a battery model that can be applied to energy management optimization is given. In this model, battery health damage can be estimated in the different states of charge (SOC and temperature of the battery pack. Then, because of the inevitability that limiting the battery health degradation will increase energy consumption, a Pareto energy management optimization problem is formed. This multi-objective optimal control problem is solved numerically by using stochastic dynamic programming (SDP and particle swarm optimization (PSO for satisfying the vehicle power demand and considering the tradeoff between energy consumption and battery health at the same time. The optimization solution is obtained offline by utilizing real historical traffic data and formed as mappings on the system operating states so as to implement online in the actual driving conditions. Finally, the simulation results carried out on the GT-SUITE-based PHEV test platform are illustrated to demonstrate that the proposed multi-objective optimal control strategy would effectively yield benefits.
Directory of Open Access Journals (Sweden)
Umberto Di Matteo
2016-01-01
Full Text Available Territorial vulnerability and risk analysis play a fundamental role in urban planning and emergency management. Requirements analysis of such aspects are possible to define more and more effective risk mitigation strategies providing efficient response plans to events. Many mitigation strategies as well as many response plans have in common the purpose of minimizing response time in order to decrease the level of vulnerability of the concerning area. The response time to a perturbing event is in fact an essential parameter to define the hazard of the considered site and literature is unanimous in considering it. In this context, the article proposes a methodology for the optimization of the location on the territory of emergency operation centers (EOCs, reducing response times and mitigating in this way the vulnerability of the area. The proposed methodology is based on a multi-criteria decision making (MCDM hybrid type AHP (Analytic Hierarchy Process-Electre. This method has been applied in the territory of Bressanone and Vipiteno (Bolzano-Italy, simulating the need to build a new barrack of Fire Department. A campaign of interviews with operators and industry experts and the collection of spatial data from the portals of the concerned authorities has been carried out in order to get the number of necessary data for the implementation of the proposed methodology.
Investigating the Optimal Management Strategy for a Healthcare Facility Maintenance Program
National Research Council Canada - National Science Library
Gaillard, Daria
2004-01-01
...: strategic partnering with an equipment management firm. The objective of this study is to create a decision-model for selecting the optimal management strategy for a healthcare organization's facility maintenance program...
Gouge, Brian; Dowlatabadi, Hadi; Ries, Francis J
2013-04-16
In contrast to capital control strategies (i.e., investments in new technology), the potential of operational control strategies (e.g., vehicle scheduling optimization) to reduce the health and climate impacts of the emissions from public transportation bus fleets has not been widely considered. This case study demonstrates that heterogeneity in the emission levels of different bus technologies and the exposure potential of bus routes can be exploited though optimization (e.g., how vehicles are assigned to routes) to minimize these impacts as well as operating costs. The magnitude of the benefits of the optimization depend on the specific transit system and region. Health impacts were found to be particularly sensitive to different vehicle assignments and ranged from worst to best case assignment by more than a factor of 2, suggesting there is significant potential to reduce health impacts. Trade-offs between climate, health, and cost objectives were also found. Transit agencies that do not consider these objectives in an integrated framework and, for example, optimize for costs and/or climate impacts alone, risk inadvertently increasing health impacts by as much as 49%. Cost-benefit analysis was used to evaluate trade-offs between objectives, but large uncertainties make identifying an optimal solution challenging.
Optimal Operation of Plug-In Electric Vehicles in Power Systems with High Wind Power Penetrations
DEFF Research Database (Denmark)
Hu, Weihao; Su, Chi; Chen, Zhe
2013-01-01
in the power systems with high wind power penetrations. In this paper, the integration of plug-in electric vehicles in the power systems with high wind power penetrations is proposed and discussed. Optimal operation strategies of PEV in the spot market are proposed in order to decrease the energy cost for PEV......The Danish power system has a large penetration of wind power. The wind fluctuation causes a high variation in the power generation, which must be balanced by other sources. The battery storage based Plug-In Electric Vehicles (PEV) may be a possible solution to balance the wind power variations...... owners. Furthermore, the application of battery storage based aggregated PEV is analyzed as a regulation services provider in the power system with high wind power penetrations. The western Danish power system where the total share of annual wind power production is more than 27% of the electrical energy...
Conceptual Design of Operation Strategies for Hybrid Electric Aircraft
Directory of Open Access Journals (Sweden)
Julian Hoelzen
2018-01-01
Full Text Available Ambitious targets to reduce emissions caused by aviation in the light of an expected ongoing rise of the air transport demand in the future drive the research of propulsion systems with lower CO2 emissions. Regional hybrid electric aircraft (HEA powered by conventional gas turbines and battery powered electric motors are investigated to test hybrid propulsion operation strategies. Especially the role of the battery within environmentally friendly concepts with significantly reduced carbon footprint is analyzed. Thus, a new simulation approach for HEA is introduced. The main findings underline the importance of choosing the right power-to-energy-ratio of a battery according to the flight mission. The gravimetric energy and power density of the electric storages determine the technologically feasibility of hybrid concepts. Cost competitive HEA configurations are found, but do not promise the targeted CO2 emission savings, when the well-to-wheel system is regarded with its actual costs. Sensitivity studies are used to determine external levers that favor the profitability of HEA.
Directory of Open Access Journals (Sweden)
E. Alizadeh
2017-12-01
Full Text Available This paper proposes a decentralized control technique to minimize the total operation cost of a DC microgrid in both grid-connected and islanded modes. In this study, a cost-based droop control scheme based on the hourly bids of all participant distributed generators (DGs and the hourly energy price of the utility is presented. An economic power sharing technique among various types of DG units is adopted to appropriately minimize the daily total operation cost of DC microgrid without a microgrid central controller. The DC microgrid may include non-dispatchable DG units (such as photovoltaic systems and dispatchable generation units. Unlike other energy management techniques, the proposed method suffers neither from forecasting errors for both load demand and renewable energy power prediction modules, nor from complicated optimization techniques. In the proposed method, all DGs and the utility are classified in a sorting rule based on their hourly bids and open market price, and then the droop parameters are determined. The simulation results are presented to verify the effectiveness of the proposed method using MATLAB/SIMULINK software. The results show that the proposed strategy is able to be implemented in various operation conditions of DC microgrid with resistance to uncertainties.
Design and development of bio-inspired framework for reservoir operation optimization
Asvini, M. Sakthi; Amudha, T.
2017-12-01
Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.
2015-03-01
biometric data collection. Capture role- player mock biometric data including finger prints, iris scans, and facial recognition photos. (MOC training...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS by Adam R. Sinsel...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS 6. AUTHOR(S) Adam R