Applying Dynamical Systems Theory to Optimize Libration Point Orbit Stationkeeping Maneuvers for WIND

Science.gov (United States)

Brown, Jonathan M.; Petersen, Jeremy D.

2014-01-01

NASA's WIND mission has been operating in a large amplitude Lissajous orbit in the vicinity of the interior libration point of the Sun-Earth/Moon system since 2004. Regular stationkeeping maneuvers are required to maintain the orbit due to the instability around the collinear libration points. Historically these stationkeeping maneuvers have been performed by applying an incremental change in velocity, or (delta)v along the spacecraft-Sun vector as projected into the ecliptic plane. Previous studies have shown that the magnitude of libration point stationkeeping maneuvers can be minimized by applying the (delta)v in the direction of the local stable manifold found using dynamical systems theory. This paper presents the analysis of this new maneuver strategy which shows that the magnitude of stationkeeping maneuvers can be decreased by 5 to 25 percent, depending on the location in the orbit where the maneuver is performed. The implementation of the optimized maneuver method into operations is discussed and results are presented for the first two optimized stationkeeping maneuvers executed by WIND.

Optimal Set-Point Synthesis in HVAC Systems

DEFF Research Database (Denmark)

Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

2007-01-01

This paper presents optimal set-point synthesis for a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger and a water-to-air heat exchanger. The objective function is composed of the electrical power for different...... components, encompassing fans, primary/secondary pump, tertiary pump, and air-to-air heat exchanger wheel; and a fraction of thermal power used by the HVAC system. The goals that have to be achieved by the HVAC system appear as constraints in the optimization problem. To solve the optimization problem......, a steady state model of the HVAC system is derived while different supplying hydronic circuits are studied for the water-to-air heat exchanger. Finally, the optimal set-points and the optimal supplying hydronic circuit are resulted....

Polyphyletic migration operator and orthogonal learning aided biogeography-based optimization for dynamic economic dispatch with valve-point effects

International Nuclear Information System (INIS)

Xiong, Guojiang; Li, Yinhong; Chen, Jinfu; Shi, Dongyuan; Duan, Xianzhong

2014-01-01

Highlights: • New method for dynamic economic dispatch problem using POLBBO. • Considering valve-point effects, ramp rate limits, transmission network losses. • POLBBO is able to balance the global exploration and the local exploitation. • An effective simultaneous constraints handling technique is proposed. • The achieved results by POLBBO are better than those reported in other literatures. - Abstract: Shortage of energy resources, rising power generation cost, and increasing electric energy demand make the dynamic economic dispatch (DED) increasingly necessary in today’s competitive electricity market. In this paper, an enhanced biogeography-based optimization (BBO) referred to as POLBBO is proposed to solve the DED problem with valve-point effects. BBO is a relatively new powerful population-based meta-heuristic algorithm inspired by biogeography and has been extensively applied to many scientific and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess good local exploitation ability but lack enough global exploration ability. To remedy the defect, on one hand, an efficient operator named polyphyletic migration operator is proposed to enhance the search ability of POLBBO. This operator can not only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is presented. The OL strategy can quickly discover useful information from the search experiences and effectively utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. In addition, an effective simultaneous constraints handling technique without penalty factor settings is developed to handle various complicated constraints of the DED problem. Finally, four test

Optimization of power system operation

CERN Document Server

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...

Probabilistic safety assessment and optimal control of hazardous technological systems. A marked point process approach

International Nuclear Information System (INIS)

Holmberg, J.

1997-04-01

The thesis models risk management as an optimal control problem for a stochastic process. The approach classes the decisions made by management into three categories according to the control methods of a point process: (1) planned process lifetime, (2) modification of the design, and (3) operational decisions. The approach is used for optimization of plant shutdown criteria and surveillance test strategies of a hypothetical nuclear power plant

Collective neurodynamic optimization for economic emission dispatch problem considering valve point effect in microgrid.

Science.gov (United States)

Wang, Tiancai; He, Xing; Huang, Tingwen; Li, Chuandong; Zhang, Wei

2017-09-01

The economic emission dispatch (EED) problem aims to control generation cost and reduce the impact of waste gas on the environment. It has multiple constraints and nonconvex objectives. To solve it, the collective neurodynamic optimization (CNO) method, which combines heuristic approach and projection neural network (PNN), is attempted to optimize scheduling of an electrical microgrid with ten thermal generators and minimize the plus of generation and emission cost. As the objective function has non-derivative points considering valve point effect (VPE), differential inclusion approach is employed in the PNN model introduced to deal with them. Under certain conditions, the local optimality and convergence of the dynamic model for the optimization problem is analyzed. The capability of the algorithm is verified in a complicated situation, where transmission loss and prohibited operating zones are considered. In addition, the dynamic variation of load power at demand side is considered and the optimal scheduling of generators within 24 h is described. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system

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

Simulation-optimization model of reservoir operation based on target storage curves

Directory of Open Access Journals (Sweden)

Hong-bin Fang

2014-10-01

Full Text Available This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization (IPSO algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.

Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

Directory of Open Access Journals (Sweden)

Thi Rein Myo

2008-11-01

Full Text Available Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.

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.

Excited meson radiative transitions from lattice QCD using variationally optimized operators

Energy Technology Data Exchange (ETDEWEB)

Shultz, Christian J. [Old Dominion Univ., Norfolk, VA (United States); Dudek, Jozef J. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Old Dominion Univ., Norfolk, VA (United States); Edwards, Robert G. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

2015-06-02

We explore the use of 'optimized' operators, designed to interpolate only a single meson eigenstate, in three-point correlation functions with a vector-current insertion. These operators are constructed as linear combinations in a large basis of meson interpolating fields using a variational analysis of matrices of two-point correlation functions. After performing such a determination at both zero and non-zero momentum, we compute three-point functions and are able to study radiative transition matrix elements featuring excited state mesons. The required two- and three-point correlation functions are efficiently computed using the distillation framework in which there is a factorization between quark propagation and operator construction, allowing for a large number of meson operators of definite momentum to be considered. We illustrate the method with a calculation using anisotopic lattices having three flavors of dynamical quark all tuned to the physical strange quark mass, considering form-factors and transitions of pseudoscalar and vector meson excitations. In conclusion, the dependence on photon virtuality for a number of form-factors and transitions is extracted and some discussion of excited-state phenomenology is presented.

A Survey of Recent Research on Optimization Models and Algorithms for Operations Management from the Process View

Directory of Open Access Journals (Sweden)

Hongying Fei

2017-01-01

Full Text Available Over the past decades, optimization in operations management has grown ever more popular not only in the academic literature but also in practice. However, the problems have varied a lot, and few literature reviews have provided an overview of the models and algorithms that are applied to the optimization in operations management. In this paper, we first classify crucial optimization areas of operations management from the process point of view and then analyze the current status and trends of the studies in those areas. The purpose of this study is to give an overview of optimization modelling and resolution approaches, which are applied to operations management.

Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response

International Nuclear Information System (INIS)

Vahid-Pakdel, M.J.; Nojavan, Sayyad; Mohammadi-ivatloo, B.; Zare, Kazem

2017-01-01

Highlights: • Studying heating market impact on energy hub operation considering price uncertainty. • Investigating impact of implementation of heat demand response on hub operation. • Presenting stochastic method to consider wind generation and prices uncertainties. - Abstract: Multi carrier energy systems or energy hubs has provided more flexibility for energy management systems. On the other hand, due to mutual impact of different energy carriers in energy hubs, energy management studies become more challengeable. The initial patterns of energy demands from grids point of view can be modified by optimal scheduling of energy hubs. In this work, optimal operation of multi carrier energy system has been studied in the presence of wind farm, electrical and thermal storage systems, electrical and thermal demand response programs, electricity market and thermal energy market. Stochastic programming is implemented for modeling the system uncertainties such as demands, market prices and wind speed. It is shown that adding new source of heat energy for providing demand of consumers with market mechanism changes the optimal operation point of multi carrier energy system. Presented mixed integer linear formulation for the problem has been solved by executing CPLEX solver of GAMS optimization software. Simulation results shows that hub’s operation cost reduces up to 4.8% by enabling the option of using thermal energy market for meeting heat demand.

Dose optimization of intra-operative high dose rate interstitial brachytherapy implants for soft tissue sarcoma

Directory of Open Access Journals (Sweden)

Jamema Swamidas

2009-01-01

Full Text Available Objective : A three dimensional (3D image-based dosimetric study to quantitatively compare geometric vs. dose-point optimization in combination with graphical optimization for interstitial brachytherapy of soft tissue sarcoma (STS. Materials and Methods : Fifteen consecutive STS patients, treated with intra-operative, interstitial Brachytherapy, were enrolled in this dosimetric study. Treatment plans were generated using dose points situated at the "central plane between the catheters", "between the catheters throughout the implanted volume", at "distances perpendicular to the implant axis" and "on the surface of the target volume" Geometrically optimized plans had dose points defined between the catheters, while dose-point optimized plans had dose points defined at a plane perpendicular to the implant axis and on the target surface. Each plan was graphically optimized and compared using dose volume indices. Results : Target coverage was suboptimal with coverage index (CI = 0.67 when dose points were defined at the central plane while it was superior when the dose points were defined at the target surface (CI=0.93. The coverage of graphically optimized plans (GrO was similar to non-GrO with dose points defined on surface or perpendicular to the implant axis. A similar pattern was noticed with conformity index (0.61 vs. 0.82. GrO were more conformal and less homogeneous compared to non-GrO. Sum index was superior for dose points defined on the surface of the target and relatively inferior for plans with dose points at other locations (1.35 vs. 1.27. Conclusions : Optimization with dose points defined away from the implant plane and on target results in superior target coverage with optimal values of other indices. GrO offer better target coverage for implants with non-uniform geometry and target volume.

Probabilistic safety assessment and optimal control of hazardous technological systems. A marked point process approach

Energy Technology Data Exchange (ETDEWEB)

Holmberg, J [VTT Automation, Espoo (Finland)

1997-04-01

The thesis models risk management as an optimal control problem for a stochastic process. The approach classes the decisions made by management into three categories according to the control methods of a point process: (1) planned process lifetime, (2) modification of the design, and (3) operational decisions. The approach is used for optimization of plant shutdown criteria and surveillance test strategies of a hypothetical nuclear power plant. 62 refs. The thesis includes also five previous publications by author.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

Science.gov (United States)

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Improving operability of spouted beds using a simple optimizing control structure

Directory of Open Access Journals (Sweden)

N. A. CORRÊA

1999-12-01

Full Text Available In operations using spouted beds, it is of major importance, from an energy consumption point of view, to operate the process as close as possible to the minimum spout flow. At this point, the speed of the gas (for example, warm air in drying operations is greater than the amount of heat and mass transfer involved, although it only transfers the minimum amount of momentum to maintain the spout. Therefore, by staying close to this minimum flow condition, it is possible to perform a stable operation and to obtain energy savings not only in the heating of the gas but also in its displacement by blowers. In order to improve the operation of such processes, a study is carried out by implementing a simple optimizing control structure on a spouted bed experimental set-up. The air flow is regulated by a frequency inverter, at the speed of blower rotation. A PI controller was used and the set-point for the air flow rate is calculated on-line by a simple and well-known minimization method called Golden Section Search. This set-point is constantly updated with values very close to the actual minimum spout flow rate. To accomplish the calculations and data acquisitions, a microcomputer with an interface and an analog signal conditioner is used .

Optimizing Probability of Detection Point Estimate Demonstration

Science.gov (United States)

Koshti, Ajay M.

2017-01-01

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.

Characterizations of fixed points of quantum operations

International Nuclear Information System (INIS)

Li Yuan

2011-01-01

Let φ A be a general quantum operation. An operator B is said to be a fixed point of φ A , if φ A (B)=B. In this note, we shall show conditions under which B, a fixed point φ A , implies that B is compatible with the operation element of φ A . In particular, we offer an extension of the generalized Lueders theorem.

Optimal operation planning of radioactive waste processing system by fuzzy theory

International Nuclear Information System (INIS)

Yang, Jin Yeong; Lee, Kun Jai

2000-01-01

This study is concerned with the applications of linear goal programming and fuzzy theory to the analysis of management and operational problems in the radioactive processing system (RWPS). The developed model is validated and verified using actual data obtained from the RWPS at Kyoto University in Japan. The solution by goal programming and fuzzy theory would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. (orig.)

Multi-point optimization on meridional shape of a centrifugal pump impeller for performance improvement

Energy Technology Data Exchange (ETDEWEB)

Pei, Ji; Wang, Wen Jie; Yuan, Shouqi [National Research Center of Pumps, Jiangsu University, Zhenjiang (China)

2016-11-15

A wide operating band is important for a pump to safely perform at maximum efficiency while saving energy. To widen the operating range, a multi-point optimization process based on numerical simulations in order to improve impeller performance of a centrifugal pump used in nuclear plant applications is proposed by this research. The Reynolds average Navier Stokes equations are utilized to perform the calculations. The meridional shape of the impeller was optimized based on the following four parameters; shroud arc radius, hub arc radius, shroud angle, and hub angle as the design variables. Efficiencies calculated under 0.6Qd, 1.0Qd and 1.62Qd were selected as the three optimized objectives. The Design of experiment method was applied to generate various impellers while 35 impellers were generated by the Latin hypercube sampling method. A Response surface function based on a second order function was applied to construct a mathematical relationship between the objectives and design variables. A multi-objective genetic algorithm was utilized to solve the response surface function to obtain the best optimized objectives as well as the best combination of design parameters. The results indicated that the pump performance predicted by numerical simulation was in agreement with the experimental performance. The optimized efficiencies based on the three operating conditions were increased by 3.9 %, 6.1 % and 2.6 %, respectively. In addition, the velocity distribution, pressure distribution, streamline and turbulence kinetic energy distribution of the optimized and reference impeller were compared and analyzed to illustrate the performance improvement.

Multi-point optimization on meridional shape of a centrifugal pump impeller for performance improvement

International Nuclear Information System (INIS)

Pei, Ji; Wang, Wen Jie; Yuan, Shouqi

2016-01-01

A wide operating band is important for a pump to safely perform at maximum efficiency while saving energy. To widen the operating range, a multi-point optimization process based on numerical simulations in order to improve impeller performance of a centrifugal pump used in nuclear plant applications is proposed by this research. The Reynolds average Navier Stokes equations are utilized to perform the calculations. The meridional shape of the impeller was optimized based on the following four parameters; shroud arc radius, hub arc radius, shroud angle, and hub angle as the design variables. Efficiencies calculated under 0.6Qd, 1.0Qd and 1.62Qd were selected as the three optimized objectives. The Design of experiment method was applied to generate various impellers while 35 impellers were generated by the Latin hypercube sampling method. A Response surface function based on a second order function was applied to construct a mathematical relationship between the objectives and design variables. A multi-objective genetic algorithm was utilized to solve the response surface function to obtain the best optimized objectives as well as the best combination of design parameters. The results indicated that the pump performance predicted by numerical simulation was in agreement with the experimental performance. The optimized efficiencies based on the three operating conditions were increased by 3.9 %, 6.1 % and 2.6 %, respectively. In addition, the velocity distribution, pressure distribution, streamline and turbulence kinetic energy distribution of the optimized and reference impeller were compared and analyzed to illustrate the performance improvement

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

Optimized Adaptive Perturb and Observe Maximum Power Point Tracking Control for Photovoltaic Generation

Directory of Open Access Journals (Sweden)

Luigi Piegari

2015-04-01

Full Text Available The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb & observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb & observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb & observe and incremental conductance techniques.

Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT

Energy Technology Data Exchange (ETDEWEB)

Aleman, Dionne M [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King' s College Road, Toronto, ON M5S 3G8 (Canada); Glaser, Daniel [Division of Optimization and Systems Theory, Department of Mathematics, Royal Institute of Technology, Stockholm (Sweden); Romeijn, H Edwin [Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109-2117 (United States); Dempsey, James F, E-mail: aleman@mie.utoronto.c, E-mail: romeijn@umich.ed, E-mail: jfdempsey@viewray.co [ViewRay, Inc. 2 Thermo Fisher Way, Village of Oakwood, OH 44146 (United States)

2010-09-21

One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.

Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT

International Nuclear Information System (INIS)

Aleman, Dionne M; Glaser, Daniel; Romeijn, H Edwin; Dempsey, James F

2010-01-01

One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.

Optimization of operation of energy supply systems with co-generation and absorption refrigeration

Directory of Open Access Journals (Sweden)

Stojiljković Mirko M.

2012-01-01

Full Text Available Co-generation systems, together with absorption refrigeration and thermal storage, can result in substantial benefits from the economic, energy and environmental point of view. Optimization of operation of such systems is important as a component of the entire optimization process in pre-construction phases, but also for short-term energy production planning and system control. This paper proposes an approach for operational optimization of energy supply systems with small or medium scale co-generation, additional boilers and heat pumps, absorption and compression refrigeration, thermal energy storage and interconnection to the electric utility grid. In this case, the objective is to minimize annual costs related to the plant operation. The optimization problem is defined as mixed integer nonlinear and solved combining modern stochastic techniques: genetic algorithms and simulated annealing with linear programming using the object oriented “ESO-MS” software solution for simulation and optimization of energy supply systems, developed as a part of this research. This approach is applied to optimize a hypothetical plant that might be used to supply a real residential settlement in Niš, Serbia. Results are compared to the ones obtained after transforming the problem to mixed 0-1 linear and applying the branch and bound method.

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...

A novel hybrid particle swarm optimization for economic dispatch with valve-point loading effects

Energy Technology Data Exchange (ETDEWEB)

Niknam, Taher, E-mail: niknam@sutech.ac.i [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Mojarrad, Hasan Doagou, E-mail: hasan_doagou@yahoo.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Meymand, Hamed Zeinoddini, E-mail: h.zeinaddini@gmail.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of)

2011-04-15

Economic dispatch (ED) is one of the important problems in the operation and management of the electric power systems which is formulated as an optimization problem. Modern heuristics stochastic optimization techniques appear to be efficient in solving ED problem without any restriction because of their ability to seek the global optimal solution. One of modern heuristic algorithms is particle swarm optimization (PSO). In PSO algorithm, particles change place to get close to the best position and find the global minimum point. Also, differential evolution (DE) is a robust statistical method for solving non-linear and non-convex optimization problem. The fast convergence of DE degrades its performance and reduces its search capability that leads to a higher probability towards obtaining a local optimum. In order to overcome this drawback a hybrid method is presented to solve the ED problem with valve-point loading effect by integrating the variable DE with the fuzzy adaptive PSO called FAPSO-VDE. DE is the main optimizer and the PSO is used to maintain the population diversity and prevent leading to misleading local optima for every improvement in the solution of the DE run. The parameters of proposed hybrid algorithm such as inertia weight, mutation and crossover factors are adaptively adjusted. The feasibility and effectiveness of the proposed hybrid algorithm is demonstrated for two case studies and results are compared with those of other methods. It is shown that FAPSO-VDE has high quality solution, superior convergence characteristics and shorter computation time.

A superlinear interior points algorithm for engineering design optimization

Science.gov (United States)

Herskovits, J.; Asquier, J.

1990-01-01

We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.

Primal Interior-Point Method for Large Sparse Minimax Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 45, č. 5 (2009), s. 841-864 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : unconstrained optimization * large-scale optimization * minimax optimization * nonsmooth optimization * interior-point methods * modified Newton methods * variable metric methods * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.445, year: 2009 http://dml.cz/handle/10338.dmlcz/140034

Optimal operational strategies for a day-ahead electricity market in the presence of market power using multi-objective evolutionary algorithms

Science.gov (United States)

Rodrigo, Deepal

2007-12-01

reinforced the selection of these algorithms. The results obtained from each of the three algorithms used in the evaluations are very comparable. Thus one could safely conclude that the results obtained are valid. Three distinct test power systems operating under different conditions were studied for evaluating the suitability of each of these algorithms. The test cases included scenarios in which the power system was unconstrained as well as constrained. Repeated simulations carried out for the same test case with varying starting points provided evidence that the algorithms and the solutions were robust. Influences of different market concentrations on the optimal economic dispatch are evidenced by the pareto-optimal-fronts obtained for each test case studied. Results obtained from a traditional linear programming (LP) based solution algorithm that is used at present by many market operators are also presented for comparison. Very high market-concentration-indices were found for each solution from the LP algorithm. This suggests the need to use a formal method for mitigating market concentration. Operating the market at industry-recommended threshold levels of market concentration for selecting an optimal operational point is presented for all test cases studied. Given that a solution-set instead of a single operating point is found from the multi-objective optimization methods, additional flexibility to select any operational point based on the preference of those operating the market clearly is an added benefit of using multi-objective optimization methods. However, in order to help the market operator, a more logical fuzzy decision criterion was tested for selecting a suitable operating point. The results show that the optimal operating point chosen using the fuzzy decision criterion provides a higher economic benefit to the market, although at a slightly increased market concentration. Since the main objective of this research was to simultaneously optimize the

Optimal Operation Method of Smart House by Controllable Loads based on Smart Grid Topology

Science.gov (United States)

Yoza, Akihiro; Uchida, Kosuke; Yona, Atsushi; Senju, Tomonobu

2013-08-01

From the perspective of global warming suppression and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all electrification apartment house or residence such as DC smart house have increased in recent years. However, due to fluctuating power from renewable energy sources and loads, supply-demand balancing fluctuations of power system become problematic. Therefore, "smart grid" has become very popular in the worldwide. This article presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuations. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuations, it is possible to reduce the maximum electric power consumption and the electric cost. This system consists of photovoltaics generator, heat pump, battery, solar collector, and load. In order to verify the effectiveness of the proposed system, MATLAB is used in simulations.

Eigenvectors and fixed point of non-linear operators

Directory of Open Access Journals (Sweden)

Giulio Trombetta

2007-12-01

Full Text Available Let X be a real infinite-dimensional Banach space and ψ a measure of noncompactness on X. Let Ω be a bounded open subset of X and A : Ω → X a ψ-condensing operator, which has no fixed points on ∂Ω.Then the fixed point index, ind(A,Ω, of A on Ω is defined (see, for example, ([1] and [18]. In particular, if A is a compact operator ind(A,Ω agrees with the classical Leray-Schauder degree of I −A on Ω relative to the point 0, deg(I −A,Ω,0. The main aim of this note is to investigate boundary conditions, under which the fixed point index of strict- ψ-contractive or ψ-condensing operators A : Ω → X is equal to zero. Correspondingly, results on eigenvectors and nonzero fixed points of k-ψ-contractive and ψ-condensing operators are obtained. In particular we generalize the Birkhoff-Kellog theorem [4] and Guo’s domain compression and expansion theorem [17]. The note is based mainly on the results contained in [7] and [8].

Blue-noise remeshing with farthest point optimization

KAUST Repository

Yan, Dongming

2014-08-01

In this paper, we present a novel method for surface sampling and remeshing with good blue-noise properties. Our approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality blue-noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue-noise properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior to the current state-of-the art approaches. © 2014 The Eurographics Association and John Wiley & Sons Ltd.

Blue-noise remeshing with farthest point optimization

KAUST Repository

Yan, Dongming; Guo, Jianwei; Jia, Xiaohong; Zhang, Xiaopeng; Wonka, Peter

2014-01-01

In this paper, we present a novel method for surface sampling and remeshing with good blue-noise properties. Our approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality blue-noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue-noise properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior to the current state-of-the art approaches. © 2014 The Eurographics Association and John Wiley & Sons Ltd.

Sequential Change-Point Detection via Online Convex Optimization

Directory of Open Access Journals (Sweden)

Yang Cao

2018-02-01

Full Text Available Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using online convex optimization algorithms such as online mirror descent, which provides a more versatile approach to tackling complex situations where recursive maximum likelihood estimators cannot be found. When the underlying distributions belong to a exponential family and the estimators satisfy the logarithm regret property, we show that this approach is nearly second-order asymptotically optimal. This means that the upper bound for the false alarm rate of the algorithm (measured by the average-run-length meets the lower bound asymptotically up to a log-log factor when the threshold tends to infinity. Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

Analysis and research on Maximum Power Point Tracking of Photovoltaic Array with Fuzzy Logic Control and Three-point Weight Comparison Method

Institute of Scientific and Technical Information of China (English)

LIN; Kuang-Jang; LIN; Chii-Ruey

2010-01-01

The Photovoltaic Array has a best optimal operating point where the array operating can obtain the maximum power.However, the optimal operating point can be compromised by the strength of solar radiation,angle,and by the change of environment and load.Due to the constant changes in these conditions,it has become very difficult to locate the optimal operating point by following a mathematical model.Therefore,this study will focus mostly on the application of Fuzzy Logic Control theory and Three-point Weight Comparison Method in effort to locate the optimal operating point of solar panel and achieve maximum efficiency in power generation. The Three-point Weight Comparison Method is the comparison between the characteristic curves of the voltage of photovoltaic array and output power;it is a rather simple way to track the maximum power.The Fuzzy Logic Control,on the other hand,can be used to solve problems that cannot be effectively dealt with by calculation rules,such as concepts,contemplation, deductive reasoning,and identification.Therefore,this paper uses these two kinds of methods to make simulation successively. The simulation results show that,the Three-point Comparison Method is more effective under the environment with more frequent change of solar radiation;however,the Fuzzy Logic Control has better tacking efficiency under the environment with violent change of solar radiation.

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 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

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

International Nuclear Information System (INIS)

Pang, X.; Rybarcyk, L.J.

2014-01-01

Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

Energy Technology Data Exchange (ETDEWEB)

Pang, X., E-mail: xpang@lanl.gov; Rybarcyk, L.J.

2014-03-21

Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster.

An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects

Directory of Open Access Journals (Sweden)

Hong-Yun Zhang

2012-09-01

Full Text Available Quantum-behaved particle swarm optimization (QPSO is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE, particle swarm optimization (PSO and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems.

24 CFR 902.47 - Management operations portion of total PHAS points.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Management operations portion of... Operations § 902.47 Management operations portion of total PHAS points. Of the total 100 points available for a PHAS score, a PHA may receive up to 30 points based on the Management Operations Indicator. ...

Optimal External-Memory Planar Point Enclosure

DEFF Research Database (Denmark)

Arge, Lars; Samoladas, Vasilis; Yi, Ke

2007-01-01

.g. spatial and temporal databases, and is dual to the important and well-studied orthogonal range searching problem. Surprisingly, despite the fact that the problem can be solved optimally in internal memory with linear space and O(log N+K) query time, we show that one cannot construct a linear sized......In this paper we study the external memory planar point enclosure problem: Given N axis-parallel rectangles in the plane, construct a data structure on disk (an index) such that all K rectangles containing a query point can be reported I/O-efficiently. This problem has important applications in e...... external memory point enclosure data structure that can be used to answer a query in O(log  B N+K/B) I/Os, where B is the disk block size. To obtain this bound, Ω(N/B 1−ε ) disk blocks are needed for some constant ε>0. With linear space, the best obtainable query bound is O(log 2 N+K/B) if a linear output...

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.

Optimal time points sampling in pathway modelling.

Science.gov (United States)

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

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...

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

The Improvement of Particle Swarm Optimization: a Case Study of Optimal Operation in Goupitan Reservoir

Science.gov (United States)

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.

Saturne II synchroton injector parameters operation and control: computerization and optimization

International Nuclear Information System (INIS)

Lagniel, J.M.

1983-01-01

The injector control system has been studied, aiming at the beam quality improvement, the increasing of the versatility, and a better machine availability. It has been choosen to realize the three following functions: - acquisition of the principal parameters of the process, so as to control them quickly and to be warned if one of them is wrong (monitoring); - the control of those parameters, one by one or by families (starting, operating point); - the research of an optimal control (on a model or on the process itself) [fr

Themoeconomic optimization of triple pressure heat recovery steam generator operating parameters for combined cycle plants

Directory of Open Access Journals (Sweden)

Mohammd Mohammed S.

2015-01-01

Full Text Available The aim of this work is to develop a method for optimization of operating parameters of a triple pressure heat recovery steam generator. Two types of optimization: (a thermodynamic and (b thermoeconomic were preformed. The purpose of the thermodynamic optimization is to maximize the efficiency of the plant. The selected objective for this purpose is minimization of the exergy destruction in the heat recovery steam generator (HRSG. The purpose of the thermoeconomic optimization is to decrease the production cost of electricity. Here, the total annual cost of HRSG, defined as a sum of annual values of the capital costs and the cost of the exergy destruction, is selected as the objective function. The optimal values of the most influencing variables are obtained by minimizing the objective function while satisfying a group of constraints. The optimization algorithm is developed and tested on a case of CCGT plant with complex configuration. Six operating parameters were subject of optimization: pressures and pinch point temperatures of every three (high, intermediate and low pressure steam stream in the HRSG. The influence of these variables on the objective function and production cost are investigated in detail. The differences between results of thermodynamic and the thermoeconomic optimization are discussed.

Komputasi Aliran Daya Optimal Sistem Tenaga Skala Besar dengan Metode Primal Dual Interior Point

Directory of Open Access Journals (Sweden)

Syafii Syafii

2016-03-01

Full Text Available This paper focuses on the use of Primal Dual Interior Point method in the analysis of optimal power flow. Optimal power flow analysis with Primal Dual Interior Point method then compared with Linear Programming Method using Matpower program. The simulation results show that the computation results of Primal Dual Interior Point similar with Linear Programming Method for total cost of generation and large power generated by each power plant. But in terms of computation time Primal Dual Interior Point method is faster than the method of Linear Programming, especially for large systems. Primal Dual Interior Point method have solved the problem in 40.59 seconds, while Linear Programming method takes longer 239.72 seconds for large-scale system 9241 bus. This is because the settlement PDIP algorithm starts from the starting point x0, which is located within the area of feasible move towards the optimal point, in contrast to the simplex method that moves along the border of the feasible from one extreme point to the other extreme point. Thus Primal Dual Interior Point method have more efficient in solving optimal power flow problem of large-scale power systems.

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Directory of Open Access Journals (Sweden)

Yongpeng Shen

2016-02-01

Full Text Available Auxiliary power units (APUs are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC emissions, carbon monoxide (CO emissions and nitric oxide (NO x emissions. Then, the multi-objective particle swarm optimization (MOPSO algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC, Federal test procedure (FTP and high way fuel economy test (HWFET driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

Conformal four point functions and the operator product expansion

International Nuclear Information System (INIS)

Dolan, F.A.; Osborn, H.

2001-01-01

Various aspects of the four point function for scalar fields in conformally invariant theories are analysed. This depends on an arbitrary function of two conformal invariants u,v. A recurrence relation for the function corresponding to the contribution of an arbitrary spin field in the operator product expansion to the four point function is derived. This is solved explicitly in two and four dimensions in terms of ordinary hypergeometric functions of variables z,x which are simply related to u,v. The operator product expansion analysis is applied to the explicit expressions for the four point function found for free scalar, fermion and vector field theories in four dimensions. The results for four point functions obtained by using the AdS/CFT correspondence are also analysed in terms of functions related to those appearing in the operator product discussion

Multiobjective Optimization of a Counterrotating Type Pump-Turbine Unit Operated at Turbine Mode

Directory of Open Access Journals (Sweden)

Jin-Hyuk Kim

2014-05-01

Full Text Available A multiobjective optimization for improving the turbine output and efficiency of a counterrotating type pump-turbine unit operated at turbine mode was carried out in this work. The blade geometry of both the runners was optimized using a hybrid multiobjective evolutionary algorithm coupled with a surrogate model. Three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model were discretized by finite volume approximations and solved on hexahedral grids to analyze the flow in the pump-turbine unit. As major hydrodynamic performance parameters, the turbine output and efficiency were selected as objective functions with two design variables related to the hub profiles of both the runner blades. These objectives were numerically assessed at twelve design points selected by Latin hypercube sampling in the design space. Response surface approximation models for the objectives were constructed based on the objective function values at the design points. A fast nondominated sorting genetic algorithm for the local search coupled with the response surface approximation models was applied to determine the global Pareto-optimal solutions. The trade-off between the two objectives was determined and described with respect to the Pareto-optimal solutions. The results of this work showed that the turbine outputs and efficiencies of optimized pump-turbine units were simultaneously improved in comparison to the reference unit.

Bilevel Optimization for Scene Segmentation of LiDAR Point Cloud

Directory of Open Access Journals (Sweden)

LI Minglei

2018-02-01

Full Text Available The segmentation of point clouds obtained by light detection and ranging (LiDAR systems is a critical step for many tasks,such as data organization,reconstruction and information extraction.In this paper,we propose a bilevel progressive optimization algorithm based on the local differentiability.First,we define the topological relation and distance metric of points in the framework of Riemannian geometry,and in the point-based level using k-means method generates over-segmentation results,e.g.super voxels.Then these voxels are formulated as nodes which consist a minimal spanning tree.High level features are extracted from voxel structures,and a graph-based optimization method is designed to yield the final adaptive segmentation results.The implementation experiments on real data demonstrate that our method is efficient and superior to state-of-the-art methods.

Point charges optimally placed to represent the multipole expansion of charge distributions.

Directory of Open Access Journals (Sweden)

Ramu Anandakrishnan

Full Text Available We propose an approach for approximating electrostatic charge distributions with a small number of point charges to optimally represent the original charge distribution. By construction, the proposed optimal point charge approximation (OPCA retains many of the useful properties of point multipole expansion, including the same far-field asymptotic behavior of the approximate potential. A general framework for numerically computing OPCA, for any given number of approximating charges, is described. We then derive a 2-charge practical point charge approximation, PPCA, which approximates the 2-charge OPCA via closed form analytical expressions, and test the PPCA on a set of charge distributions relevant to biomolecular modeling. We measure the accuracy of the new approximations as the RMS error in the electrostatic potential relative to that produced by the original charge distribution, at a distance 2x the extent of the charge distribution--the mid-field. The error for the 2-charge PPCA is found to be on average 23% smaller than that of optimally placed point dipole approximation, and comparable to that of the point quadrupole approximation. The standard deviation in RMS error for the 2-charge PPCA is 53% lower than that of the optimal point dipole approximation, and comparable to that of the point quadrupole approximation. We also calculate the 3-charge OPCA for representing the gas phase quantum mechanical charge distribution of a water molecule. The electrostatic potential calculated by the 3-charge OPCA for water, in the mid-field (2.8 Å from the oxygen atom, is on average 33.3% more accurate than the potential due to the point multipole expansion up to the octupole order. Compared to a 3 point charge approximation in which the charges are placed on the atom centers, the 3-charge OPCA is seven times more accurate, by RMS error. The maximum error at the oxygen-Na distance (2.23 Å is half that of the point multipole expansion up to the octupole

The resilience of an operating point for a fusion power plant

Energy Technology Data Exchange (ETDEWEB)

Ward, David, E-mail: david.ward@ccfe.ac.uk; Kemp, Richard

2015-10-15

Highlights: • The need to control a power plant changes our view of the optimum design. • The need for control can be reduced by finding resilient design points. • It is important to include resilience and control in selecting design points. • Including these additional constraints reduces flexibility in choice of operating points. - Abstract: The operating point for fusion power plant design concepts is often determined by simultaneously satisfying the requirements of all of the main plant systems and finding an optimum solution, for instance the one with the lowest capital cost or cost of electricity. This static assessment takes no account of the sensitivity of that operating point to variations in key parameters and therefore includes no information about how difficult to adjust and control the chosen operating point may be. Control of the operation point is a large subject with much work still to be done, and is expected to play an increasing role in the future in choosing the optimum design point. Here we present results of two analyses: one relates to the ability to load follow, that is, to vary the power production in the light of varying demands for power from the electricity network; the other investigates in simple terms what choices we can make to improve the resilience of static operating points.

Photovoltaic System with Smart Tracking of the Optimal Working Point

Directory of Open Access Journals (Sweden)

PATARAU, T.

2010-08-01

Full Text Available A photovoltaic (PV system, based on a Maximum Power Point Tracking (MPPT controller that extracts the maximum possible output power from the solar panel is described. Output efficiency of a PV energy system can be achieved only if the system working point is brought near the maximum power point (MPP. The proposed system, making use of several MPPT control algorithms (Perturb and Observe, Incremental conductance, Fuzzy Logic, demonstrates in simulations as well as in real experiments good tracking of the optimal working point.

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

Multi-Objective Distribution Network Operation Based on Distributed Generation Optimal Placement Using New Antlion Optimizer Considering Reliability

Directory of Open Access Journals (Sweden)

KHANBABAZADEH Javad

2016-10-01

Full Text Available Distribution network designers and operators are trying to deliver electrical energy with high reliability and quality to their subscribers. Due to high losses in the distribution systems, using distributed generation can improves reliability, reduces losses and improves voltage profile of distribution network. Therefore, the choice of the location of these resources and also determining the amount of their generated power to maximize the benefits of this type of resource is an important issue which is discussed from different points of view today. In this paper, a new multi-objective optimal location and sizing of distributed generation resources is performed to maximize its benefits on the 33 bus distribution test network considering reliability and using a new Antlion Optimizer (ALO. The benefits for DG are considered as system losses reduction, system reliability improvement and benefits from the sale electricity and voltage profile improvement. For each of the mentioned benefits, the ALO algorithm is used to optimize the location and sizing of distributed generation resources. In order to verify the proposed approach, the obtained results have been analyzed and compared with the results of particle swarm optimization (PSO algorithm. The results show that the ALO has shown better performance in optimization problem solution versus PSO.

Schroedinger operators with point interactions and short range expansions

International Nuclear Information System (INIS)

Albeverio, S.; Hoeegh-Krohn, R.; Oslo Univ.

1984-01-01

We give a survey of recent results concerning Schroedinger operators with point interactions in R 3 . In the case where the point interactions are located at a discrete set of points we discuss results about the resolvent, the spectrum, the resonances and the scattering quantities. We also discuss the approximation of point interactions by short range local potentials (short range or low energy expansions) and the one electron model of a 3-dimensional crystal. Moreover we discuss Schroedinger operators with Coulomb plus point interactions, with applications to the determination of scattering lengths and of level shifts in mesic atoms. Further applications to the multiple well problem, to multiparticle systems, to crystals with random impurities, to polymers and quantum fields are also briefly discussed. (orig.)

78 FR 23845 - Drawbridge Operation Regulations; Narrow Bay, Smith Point, NY

Science.gov (United States)

2013-04-23

... Operation Regulations; Narrow Bay, Smith Point, NY AGENCY: Coast Guard, DHS. ACTION: Notice of temporary... deviation from the regulation governing the operation of the Smith Point Bridge, mile 6.1, across Narrow Bay, between Smith Point and Fire Island, New York. The deviation is necessary to facilitate the Smith Point...

A primal-dual interior point method for large-scale free material optimization

DEFF Research Database (Denmark)

Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias

2015-01-01

Free Material Optimization (FMO) is a branch of structural optimization in which the design variable is the elastic material tensor that is allowed to vary over the design domain. The requirements are that the material tensor is symmetric positive semidefinite with bounded trace. The resulting...... optimization problem is a nonlinear semidefinite program with many small matrix inequalities for which a special-purpose optimization method should be developed. The objective of this article is to propose an efficient primal-dual interior point method for FMO that can robustly and accurately solve large...... of iterations the interior point method requires is modest and increases only marginally with problem size. The computed optimal solutions obtain a higher precision than other available special-purpose methods for FMO. The efficiency and robustness of the method is demonstrated by numerical experiments on a set...

A novel membrane-based process to isolate peroxidase from horseradish roots: optimization of operating parameters.

Science.gov (United States)

Liu, Jianguo; Yang, Bo; Chen, Changzhen

2013-02-01

The optimization of operating parameters for the isolation of peroxidase from horseradish (Armoracia rusticana) roots with ultrafiltration (UF) technology was systemically studied. The effects of UF operating conditions on the transmission of proteins were quantified using the parameter scanning UF. These conditions included solution pH, ionic strength, stirring speed and permeate flux. Under optimized conditions, the purity of horseradish peroxidase (HRP) obtained was greater than 84 % after a two-stage UF process and the recovery of HRP from the feedstock was close to 90 %. The resulting peroxidase product was then analysed by isoelectric focusing, SDS-PAGE and circular dichroism, to confirm its isoelectric point, molecular weight and molecular secondary structure. The effects of calcium ion on HRP specific activities were also experimentally determined.

Operating point considerations for the Reference Theta-Pinch Reactor (RTPR)

International Nuclear Information System (INIS)

Krakowski, R.A.; Miller, R.L.; Hagenson, R.L.

1976-01-01

Aspects of the continuing engineering design-point reassessment and optimization of the Reference Theta-Pinch Reactor (RTPR) are discussed. An updated interim design point which achieves a favorable energy balance and involves relaxed technological requirements, which nonetheless satisfy more rigorous physics and engineering constraints, is presented

UMTS network planning, optimization, and inter-operation with GSM

CERN Document Server

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

Application study of evolutionary operation methods in optimization of process parameters for mosquito coils industry

Science.gov (United States)

Ginting, E.; Tambunanand, M. M.; Syahputri, K.

2018-02-01

Evolutionary Operation Methods (EVOP) is a method that is designed used in the process of running or operating routinely in the company to enables high productivity. Quality is one of the critical factors for a company to win the competition. Because of these conditions, the research for products quality has been done by gathering the production data of the company and make a direct observation to the factory floor especially the drying department to identify the problem which is the high water content in the mosquito incense coil. PT.X which is producing mosquito coils attempted to reduce product defects caused by the inaccuracy of operating conditions. One of the parameters of good quality insect repellent that is water content, that if the moisture content is too high then the product easy to mold and broken, and vice versa if it is too low the products are easily broken and burn shorter hours. Three factors that affect the value of the optimal water content, the stirring time, drying temperature and drying time. To obtain the required conditions Evolutionary Operation (EVOP) methods is used. Evolutionary Operation (EVOP) is used as an efficient technique for optimization of two or three variable experimental parameters using two-level factorial designs with center point. Optimal operating conditions in the experiment are stirring time performed for 20 minutes, drying temperature at 65°C, and drying time for 130 minutes. The results of the analysis based on the method of Evolutionary Operation (EVOP) value is the optimum water content of 6.90%, which indicates the value has approached the optimal in a production plant that is 7%.

Near-maximum-power-point-operation (nMPPO) design of photovoltaic power generation system

Energy Technology Data Exchange (ETDEWEB)

Huang, B.J.; Sun, F.S.; Ho, R.W. [Department of Mechanical Engineering, National Taiwan University, Taipei 106, Taiwan (China)

2006-08-15

The present study proposes a PV system design, called 'near-maximum power-point-operation' (nMPPO) that can maintain the performance very close to PV system with MPPT (maximum-power-point tracking) but eliminate hardware of the MPPT. The concept of nMPPO is to match the design of battery bank voltage V{sub set} with the MPP (maximum-power point) of the PV module based on an analysis using meteorological data. Three design methods are used in the present study to determine the optimal V{sub set}. The analytical results show that nMPPO is feasible and the optimal V{sub set} falls in the range 13.2-15.0V for MSX60 PV module. The long-term performance simulation shows that the overall nMPPO efficiency {eta}{sub nMPPO} is higher than 94%. Two outdoor field tests were carried out in the present study to verify the design of nMPPO. The test results for a single PV module (60Wp) indicate that the nMPPO efficiency {eta}{sub nMPPO} is mostly higher than 93% at various PV temperature T{sub pv}. Another long-term field test of 1kWp PV array using nMPPO shows that the power generation using nMPPO is almost identical with MPPT at various weather conditions and T{sub pv} variation from 24{sup o}C to 70{sup o}C. (author)

Operating principle of Soft Open Points for electrical distribution network operation

International Nuclear Information System (INIS)

Cao, Wanyu; Wu, Jianzhong; Jenkins, Nick; Wang, Chengshan; Green, Timothy

2016-01-01

Highlights: • Two control modes were developed for a B2B VSCs based SOP. • The SOP operating principle was investigated under various network conditions. • The performance of the SOP using two control modes was analyzed. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.

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

Point-and-stare operation and high-speed image acquisition in real-time hyperspectral imaging

Science.gov (United States)

Driver, Richard D.; Bannon, David P.; Ciccone, Domenic; Hill, Sam L.

2010-04-01

The design and optical performance of a small-footprint, low-power, turnkey, Point-And-Stare hyperspectral analyzer, capable of fully automated field deployment in remote and harsh environments, is described. The unit is packaged for outdoor operation in an IP56 protected air-conditioned enclosure and includes a mechanically ruggedized fully reflective, aberration-corrected hyperspectral VNIR (400-1000 nm) spectrometer with a board-level detector optimized for point and stare operation, an on-board computer capable of full system data-acquisition and control, and a fully functioning internal hyperspectral calibration system for in-situ system spectral calibration and verification. Performance data on the unit under extremes of real-time survey operation and high spatial and high spectral resolution will be discussed. Hyperspectral acquisition including full parameter tracking is achieved by the addition of a fiber-optic based downwelling spectral channel for solar illumination tracking during hyperspectral acquisition and the use of other sensors for spatial and directional tracking to pinpoint view location. The system is mounted on a Pan-And-Tilt device, automatically controlled from the analyzer's on-board computer, making the HyperspecTM particularly adaptable for base security, border protection and remote deployments. A hyperspectral macro library has been developed to control hyperspectral image acquisition, system calibration and scene location control. The software allows the system to be operated in a fully automatic mode or under direct operator control through a GigE interface.

Free-time and fixed end-point multi-target optimal control theory: Application to quantum computing

International Nuclear Information System (INIS)

Mishima, K.; Yamashita, K.

2011-01-01

Graphical abstract: The two-state Deutsch-Jozsa algortihm used to demonstrate the utility of free-time and fixed-end point multi-target optimal control theory. Research highlights: → Free-time and fixed-end point multi-target optimal control theory (FRFP-MTOCT) was constructed. → The features of our theory include optimization of the external time-dependent perturbations with high transition probabilities, that of the temporal duration, the monotonic convergence, and the ability to optimize multiple-laser pulses simultaneously. → The advantage of the theory and a comparison with conventional fixed-time and fixed end-point multi-target optimal control theory (FIFP-MTOCT) are presented by comparing data calculated using the present theory with those published previously [K. Mishima, K. Yamashita, Chem. Phys. 361 (2009) 106]. → The qubit system of our interest consists of two polar NaCl molecules coupled by dipole-dipole interaction. → The calculation examples show that our theory is useful for minor adjustment of the external fields. - Abstract: An extension of free-time and fixed end-point optimal control theory (FRFP-OCT) to monotonically convergent free-time and fixed end-point multi-target optimal control theory (FRFP-MTOCT) is presented. The features of our theory include optimization of the external time-dependent perturbations with high transition probabilities, that of the temporal duration, the monotonic convergence, and the ability to optimize multiple-laser pulses simultaneously. The advantage of the theory and a comparison with conventional fixed-time and fixed end-point multi-target optimal control theory (FIFP-MTOCT) are presented by comparing data calculated using the present theory with those published previously [K. Mishima, K. Yamashita, Chem. Phys. 361, (2009), 106]. The qubit system of our interest consists of two polar NaCl molecules coupled by dipole-dipole interaction. The calculation examples show that our theory is useful for minor

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.

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.

76 FR 60733 - Drawbridge Operation Regulations; Narrow Bay, Smith Point, NY

Science.gov (United States)

2011-09-30

... Operation Regulations; Narrow Bay, Smith Point, NY AGENCY: Coast Guard, DHS. ACTION: Notice of temporary... deviation from the regulation governing the operation of the Smith Point Bridge, 6.1, across Narrow Bay, between Smith Point and Fire Island, New York. The deviation is necessary to facilitate bridge...

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.

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.

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 Energy Management of Multi-Microgrids with Sequentially Coordinated Operations

Directory of Open Access Journals (Sweden)

Nah-Oak Song

2015-08-01

Full Text Available We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically modeled to find the optimal operation conditions and illustrated with physical interpretation of how to achieve optimal energy management in the cooperative multi-microgrid community. This global electric energy optimization of the cooperative community is realized by the ancillary internal trading between the microgrids in the cooperative community which reduces the extra cost from unnecessary external trading by adjusting the electric energy production amounts of combined heat and power (CHP generators and amounts of both internal and external electric energy trading of the cooperative community. A simulation study is also conducted to validate the proposed mathematical energy management models.

Measuring Operational Success: Establishing Criteria to Benchmark the Point of Culmination

National Research Council Canada - National Science Library

Caraccilo, Dominic

1997-01-01

... has for the establishment of criteria that measure operational success on the battlefield. This void, in-turn, impacts directly on the operational commander's capability to identify his point(s) of culmination...

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)

Hybrid collaborative optimization based on selection strategy of initial point and adaptive relaxation

Energy Technology Data Exchange (ETDEWEB)

Ji, Aimin; Yin, Xu; Yuan, Minghai [Hohai University, Changzhou (China)

2015-09-15

There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in inappropriate relaxation factors. To solve these problems, we first develop the Latin hypercube design (LHD) to determine an initial point of optimization, and then use the non-linear programming by quadratic Lagrangian (NLPQL) to search for the global solution. The effectiveness of the initial point selection strategy is verified by three benchmark functions with some dimensions and different complexities. Then we propose the Adaptive relaxation collaborative optimization (ARCO) algorithm to solve the inconsistency between the system level and the disciplines level, and in this method, the relaxation factors are determined according to the three separated stages of CO respectively. The performance of the ARCO algorithm is compared with the standard collaborative algorithm and the constant relaxation collaborative algorithm with a typical numerical example, which indicates that the ARCO algorithm is more efficient and accurate. Finally, we propose a Hybrid collaborative optimization (HCO) approach, which integrates the selection strategy of initial point with the ARCO algorithm. The results show that HCO can achieve the global optimal solution without the initial value and it also has advantages in convergence, accuracy and robustness. Therefore, the proposed HCO approach can solve the CO problems with applications in the spindle and the speed reducer.

Hybrid collaborative optimization based on selection strategy of initial point and adaptive relaxation

International Nuclear Information System (INIS)

Ji, Aimin; Yin, Xu; Yuan, Minghai

2015-01-01

There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in inappropriate relaxation factors. To solve these problems, we first develop the Latin hypercube design (LHD) to determine an initial point of optimization, and then use the non-linear programming by quadratic Lagrangian (NLPQL) to search for the global solution. The effectiveness of the initial point selection strategy is verified by three benchmark functions with some dimensions and different complexities. Then we propose the Adaptive relaxation collaborative optimization (ARCO) algorithm to solve the inconsistency between the system level and the disciplines level, and in this method, the relaxation factors are determined according to the three separated stages of CO respectively. The performance of the ARCO algorithm is compared with the standard collaborative algorithm and the constant relaxation collaborative algorithm with a typical numerical example, which indicates that the ARCO algorithm is more efficient and accurate. Finally, we propose a Hybrid collaborative optimization (HCO) approach, which integrates the selection strategy of initial point with the ARCO algorithm. The results show that HCO can achieve the global optimal solution without the initial value and it also has advantages in convergence, accuracy and robustness. Therefore, the proposed HCO approach can solve the CO problems with applications in the spindle and the speed reducer

Point-based warping with optimized weighting factors of displacement vectors

Science.gov (United States)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

Optimizing Reservoir Operation to Adapt to the Climate Change

Science.gov (United States)

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.

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.

Design and development of bio-inspired framework for reservoir operation optimization

Science.gov (United States)

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.

An improved artificial physical optimization algorithm for dynamic dispatch of generators with valve-point effects and wind power

International Nuclear Information System (INIS)

Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan

2014-01-01

Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a

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

A trust region interior point algorithm for optimal power flow problems

Energy Technology Data Exchange (ETDEWEB)

Wang Min [Hefei University of Technology (China). Dept. of Electrical Engineering and Automation; Liu Shengsong [Jiangsu Electric Power Dispatching and Telecommunication Company (China). Dept. of Automation

2005-05-01

This paper presents a new algorithm that uses the trust region interior point method to solve nonlinear optimal power flow (OPF) problems. The OPF problem is solved by a primal/dual interior point method with multiple centrality corrections as a sequence of linearized trust region sub-problems. It is the trust region that controls the linear step size and ensures the validity of the linear model. The convergence of the algorithm is improved through the modification of the trust region sub-problem. Numerical results of standard IEEE systems and two realistic networks ranging in size from 14 to 662 buses are presented. The computational results show that the proposed algorithm is very effective to optimal power flow applications, and favors the successive linear programming (SLP) method. Comparison with the predictor/corrector primal/dual interior point (PCPDIP) method is also made to demonstrate the superiority of the multiple centrality corrections technique. (author)

Deterministic operations research models and methods in linear optimization

CERN Document Server

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

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

Science.gov (United States)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Control of the electrical operating point of an electric discharge by mean of its power supply; Controle du point de fonctionnement des decharges electriques par l'intermediaire de leur alimentation

Energy Technology Data Exchange (ETDEWEB)

Salanne, J.Ph.

2005-11-15

The operating points obtained by the coupling of the power supply with the electric discharge system can be unstable because of the dynamical behaviour of the discharge or because of a change in its length. In this work, the different possible couplings existing between the discharge and the characteristics of its power supply are analyzed in order to optimize the design and control of the power supply and to control the operating point. Analytical and numerical modeling of the system are proposed which allow to simulate the couplings between the power supply and the discharge. This approach is completed by experimental investigations allowing to consider the cases of peak/peak discharges, dielectric barrier discharges (DBD), and gliding arcs. (J.S.)

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)

Optimal scope of supply chain network & operations design

NARCIS (Netherlands)

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

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)

Surrogate runner model for draft tube losses computation within a wide range of operating points

International Nuclear Information System (INIS)

Susan-Resiga, R; Ciocan, T; Muntean, S; De Colombel, T; Leroy, P

2014-01-01

We introduce a quasi two-dimensional (Q2D) methodology for assessing the swirling flow exiting the runner of hydraulic turbines at arbitrary operating points, within a wide operating range. The Q2D model does not need actual runner computations, and as a result it represents a surrogate runner model for a-priori assessment of the swirling flow ingested by the draft tube. The axial, radial and circumferential velocity components are computed on a conical section located immediately downstream the runner blades trailing edge, then used as inlet conditions for regular draft tube computations. The main advantage of our model is that it allows the determination of the draft tube losses within the intended turbine operating range in the early design stages of a new or refurbished runner, thus providing a robust and systematic methodology to meet the optimal requirements for the flow at the runner outlet

Primal-Dual Interior Point Multigrid Method for Topology Optimization

Czech Academy of Sciences Publication Activity Database

Kočvara, Michal; Mohammed, S.

2016-01-01

Roč. 38, č. 5 (2016), B685-B709 ISSN 1064-8275 Grant - others:European Commission - EC(XE) 313781 Institutional support: RVO:67985556 Keywords : topology optimization * multigrid method s * interior point method Subject RIV: BA - General Mathematics Impact factor: 2.195, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0462418.pdf

Optimal Control and Operation Strategy for Wind Turbines Contributing to Grid Primary Frequency Regulation

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.

Parametric Optimization of Some Critical Operating System Functions--An Alternative Approach to the Study of Operating Systems Design

Science.gov (United States)

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…

Design principles and operating principles: the yin and yang of optimal functioning.

Science.gov (United States)

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.

Fuzzy multiobjective models for optimal operation of a hydropower system

Science.gov (United States)

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.

Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

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.

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.

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

Science.gov (United States)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant-Friedrichs-Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

Greenhouse gases emission assessment in residential sector through buildings simulations and operation optimization

International Nuclear Information System (INIS)

Stojiljković, Mirko M.; Ignjatović, Marko G.; Vučković, Goran D.

2015-01-01

Buildings use a significant amount of primary energy and largely contribute to greenhouse gases emission. Cost optimality and cost effectiveness, including cost-optimal operation, are important for the adoption of energy efficient and environmentally friendly technologies. The long-term assessment of buildings-related greenhouse gases emission might take into account cost-optimal operation of their energy systems. This is often not the case in the literature. Long-term operation optimization problems are often of large scale and computationally intensive and time consuming. This paper formulates a bottom-up methodology relying on an efficient, but precise operation optimization approach, applicable to long-term problems and use with buildings simulations. We suggest moving-horizon short-term optimization to determine near-optimal operation modes and show that this approach, applied to flexible energy systems without seasonal storage, have satisfactory efficiency and accuracy compared with solving problem for an entire year. We also confirm it as a valuable pre-solve technique. Approach applicability and the importance of energy systems optimization are illustrated with a case study considering buildings envelope improvements and cogeneration and heat storage implementation in an urban residential settlement. EnergyPlus is used for buildings simulations while mixed integer linear programming optimization problems are constructed and solved using the custom-built software and the branch-and-cut solver Gurobi Optimizer. - Highlights: • Bottom-up approach for greenhouse gases emission assessment is presented. • Short-term moving-horizon optimization is used to define operation regimes. • Operation optimization and buildings simulations are connected with modeling tool. • Illustrated optimization method performed efficiently and gave accurate results.

Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation

Science.gov (United States)

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.

Modified Chaos Particle Swarm Optimization-Based Optimized Operation Model for Stand-Alone CCHP Microgrid

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.

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...

Operation Characteristics Optimization of Low Power Three-Phase Asynchronous Motors

Directory of Open Access Journals (Sweden)

VLAD, I.

2014-02-01

Full Text Available Most published papers on low power asynchronous motors were aimed to achieve better operational performances in different operating conditions. The optimal design of the general-purpose motors requires searching and selecting an electric machine to meet minimum operating costs criterion and certain customer imposed restrictive conditions. In this paper, there are many significant simulations providing qualitative and quantitative information on reducing active and reactive energy losses in motors, and on parameters and constructive solution. The optimization study applied the minimal operating costs criterion, and it took into account the starting restrictive conditions. Thirteen variables regarding electromagnetic stresses and main constructive dimensions were considered. The operating costs of the optimized motor decreased with 25.6%, as compared to the existing solution. This paper can be a practical and theoretical support for the development and implementation of modern design methods, based on theoretical and experimental study of stationary and transient processes in low power motors, to increase efficiency and power factor.

Optimal cutoff points for HOMA-IR and QUICKI in the diagnosis of metabolic syndrome and non-alcoholic fatty liver disease: A population based study.

Science.gov (United States)

Motamed, Nima; Miresmail, Seyed Javad Haji; Rabiee, Behnam; Keyvani, Hossein; Farahani, Behzad; Maadi, Mansooreh; Zamani, Farhad

2016-03-01

The present study was carried out to determine the optimal cutoff points for homeostatic model assessment (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) in the diagnosis of metabolic syndrome (MetS) and non-alcoholic fatty liver disease (NAFLD). The baseline data of 5511 subjects aged ≥18years of a cohort study in northern Iran were utilized to analyze. Receiver operating characteristic (ROC) analysis was conducted to determine the discriminatory capability of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD. Youden index was utilized to determine the optimal cutoff points of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD. The optimal cutoff points for HOMA-IR in the diagnosis of MetS and NAFLD were 2.0 [sensitivity=64.4%, specificity=66.8%] and 1.79 [sensitivity=66.2%, specificity=62.2%] in men and were 2.5 [sensitivity=57.6%, specificity=67.9%] and 1.95 [sensitivity=65.1%, specificity=54.7%] in women respectively. Furthermore, the optimal cutoff points for QUICKI in the diagnosis of MetS and NAFLD were 0.343 [sensitivity=63.7%, specificity=67.8%] and 0.347 [sensitivity=62.9%, specificity=65.0%] in men and were 0.331 [sensitivity=55.7%, specificity=70.7%] and 0.333 [sensitivity=53.2%, specificity=67.7%] in women respectively. Not only the optimal cutoff points of HOMA-IR and QUICKI were different for MetS and NAFLD, but also different cutoff points were obtained for men and women for each of these two conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Two-Stage Chaos Optimization Search Application in Maximum Power Point Tracking of PV Array

Directory of Open Access Journals (Sweden)

Lihua Wang

2014-01-01

Full Text Available In order to deliver the maximum available power to the load under the condition of varying solar irradiation and environment temperature, maximum power point tracking (MPPT technologies have been used widely in PV systems. Among all the MPPT schemes, the chaos method is one of the hot topics in recent years. In this paper, a novel two-stage chaos optimization method is presented which can make search faster and more effective. In the process of proposed chaos search, the improved logistic mapping with the better ergodic is used as the first carrier process. After finding the current optimal solution in a certain guarantee, the power function carrier as the secondary carrier process is used to reduce the search space of optimized variables and eventually find the maximum power point. Comparing with the traditional chaos search method, the proposed method can track the change quickly and accurately and also has better optimization results. The proposed method provides a new efficient way to track the maximum power point of PV array.

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.

Applications of Operational Research Techniques in Optimization to Visit Tourist Points of Vina del Mar

Directory of Open Access Journals (Sweden)

Joao CARDOSO NETO

2012-01-01

Full Text Available Chile is a country with great attractions for tourists in South America and the whole world. Among the many tourist Chilean attractions the city of Vina del Mar is one of the highlights, recognized nationally and internationally as one of the most beautiful places for summer. In Vina del Mar tourists have many options for leisure, besides pretty beaches, e.g. playa renaca, the city has beautiful squares and castles, e.g. Castillo Wulff built more than 100 (one hundred years ago. It is noteworthy that already exist over there five (5 tourist itineraries, so this work was developed in order to determine the best routes to these existing itineraries, and create a unique route that includes all the tourist points in Vina del Mar, because in this way, the tourists visiting this city can minimize the time spent in traveling, as well as optimize their moments of leisure, taking the opportunity to know all the city attractions. To determine shorter ways to do it and then propose some suggestions for improvement of the quality of the tourist service offered, it had used the exact method, by solving the mathematical model of the TSP (Traveling Salesman Problem, and the heuristic method, using the most economic insertion algorithm.

Total output operation chart optimization of cascade reservoirs and its application

International Nuclear Information System (INIS)

Jiang, Zhiqiang; Ji, Changming; Sun, Ping; Wang, Liping; Zhang, Yanke

2014-01-01

Highlights: • We propose a new double nested model for cascade reservoirs operation optimization. • We use two methods to extract the output distribution ratio. • The adopted two methods perform better than the widely used methods at present. • Stepwise regression method performs better than mean value method on the whole. - Abstract: With the rapid development of cascade hydropower stations in recent decades, the cascade system composed of multiple reservoirs needs unified operation and management. However, the output distribution problem has not yet been solved reasonably when the total output of cascade system obtained, which makes the full utilization of hydropower resources in cascade reservoirs very difficult. Discriminant criterion method is a traditional and common method to solve the output distribution problem at present, but some shortcomings cannot be ignored in the practical application. In response to the above concern, this paper proposes a new total output operation chart optimization model and a new optimal output distribution model, the two models constitute to a double nested model with the goal of maximizing power generation. This paper takes the cascade reservoirs of Li Xianjiang River in China as an instance to obtain the optimal total output operation chart by the proposed double nested model and the 43 years historical runoff data, progressive searching method and progressive optimality algorithm are used in solving the model. In order to take the obtained total output operation chart into practical operation, mean value method and stepwise regression method are adopted to extract the output distribution ratios on the basis of the optimal simulation intermediate data. By comparing with discriminant criterion method and conventional method, the combined utilization of total output operation chart and output distribution ratios presents better performance in terms of power generation and assurance rate, which proves it is an effective

Computing three-point functions for short operators

International Nuclear Information System (INIS)

Bargheer, Till; Institute for Advanced Study, Princeton, NJ; Minahan, Joseph A.; Pereira, Raul

2013-11-01

We compute the three-point structure constants for short primary operators of N=4 super Yang.Mills theory to leading order in 1/√(λ) by mapping the problem to a flat-space string theory calculation. We check the validity of our procedure by comparing to known results for three chiral primaries. We then compute the three-point functions for any combination of chiral and non-chiral primaries, with the non-chiral primaries all dual to string states at the first massive level. Along the way we find many cancellations that leave us with simple expressions, suggesting that integrability is playing an important role.

Computing three-point functions for short operators

Energy Technology Data Exchange (ETDEWEB)

Bargheer, Till [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Institute for Advanced Study, Princeton, NJ (United States). School of Natural Sciences; Minahan, Joseph A.; Pereira, Raul [Uppsala Univ. (Sweden). Dept. of Physics and Astronomy

2013-11-15

We compute the three-point structure constants for short primary operators of N=4 super Yang.Mills theory to leading order in 1/√(λ) by mapping the problem to a flat-space string theory calculation. We check the validity of our procedure by comparing to known results for three chiral primaries. We then compute the three-point functions for any combination of chiral and non-chiral primaries, with the non-chiral primaries all dual to string states at the first massive level. Along the way we find many cancellations that leave us with simple expressions, suggesting that integrability is playing an important role.

Point-splitting regularization of composite operators and anomalies

International Nuclear Information System (INIS)

Novotny, J.; Schnabl, M.

2000-01-01

The point-splitting regularization technique for composite operators is discussed in connection with anomaly calculation. We present a pedagogical and self-contained review of the topic with an emphasis on the technical details. We also develop simple algebraic tools to handle the path ordered exponential insertions used within the covariant and non-covariant version of the point-splitting method. The method is then applied to the calculation of the chiral, vector, trace, translation and Lorentz anomalies within diverse versions of the point-splitting regularization and a connection between the results is described. As an alternative to the standard approach we use the idea of deformed point-split transformation and corresponding Ward-Takahashi identities rather than an application of the equation of motion, which seems to reduce the complexity of the calculations. (orig.)

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.

Optimal configuration of spatial points in the reactor cell

International Nuclear Information System (INIS)

Bosevski, T.

1968-01-01

Optimal configuration of spatial points was chosen in respect to the total number needed for integration of reactions in the reactor cell. Previously developed code VESTERN was used for numerical verification of the method on a standard reactor cell. The code applies the collision probability method for calculating the neutron flux distribution. It is shown that the total number of spatial points is twice smaller than the respective number of spatial zones needed for determination of number of reactions in the cell, with the preset precision. This result shows the direction for further condensing of the procedure for calculating the space-energy distribution of the neutron flux in a reactors cell [sr

Dynamic optimization of distribution networks. Closed loop operation results; Dynamische Optimierung der Verteilnetze. Closed loop Betriebsergebnisse

Energy Technology Data Exchange (ETDEWEB)

Ilo, Albana [Siemens AG, Wien (Austria); Schaffer, Walter; Rieder, Thomas [Salzburg Netz GmbH, Salzburg (Austria); Dzafic, Izudin [Siemens AG, Nuernberg (Germany)

2012-07-01

A holistic approach of power system control that includes all voltage levels from highest to low voltage is provided. The power grid is conceived as a supply chain. The medium voltage grid represents the central link. The implemented automatic voltage control and the dynamic operation optimization are based on Distribution System State Estimator (DSSE) and Volt/Var Control (VVC) applications. The last one realizes the dynamic optimization of distribution network combining the reactive power of the decentralized generation, capacitors and voltage set points of on-line tap changers. Application of this method has shown, that by using the dynamic voltage control the grid can be stable operated near the low voltage limit. The conservation voltage reduction can be applied in real time. Furthermore the integration of the decentralized generation is facilitated with minimal costs. Until now in this regard required network expansion can be prevented or delayed. (orig.)

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

Energy Technology Data Exchange (ETDEWEB)

Liu, Youshan, E-mail: ysliu@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); Teng, Jiwen, E-mail: jwteng@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); Xu, Tao, E-mail: xutao@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101 (China); Badal, José, E-mail: badal@unizar.es [Physics of the Earth, Sciences B, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain)

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant–Friedrichs–Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

International Nuclear Information System (INIS)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-01-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant–Friedrichs–Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

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)

Optimization of Operations Resources via Discrete Event Simulation Modeling

Science.gov (United States)

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 the bank's operating portfolio

Science.gov (United States)

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.

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.

Revisiting the dilatation operator of the Wilson-Fisher fixed point

Energy Technology Data Exchange (ETDEWEB)

Liendo, Pedro [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group

2017-01-15

We revisit the order ε dilatation operator of the Wilson-Fisher fixed point obtained by Kehrein, Pismak, and Wegner in light of recent results in conformal field theory. Our approach is algebraic and based only on symmetry principles. The starting point of our analysis is that the first correction to the dilatation operator is a conformal invariant, which implies that its form is fixed up to an infinite set of coefficients associated with the scaling dimensions of higher-spin currents. These coefficients can be fixed using well-known perturbative results, however, they were recently re-obtained using CFT arguments without relying on perturbation theory. Our analysis then implies that all order-ε scaling dimensions of the Wilson-Fisher fixed point can be fixed by symmetry.

Optimal reservoir operation policies using novel nested algorithms

Science.gov (United States)

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

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 for steady-state and hybrid operations of ITER by using scaling models of divertor heat load

International Nuclear Information System (INIS)

Murakami, Yoshiki; Itami, Kiyoshi; Sugihara, Masayoshi; Fujieda, Hirobumi.

1992-09-01

Steady-state and hybrid mode operations of ITER are investigated by 0-D power balance calculations assuming no radiation and charge-exchange cooling in divertor region. Operation points are optimized with respect to divertor heat load which must be reduced to the level of ignition mode (∼5 MW/m 2 ). Dependence of the divertor heat load on the variety of the models, i.e., constant-χ model, Bohm-type-χ model and JT-60U empirical scaling model, is also discussed. The divertor heat load increases linearly with the fusion power (P FUS ) in all models. The possible highest fusion power much differs for each model with an allowable divertor heat load. The heat load evaluated by constant-χ model is, for example, about 1.8 times larger than that by Bohm-type-χ model at P FUS = 750 MW. Effect of reduction of the helium accumulation, improvements of the confinement capability and the current-drive efficiency are also investigated aiming at lowering the divertor heat load. It is found that NBI power should be larger than about 60 MW to obtain a burn time longer than 2000 s. The optimized operation point, where the minimum divertor heat load is achieved, does not depend on the model and is the point with the minimum-P FUS and the maximum-P NBI . When P FUS = 690 MW and P NBI = 110 MW, the divertor heat load can be reduced to the level of ignition mode without impurity seeding if H = 2.2 is achieved. Controllability of the current-profile is also discussed. (J.P.N.)

A Particle Swarm Optimization Algorithm for Optimal Operating Parameters of VMI Systems in a Two-Echelon Supply Chain

Science.gov (United States)

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.

Determination of the Optimal Operating Parameters for Jefferson Laboratory's Cryogenic Cold Compressor Systems

Energy Technology Data Exchange (ETDEWEB)

Wilson, Jr., Joe D. [Christopher Newport Univ., Newport News, VA (United States)

2003-01-01

The technology of Jefferson Laboratory's (JLab) Continuous Electron Beam Accelerator Facility (CEBAF) and Free Electron Laser (FEL) requires cooling from one of the world's largest 2K helium refrigerators known as the Central Helium Liquefier (CHL). The key characteristic of CHL is the ability to maintain a constant low vapor pressure over the large liquid helium inventory using a series of five cold compressors. The cold compressor system operates with a constrained discharge pressure over a range of suction pressures and mass flows to meet the operational requirements of CEBAF and FEL. The research topic is the prediction of the most thermodynamically efficient conditions for the system over its operating range of mass flows and vapor pressures with minimum disruption to JLab operations. The research goal is to find the operating points for each cold compressor for optimizing the overall system at any given flow and vapor pressure.

Improving Small Signal Stability through Operating Point Adjustment

Energy Technology Data Exchange (ETDEWEB)

Huang, Zhenyu; Zhou, Ning; Tuffner, Francis K.; Chen, Yousu; Trudnowski, Daniel J.; Mittelstadt, William; Hauer, John F.; Dagle, Jeffery E.

2010-09-30

ModeMeter techniques for real-time small signal stability monitoring continue to mature, and more and more phasor measurements are available in power systems. It has come to the stage to bring modal information into real-time power system operation. This paper proposes to establish a procedure for Modal Analysis for Grid Operations (MANGO). Complementary to PSS’s and other traditional modulation-based control, MANGO aims to provide suggestions such as increasing generation or decreasing load for operators to mitigate low-frequency oscillations. Different from modulation-based control, the MANGO procedure proactively maintains adequate damping for all time, instead of reacting to disturbances when they occur. Effect of operating points on small signal stability is presented in this paper. Implementation with existing operating procedures is discussed. Several approaches for modal sensitivity estimation are investigated to associate modal damping and operating parameters. The effectiveness of the MANGO procedure is confirmed through simulation studies of several test systems.

Modeling and operation optimization of a proton exchange membrane fuel cell system for maximum efficiency

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.

Optimal control of load-following operations in a pressurized water reactor

International Nuclear Information System (INIS)

Zhao Fuyu; Zhou Dawei

2000-01-01

According to the optimal control theory, the problem of load-following operation in a pressurized water reactor is formulated as a nonlinear-quadratic optimal control problem. One-dimensional core model is adopted. A successful optimization algorithm DDPSR is proposed to solving the obtained problem. The research results show that the DDPSR can converge with a long time interval and needs very small iteration number and computing time, and the practical reactor can be fairly operated in an optimal load-following manner and axial offset satisfies the required value from beginning to end. Control characters of boron concentration are discussed specially

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...

An adaptive immune optimization algorithm with dynamic lattice searching operation for fast optimization of atomic clusters

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

Multicore PSO Operation for Maximum Power Point Tracking of a Distributed Photovoltaic System under Partially Shading Condition

Directory of Open Access Journals (Sweden)

Ru-Min Chao

2016-01-01

Full Text Available This paper identifies the partial shading problem of a PV module using the one-diode model and simulating the characteristics exhibiting multiple-peak power output condition that is similar to a PV array. A modified particle swarm optimization (PSO algorithm based on the suggested search-agent deployment, retracking condition, and multicore operation is proposed in order to continuously locate the global maximum power point for the PV system. Partial shading simulation results for up to 16 modules in series/parallel formats are presented. A distributed PV system consisting of up to 8 a-silicon thin film PV panels and also having a dedicated DC/DC buck converter on each of the modules is tested. The converter reaches its steady state voltage output in 10 ms. However for MPPT operation, voltage, and current measurement interval is set to 20 ms to avoid unnecessary noise from the entire electric circuit. Based on the simulation and experiment results, each core of the proposed PSO operation should control no more than 4 PV modules in order to have the maximum tracking accuracy and minimum overall tracking time. Tracking for the global maximum power point of a distributed PV system under various partial shading conditions can be done within 1.3 seconds.

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.

Stabilizing operation point technique based on the tunable distributed feedback laser for interferometric sensors

Science.gov (United States)

Mao, Xuefeng; Zhou, Xinlei; Yu, Qingxu

2016-02-01

We describe a stabilizing operation point technique based on the tunable Distributed Feedback (DFB) laser for quadrature demodulation of interferometric sensors. By introducing automatic lock quadrature point and wavelength periodically tuning compensation into an interferometric system, the operation point of interferometric system is stabilized when the system suffers various environmental perturbations. To demonstrate the feasibility of this stabilizing operation point technique, experiments have been performed using a tunable-DFB-laser as light source to interrogate an extrinsic Fabry-Perot interferometric vibration sensor and a diaphragm-based acoustic sensor. Experimental results show that good tracing of Q-point was effectively realized.

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto

2018-01-12

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

Optimization of temperature differences in a utilizer in relation to the lowest sum of capital and operating cost

International Nuclear Information System (INIS)

Kustrin, I.; Tuma, M.

1992-01-01

Our environment and nature are currently overburdened with the emission of noxious substances. Steam boilers fired with coal are therefore not very popular. Wherever possible, they are being replaced by devices which are less harmful for the environment because they use different fuel. This paper discusses replacing a steam boiler with a gas turbine and an utilizer. A mathematical model for performing the optimization of capital and operating costs is presented. The model optimizes the degree of preheating of the flue gases i.e. the temperature of the entering flue gases. The smallest temperature difference (pinch point) was not estimated by the pinch technology because the presented example is relatively simple and the pinch point temperature difference was chosen according to the values reported in various literature sources. The optimization is supplemented with an analysis of the thermal and exergetical efficiencies of the utilizer under different conditions (average temperature difference between the hot gases and water or steam, exit temperature of the hot gases), which condition the choice of the type of utilizer

Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood

NARCIS (Netherlands)

Asadi, A.R.; Roos, C.

2015-01-01

In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author.

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.

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

Optimal Operation of Energy Storage in Power Transmission and Distribution

Science.gov (United States)

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

Optimizing integrated airport surface and terminal airspace operations under uncertainty

Science.gov (United States)

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

The optimization of nuclear power plants operation modes in emergency situations

Science.gov (United States)

Zagrebayev, A. M.; Trifonenkov, A. V.; Ramazanov, R. N.

2018-01-01

An emergency situations resulting in the necessity for temporary reactor trip may occur at the nuclear power plant while normal operating mode. The paper deals with some of the operation c aspects of nuclear power plant operation in emergency situations and during threatened period. The xenon poisoning causes limitations on the variety of statements of the problem of calculating characteristics of a set of optimal reactor power off controls. The article show a possibility and feasibility of new sets of optimization tasks for the operation of nuclear power plants under conditions of xenon poisoning in emergency circumstances.

On Implementing a Homogeneous Interior-Point Algorithm for Nonsymmetric Conic Optimization

DEFF Research Database (Denmark)

Skajaa, Anders; Jørgensen, John Bagterp; Hansen, Per Christian

Based on earlier work by Nesterov, an implementation of a homogeneous infeasible-start interior-point algorithm for solving nonsymmetric conic optimization problems is presented. Starting each iteration from (the vicinity of) the central path, the method computes (nearly) primal-dual symmetric...... approximate tangent directions followed by a purely primal centering procedure to locate the next central primal-dual point. Features of the algorithm include that it makes use only of the primal barrier function, that it is able to detect infeasibilities in the problem and that no phase-I method is needed...

Building optimal regression tree by ant colony system-genetic algorithm: Application to modeling of melting points

Energy Technology Data Exchange (ETDEWEB)

Hemmateenejad, Bahram, E-mail: hemmatb@sums.ac.ir [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of); Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz (Iran, Islamic Republic of); Shamsipur, Mojtaba [Department of Chemistry, Razi University, Kermanshah (Iran, Islamic Republic of); Zare-Shahabadi, Vali [Young Researchers Club, Mahshahr Branch, Islamic Azad University, Mahshahr (Iran, Islamic Republic of); Akhond, Morteza [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of)

2011-10-17

Highlights: {yields} Ant colony systems help to build optimum classification and regression trees. {yields} Using of genetic algorithm operators in ant colony systems resulted in more appropriate models. {yields} Variable selection in each terminal node of the tree gives promising results. {yields} CART-ACS-GA could model the melting point of organic materials with prediction errors lower than previous models. - Abstract: The classification and regression trees (CART) possess the advantage of being able to handle large data sets and yield readily interpretable models. A conventional method of building a regression tree is recursive partitioning, which results in a good but not optimal tree. Ant colony system (ACS), which is a meta-heuristic algorithm and derived from the observation of real ants, can be used to overcome this problem. The purpose of this study was to explore the use of CART and its combination with ACS for modeling of melting points of a large variety of chemical compounds. Genetic algorithm (GA) operators (e.g., cross averring and mutation operators) were combined with ACS algorithm to select the best solution model. In addition, at each terminal node of the resulted tree, variable selection was done by ACS-GA algorithm to build an appropriate partial least squares (PLS) model. To test the ability of the resulted tree, a set of approximately 4173 structures and their melting points were used (3000 compounds as training set and 1173 as validation set). Further, an external test set containing of 277 drugs was used to validate the prediction ability of the tree. Comparison of the results obtained from both trees showed that the tree constructed by ACS-GA algorithm performs better than that produced by recursive partitioning procedure.

Control strategy for power management, efficiency-optimization and operating-safety of a 5-kW solid oxide fuel cell system

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

Synergy optimization and operation management on syndicate complementary knowledge cooperation

Science.gov (United States)

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.

Parallel point-multiplication architecture using combined group operations for high-speed cryptographic applications.

Directory of Open Access Journals (Sweden)

Md Selim Hossain

Full Text Available In this paper, we propose a novel parallel architecture for fast hardware implementation of elliptic curve point multiplication (ECPM, which is the key operation of an elliptic curve cryptography processor. The point multiplication over binary fields is synthesized on both FPGA and ASIC technology by designing fast elliptic curve group operations in Jacobian projective coordinates. A novel combined point doubling and point addition (PDPA architecture is proposed for group operations to achieve high speed and low hardware requirements for ECPM. It has been implemented over the binary field which is recommended by the National Institute of Standards and Technology (NIST. The proposed ECPM supports two Koblitz and random curves for the key sizes 233 and 163 bits. For group operations, a finite-field arithmetic operation, e.g. multiplication, is designed on a polynomial basis. The delay of a 233-bit point multiplication is only 3.05 and 3.56 μs, in a Xilinx Virtex-7 FPGA, for Koblitz and random curves, respectively, and 0.81 μs in an ASIC 65-nm technology, which are the fastest hardware implementation results reported in the literature to date. In addition, a 163-bit point multiplication is also implemented in FPGA and ASIC for fair comparison which takes around 0.33 and 0.46 μs, respectively. The area-time product of the proposed point multiplication is very low compared to similar designs. The performance ([Formula: see text] and Area × Time × Energy (ATE product of the proposed design are far better than the most significant studies found in the literature.

Benchmarking of radiological departments. Starting point for successful process optimization

International Nuclear Information System (INIS)

Busch, Hans-Peter

2010-01-01

Continuous optimization of the process of organization and medical treatment is part of the successful management of radiological departments. The focus of this optimization can be cost units such as CT and MRI or the radiological parts of total patient treatment. Key performance indicators for process optimization are cost- effectiveness, service quality and quality of medical treatment. The potential for improvements can be seen by comparison (benchmark) with other hospitals and radiological departments. Clear definitions of key data and criteria are absolutely necessary for comparability. There is currently little information in the literature regarding the methodology and application of benchmarks especially from the perspective of radiological departments and case-based lump sums, even though benchmarking has frequently been applied to radiological departments by hospital management. The aim of this article is to describe and discuss systematic benchmarking as an effective starting point for successful process optimization. This includes the description of the methodology, recommendation of key parameters and discussion of the potential for cost-effectiveness analysis. The main focus of this article is cost-effectiveness (efficiency and effectiveness) with respect to cost units and treatment processes. (orig.)

Improved Full-Newton Step O(nL) Infeasible Interior-Point Method for Linear Optimization

NARCIS (Netherlands)

Gu, G.; Mansouri, H.; Zangiabadi, M.; Bai, Y.Q.; Roos, C.

2009-01-01

We present several improvements of the full-Newton step infeasible interior-point method for linear optimization introduced by Roos (SIAM J. Optim. 16(4):1110–1136, 2006). Each main step of the method consists of a feasibility step and several centering steps. We use a more natural feasibility step,

Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Directory of Open Access Journals (Sweden)

Peitong Zhang

2017-01-01

Full Text Available Skip-stop operation is a low cost approach to improving the efficiency of metro operation and passenger travel experience. This paper proposes a novel method to optimize the skip-stop scheme for bidirectional metro lines so that the average passenger travel time can be minimized. Different from the conventional “A/B” scheme, the proposed Flexible Skip-Stop Scheme (FSSS can better accommodate spatially and temporally varied passenger demand. A genetic algorithm (GA based approach is then developed to efficiently search for the optimal solution. A case study is conducted based on a real world bidirectional metro line in Shenzhen, China, using the time-dependent passenger demand extracted from smart card data. It is found that the optimized skip-stop operation is able to reduce the average passenger travel time and transit agencies may benefit from this scheme due to energy and operational cost savings. Analyses are made to evaluate the effects of that fact that certain number of passengers fail to board the right train (due to skip operation. Results show that FSSS always outperforms the all-stop scheme even when most passengers of the skipped OD pairs are confused and cannot get on the right train.

Optimal design and operation of a photovoltaic-electrolyser system using particle swarm optimisation

Science.gov (United States)

Sayedin, Farid; Maroufmashat, Azadeh; Roshandel, Ramin; Khavas, Sourena Sattari

2016-07-01

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different sizes of PV systems, various ambient temperatures and different locations with various climaticconditions. The results show that for the given location and the PV system, the energy transfer efficiency of PV/EL system can reach up to 97.83%.

78 FR 58570 - Environmental Assessment; Entergy Nuclear Operations, Inc., Big Rock Point

Science.gov (United States)

2013-09-24

... Assessment; Entergy Nuclear Operations, Inc., Big Rock Point AGENCY: Nuclear Regulatory Commission. ACTION... applicant or the licensee), for the Big Rock Point (BRP) Independent Spent Fuel Storage Installation (ISFSI... Rock Point (BRP) Independent Spent Fuel Storage Installation (ISFSI). II. Environmental Assessment (EA...

Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration

Directory of Open Access Journals (Sweden)

Yutong Liu

2012-01-01

Full Text Available Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed and target (reference image. Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (=5 each. In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (<0.05 in registration accuracy by landmark optimization in most data sets and trends towards improvement (<0.1 in others as compared to manual landmark selection.

Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms

NARCIS (Netherlands)

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

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

Energy Technology Data Exchange (ETDEWEB)

Belati, Edmarcio A. [CIMATEC - SENAI, Salvador, BA (Brazil); Alves, Dilson A. [Electrical Engineering Department, FEIS, UNESP - Sao Paulo State University (Brazil); da Costa, Geraldo R.M. [Electrical Engineering Department, EESC, USP - Sao Paulo University (Brazil)

2008-09-15

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (author)

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

Science.gov (United States)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

On Motivating Operations at the Point of Online Purchase Setting

Science.gov (United States)

Fagerstrom, Asle; Arntzen, Erik

2013-01-01

Consumer behavior analysis can be applied over a wide range of economic topics in which the main focus is the contingencies that influence the behavior of the economic agent. This paper provides an overview on the work that has been done on the impact from motivating operations at the point of online purchase situation. Motivating operations, a…

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

Optimization and control of a continuous polymerization reactor

Directory of Open Access Journals (Sweden)

L. A. Alvarez

2012-12-01

Full Text Available This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO, the Model Predictive Control (MPC and a Target Calculation (TC that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.

Nickel-Cadmium Battery Operation Management Optimization Using Robust Design

Science.gov (United States)

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.

Short-term optimal operation of Three-gorge and Gezhouba cascade hydropower stations in non-flood season with operation rules from data mining

International Nuclear Information System (INIS)

Ma Chao; Lian Jijian; Wang Junna

2013-01-01

Highlights: ► Short-term optimal operation of Three-gorge and Gezhouba hydropower stations was studied. ► Key state variable and exact constraints were proposed to improve numerical model. ► Operation rules proposed were applied in population initiation step for faster optimization. ► Culture algorithm with difference evolution was selected as optimization method. ► Model and method proposed were verified by case study with feasible operation solutions. - Abstract: Information hidden in the characteristics and relationship data of a cascade hydropower stations can be extracted by data-mining approaches to be operation rules and optimization support information. In this paper, with Three-gorge and Gezhouba cascade hydropower stations as an example, two operation rules are proposed due to different operation efficiency of water turbines and tight water volume and hydraulic relationship between two hydropower stations. The rules are applied to improve optimization model with more exact decision and state variables and constraints. They are also used in the population initiation step to develop better individuals with culture algorithm with differential evolution as an optimization method. In the case study, total feasible population and the best solution based on an initial population with an operation rule can be obtained with a shorter computation time than that of a pure random initiated population. Amount of electricity generation in a dispatch period with an operation rule also increases with an average increase rate of 0.025%. For a fixed water discharge process of Three-gorge hydropower station, there is a better rule to decide an operation plan of Gezhouba hydropower station in which total hydraulic head for electricity generation is optimized and distributed with inner-plant economic operation considered.

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.

OPTIMIZATION OF AGGREGATION AND SEQUENTIAL-PARALLEL EXECUTION MODES OF INTERSECTING OPERATION SETS

Directory of Open Access Journals (Sweden)

G. М. Levin

2016-01-01

Full Text Available A mathematical model and a method for the problem of optimization of aggregation and of sequential- parallel execution modes of intersecting operation sets are proposed. The proposed method is based on the two-level decomposition scheme. At the top level the variant of aggregation for groups of operations is selected, and at the lower level the execution modes of operations are optimized for a fixed version of aggregation.

Increase of Gas-Turbine Plant Efficiency by Optimizing Operation of Compressors

Science.gov (United States)

Matveev, V.; Goriachkin, E.; Volkov, A.

2018-01-01

The article presents optimization method for improving of the working process of axial compressors of gas turbine engines. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.

Driving external chemistry optimization via operations management principles.

Science.gov (United States)

Bi, F Christopher; Frost, Heather N; Ling, Xiaolan; Perry, David A; Sakata, Sylvie K; Bailey, Simon; Fobian, Yvette M; Sloan, Leslie; Wood, Anthony

2014-03-01

Confronted with the need to significantly raise the productivity of remotely located chemistry CROs Pfizer embraced a commitment to continuous improvement which leveraged the tools from both Lean Six Sigma and queue management theory to deliver positive measurable outcomes. During 2012 cycle times were reduced by 48% by optimization of the work in progress and conducting a detailed workflow analysis to identify and address pinch points. Compound flow was increased by 29% by optimizing the request process and de-risking the chemistry. Underpinning both achievements was the development of close working relationships and productive communications between Pfizer and CRO chemists. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimization Algorithms for Calculation of the Joint Design Point in Parallel Systems

DEFF Research Database (Denmark)

Enevoldsen, I.; Sørensen, John Dalsgaard

1992-01-01

In large structures it is often necessary to estimate the reliability of the system by use of parallel systems. Optimality criteria-based algorithms for calculation of the joint design point in a parallel system are described and efficient active set strategies are developed. Three possible...

System and method of cylinder deactivation for optimal engine torque-speed map operation

Science.gov (United States)

Sujan, Vivek A; Frazier, Timothy R; Follen, Kenneth; Moon, Suk-Min

2014-11-11

This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.

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...

Positive-operator-valued measure optimization of classical correlations

NARCIS (Netherlands)

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.

Energy Optimization Assessment at U.S. Army Installations: West Point Military Academy, NY

Science.gov (United States)

2008-09-01

chillers to work unnecessarily more than needed. Other buildings had setpoints at different areas above 55 °F. Many buildings are air-conditioned and... optimal . The cost of 12.5 cents/KWh makes it unlikely, especially where steam adsorption chillers exist. 11.8.2 Solution Use the existing steam...ER D C/ CE R L TR -0 8 -1 4 Energy Optimization Assessment at U.S. Army Installations West Point Military Academy, NY David M

Point-form electrodynamics and the construction of conserved current operators

International Nuclear Information System (INIS)

Klink, W.H.

2003-01-01

A general procedure for constructing conserved electromagnetic current operators in the presence of hadronic interactions is given. The four-momentum operator in point-form relativistic quantum mechanics is written as the sum of hadronic, photon, and electromagnetic four-momentum operators, where the electromagnetic four-momentum operator is generated from a vertex operator, in which a conserved current operator is contracted with the four-vector potential operator. The current operator is the sum of free, dynamically determined and model-dependent operators. The dynamically determined current operator is formed form a free current operator and the interacting hadronic four-momentum operator, in such a way that the sum of free and dynamically determined current operators is conserved with respect to the hadronic interactions. The model-dependent operator is a many-body current operator, formed as the commutator of an antisymmetric operator with the hadronic four-momentum operator. It is shown that such an operator is also conserved with respect to the hadronic interactions and also does not renormalize the charge. Refs. 9 (author)

Long-period gratings in photonic crystal fibers operating near the phase-matching turning point for evanescent chemical and biochemical sensing

Science.gov (United States)

Kanka, Jiri

2012-06-01

Fiber-optic long-period grating (LPG) operating near the dispersion turning point in its phase matching curve (PMC), referred to as a Turn Around Point (TAP) LPG, is known to be extremely sensitive to external parameters. Moreover, in a TAP LPG the phase matching condition can be almost satisfied over large spectral range, yielding a broadband LPG operation. TAP LPGs have been investigated, namely for use as broadband mode convertors and biosensors. So far TAP LPGs have been realized in specially designed or post-processed conventional fibers, not yet in PCFs, which allow a great degree of freedom in engineering the fiber's dispersion properties through the control of the PCF structural parameters. We have developed the design optimization technique for TAP PCF LPGs employing the finite element method for PCF modal analysis in a combination with the Nelder-Mead simplex method for minimizing the objective function based on target-specific PCF properties. Using this tool we have designed TAP PCF LPGs for specified wavelength ranges and refractive indices of medium in the air holes. Possible TAP PCF-LPG operational regimes - dual-resonance, broadband mode conversion and transmitted intensity-based operation - will be demonstrated numerically. Potential and limitations of TAP PCF-LPGs for evanescent chemical and biochemical sensing will be assessed.

A robust optimization based approach for microgrid operation in deregulated environment

International Nuclear Information System (INIS)

Gupta, R.A.; Gupta, Nand Kishor

2015-01-01

Highlights: • RO based approach developed for optimal MG operation in deregulated environment. • Wind uncertainty modeled by interval forecasting through ARIMA model. • Proposed approach evaluated using two realistic case studies. • Proposed approach evaluated the impact of degree of robustness. • Proposed approach gives a significant reduction in operation cost of microgrid. - Abstract: Micro Grids (MGs) are clusters of Distributed Energy Resource (DER) units and loads. MGs are self-sustainable and generally operated in two modes: (1) grid connected and (2) grid isolated. In deregulated environment, the operation of MG is managed by the Microgrid Operator (MO) with an objective to minimize the total cost of operation. The MG management is crucial in the deregulated power system due to (i) integration of intermittent renewable sources such as wind and Photo Voltaic (PV) generation, and (ii) volatile grid prices. This paper presents robust optimization based approach for optimal MG management considering wind power uncertainty. Time series based Autoregressive Integrated Moving Average (ARIMA) model is used to characterize the wind power uncertainty through interval forecasting. The proposed approach is illustrated through a case study having both dispatchable and non-dispatchable generators through different modes of operation. Further the impact of degree of robustness is analyzed in both cases on the total cost of operation of the MG. A comparative analysis between obtained results using proposed approach and other existing approach shows the strength of proposed approach in cost minimization in MG management

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:

State-of-The-Art of Modeling Methodologies and Optimization Operations in Integrated Energy System

Science.gov (United States)

Zheng, Zhan; Zhang, Yongjun

2017-08-01

Rapid advances in low carbon technologies and smart energy communities are reshaping future patterns. Uncertainty in energy productions and demand sides are paving the way towards decentralization management. Current energy infrastructures could not meet with supply and consumption challenges, along with emerging environment and economic requirements. Integrated Energy System(IES) whereby electric power, natural gas, heating couples with each other demonstrates that such a significant technique would gradually become one of main comprehensive and optimal energy solutions with high flexibility, friendly renewables absorption and improving efficiency. In these global energy trends, we summarize this literature review. Firstly the accurate definition and characteristics of IES have been presented. Energy subsystem and coupling elements modeling issues are analyzed. It is pointed out that decomposed and integrated analysis methods are the key algorithms for IES optimization operations problems, followed by exploring the IES market mechanisms. Finally several future research tendencies of IES, such as dynamic modeling, peer-to-peer trading, couple market design, sare under discussion.

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.

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)

Singular Spectrum Near a Singular Point of Friedrichs Model Operators of Absolute Type

International Nuclear Information System (INIS)

Iakovlev, Serguei I.

2006-01-01

In L 2 (R) we consider a family of self adjoint operators of the Friedrichs model: A m =|t| m +V. Here |t| m is the operator of multiplication by the corresponding function of the independent variable t element of R, and (perturbation) is a trace-class integral operator with a continuous Hermitian kernel ν(t,x) satisfying some smoothness condition. These absolute type operators have one singular point of order m>0. Conditions on the kernel ν(t,x) are found guaranteeing the absence of the point spectrum and the singular continuous one of such operators near the origin. These conditions are actually necessary and sufficient. They depend on the finiteness of the rank of a perturbation operator and on the order of singularity. The sharpness of these conditions is confirmed by counterexamples

Fixed point of the parabolic renormalization operator

CERN Document Server

Lanford III, Oscar E

2014-01-01

This monograph grew out of the authors' efforts to provide a natural geometric description for the class of maps invariant under parabolic renormalization and for the Inou-Shishikura fixed point itself as well as to carry out a computer-assisted study of the parabolic renormalization operator. It introduces a renormalization-invariant class of analytic maps with a maximal domain of analyticity and rigid covering properties and presents a numerical scheme for computing parabolic renormalization of a germ, which is used to compute the Inou-Shishikura renormalization fixed point.   Inside, readers will find a detailed introduction into the theory of parabolic bifurcation,  Fatou coordinates, Écalle-Voronin conjugacy invariants of parabolic germs, and the definition and basic properties of parabolic renormalization.   The systematic view of parabolic renormalization developed in the book and the numerical approach to its study will be interesting to both experts in the field as well as graduate students wishi...

A method for aggregating external operating conditions in multi-generation system optimization models

DEFF Research Database (Denmark)

Lythcke-Jørgensen, Christoffer Ernst; Münster, Marie; Ensinas, Adriano Viana

2016-01-01

This paper presents a novel, simple method for reducing external operating condition datasets to be used in multi-generation system optimization models. The method, called the Characteristic Operating Pattern (CHOP) method, is a visually-based aggregation method that clusters reference data based...... on parameter values rather than time of occurrence, thereby preserving important information on short-term relations between the relevant operating parameters. This is opposed to commonly used methods where data are averaged over chronological periods (months or years), and extreme conditions are hidden...... in the averaged values. The CHOP method is tested in a case study where the operation of a fictive Danish combined heat and power plant is optimized over a historical 5-year period. The optimization model is solved using the full external operating condition dataset, a reduced dataset obtained using the CHOP...

Optimal Design of Modern Transformerless PV Inverter Topologies

OpenAIRE

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inver...

Economic Optimization Analysis of Chengdu Electric Community Bus Operation

Science.gov (United States)

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.

Multi-Level Energy Management and Optimal Control of a Residential DC Microgrid

DEFF Research Database (Denmark)

Diaz, Enrique Rodriguez; Anvari-Moghaddam, Amjad; Quintero, Juan Carlos Vasquez

2017-01-01

of a residential DC microgrid (R-DCMG) with different distributed generations (DGs) and loads is proposed and implemented as an optimal hierarchical control strategy. A system-level optimizer is designed to calculate the optimal operating points of the controllable energy sources (CESs) when needed, while lower......-level controllers are utilized to enforce the CESs to follow optimal set-points....

Optimal Operational Monetary Policy Rules in an Endogenous Growth Model: a calibrated analysis

OpenAIRE

Arato, Hiroki

2009-01-01

This paper constructs an endogenous growth New Keynesian model and considers growth and welfare effect of Taylor-type (operational) monetary policy rules. The Ramsey equilibrium and optimal operational monetary policy rule is also computed. In the calibrated model, the Ramseyoptimal volatility of inflation rate is smaller than that in standard exogenous growth New Keynesian model with physical capital accumulation. Optimal operational monetary policy rule makes nominal interest rate respond s...

Optimal robust control strategy of a solid oxide fuel cell system

Science.gov (United States)

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.

Constructing an optimal decision tree for FAST corner point detection

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2011-01-01

In this paper, we consider a problem that is originated in computer vision: determining an optimal testing strategy for the corner point detection problem that is a part of FAST algorithm [11,12]. The problem can be formulated as building a decision tree with the minimum average depth for a decision table with all discrete attributes. We experimentally compare performance of an exact algorithm based on dynamic programming and several greedy algorithms that differ in the attribute selection criterion. © 2011 Springer-Verlag.

A practical algorithm for optimal operation management of distribution network including fuel cell power plants

Energy Technology Data Exchange (ETDEWEB)

Niknam, Taher; Meymand, Hamed Zeinoddini; Nayeripour, Majid [Electrical and Electronic Engineering Department, Shiraz University of Technology, Shiraz (Iran)

2010-08-15

Fuel cell power plants (FCPPs) have been taken into a great deal of consideration in recent years. The continuing growth of the power demand together with environmental constraints is increasing interest to use FCPPs in power system. Since FCPPs are usually connected to distribution network, the effect of FCPPs on distribution network is more than other sections of power system. One of the most important issues in distribution networks is optimal operation management (OOM) which can be affected by FCPPs. This paper proposes a new approach for optimal operation management of distribution networks including FCCPs. In the article, we consider the total electrical energy losses, the total electrical energy cost and the total emission as the objective functions which should be minimized. Whereas the optimal operation in distribution networks has a nonlinear mixed integer optimization problem, the optimal solution could be obtained through an evolutionary method. We use a new evolutionary algorithm based on Fuzzy Adaptive Particle Swarm Optimization (FAPSO) to solve the optimal operation problem and compare this method with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO) and Tabu Search (TS) over two distribution test feeders. (author)

Triple solutions for multi-point boundary-value problem with p-Laplace operator

Directory of Open Access Journals (Sweden)

Yansheng Liu

2009-11-01

Full Text Available Using a fixed point theorem due to Avery and Peterson, this article shows the existence of solutions for multi-point boundary-value problem with p-Laplace operator and parameters. Also, we present an example to illustrate the results obtained.

SU-F-P-61: Does It Matter Not to Use Optimization Points at the Apex for Vaginal Cylinder HDR Brachytherapy Planning?

Energy Technology Data Exchange (ETDEWEB)

Kim, Y [University Of Iowa, College of Medicine, Iowa City, IN (United States)

2016-06-15

Purpose: To test the impact of the use of apex optimization points for new vaginal cylinder (VC) applicators. Methods: New “ClickFit” single channel VC applicators (Varian) that have a different top thicknesses but the same diameters as the old VC applicators (2.3 cm diameter, 2.6 cm, 3.0 cm, and 3.5 cm) were compared using phantom studies. Old VC applicator plans without apex optimization points were also compared to the plans with the optimization points. The apex doses were monitored at 5 mm depth doses (8 points) where a prescription dose (Rx) of 6Gy was prescribed. VC surface doses (8 points) were also analyzed. Results: The new VC applicator plans without apex optimization points presented significantly lower 5mm depth doses than Rx (on average −31 ± 7%, p <0.00001) due to their thicker VC tops (3.4 ± 1.1 mm thicker with the range of 1.2 to 4.4 mm) than the old VC applicators. Old VC applicator plans also showed a statistically significant reduction (p <0.00001) due to Ir-192 source anisotropic effect at the apex region but the % reduction over Rx was only −7 ± 9%. However, by adding apex optimization points to the new VC applicator plans, the plans improved 5 mm depth doses (−7 ± 9% over Rx) that were not statistically different from old VC plans (p = 0.923), along with apex VC surface doses (−22 ± 10% over old VC versus −46 ± 7% without using apex optimization points). Conclusion: The use of apex optimization points are important in order to avoid significant additional cold doses (−24 ± 2%) at the prescription depth (5 mm) of apex, especially for the new VC applicators that have thicker tops.

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.

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...

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....

Optimization of operating schedule of machines in granite industry using evolutionary algorithms

International Nuclear Information System (INIS)

Loganthurai, P.; Rajasekaran, V.; Gnanambal, K.

2014-01-01

Highlights: • Operating time of machines in granite industries was studied. • Operating time has been optimized using evolutionary algorithms such as PSO, DE. • The maximum demand has been reduced. • Hence the electricity cost of the industry and feeder stress have been reduced. - Abstract: Electrical energy consumption cost plays an important role in the production cost of any industry. The electrical energy consumption cost is calculated as two part tariff, the first part is maximum demand cost and the second part is energy consumption cost or unit cost (kW h). The maximum demand cost can be reduced without affecting the production. This paper focuses on the reduction of maximum demand by proper operating schedule of major equipments. For this analysis, various granite industries are considered. The major equipments in granite industries are cutting machine, polishing machine and compressor. To reduce the maximum demand, the operating time of polishing machine is rescheduled by optimization techniques such as Differential Evolution (DE) and particle swarm optimization (PSO). The maximum demand costs are calculated before and after rescheduling. The results show that if the machines are optimally operated, the cost is reduced. Both DE and PSO algorithms reduce the maximum demand cost at the same rate for all the granite industries. However, the optimum scheduling obtained by DE reduces the feeder power flow than the PSO scheduling

Choosing the Optimal Number of B-spline Control Points (Part 1: Methodology and Approximation of Curves)

Science.gov (United States)

Harmening, Corinna; Neuner, Hans

2016-09-01

Due to the establishment of terrestrial laser scanner, the analysis strategies in engineering geodesy change from pointwise approaches to areal ones. These areal analysis strategies are commonly built on the modelling of the acquired point clouds. Freeform curves and surfaces like B-spline curves/surfaces are one possible approach to obtain space continuous information. A variety of parameters determines the B-spline's appearance; the B-spline's complexity is mostly determined by the number of control points. Usually, this number of control points is chosen quite arbitrarily by intuitive trial-and-error-procedures. In this paper, the Akaike Information Criterion and the Bayesian Information Criterion are investigated with regard to a justified and reproducible choice of the optimal number of control points of B-spline curves. Additionally, we develop a method which is based on the structural risk minimization of the statistical learning theory. Unlike the Akaike and the Bayesian Information Criteria this method doesn't use the number of parameters as complexity measure of the approximating functions but their Vapnik-Chervonenkis-dimension. Furthermore, it is also valid for non-linear models. Thus, the three methods differ in their target function to be minimized and consequently in their definition of optimality. The present paper will be continued by a second paper dealing with the choice of the optimal number of control points of B-spline surfaces.

Optimal operating conditions for external cavity semiconductor laser optical chaos communication system

International Nuclear Information System (INIS)

Priyadarshi, S; Pierce, I; Hong, Y; Shore, K A

2012-01-01

In optical chaos communications a message is masked in the noise-like broadband output of a chaotic transmitter laser, and message recovery is enabled through the synchronization of the transmitter and the (chaotic) receiver laser. Key issues are to identify the laser operating conditions which provide the highest quality synchronization conditions and those which provide optimized message extraction. In general such operating conditions are not coincident. In this paper numerical simulations are performed with the aim of identifying a regime of operation where the highest quality synchronization and optimizing message extraction efficiency are achieved simultaneously. Use of such an operating regime will facilitate practical deployment of optical chaos communications systems without the need for re-adjustment of laser operating conditions in the field. (paper)

47 CFR 90.471 - Points of operation in internal transmitter control systems.

Science.gov (United States)

2010-10-01

...) SAFETY AND SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES Transmitter Control Internal Transmitter Control Systems § 90.471 Points of operation in internal transmitter control systems. The... licensee for internal communications and transmitter control purposes. Operating positions in internal...

Optimal distribution of reactivity excess in a system of reactors operating at a variable loading schedule

International Nuclear Information System (INIS)

Bolsunov, A.A.; Zagrebaev, A.M.; Naumov, V.I.

1979-01-01

Considered is the task of reactivity excess distribution optimization in the system of reactors for the purpose of minimazing the summary power production losses at the fixed loading schedule. Mathematical formulation of the task is presented. Given are the curves, characterizing the dependence of possible degree of the reactor power drop on reactivity excees for non-stationary Xe poisoning at different nominal density of neutron flux. Analyzing the results, it is concluded that in case, when the reactors differ only in neutron flux density the reactor with lower neutron flux density should be involved in the variable operation schedule first as the poisoning of this reactor will be less, and therefore, the losses of the system power production will be less. It is advisable to reserve the reactivity excess in the reactor with greater power or in the reactor with higher burnup rate. It is stressed that the obtained results of the optimization task solution point out the possibility of obtaining the certain ecomonic effect and permit to correct the requirements on mobility of separate power units at system approach to NPP operation in a variable loading schedule

Quantum behaved Particle Swarm Optimization with Differential Mutation operator applied to WWER-1000 in-core fuel management optimization

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

On the Optimization of Point Absorber Buoys

Directory of Open Access Journals (Sweden)

Linnea Sjökvist

2014-05-01

Full Text Available A point absorbing wave energy converter (WEC is a complicated dynamical system. A semi-submerged buoy drives a power take-off device (PTO, which acts as a linear or non-linear damper of the WEC system. The buoy motion depends on the buoy geometry and dimensions, the mass of the moving parts of the system and on the damping force from the generator. The electromagnetic damping in the generator depends on both the generator specifications, the connected load and the buoy velocity. In this paper a velocity ratio has been used to study how the geometric parameters buoy draft and radius, assuming constant generator damping coefficient, affects the motion and the energy absorption of a WEC. It have been concluded that an optimal buoy geometry can be identified for a specific generator damping. The simulated WEC performance have been compared with experimental values from two WECs with similar generators but different buoys. Conclusions have been drawn about their behaviour.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

Science.gov (United States)

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.

Online Optimization Method for Operation of Generators in a Micro Grid

Science.gov (United States)

Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

Nested algorithms for optimal reservoir operation and their embedding in a decision support platform

NARCIS (Netherlands)

Delipetrev, B.

2016-01-01

Reservoir operation is a multi-objective optimization problem traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation named nested DP (nDP), nested SDP (nSDP), nested reinforcement

Comparison of Heuristic Methods Applied for Optimal Operation of Water Resources

Directory of Open Access Journals (Sweden)

Alireza Borhani Dariane

2009-01-01

Full Text Available Water resources optimization problems are usually complex and hard to solve using the ordinary optimization methods, or they are at least  not economically efficient. A great number of studies have been conducted in quest of suitable methods capable of handling such problems. In recent years, some new heuristic methods such as genetic and ant algorithms have been introduced in systems engineering. Preliminary applications of these methods in water resources problems have shown that some of them are powerful tools, capable of solving complex problems. In this paper, the application of such heuristic methods as Genetic Algorithm (GA and Ant Colony Optimization (ACO have been studied for optimizing reservoir operation. The Dez Dam reservoir inIranwas chosen for a case study. The methods were applied and compared using short-term (one year and long-term models. Comparison of the results showed that GA outperforms both DP and ACO in finding true global optimum solutions and operating rules.

Optimization of startup and shutdown operation of simulated moving bed chromatographic processes.

Science.gov (United States)

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.

Automated and continuously operating acid dew point measuring instrument for flue gases

Energy Technology Data Exchange (ETDEWEB)

Reckmann, D.; Naundorf, G.

1986-06-01

Design and operation is explained for a sulfuric acid dew point indicator for continuous flue gas temperature control. The indicator operated successfully in trial tests over several years with brown coal, gas and oil combustion in a measurement range of 60 to 180 C. The design is regarded as uncomplicated and easy to manufacture. Its operating principle is based on electric conductivity measurement on a surface on which sulfuric acid vapor has condensed. A ring electrode and a PtRh/Pt thermal element as central electrode are employed. A scheme of the equipment design is provided. Accuracy of the indicator was compared to manual dew point sondes manufactured by Degussa and showed a maximum deviation of 5 C. Manual cleaning after a number of weeks of operation is required. Fly ash with a high lime content increases dust buildup and requires more frequent cleaning cycles.

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

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

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.

Enhancing State-of-the-art Multi-objective Optimization Algorithms by Applying Domain Specific Operators

DEFF Research Database (Denmark)

Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

2015-01-01

optimization problems where the environment does not change dynamically. For that reason, the requirement for convergence in static optimization problems is not as timecritical as for dynamic optimization problems. Most MOEAs use generic variables and operators that scale to static multi-objective optimization...... problem. The domain specific operators only encode existing knowledge about the environment. A comprehensive comparative study is provided to evaluate the results of applying the CONTROLEUM-GA compared to NSGAII, e-NSGAII and e- MOEA. Experimental results demonstrate clear improvements in convergence time...

Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

Science.gov (United States)

Mehr, Ali Farhang; Tumer, Irem

2005-01-01

In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

Optimal Operation System of the Integrated District Heating System with Multiple Regional Branches

Science.gov (United States)

Kim, Ui Sik; Park, Tae Chang; Kim, Lae-Hyun; Yeo, Yeong Koo

This paper presents an optimal production and distribution management for structural and operational optimization of the integrated district heating system (DHS) with multiple regional branches. A DHS consists of energy suppliers and consumers, district heating pipelines network and heat storage facilities in the covered region. In the optimal management system, production of heat and electric power, regional heat demand, electric power bidding and sales, transport and storage of heat at each regional DHS are taken into account. The optimal management system is formulated as a mixed integer linear programming (MILP) where the objectives is to minimize the overall cost of the integrated DHS while satisfying the operation constraints of heat units and networks as well as fulfilling heating demands from consumers. Piecewise linear formulation of the production cost function and stairwise formulation of the start-up cost function are used to compute nonlinear cost function approximately. Evaluation of the total overall cost is based on weekly operations at each district heat branches. Numerical simulations show the increase of energy efficiency due to the introduction of the present optimal management system.

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.

Optimality with feedback control in relativistic dynamics of a mass point. Part 1

International Nuclear Information System (INIS)

Blaquiere, A.; Pauchard, M.; Tahri-Yousfi, N.; Wickers, D.

1984-01-01

This article is an account of part of a research task currently in progress; it deals with relativistic dynamics of a mass-point from the point of view of the theory of optimal feedback control. In the first part, the theoretical frame is presented with an application to the case of special Relativity. This application shows that the way followed in this article is a natural one for approaching Wave mechanics, and that it closely parallels the way along which Louis de Broglie introduced Wave mechanics [fr

Real time production optimization

Energy Technology Data Exchange (ETDEWEB)

Saputelli, Luigi; Otavio, Joao; Araujo, Turiassu; Escorcia, Alvaro [Halliburton, Houston, TX (United States). Landmark Division

2004-07-01

Production optimization encompasses various activities of measuring, analyzing, modeling, prioritizing and implementing actions to enhance productivity of a field. We present a state-of-the-art framework for optimizing production on a continuous basis as new sensor data is acquired in real time. Permanently acquired data is modeled and analyzed in order to create predictive models. A model based control strategy is used to regulate well and field instrumentation. The optimum field operating point, which changes with time, satisfies the maximum economic return. This work is a starting point for further development in automatic, intelligent reservoir technologies which get the most out of the abilities of permanent, instrumented wells and remotely activated downhole completions. The strategy, tested with history-matched data from a compartmentalised giant field, proved to reduce operating costs while increasing oil recovery by 27% in this field. (author)

Optimization of an experimental hybrid microgrid operation: reliability and economic issues

OpenAIRE

Milo, Aitor; Gaztañaga, Haizea; Etxeberria Otadui, Ion; Bilbao, Endika; Rodríguez Cortés, Pedro

2009-01-01

In this paper a hybrid microgrid system, composed of RES (Renewable Energy System) and CHP (Combined Heat and Power) systems together with a battery based storage system is presented. The microgrid is accompanied by a centralized energy management system (CEMS) in order to optimize the microgrid operation both in grid-connected and in stand-alone modes. In grid-connected mode the optimization of the economic exploitation of the microgrid is privileged by applying optim...

Point of Maintenance Ruggedized Operational Device Evaluation and Observation Test Report

National Research Council Canada - National Science Library

Gorman, Megan

2002-01-01

.... The Ruggedized Operational Device Evaluation and Observation (RODEO) test examined hardware packaging, software user interface, and environmental factors associated with the usability of potential Point of Maintenance (POMx) electronic tools...

Cooperative scattering of scalar waves by optimized configurations of point scatterers

Science.gov (United States)

Schäfer, Frank; Eckert, Felix; Wellens, Thomas

2017-12-01

We investigate multiple scattering of scalar waves by an ensemble of N resonant point scatterers in three dimensions. For up to N = 21 scatterers, we numerically optimize the positions of the individual scatterers, to maximize the total scattering cross section for an incoming plane wave, on the one hand, and to minimize the decay rate associated to a long-lived scattering resonance, on the other. In both cases, the optimum is achieved by configurations where all scatterers are placed on a line parallel to the direction of the incoming plane wave. The associated maximal scattering cross section increases quadratically with the number of scatterers for large N, whereas the minimal decay rate—which is realized by configurations that are not the same as those that maximize the scattering cross section—decreases exponentially as a function of N. Finally, we also analyze the stability of our optimized configurations with respect to small random displacements of the scatterers. These results demonstrate that optimized configurations of scatterers bear a considerable potential for applications such as quantum memories or mirrors consisting of only a few atoms.

[Numerical simulation and operation optimization of biological filter].

Science.gov (United States)

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.

Optimal, Risk-based Operation and Maintenance Planning for Offshore Wind Turbines

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2008-01-01

For offshore wind turbines costs to operation and maintenance are substantial. This paper describes a risk-based life-cycle approach for optimal planning of operation and maintenance. The approach is based on pre-posterior Bayesian decision theory. Deterioration mechanisms such as fatigue...

Interactive Land-Use Optimization Using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation

Science.gov (United States)

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P.

2017-09-01

In this work, we devise an efficient method for the land-use optimization problem based on Laguerre Voronoi diagram. Previous Voronoi diagram-based methods are more efficient and more suitable for interactive design than discrete optimization-based method, but, in many cases, their outputs do not satisfy area constraints. To cope with the problem, we propose a force-directed graph drawing algorithm, which automatically allocates generating points of Voronoi diagram to appropriate positions. Then, we construct a Laguerre Voronoi diagram based on these generating points, use linear programs to adjust each cell, and reconstruct the diagram based on the adjustment. We adopt the proposed method to the practical case study of Chiang Mai University's allocated land for a mixed-use complex. For this case study, compared to other Voronoi diagram-based method, we decrease the land allocation error by 62.557 %. Although our computation time is larger than the previous Voronoi-diagram-based method, it is still suitable for interactive design.

Genetic Algorithm (GA Method for Optimization of Multi-Reservoir Systems Operation

Directory of Open Access Journals (Sweden)

Shervin Momtahen

2006-01-01

Full Text Available A Genetic Algorithm (GA method for optimization of multi-reservoir systems operation is proposed in this paper. In this method, the parameters of operating policies are optimized using system simulation results. Hence, any operating problem with any sort of objective function, constraints and structure of operating policy can be optimized by GA. The method is applied to a 3-reservoir system and is compared with two traditional methods of Stochastic Dynamic Programming and Dynamic Programming and Regression. The results show that GA is superior both in objective function value and in computational speed. The proposed method is further improved using a mutation power updating rule and a varying period simulation method. The later is a novel procedure proposed in this paper that is believed to help in solving computational time problem in large systems. These revisions are evaluated and proved to be very useful in converging to better solutions in much less time. The final GA method is eventually evaluated as a very efficient procedure that is able to solve problems of large multi-reservoir system which is usually impossible by traditional methods. In fact, the real performance of the GA method starts where others fail to function.

Operational limits of a three level neutral point clamped converter used for controlling a hybrid energy storage system

International Nuclear Information System (INIS)

Etxeberria, A.; Vechiu, I.; Camblong, H.; Kreckelbergh, S.; Bacha, S.

2014-01-01

Highlights: • The control of a hybrid storage system using a Three Level NPC converter is analysed. • A sinusoidal PWM with an offset injection is used to control the storage system. • The operation of the selected converter is analysed in its entire operation range. • The operational limits of the Three Level NPC converter are defined. - Abstract: This work analyses the use of a Three-Level Neutral Point Clamped (3LNPC) converter to control the power flow of a Hybrid Energy Storage System (HESS) and at the same time interconnect it with the common AC bus of a microgrid. Nowadays there is not any storage technology capable of offering a high energy storage capacity, a high power capacity and a fast response at the same time. Therefore, the necessity of hybridising more than one storage technology is a widely accepted idea in order to satisfy the mentioned requirements. This work shows how the operational limits of the 3LNPC converter can be calculated and integrated in a control structure to facilitate an optimal use of the HESS according to the rules fixed by the user

Is the 90th Percentile Adequate? The Optimal Waist Circumference Cutoff Points for Predicting Cardiovascular Risks in 124,643 15-Year-Old Taiwanese Adolescents.

Directory of Open Access Journals (Sweden)

Jason Jiunshiou Lee

Full Text Available Adolescent obesity has increased to alarming proportions globally. However, few studies have investigated the optimal waist circumference (WC of Asian adolescents. This study sought to establish the optimal WC cutoff points that identify a cluster of cardiovascular risk factors (CVRFs among 15-year-old ethnically Chinese adolescents. This study was a regional population-based study on the CVRFs among adolescents who enrolled in all the senior high schools in Taipei City, Taiwan, between 2011 and 2014. Four cross-sectional health examinations of first-year senior high school (grade 10 students were conducted from September to December of each year. A total of 124,643 adolescents aged 15 (boys: 63,654; girls: 60,989 were recruited. Participants who had at least three of five CVRFs were classified as the high-risk group. We used receiver-operating characteristic curves and the area under the curve (AUC to determine the optimal WC cutoff points and the accuracy of WC in predicting high cardiovascular risk. WC was a good predictor for high cardiovascular risk for both boys (AUC: 0.845, 95% confidence interval [CI]: 0.833-0.857 and girls (AUC: 0.763, 95% CI: 0.731-0.795. The optimal WC cutoff points were ≥78.9 cm for boys (77th percentile and ≥70.7 cm for girls (77th percentile. Adolescents with normal weight and an abnormal WC were more likely to be in the high cardiovascular risk group (odds ratio: 3.70, 95% CI: 2.65-5.17 compared to their peers with normal weight and normal WC. The optimal WC cutoff point of 15-year-old Taiwanese adolescents for identifying CVRFs should be the 77th percentile; the 90th percentile of the WC might be inadequate. The high WC criteria can help health professionals identify higher proportion of the adolescents with cardiovascular risks and refer them for further evaluations and interventions. Adolescents' height, weight and WC should be measured as a standard practice in routine health checkups.

Product quality driven design of bakery operations using dynamic optimization

NARCIS (Netherlands)

Hadiyanto, M.; Esveld, D.C.; Boom, R.M.; Straten, van G.; Boxtel, van A.J.B.

2008-01-01

Abstract Quality driven design uses specified product qualities as a starting point for process design. By backward reasoning the required process conditions and processing system were found. In this work dynamic optimization was used as a tool to generate processing solutions for baking processes

An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

Science.gov (United States)

Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

2018-03-01

Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

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.

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

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...

Development of Optimal Stressor Scenarios for New Operational Energy Systems

Science.gov (United States)

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

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)

Optimal Design of Modern Transformerless PV Inverter Topologies

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inverter design variables are derived for each PV inverter topology and installation site. The H5, H6, neutral point...... clamped, active-neutral point clamped and conergy-NPC PV inverters designed using the proposed optimization process feature lower levelized cost of generated electricity and lifetime cost, longer mean time between failures and inject more PV-generated energy into the electric grid than their nonoptimized......The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during...

Improved Full-Newton Step O(nL) Infeasible Interior-Point Method for Linear Optimization

OpenAIRE

Gu, G.; Mansouri, H.; Zangiabadi, M.; Bai, Y.Q.; Roos, C.

2009-01-01

We present several improvements of the full-Newton step infeasible interior-point method for linear optimization introduced by Roos (SIAM J. Optim. 16(4):1110–1136, 2006). Each main step of the method consists of a feasibility step and several centering steps. We use a more natural feasibility step, which targets the ?+-center of the next pair of perturbed problems. As for the centering steps, we apply a sharper quadratic convergence result, which leads to a slightly wider neighborhood for th...

Optimization of dynamic economic dispatch with valve-point effect using chaotic sequence based differential evolution algorithms

International Nuclear Information System (INIS)

He Dakuo; Dong Gang; Wang Fuli; Mao Zhizhong

2011-01-01

A chaotic sequence based differential evolution (DE) approach for solving the dynamic economic dispatch problem (DEDP) with valve-point effect is presented in this paper. The proposed method combines the DE algorithm with the local search technique to improve the performance of the algorithm. DE is the main optimizer, while an approximated model for local search is applied to fine tune in the solution of the DE run. To accelerate convergence of DE, a series of constraints handling rules are adopted. An initial population obtained by using chaotic sequence exerts optimal performance of the proposed algorithm. The combined algorithm is validated for two test systems consisting of 10 and 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other algorithms reported in literatures for DEDP considering valve-point effects.

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.

Optimation of Operation System Integration between Main and Feeder Public Transport (Case Study: Trans Jakarta-Kopaja Bus Services)

Science.gov (United States)

Miharja, M.; Priadi, Y. N.

2018-05-01

Promoting a better public transport is a key strategy to cope with urban transport problems which are mostly caused by a huge private vehicle usage. A better public transport service quality not only focuses on one type of public transport mode, but also concerns on inter modes service integration. Fragmented inter mode public transport service leads to a longer trip chain as well as average travel time which would result in its failure to compete with a private vehicle. This paper examines the optimation process of operation system integration between Trans Jakarta Bus as the main public transport mode and Kopaja Bus as feeder public transport service in Jakarta. Using scoring-interview method combined with standard parameters in operation system integration, this paper identifies the key factors that determine the success of the two public transport operation system integrations. The study found that some key integration parameters, such as the cancellation of “system setoran”, passenger get in-get out at official stop points, and systematic payment, positively contribute to a better service integration. However, some parameters such as fine system, time and changing point reliability, and information system reliability are among those which need improvement. These findings are very useful for the authority to set the right strategy to improve operation system integration between Trans Jakarta and Kopaja Bus services.

Optimization of the NIF ignition point design hohlraum

International Nuclear Information System (INIS)

Callahan, D A; Hinkel, D E; Berger, R L; Divol, L; Dixit, S N; Edwards, M J; Haan, S W; Jones, O S; Lindl, J D; Meezan, N B; Michel, P A; Pollaine, S M; Suter, L J; Town, R P J; Bradley, P A

2008-01-01

In preparation for the start of NIF ignition experiments, we have designed a porfolio of targets that span the temperature range that is consistent with initial NIF operations: 300 eV, 285 eV, and 270 eV. Because these targets are quite complicated, we have developed a plan for choosing the optimum hohlraum for the first ignition attempt that is based on this portfolio of designs coupled with early NIF experiements using 96 beams. These early experiments will measure the laser plasma instabilities of the candidate designs and will demonstrate our ability to tune symmetry in these designs. These experimental results, coupled with the theory and simulations that went into the designs, will allow us to choose the optimal hohlraum for the first NIF ignition attempt

Optimization of the NIF ignition point design hohlraum

Science.gov (United States)

Callahan, D. A.; Hinkel, D. E.; Berger, R. L.; Divol, L.; Dixit, S. N.; Edwards, M. J.; Haan, S. W.; Jones, O. S.; Lindl, J. D.; Meezan, N. B.; Michel, P. A.; Pollaine, S. M.; Suter, L. J.; Town, R. P. J.; Bradley, P. A.

2008-05-01

In preparation for the start of NIF ignition experiments, we have designed a porfolio of targets that span the temperature range that is consistent with initial NIF operations: 300 eV, 285 eV, and 270 eV. Because these targets are quite complicated, we have developed a plan for choosing the optimum hohlraum for the first ignition attempt that is based on this portfolio of designs coupled with early NIF experiements using 96 beams. These early experiments will measure the laser plasma instabilities of the candidate designs and will demonstrate our ability to tune symmetry in these designs. These experimental results, coupled with the theory and simulations that went into the designs, will allow us to choose the optimal hohlraum for the first NIF ignition attempt.

Two-point functions and logarithmic boundary operators in boundary logarithmic conformal field theories

International Nuclear Information System (INIS)

Ishimoto, Yukitaka

2004-01-01

Amongst conformal field theories, there exist logarithmic conformal field theories such as c p,1 models. We have investigated c p,q models with a boundary in search of logarithmic theories and have found logarithmic solutions of two-point functions in the context of the Coulomb gas picture. We have also found the relations between coefficients in the two-point functions and correlation functions of logarithmic boundary operators, and have confirmed the solutions in [hep-th/0003184]. Other two-point functions and boundary operators have also been studied in the free boson construction of boundary CFT with SU(2) k symmetry in regard to logarithmic theories. This paper is based on a part of D. Phil. Thesis [hep-th/0312160]. (author)

Comparison of Optimization and Two-point Methods in Estimation of Soil Water Retention Curve

Science.gov (United States)

Ghanbarian-Alavijeh, B.; Liaghat, A. M.; Huang, G.

2009-04-01

Soil water retention curve (SWRC) is one of the soil hydraulic properties in which its direct measurement is time consuming and expensive. Since, its measurement is unavoidable in study of environmental sciences i.e. investigation of unsaturated hydraulic conductivity and solute transport, in this study the attempt is to predict soil water retention curve from two measured points. By using Cresswell and Paydar (1996) method (two-point method) and an optimization method developed in this study on the basis of two points of SWRC, parameters of Tyler and Wheatcraft (1990) model (fractal dimension and air entry value) were estimated and then water content at different matric potentials were estimated and compared with their measured values (n=180). For each method, we used both 3 and 1500 kPa (case 1) and 33 and 1500 kPa (case 2) as two points of SWRC. The calculated RMSE values showed that in the Creswell and Paydar (1996) method, there exists no significant difference between case 1 and case 2. However, the calculated RMSE value in case 2 (2.35) was slightly less than case 1 (2.37). The results also showed that the developed optimization method in this study had significantly less RMSE values for cases 1 (1.63) and 2 (1.33) rather than Cresswell and Paydar (1996) method.

Energy and operation management of a microgrid using particle swarm optimization

Science.gov (United States)

Radosavljević, Jordan; Jevtić, Miroljub; Klimenta, Dardan

2016-05-01

This article presents an efficient algorithm based on particle swarm optimization (PSO) for energy and operation management (EOM) of a microgrid including different distributed generation units and energy storage devices. The proposed approach employs PSO to minimize the total energy and operating cost of the microgrid via optimal adjustment of the control variables of the EOM, while satisfying various operating constraints. Owing to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties and market prices, a probabilistic approach in the EOM is introduced. The proposed method is examined and tested on a typical grid-connected microgrid including fuel cell, gas-fired microturbine, wind turbine, photovoltaic and energy storage devices. The obtained results prove the efficiency of the proposed approach to solve the EOM of the microgrids.

Optimal power flow for technically feasible Energy Management systems in Islanded Microgrids

DEFF Research Database (Denmark)

Sanseverino, Eleonora Riva; T. T. Quynh, T.; Di Silvestre, Maria Luisa

2016-01-01

This paper presents a combined optimal energy and power flow management for islanded microgrids. The highest control level in this case will provide a feasible and optimized operating point around the economic optimum. In order to account for both unbalanced and balanced loads, the optimal power...... flow is carried out using a Glow-worm Swarm Optimizer. The control level is organized into two different sub-levels, the highest of which accounts for minimum cost operation and the lowest one solving the optimal power flow and devising the set points of inverter interfaced generation units...... and rotating machines with a minimum power loss. A test has been carried out for 6 bus islanded microgrids to show the efficiency and feasibility of the proposed technique....

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

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.

Induction Motors Most Efficient Operation Points in Pumped Storage Systems

DEFF Research Database (Denmark)

Busca-Forcos, Andreea; Marinescu, Corneliu; Busca, Cristian

2015-01-01

A clear focus is nowadays on developing and improving the energy storage technologies. Pumped storage is a well-established one, and is capable of enhancing the integration of renewable energy sources. Pumped storage has an efficiency between 70-80%, and each of its elements affects it. Increased...... efficiency is desired especially when operating with renewable energy systems, which present low energy conversion factor (up to 50% - performance coefficient for wind turbines, and efficiency up to 40% for photovoltaic systems). In this paper the most efficient operation points of the induction motors...... in pumped storage systems are established. The variable speed operation of the pumped storage systems and motor loading conditions for pump applications have been the key factors for achieving the purpose of the paper....

Optimal operation of smart houses by a real-time rolling horizon algorithm

NARCIS (Netherlands)

Paterakis, N.G.; Pappi, I.N.; Catalão, J.P.S.; Erdinc, O.

2016-01-01

In this paper, a novel real-time rolling horizon optimization framework for the optimal operation of a smart household is presented. A home energy management system (HEMS) model based on mixed-integer linear programming (MILP) is developed in order to minimize the energy procurement cost considering

Optimization of the Brillouin operator on the KNL architecture

Science.gov (United States)

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 Operation of Electric Vehicles in Competitive Electricity Markets and Its Impact on Distribution Power Systems

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...

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...

A New Tool for Environmental and Economic Optimization of Hydropower Operations

Science.gov (United States)

Saha, S.; Hayse, J. W.

2012-12-01

As part of a project funded by the U.S. Department of Energy, researchers from Argonne, Oak Ridge, Pacific Northwest, and Sandia National Laboratories collaborated on the development of an integrated toolset to enhance hydropower operational decisions related to economic value and environmental performance. As part of this effort, we developed an analytical approach (Index of River Functionality, IRF) and an associated software tool to evaluate how well discharge regimes achieve ecosystem management goals for hydropower facilities. This approach defines site-specific environmental objectives using relationships between environmental metrics and hydropower-influenced flow characteristics (e.g., discharge or temperature), with consideration given to seasonal timing, duration, and return frequency requirements for the environmental objectives. The IRF approach evaluates the degree to which an operational regime meets each objective and produces a score representing how well that regime meets the overall set of defined objectives. When integrated with other components in the toolset that are used to plan hydropower operations based upon hydrologic forecasts and various constraints on operations, the IRF approach allows an optimal release pattern to be developed based upon tradeoffs between environmental performance and economic value. We tested the toolset prototype to generate a virtual planning operation for a hydropower facility located in the Upper Colorado River basin as a demonstration exercise. We conducted planning as if looking five months into the future using data for the recently concluded 2012 water year. The environmental objectives for this demonstration were related to spawning and nursery habitat for endangered fishes using metrics associated with maintenance of instream habitat and reconnection of the main channel with floodplain wetlands in a representative reach of the river. We also applied existing mandatory operational constraints for the

Generation of uniformly distributed dose points for anatomy-based three-dimensional dose optimization methods in brachytherapy.

Science.gov (United States)

Lahanas, M; Baltas, D; Giannouli, S; Milickovic, N; Zamboglou, N

2000-05-01

We have studied the accuracy of statistical parameters of dose distributions in brachytherapy using actual clinical implants. These include the mean, minimum and maximum dose values and the variance of the dose distribution inside the PTV (planning target volume), and on the surface of the PTV. These properties have been studied as a function of the number of uniformly distributed sampling points. These parameters, or the variants of these parameters, are used directly or indirectly in optimization procedures or for a description of the dose distribution. The accurate determination of these parameters depends on the sampling point distribution from which they have been obtained. Some optimization methods ignore catheters and critical structures surrounded by the PTV or alternatively consider as surface dose points only those on the contour lines of the PTV. D(min) and D(max) are extreme dose values which are either on the PTV surface or within the PTV. They must be avoided for specification and optimization purposes in brachytherapy. Using D(mean) and the variance of D which we have shown to be stable parameters, achieves a more reliable description of the dose distribution on the PTV surface and within the PTV volume than does D(min) and D(max). Generation of dose points on the real surface of the PTV is obligatory and the consideration of catheter volumes results in a realistic description of anatomical dose distributions.

Possible THz gain in superlattices at a stable operation point

DEFF Research Database (Denmark)

Wacker, Andreas; Allen, S. J.; Scott, J. S.

1997-01-01

We demonstrate that semiconductor superlattices may provide gain at THz frequencies at an operation point which is stable against fluctuations at lower frequency. While an explicit experimental demonstration for the sample considered could not be achieved, the underlying principle of quantum resp...... response is quite general and may prove successful for differently designed superlattices....

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)

Successfull operation of biogas plants. Data acquisition as a basis of successful optimization measures; Erfolgreicher Betrieb von Biogasanlagen. Datenerfassung als Grundlage erfolgreicher Optimierungsmassnahmen

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-09-19

Within the 2nd Bayreuth expert meeting on biomass at 6th June, 2012 in Bayreuth (Federal Republic of Germany), the following lectures were held: (1) Presentation of the activities in the bio energy sector of the Landwirtschaftliche Lehranstalt Bayreuth (Rainer Prischenk); (2) State of the art of utilizing biogas in Oberfranken from the view of FVB e.V. (Wolfgang Holland Goetz); (3) Optimization of the plant operation by means of an intelligent control (Christian Seier); (4) Process optimization by means of identification of losses of biogas and evaluation of the load behaviour and emission behaviour of gas engines (Wolfgang Schreier); (5) Data acquisition and implementation of optimization measures from the point of view of an environmental verifier (Thorsten Grantner); (6) Economic analysis and optimization by means of the Lfl program BZA Biogas (Josef Winkler); (7) Detailed data acquisition as a necessary basis of the process optimization (Timo Herfter); (8) Case examples of the biologic support of biogas plants and their correct evaluation (Birgit Pfeifer); (9) A systematic acquisition of operational data as a basis for the increase of efficiency using the Praxisforschungsbiogasanlage of the University Hohenheim (Hans-Joachim Naegele); (10) Practical report: The biogas plant Sochenberg towards 100% utilization of energy (Uli Bader).

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

Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties

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.

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.

Optimal Planning and Operation Management of a Ship Electrical Power System with Energy Storage System

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...

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...

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

Science.gov (United States)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of

Optimized knock-in of point mutations in zebrafish using CRISPR/Cas9.

Science.gov (United States)

Prykhozhij, Sergey V; Fuller, Charlotte; Steele, Shelby L; Veinotte, Chansey J; Razaghi, Babak; Robitaille, Johane M; McMaster, Christopher R; Shlien, Adam; Malkin, David; Berman, Jason N

2018-06-14

We have optimized point mutation knock-ins into zebrafish genomic sites using clustered regularly interspaced palindromic repeats (CRISPR)/Cas9 reagents and single-stranded oligodeoxynucleotides. The efficiency of knock-ins was assessed by a novel application of allele-specific polymerase chain reaction and confirmed by high-throughput sequencing. Anti-sense asymmetric oligo design was found to be the most successful optimization strategy. However, cut site proximity to the mutation and phosphorothioate oligo modifications also greatly improved knock-in efficiency. A previously unrecognized risk of off-target trans knock-ins was identified that we obviated through the development of a workflow for correct knock-in detection. Together these strategies greatly facilitate the study of human genetic diseases in zebrafish, with additional applicability to enhance CRISPR-based approaches in other animal model systems.

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.

Matrix product density operators: Renormalization fixed points and boundary theories

Energy Technology Data Exchange (ETDEWEB)

Cirac, J.I. [Max-Planck-Institut für Quantenoptik, Hans-Kopfermann-Str. 1, D-85748 Garching (Germany); Pérez-García, D., E-mail: dperezga@ucm.es [Departamento de Análisis Matemático, Universidad Complutense de Madrid, Plaza de Ciencias 3, 28040 Madrid (Spain); ICMAT, Nicolas Cabrera, Campus de Cantoblanco, 28049 Madrid (Spain); Schuch, N. [Max-Planck-Institut für Quantenoptik, Hans-Kopfermann-Str. 1, D-85748 Garching (Germany); Verstraete, F. [Department of Physics and Astronomy, Ghent University (Belgium); Vienna Center for Quantum Technology, University of Vienna (Austria)

2017-03-15

We consider the tensors generating matrix product states and density operators in a spin chain. For pure states, we revise the renormalization procedure introduced in (Verstraete et al., 2005) and characterize the tensors corresponding to the fixed points. We relate them to the states possessing zero correlation length, saturation of the area law, as well as to those which generate ground states of local and commuting Hamiltonians. For mixed states, we introduce the concept of renormalization fixed points and characterize the corresponding tensors. We also relate them to concepts like finite correlation length, saturation of the area law, as well as to those which generate Gibbs states of local and commuting Hamiltonians. One of the main result of this work is that the resulting fixed points can be associated to the boundary theories of two-dimensional topological states, through the bulk-boundary correspondence introduced in (Cirac et al., 2011).

An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators

Directory of Open Access Journals (Sweden)

Jiuyuan Huo

2017-02-01

Full Text Available To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC inspired by the intelligent foraging behavior of honey bees was proposed in this paper. The proposed algorithm utilizes the Pareto dominance theory and takes advantage of adaptive grid and regulation operator mechanisms. The adaptive grid technique is used to adaptively assess the Pareto front maintained in an external archive and the regulation operator is used to balance the weights of the local search and the global search in the evolution of the algorithm. The performance of RMOABC was evaluated in comparison with other nature inspired algorithms includes NSGA-II and MOEA/D. The experiments results demonstrated that the RMOABC approach has better accuracy and minimal execution time.

Research on Cascade Reservoirs’ Short-Term Optimal Operation under the Effect of Reverse Regulation

Directory of Open Access Journals (Sweden)

Changming Ji

2018-06-01

Full Text Available Currently research on joint operation of a large reservoir and its re-regulating reservoir focuses on either water quantity regulation or water head regulation. The accuracy of relevant models is in need of improvement if the influence of factors such as water flow hysteresis and the aftereffect of tail water level variation are taken into consideration. In this paper, given the actual production of Pankou-Xiaoxuan cascade hydropower stations that combines two operation modes (‘electricity to water’ and ‘water to electricity’, a coupling model of their short-term optimal operation is developed, which considers Xiaoxuan reservoir’s regulating effect on Pankou reservoir’s outflow volume and water head. Factors such as water flow hysteresis and the aftereffect of tail water level variation are also considered to enhance the model’s accuracy. The Backward Propagation (BP neural network is employed for precise calculation of the downstream reservoir’s inflow and the upstream reservoir’s tail water level. Besides, we put forth Accompanying Progressive Optimality Algorithm (APOA to solve the coupling model with aftereffect. An example is given to verify the scientificity of the proposed model and the advantages of APOA. Through analysis of the model calculation results, the optimal operation rules of the cascade reservoirs are obtained in terms of water quantity regulation and water head regulation, which can provide scientific reference for cascade reservoirs’ optimal operation.

Integrated Emission Management strategy for cost-optimal engine-aftertreatment operation

NARCIS (Netherlands)

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

Numerical study of a novel dew point evaporative cooling system

Energy Technology Data Exchange (ETDEWEB)

Riangvilaikul, B.; Kumar, S. [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120 (Thailand)

2010-11-15

Dew point evaporative cooling system is an alternative to vapor compression air conditioning system for sensible cooling of ventilation air. This paper presents the theoretical performance of a novel dew point evaporative cooling system operating under various inlet air conditions (covering dry, moderate and humid climate) and influence of major operating parameters (namely, velocity, system dimension and the ratio of working air to intake air). A model of the dew point evaporative cooling system has been developed to simulate the heat and mass transfer processes. The outlet air conditions and system effectiveness predicted by the model using numerical method for known inlet parameters have been validated with experimental findings and with recent literature. The model was used to optimize the system parameters and to investigate the system effectiveness operating under various inlet air conditions. (author)

76 FR 65118 - Drawbridge Operation Regulation; Bear Creek, Sparrows Point, MD

Science.gov (United States)

2011-10-20

...-AA09 Drawbridge Operation Regulation; Bear Creek, Sparrows Point, MD AGENCY: Coast Guard, DHS. ACTION... regulation. The Baltimore County Revenue Authority (Dundalk Avenue) highway toll drawbridge across Bear Creek... applicable or necessary. Basis and Purpose The drawbridge across Bear Creek, mile 1.5 was removed and...

Model-based optimization strategy of chiller driven liquid desiccant dehumidifier with genetic algorithm

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

WE-B-304-00: Point/Counterpoint: Biological Dose Optimization

International Nuclear Information System (INIS)

2015-01-01

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning by the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations

Maximum Power Point Tracking for Brushless DC Motor-Driven Photovoltaic Pumping Systems Using a Hybrid ANFIS-FLOWER Pollination Optimization Algorithm

Directory of Open Access Journals (Sweden)

Neeraj Priyadarshi

2018-04-01

Full Text Available In this research paper, a hybrid Artificial Neural Network (ANN-Fuzzy Logic Control (FLC tuned Flower Pollination Algorithm (FPA as a Maximum Power Point Tracker (MPPT is employed to amend root mean square error (RMSE of photovoltaic (PV modeling. Moreover, Gaussian membership functions have been considered for fuzzy controller design. This paper interprets the Luo converter occupied brushless DC motor (BLDC-directed PV water pump application. Experimental responses certify the effectiveness of the suggested motor-pump system supporting diverse operating states. The Luo converter, a newly developed DC-DC converter, has high power density, better voltage gain transfer and superior output waveform and can track optimal power from PV modules. For BLDC speed control there is no extra circuitry, and phase current sensors are enforced for this scheme. The most recent attempt using adaptive neuro-fuzzy inference system (ANFIS-FPA-operated BLDC directed PV pump with advanced Luo converter, has not been formerly conferred.

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.

The application of optimization of protection to regulation and operational practice

International Nuclear Information System (INIS)

Ilari, O.

1989-01-01

Optimization of protection and the problems of its practical application have been of concern for several years to the NEA Committee on Radiation Protection and Public Health. The present paper summarizes the principal conclusions of a meeting on this topic organized by the NEA in March 1988, with the participation of radiation protection, nuclear safety and radioactive waste management experts. From the results of the meeting it appears that there is now as increasingly solid background of knowledge and common understanding of the conceptual aspects of optimization of protection. However, its degree of implementation in the regulatory and operational practices is very uneven. The areas of plant design and operation appear the most promising in terms of examples of concrete application, whilst severe reservations exist in the nuclear safety community on the possibility of applying this approach to the prevention of nuclear accidents. There is also consensus on the fact that optimization of protection can only play a partial and minor role in decisions concerning the choice of radioactive waste disposal options

An Effective, Robust And Parallel Implementation Of An Interior Point Algorithm For Limit State Optimization

DEFF Research Database (Denmark)

Dollerup, Niels; Jepsen, Michael S.; Damkilde, Lars

2013-01-01

The artide describes a robust and effective implementation of the interior point optimization algorithm. The adopted method includes a precalculation step, which reduces the number of variables by fulfilling the equilibrium equations a priori. This work presents an improved implementation of the ...

SUMMARY AND EVALUATION OF STARTUP AND OPERATING EXPERIENCE AT INDIAN POINT STATION

Energy Technology Data Exchange (ETDEWEB)

Freyberg, R. H.; Prestele, J. A.

1963-09-15

A description of the Indian Point Power Station is given aiong with a summary and evaluation of startup and operating experience. Equipment failures and problems and various corrective measures are also outlined. (C.E.S.)

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

Science.gov (United States)

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of

Optimization of conventional rule curves coupled with hedging rules for reservoir operation

DEFF Research Database (Denmark)

Taghian, Mehrdad; Rosbjerg, Dan; Haghighi, Ali

2014-01-01

As a common approach to reservoir operating policies, water levels at the end of each time interval should be kept at or above the rule curve. In this study, the policy is captured using rationing of the target yield to reduce the intensity of severe water shortages. For this purpose, a hybrid...... to achieve the optimal water allocation and the target storage levels for reservoirs. As a case study, a multipurpose, multireservoir system in southern Iran is selected. The results show that the model has good performance in extracting the optimum policy for reservoir operation under both normal...... model is developed to optimize simultaneously both the conventional rule curve and the hedging rule. In the compound model, a simple genetic algorithm is coupled with a simulation program, including an inner linear programming algorithm. In this way, operational policies are imposed by priority concepts...

47 CFR 90.473 - Operation of internal transmitter control systems through licensed fixed control points.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Operation of internal transmitter control... Transmitter Control Internal Transmitter Control Systems § 90.473 Operation of internal transmitter control systems through licensed fixed control points. An internal transmitter control system may be operated...

Estimation of the laser cutting operating cost by support vector regression methodology

Science.gov (United States)

Jović, Srđan; Radović, Aleksandar; Šarkoćević, Živče; Petković, Dalibor; Alizamir, Meysam

2016-09-01

Laser cutting is a popular manufacturing process utilized to cut various types of materials economically. The operating cost is affected by laser power, cutting speed, assist gas pressure, nozzle diameter and focus point position as well as the workpiece material. In this article, the process factors investigated were: laser power, cutting speed, air pressure and focal point position. The aim of this work is to relate the operating cost to the process parameters mentioned above. CO2 laser cutting of stainless steel of medical grade AISI316L has been investigated. The main goal was to analyze the operating cost through the laser power, cutting speed, air pressure, focal point position and material thickness. Since the laser operating cost is a complex, non-linear task, soft computing optimization algorithms can be used. Intelligent soft computing scheme support vector regression (SVR) was implemented. The performance of the proposed estimator was confirmed with the simulation results. The SVR results are then compared with artificial neural network and genetic programing. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR compared to other soft computing methodologies. The new optimization methods benefit from the soft computing capabilities of global optimization and multiobjective optimization rather than choosing a starting point by trial and error and combining multiple criteria into a single criterion.

Computer-assisted three-dimensional correlation between the femoral neck-shaft angle and the optimal entry point for antegrade nailing.

Science.gov (United States)

Anastopoulos, George; Chissas, Dionisios; Dourountakis, Joseph; Ntagiopoulos, Panagiotis G; Magnisalis, Evaggelos; Asimakopoulos, Antonios; Xenakis, Theodore A

2010-03-01

Optimal entry point for antegrade femoral intramedullary nailing (IMN) remains controversial in the current medical literature. The definition of an ideal entry point for femoral IMN would implicate a tenseless introduction of the implant into the canal with anatomical alignment of the bone fragments. This study was undertaken in order to investigate possible existing relationships between the true 3D geometric parameters of the femur and the location of the optimum entry point. A sample population of 22 cadaveric femurs was used (mean age=51.09+/-14.82 years). Computed-tomography sections every 0.5mm for the entire length of femurs were produced. These sections were subsequently reconstructed to generate solid computer models of the external anatomy and medullary canal of each femur. Solid models of all femurs were subjected to a series of geometrical manipulations and computations using standard computer-aided-design tools. In the sagittal plane, the optimum entry point always lied a few millimeters behind the femoral neck axis (mean=3.5+/-1.5mm). In the coronal plane the optimum entry point lied at a location dependent on the femoral neck-shaft angle. Linear regression on the data showed that the optimal entry point is clearly correlated to the true 3D femoral neck-shaft angle (R(2)=0.7310) and the projected femoral neck-shaft angle (R(2)=0.6289). Anatomical parameters of the proximal femur, such as the varus-valgus angulation, are key factors in the determination of optimal entry point for nailing. The clinical relevance of the results is that in varus hips (neck-shaft angle shaft angle between 120 degrees and 130 degrees , the optimal entry point lies just medially to the trochanter tip (at the piriformis fossa) and the use of stiff implants is safe. In hips with neck-shaft angle over 130 degrees the anatomical axis of the canal is medially to the base of the neck, in a "restricted area". In these cases the entry point should be located at the insertion of the

Investigation of point triangulation methods for optimality and performance in Structure from Motion systems

DEFF Research Database (Denmark)

Structure from Motion (SFM) systems are composed of cameras and structure in the form of 3D points and other features. It is most often that the structure components outnumber the cameras by a great margin. It is not uncommon to have a configuration with 3 cameras observing more than 500 3D points...... an overview of existing triangulation methods with emphasis on performance versus optimality, and will suggest a fast triangulation algorithm based on linear constraints. The structure and camera motion estimation in a SFM system is based on the minimization of some norm of the reprojection error between...

An effective, robust and parallel implementation of an interior point algorithm for limit state optimization

DEFF Research Database (Denmark)

Dollerup, Niels; Jepsen, Michael S.; Frier, Christian

2014-01-01

A robust and effective finite element based implementation of lower bound limit state analysis applying an interior point formulation is presented in this paper. The lower bound formulation results in a convex optimization problem consisting of a number of linear constraints from the equilibrium...

3D shape optimization of fan vanes for multiple operating regimes subject to efficiency and noise-related excellence criteria and constraints

Directory of Open Access Journals (Sweden)

Ivo Marinić-Kragić

2016-01-01

Full Text Available Fully generic 3D shapes of centrifugal roof fan vanes are explored based on a custom-developed numerical workflow with the ability to vary the vane 3D shape by manipulating the control points of parametric surfaces and change the number of vanes and rotation speed. An excellence formulation is based on design flow efficiency, multi-regime operational conditions and noise criteria for various cases, including multi-objective optimization. Multiple cases of optimization demonstrate the suitability of customized and individualized fan designs for specific working environments according to the selected excellence criteria. Noise analysis is considered as an additional decision-making tool for cases where multiple solutions of equal efficiency are generated and as an additional criteria for multi-objective optimization. The 3D vane shape enables further gains in efficiency compared to 2D shape optimization, while multi-objective optimization with noise as an additional criterion shows potential to greatly reduce the roof fan noise with only small losses in efficiency. The developed workflow which comprises (i a 3D parametric shape modeler, (ii an evolutionary optimizer and (iii a computational fluid dynamics (CFD simulator can be viewed as an integral tool for optimizing the designs of roof fans under custom conditions.

Optimization of costs of Port Operations in Nigeria: A Scenario For ...

African Journals Online (AJOL)

2013-03-01

Mar 1, 2013 ... +Department of Maritime Management Technology,. Federal ... Abstract. This study attempts to optimize the cost of port operations in Nigeria. ..... Slack. Original Value. Lower. Bound. Upper Bound. Const. 1. 0. 685.7727. 672.

Feedback dew-point sensor utilizing optimally cut plastic optical fibres

Science.gov (United States)

Hadjiloucas, S.; Irvine, J.; Keating, D. A.

2000-01-01

A plastic optical fibre reflectance sensor that makes full use of the critical angle of the fibres is implemented to monitor dew formation on a Peltier-cooled reflector surface. The optical configuration permits isolation of optoelectronic components from the sensing head and better light coupling between the reflector and the detecting fibre, giving a better signal of the onset of dew formation on the reflector. Continuous monitoring of the rate of change in reflectance as well as the absolute reflectance signals, the use of a novel polymethyl-methacrylate-coated hydrophobic film reflector on the Peltier element and the application of feedback around the point of dew formation, further reduces the possibility of contamination of the sensor head. Under closed-loop operation, the sensor is capable of cycling around the point of dew formation at a frequency of 2.5 Hz.

ATP-gamma-S shifts the operating point of outer hair cell transduction towards scala tympani.

Science.gov (United States)

Bobbin, Richard P; Salt, Alec N

2005-07-01

ATP receptor agonists and antagonists alter cochlear mechanics as measured by changes in distortion product otoacoustic emissions (DPOAE). Some of the effects on DPOAEs are consistent with the hypothesis that ATP affects mechano-electrical transduction and the operating point of the outer hair cells (OHCs). This hypothesis was tested by monitoring the effect of ATP-gamma-S on the operating point of the OHCs. Guinea pigs anesthetized with urethane and with sectioned middle ear muscles were used. The cochlear microphonic (CM) was recorded differentially (scala vestibuli referenced to scala tympani) across the basal turn before and after perfusion (20 min) of the perilymph compartment with artificial perilymph (AP) and ATP-gamma-S dissolved in AP. The operating point was derived from the cochlear microphonics (CM) recorded in response low frequency (200 Hz) tones at high level (106, 112 and 118 dB SPL). The analysis procedure used a Boltzmann function to simulate the CM waveform and the Boltzmann parameters were adjusted to best-fit the calculated waveform to the CM. Compared to the initial perfusion with AP, ATP-gamma-S (333 microM) enhanced peak clipping of the positive peak of the CM (that occurs during organ of Corti displacements towards scala tympani), which was in keeping with ATP-induced displacement of the transducer towards scala tympani. CM waveform analysis quantified the degree of displacement and showed that the changes were consistent with the stimulus being centered on a different region of the transducer curve. The change of operating point meant that the stimulus was applied to a region of the transducer curve where there was greater saturation of the output on excursions towards scala tympani and less saturation towards scala vestibuli. A significant degree of recovery of the operating point was observed after washing with AP. Dose response curves generated by perfusing ATP-gamma-S (333 microM) in a cumulative manner yielded an EC(50) of 19.8 micro

Optimal Operation and Dispatch of Voltage Regulation Devices Considering High Penetrations of Distributed Photovoltaic Generation

Energy Technology Data Exchange (ETDEWEB)

Mather, Barry A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cho, Gyu-Jung [Sungkyunkwan University; Oh, Yun-Sik [Sungkyunkwan University; Kim, Min-Sung [Sungkyunkwan University; Kim, Ji-Soo [Sungkyunkwan University; Kim, Chul-Hwan [Sungkyunkwan University

2017-06-29

Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation of the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.

Scenario based optimization of a container vessel with respect to its projected operating conditions

Science.gov (United States)

Wagner, Jonas; Binkowski, Eva; Bronsart, Robert

2014-06-01

In this paper the scenario based optimization of the bulbous bow of the KRISO Container Ship (KCS) is presented. The optimization of the parametrically modeled vessel is based on a statistically developed operational profile generated from noon-to-noon reports of a comparable 3600 TEU container vessel and specific development functions representing the growth of global economy during the vessels service time. In order to consider uncertainties, statistical fluctuations are added. An analysis of these data lead to a number of most probable upcoming operating conditions (OC) the vessel will stay in the future. According to their respective likeliness an objective function for the evaluation of the optimal design variant of the vessel is derived and implemented within the parametrical optimization workbench FRIENDSHIP Framework. In the following this evaluation is done with respect to vessel's calculated effective power based on the usage of potential flow code. The evaluation shows, that the usage of scenarios within the optimization process has a strong influence on the hull form.

Modeling Optimal Scheduling for Pumping System to Minimize Operation Cost and Enhance Operation Reliability

Directory of Open Access Journals (Sweden)

Yin Luo

2012-01-01

Full Text Available Traditional pump scheduling models neglect the operation reliability which directly relates with the unscheduled maintenance cost and the wear cost during the operation. Just for this, based on the assumption that the vibration directly relates with the operation reliability and the degree of wear, it could express the operation reliability as the normalization of the vibration level. The characteristic of the vibration with the operation point was studied, it could be concluded that idealized flow versus vibration plot should be a distinct bathtub shape. There is a narrow sweet spot (80 to 100 percent BEP to obtain low vibration levels in this shape, and the vibration also follows similar law with the square of the rotation speed without resonance phenomena. Then, the operation reliability could be modeled as the function of the capacity and rotation speed of the pump and add this function to the traditional model to form the new. And contrast with the tradition method, the result shown that the new model could fix the result produced by the traditional, make the pump operate in low vibration, then the operation reliability could increase and the maintenance cost could decrease.

Simulation and OR (operations research) in combination for practical optimization

NARCIS (Netherlands)

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 of fuel-cell tram operation based on two dimension dynamic programming

Science.gov (United States)

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.

Energy Hub’s Structural and Operational Optimization for Minimal Energy Usage Costs in Energy Systems

Directory of Open Access Journals (Sweden)

Thanh Tung Ha

2018-03-01

Full Text Available The structural and optimal operation of an Energy Hub (EH has a tremendous influence on the hub’s performance and reliability. This paper envisions an innovative methodology that prominently increases the synergy between structural and operational optimization and targets system cost affordability. The generalized energy system structure is presented theoretically with all selective hub sub-modules, including electric heater (EHe and solar sources block sub-modules. To minimize energy usage cost, an energy hub is proposed that consists of 12 kinds of elements (i.e., energy resources, conversion, and storage functions and is modeled mathematically in a General Algebraic Modeling System (GAMS, which indicates the optimal hub structure’s corresponding elements with binary variables (0, 1. Simulation results contrast with 144 various scenarios established in all 144 categories of hub structures, in which for each scenario the corresponding optimal operation cost is previously calculated. These case studies demonstrate the effectiveness of the suggested model and methodology. Finally, avenues for future research are also prospected.

Optimal dimensioning of low-energy district heating networks with operational planning

DEFF Research Database (Denmark)

Tol, Hakan; Svendsen, Svend

2012-01-01

in design stage resulted in satisfaction of heat demand of the house in low temperature operation. In this paper the operational planning of the low-energy DH systems was investigated to reduce the dimensions of the distribution network with consideration given both to current high-heat and future low......-heat demand situations. The operational planning was based on boosting (increasing) the supply temperature at peak-demand situations which occur rarely over a year period. Hence optimal pipe dimensions of low-energy DH systems were investigated based on the dynamic response of in-house heating systems...... of operational planning in comparison to DH network dimensioned according to high heat demand situation....

Simplified model-based optimal control of VAV air-conditioning system

Energy Technology Data Exchange (ETDEWEB)

Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal, PQ (Canada). Dept. of Construction Engineering

2005-07-01

The improvement of Variable Air Volume (VAV) system performance is one of several attempts being made to minimize the high energy use associated with the operation of heating, ventilation and air conditioning (HVAC) systems. A Simplified Optimization Process (SOP) comprised of controller set point strategies and a simplified VAV model was presented in this paper. The aim of the SOP was to determine supply set points. The advantage of the SOP over previous methods was that it did not require a detailed VAV model and optimization program. In addition, the monitored data for representative local-loop control can be checked on-line, after which controller set points can be updated in order to ensure proper operation by opting for real situations with minimum energy use. The SOP was validated using existing monitoring data and a model of an existing VAV system. Energy use simulations were compared to that of the existing VAV system. At each simulation step, 3 controller set point values were proposed and studied using the VAV model in order to select a value for each point which corresponded to the best performance of the VAV system. Simplified VAV component models were presented. Strategies for controller set points were described, including zone air temperature, duct static pressure set points; chilled water supply set points and supply air temperature set points. Simplified optimization process calculations were presented. Results indicated that the SOP provided significant energy savings when applied to specific AHU systems. In a comparison with a Detailed Optimization Process (DOP), the SOP was capable of determining set points close to those obtained by the DOP. However, it was noted that the controller set points determined by the SOP need a certain amount of time to reach optimal values when outdoor conditions or thermal loads are significantly changed. It was suggested that this disadvantage could be overcome by the use of a dynamic incremental value, which

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.

Common fixed points in best approximation for Banach operator pairs with Ciric type I-contractions

Science.gov (United States)

Hussain, N.

2008-02-01

The common fixed point theorems, similar to those of Ciric [Lj.B. Ciric, On a common fixed point theorem of a Gregus type, Publ. Inst. Math. (Beograd) (N.S.) 49 (1991) 174-178; Lj.B. Ciric, On Diviccaro, Fisher and Sessa open questions, Arch. Math. (Brno) 29 (1993) 145-152; Lj.B. Ciric, On a generalization of Gregus fixed point theorem, Czechoslovak Math. J. 50 (2000) 449-458], Fisher and Sessa [B. Fisher, S. Sessa, On a fixed point theorem of Gregus, Internat. J. Math. Math. Sci. 9 (1986) 23-28], Jungck [G. Jungck, On a fixed point theorem of Fisher and Sessa, Internat. J. Math. Math. Sci. 13 (1990) 497-500] and Mukherjee and Verma [R.N. Mukherjee, V. Verma, A note on fixed point theorem of Gregus, Math. Japon. 33 (1988) 745-749], are proved for a Banach operator pair. As applications, common fixed point and approximation results for Banach operator pair satisfying Ciric type contractive conditions are obtained without the assumption of linearity or affinity of either T or I. Our results unify and generalize various known results to a more general class of noncommuting mappings.

The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization.

Science.gov (United States)

Błażej, Paweł; Wnȩtrzak, Małgorzata; Mackiewicz, Paweł

2016-12-01

One of theories explaining the present structure of canonical genetic code assumes that it was optimized to minimize harmful effects of amino acid replacements resulting from nucleotide substitutions and translational errors. A way to testify this concept is to find the optimal code under given criteria and compare it with the canonical genetic code. Unfortunately, the huge number of possible alternatives makes it impossible to find the optimal code using exhaustive methods in sensible time. Therefore, heuristic methods should be applied to search the space of possible solutions. Evolutionary algorithms (EA) seem to be ones of such promising approaches. This class of methods is founded both on mutation and crossover operators, which are responsible for creating and maintaining the diversity of candidate solutions. These operators possess dissimilar characteristics and consequently play different roles in the process of finding the best solutions under given criteria. Therefore, the effective searching for the potential solutions can be improved by applying both of them, especially when these operators are devised specifically for a given problem. To study this subject, we analyze the effectiveness of algorithms for various combinations of mutation and crossover probabilities under three models of the genetic code assuming different restrictions on its structure. To achieve that, we adapt the position based crossover operator for the most restricted model and develop a new type of crossover operator for the more general models. The applied fitness function describes costs of amino acid replacement regarding their polarity. Our results indicate that the usage of crossover operators can significantly improve the quality of the solutions. Moreover, the simulations with the crossover operator optimize the fitness function in the smaller number of generations than simulations without this operator. The optimal genetic codes without restrictions on their structure

How does network design constrain optimal operation of intermittent water supply?

Science.gov (United States)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2015-11-01

Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.

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.

Optimal operation of water distribution networks by predictive control ...

African Journals Online (AJOL)

This paper presents an approach for the operational optimisation of potable water distribution networks. The maximisation of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objectives. The first objective ...

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

78 FR 44881 - Drawbridge Operation Regulation; York River, Between Yorktown and Gloucester Point, VA

Science.gov (United States)

2013-07-25

... deviation from the operating schedule that governs the operation of the Coleman Memorial Bridge (US 17/George P. Coleman Memorial Swing Bridge) across the York River, mile 7.0, between Gloucester Point and Yorktown, VA. This deviation is necessary to facilitate maintenance work on the moveable spans on the...

Factors influencing the profitability of optimizing control systems

International Nuclear Information System (INIS)

Broussaud, A.; Guyot, O.

1999-01-01

Optimizing control systems supplement conventional Distributed Control Systems and Programmable Logic Controllers. They continuously implement set points, which aim at maximizing the profitability of plant operation. They are becoming an integral part of modern mineral processing plants. This trend is justified by economic considerations, optimizing control being among the most cost-effective methods of improving metallurgical plant performance. The paper successively analyzes three sets of factors, which influence the profitability of optimizing control systems, and provides guidelines for analyzing the potential value of an optimizing control system at a given operation: external factors, such as economic factors and factors related to plant feed; features of the optimizing control system; and subsequent maintenance of the optimizing control system. It is shown that pay back times for optimization control projects are typically measured in days. The OCS software used by the authors for their applications is described briefly. (author)

Application of ELD and load forecast in optimal operation of industrial boiler plants equipped with thermal stores

International Nuclear Information System (INIS)

Cao Jiacong

2007-01-01

Optimal operation of industrial boiler plants with objects of high energy efficiency and low fuel cost is still well worth investigating when energy problem becomes a world's concern, for there are a great number of boiler plants serving industries. The optimization of operation is a measure that is less expensive and easier to carry out than many other measures. Economic load dispatch (ELD) is an effective approach to optimal operation of industrial boiler plants. In the paper a newly developed method referred to as the method of minimum-departure model (MDM) is used in the ELD for boiler plants. It is more convenient for carrying out ELD when boiler plants are equipped with thermal energy stores that usually adopt the working mode of optimal segmentation of a daily load curve. In the case of industrial boiler plants, ELD needs a prerequisite, viz., the accurate load forecast, which is performed using artificial neural networks in this paper. A computer program for the optimal operation was completed and applied to an example, which results the minimum daily fuel cost of the whole boiler plant

Research on crude oil storage and transportation based on optimization algorithm

Science.gov (United States)

Yuan, Xuhua

2018-04-01

At present, the optimization theory and method have been widely used in the optimization scheduling and optimal operation scheme of complex production systems. Based on C++Builder 6 program development platform, the theoretical research results are implemented by computer. The simulation and intelligent decision system of crude oil storage and transportation inventory scheduling are designed. The system includes modules of project management, data management, graphics processing, simulation of oil depot operation scheme. It can realize the optimization of the scheduling scheme of crude oil storage and transportation system. A multi-point temperature measuring system for monitoring the temperature field of floating roof oil storage tank is developed. The results show that by optimizing operating parameters such as tank operating mode and temperature, the total transportation scheduling costs of the storage and transportation system can be reduced by 9.1%. Therefore, this method can realize safe and stable operation of crude oil storage and transportation system.

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.

Minimization of the LCA impact of thermodynamic cycles using a combined simulation-optimization approach

Energy Technology Data Exchange (ETDEWEB)

Brunet, Robert; Cortes, Daniel [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Guillen-Gosalbez, Gonzalo [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Jimenez, Laureano [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Boer, Dieter [Departament d' Enginyeria Mecanica, Escola Tecnica Superior d' Enginyeria, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona (Spain)

2012-12-15

This work presents a computational approach for the simultaneous minimization of the total cost and environmental impact of thermodynamic cycles. Our method combines process simulation, multi-objective optimization and life cycle assessment (LCA) within a unified framework that identifies in a systematic manner optimal design and operating conditions according to several economic and LCA impacts. Our approach takes advantages of the complementary strengths of process simulation (in which mass, energy balances and thermodynamic calculations are implemented in an easy manner) and rigorous deterministic optimization tools. We demonstrate the capabilities of this strategy by means of two case studies in which we address the design of a 10 MW Rankine cycle modeled in Aspen Hysys, and a 90 kW ammonia-water absorption cooling cycle implemented in Aspen Plus. Numerical results show that it is possible to achieve environmental and cost savings using our rigorous approach. - Highlights: Black-Right-Pointing-Pointer Novel framework for the optimal design of thermdoynamic cycles. Black-Right-Pointing-Pointer Combined use of simulation and optimization tools. Black-Right-Pointing-Pointer Optimal design and operating conditions according to several economic and LCA impacts. Black-Right-Pointing-Pointer Design of a 10MW Rankine cycle in Aspen Hysys, and a 90kW absorption cycle in Aspen Plus.

Solving optimum operation of single pump unit problem with ant colony optimization (ACO) algorithm

International Nuclear Information System (INIS)

Yuan, Y; Liu, C

2012-01-01

For pumping stations, the effective scheduling of daily pump operations from solutions to the optimum design operation problem is one of the greatest potential areas for energy cost-savings, there are some difficulties in solving this problem with traditional optimization methods due to the multimodality of the solution region. In this case, an ACO model for optimum operation of pumping unit is proposed and the solution method by ants searching is presented by rationally setting the object function and constrained conditions. A weighted directed graph was constructed and feasible solutions may be found by iteratively searching of artificial ants, and then the optimal solution can be obtained by applying the rule of state transition and the pheromone updating. An example calculation was conducted and the minimum cost was found as 4.9979. The result of ant colony algorithm was compared with the result from dynamic programming or evolutionary solving method in commercial software under the same discrete condition. The result of ACO is better and the computing time is shorter which indicates that ACO algorithm can provide a high application value to the field of optimal operation of pumping stations and related fields.

Scenario based optimization of a container vessel with respect to its projected operating conditions

Directory of Open Access Journals (Sweden)

Wagner Jonas

2014-06-01

Full Text Available In this paper the scenario based optimization of the bulbous bow of the KRISO Container Ship (KCS is presented. The optimization of the parametrically modeled vessel is based on a statistically developed operational profile generated from noon-to-noon reports of a comparable 3600 TEU container vessel and specific development functions representing the growth of global economy during the vessels service time. In order to consider uncertainties, statistical fluctuations are added. An analysis of these data lead to a number of most probable upcoming operating conditions (OC the vessel will stay in the future. According to their respective likeliness an objective function for the evaluation of the optimal design variant of the vessel is derived and implemented within the parametrical optimization workbench FRIENDSHIP Framework. In the following this evaluation is done with respect to vessel’s calculated effective power based on the usage of potential flow code. The evaluation shows, that the usage of scenarios within the optimization process has a strong influence on the hull form.

Scenario based optimization of a container vessel with respect to its projected operating conditions

Directory of Open Access Journals (Sweden)

Jonas Wagner

2014-06-01

Full Text Available In this paper the scenario based optimization of the bulbous bow of the KRISO Container Ship (KCS is presented. The optimization of the parametrically modeled vessel is based on a statistically developed operational profile generated from noon-to-noon reports of a comparable 3600 TEU container vessel and specific development functions representing the growth of global economy during the vessels service time. In order to consider uncertainties, statistical fluctuations are added. An analysis of these data lead to a number of most probable upcoming operating conditions (OC the vessel will stay in the future. According to their respective likeliness an objective function for the evaluation of the optimal design variant of the vessel is derived and implemented within the parametrical optimization workbench FRIENDSHIP Framework. In the following this evaluation is done with respect to vessel's calculated effective power based on the usage of potential flow code. The evaluation shows, that the usage of scenarios within the optimization process has a strong influence on the hull form.

Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

Science.gov (United States)

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

Sensitivities and Tipping Points of Power System Operations to Fluctuations Caused by Water Availability and Fuel Prices

Science.gov (United States)

O'Connell, M.; Macknick, J.; Voisin, N.; Fu, T.

2017-12-01

The western US electric grid is highly dependent upon water resources for reliable operation. Hydropower and water-cooled thermoelectric technologies represent 67% of generating capacity in the western region of the US. While water resources provide a significant amount of generation and reliability for the grid, these same resources can represent vulnerabilities during times of drought or low flow conditions. A lack of water affects water-dependent technologies and can result in more expensive generators needing to run in order to meet electric grid demand, resulting in higher electricity prices and a higher cost to operate the grid. A companion study assesses the impact of changes in water availability and air temperatures on power operations by directly derating hydro and thermo-electric generators. In this study we assess the sensitivities and tipping points of water availability compared with higher fuel prices in electricity sector operations. We evaluate the impacts of varying electricity prices by modifying fuel prices for coal and natural gas. We then analyze the difference in simulation results between changes in fuel prices in combination with water availability and air temperature variability. We simulate three fuel price scenarios for a 2010 baseline scenario along with 100 historical and future hydro-climate conditions. We use the PLEXOS electricity production cost model to optimize power system dispatch and cost decisions under each combination of fuel price and water constraint. Some of the metrics evaluated are total production cost, generation type mix, emissions, transmission congestion, and reserve procurement. These metrics give insight to how strained the system is, how much flexibility it still has, and to what extent water resource availability or fuel prices drive changes in the electricity sector operations. This work will provide insights into current electricity operations as well as future cases of increased penetration of variable

Optimal year-round operation of a concentrated solar energy plant in the south of Europe

International Nuclear Information System (INIS)

Martín, Lidia; Martín, Mariano

2013-01-01

We present the year-round optimization of the operation of a concentrated solar power facility evaluating the molten salts storage, the power block and cooling. We locate the plant in the south of Europe, Almería (Spain), where high solar radiation is available. The operation of the plant is a function of the solar incidence as well as the climate and atmospheric conditions. The optimization of the system is formulated as a multiperiod Non-linear Programming problem (NLP) that is solved for the optimal production of electricity over a year defining the main operating variables of the thermal and cooling cycles. For a maximum of 25 MW in summer and a minimum of 9.5 MW in winter the annual production cost of electricity is 0.15 €/kWh consuming an average of 2.1 L water /kWh. The investment for the plant is 260 M€. Scale-up studies reveal that the production cost can decrease by half while the investment per unit of power should become competitive with current coal based power plants if solar and coal facilities present similar production capacities. -- Highlights: • Plant design so far relies on process simulation and only partial optimization studies. • We optimize the operation of a concentrated solar power plant. • The facility involves solar field, molten salts, steam and electricity generation and cooling. • The results are promising and validate literature sensitive studies

Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response

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 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

A common fixed point for operators in probabilistic normed spaces

International Nuclear Information System (INIS)

Ghaemi, M.B.; Lafuerza-Guillen, Bernardo; Razani, A.

2009-01-01

Probabilistic Metric spaces was introduced by Karl Menger. Alsina, Schweizer and Sklar gave a general definition of probabilistic normed space based on the definition of Menger [Alsina C, Schweizer B, Sklar A. On the definition of a probabilistic normed spaces. Aequationes Math 1993;46:91-8]. Here, we consider the equicontinuity of a class of linear operators in probabilistic normed spaces and finally, a common fixed point theorem is proved. Application to quantum Mechanic is considered.

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

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...

Optimal Operation of the Integrated Electrical and Heating Systems to Accommodate the Intermittent Renewable Sources

DEFF Research Database (Denmark)

Li, Jinghua; Fang, Jiakun; Zeng, Qing

2016-01-01

The integration of electrical and heating systems has great potential to enhance the flexibility of power systems to accommodate more renewable power such as the wind and solar. This study was to investigate an optimal way to integrate the energy of both systems in urban areas. The amount of energy...... the effectiveness of the proposed solution. The results showed that coordinated optimization of the energy distribution have significant benefits for reducing wind curtailment, operation cost, and energy losses. The proposed model and methodology could help system operators with decision support in the emerging...... conversion between the electrical system and heating system was optimally decided so that the demand within both systems could be met at the least operational cost. Besides, the best node to join with the electrical system and heating system was chosen by consideration of the energy transmission loss...

Energy-Dissipation Performance of Combined Low Yield Point Steel Plate Damper Based on Topology Optimization and Its Application in Structural Control

Directory of Open Access Journals (Sweden)

Haoxiang He

2016-01-01

Full Text Available In view of the disadvantages such as higher yield stress and inadequate adjustability, a combined low yield point steel plate damper involving low yield point steel plates and common steel plates is proposed. Three types of combined plate dampers with new hollow shapes are proposed, and the specific forms include interior hollow, boundary hollow, and ellipse hollow. The “maximum stiffness” and “full stress state” are used as the optimization objectives, and the topology optimization of different hollow forms by alternating optimization method is to obtain the optimal shape. Various combined steel plate dampers are calculated by finite element simulation, the results indicate that the initial stiffness of the boundary optimized damper and interior optimized damper is lager, the hysteresis curves are full, and there is no stress concentration. These two types of optimization models made in different materials rations are studied by numerical simulation, and the adjustability of yield stress of these combined dampers is verified. The nonlinear dynamic responses, seismic capacity, and damping effect of steel frame structures with different combined dampers are analyzed. The results show that the boundary optimized damper has better energy-dissipation capacity and is suitable for engineering application.

Safer operating conditions and optimal scaling-up process for cyclohexanone peroxide reaction

International Nuclear Information System (INIS)

Zang, Na; Qian, Xin-Ming; Liu, Zhen-Yi; Shu, Chi-Min

2015-01-01

Highlights: • Thermal hazard of cyclohexanone peroxide reaction was measured by experimental techniques. • Levenberg–Marquardt algorithm was adopted to evaluate kinetic parameters. • Safer operating conditions at laboratory scale were acquired by BDs and TDs. • The verified safer operating conditions were used to obtain the optimal scale-up parameters applied in industrial plants. - Abstract: The cyclohexanone peroxide reaction process, one of the eighteen hazardous chemical processes identified in China, is performed in indirectly cooled semibatch reactors. The peroxide reaction is added to a mixture of hydrogen peroxide and nitric acid, which form heterogeneous liquid–liquid systems. A simple and general procedure for building boundary and temperature diagrams of peroxide process is given here to account for the overall kinetic expressions. Such a procedure has been validated by comparison with experimental data. Thermally safer operating parameters were obtained at laboratory scale, and the scaled-up procedure was performed to give the minimum dosing time in an industrial plant, which is in favor of maximizing industrial reactor productivity. The results are of great significance for governing the peroxide reaction process apart from the thermal runaway region. It also greatly aids in determining optimization on operating parameters in industrial plants.

Chiral measurements with the Fixed-Point Dirac operator and construction of chiral currents

International Nuclear Information System (INIS)

Hasenfratz, P.; Hauswirth, S.; Holland, K.; Joerg, T.; Niedermayer, F.

2002-01-01

In this preliminary study, we examine the chiral properties of the parametrized Fixed-Point Dirac operator D FP , see how to improve its chirality via the Overlap construction, measure the renormalized quark condensate Σ-circumflex and the topological susceptibility χ t , and investigate local chirality of near zero modes of the Dirac operator. We also give a general construction of chiral currents and densities for chiral lattice actions

Manufacturing enterprise’s logistics operational cost simulation and optimization from the perspective of inter-firm network

Directory of Open Access Journals (Sweden)

Chun Fu

2015-05-01

Full Text Available Purpose: By studying the case of a Changsha engineering machinery manufacturing firm, this paper aims to find out the optimization tactics to reduce enterprise’s logistics operational cost. Design/methodology/approach: This paper builds the structure model of manufacturing enterprise’s logistics operational costs from the perspective of inter-firm network and simulates the model based on system dynamics. Findings: It concludes that applying system dynamics in the research of manufacturing enterprise’s logistics cost control can better reflect the relationship of factors in the system. And the case firm can optimize the logistics costs by implement joint distribution. Research limitations/implications: This study still lacks comprehensive consideration about the variables quantities and quantitative of the control factors. In the future, we should strengthen the collection of data and information about the engineering manufacturing firms and improve the logistics operational cost model. Practical implications: This study puts forward some optimization tactics to reduce enterprise’s logistics operational cost. And it is of great significance for enterprise’s supply chain management optimization and logistics cost control. Originality/value: Differing from the existing literatures, this paper builds the structure model of manufacturing enterprise’s logistics operational costs from the perspective of inter-firm network and simulates the model based on system dynamics.

Least median of squares filtering of locally optimal point matches for compressible flow image registration

International Nuclear Information System (INIS)

Castillo, Edward; Guerrero, Thomas; Castillo, Richard; White, Benjamin; Rojo, Javier

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. (paper)

Optimization for set-points and robust model predictive control for steam generator in nuclear power plants

International Nuclear Information System (INIS)

Osgouee, Ahmad

2010-01-01

many advanced control methods proposed for the control of nuclear SG water level, operators are still experiencing difficulties especially at low powers. Therefore, it seems that a suitable controller to replace the manual operations is still needed. In this paper optimization of SGL set-points and designing a robust control for SGL control system using will be discussed

Optimizing Water Use and Hydropower Production in Operational Reservoir System Scheduling with RiverWare

Science.gov (United States)

Magee, T. M.; Zagona, E. A.

2017-12-01

Practical operational optimization of multipurpose reservoir systems is challenging for several reasons. Each purpose has its own constraints which may conflict with those of other purposes. While hydropower generation typically provides the bulk of the revenue, it is also among the lowest priority purposes. Each river system has important details that are specific to the location such as hydrology, reservoir storage capacity, physical limitations, bottlenecks, and the continuing evolution of operational policy. In addition, reservoir operations models include discrete, nonlinear, and nonconvex physical processes and if-then operating policies. Typically, the forecast horizon for scheduling needs to be extended far into the future to avoid near term (e.g., a few hours or a day) scheduling decisions that result in undesirable future states; this makes the computational effort much larger than may be expected. Put together, these challenges lead to large and customized mathematical optimization problems which must be solved efficiently to be of practical use. In addition, the solution process must be robust in an operational setting. We discuss a unique modeling approach in RiverWare that meets these challenges in an operational setting. The approach combines a Preemptive Linear Goal Programming optimization model to handle prioritized policies complimented by preprocessing and postprocessing with Rulebased Simulation to improve the solution with regard to nonlinearities, discrete issues, and if-then logic. An interactive policy language with a graphical user interface allows modelers to customize both the optimization and simulation based on the unique aspects of the policy for their system while the routine physical aspect of operations are modeled automatically. The modeler is aided by a set of compiled predefined functions and functions shared by other modelers. We illustrate the success of the approach with examples from daily use at the Tennessee Valley

Optimization of an electrostatic quadrupole doublet focusing systems

Energy Technology Data Exchange (ETDEWEB)

Hussein, Oday A., E-mail: oah@sc.nahrainuniv.edu.iq [Department of Physics, College of Science, Al-Nahrain University, Baghdad (Iraq); Sise, Omer [Department of Science Education, Faculty of Education, Suleyman Demirel University, Isparta (Turkey)

2017-05-15

Highlights: • The imaging properties of an electrostatic quadrupole doublet lens were analyzed with the aid of computer simulation. • The optimal electrode voltages which lead to stigmatic image in both planes of the quadrupole doublet lens with minimum spot size at position sensitive detector (PSD) were found for two operation modes: point-to-point focusing and parallel-to-point focusing. • The imaging properties of are very sensitive to the lunching angle of the electron-beam. - Abstract: The imaging properties of an electrostatic quadrupole doublet lens were analyzed with the aid of computer simulation. The optimal electrode voltages which lead to stigmatic image in both planes of the quadrupole doublet lens with minimum spot size at position sensitive detector (PSD) were found for two operation modes: point-to-point focusing and parallel-to-point focusing. The optical properties as: Magnifications, spot sizes in the image plane and aberration figures were discussed. The results showed that the focusing of the lens was strong in the xy-plane in comparison with the focusing in the xz-plane. The distortion of the image was greater when the image position will be close to the lens in comparison with object position. Also, the imaging properties were very sensitive to the lunching angle of the electron-beam.

Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation

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.

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.

Optimal operating rules definition in complex water resource systems combining fuzzy logic, expert criteria and stochastic programming

Science.gov (United States)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

2016-04-01

This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to

Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

Science.gov (United States)

Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

2017-08-01

The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

Optimization of hybrid imaging systems based on maximization of kurtosis of the restored point spread function

DEFF Research Database (Denmark)

Demenikov, Mads

2011-01-01

to optimization results based on full-reference image measures of restored images. In comparison with full-reference measures, the kurtosis measure is fast to compute and requires no images, noise distributions, or alignment of restored images, but only the signal-to-noise-ratio. © 2011 Optical Society of America.......I propose a novel, but yet simple, no-reference, objective image quality measure based on the kurtosis of the restored point spread function. Using this measure, I optimize several phase masks for extended-depth-of-field in hybrid imaging systems and obtain results that are identical...

$\\mathcal{C}$, $\\mathcal{P}$, $\\mathcal{T}$ operations and classical point charged particle dynamics

OpenAIRE

Torromé, Ricardo Gallego

2014-01-01

The action of parity inversion, time inversion and charge conjugation operations on several differential equations for a classical point charged particle are described. Moreover, we consider the notion of {\\it symmetrized acceleration} $\\Delta_q$ that for models of point charged electrodynamics is sensitive to deviations from the standard Lorentz force equation. It is shown that $\\Delta_q$ can be observed with current or near future technology and that it is an useful quantity for probing rad...

Conditions for characterizing the structure of optimal strategies in infinite-horizon dynamic programs

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

Optimizing the wireless power transfer over MIMO Channels

Science.gov (United States)

Wiedmann, Karsten; Weber, Tobias

2017-09-01

In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.

Optimizing the wireless power transfer over MIMO Channels

Directory of Open Access Journals (Sweden)

K. Wiedmann

2017-09-01

Full Text Available In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.

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

A Class of Large-Update and Small-Update Primal-Dual Interior-Point Algorithms for Linear Optimization

NARCIS (Netherlands)

Bai, Y.Q.; Lesaja, G.; Roos, C.; Wang, G.Q.; El Ghami, M.

2008-01-01

In this paper we present a class of polynomial primal-dual interior-point algorithms for linear optimization based on a new class of kernel functions. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel

Sequential function approximation on arbitrarily distributed point sets

Science.gov (United States)

Wu, Kailiang; Xiu, Dongbin

2018-02-01

We present a randomized iterative method for approximating unknown function sequentially on arbitrary point set. The method is based on a recently developed sequential approximation (SA) method, which approximates a target function using one data point at each step and avoids matrix operations. The focus of this paper is on data sets with highly irregular distribution of the points. We present a nearest neighbor replacement (NNR) algorithm, which allows one to sample the irregular data sets in a near optimal manner. We provide mathematical justification and error estimates for the NNR algorithm. Extensive numerical examples are also presented to demonstrate that the NNR algorithm can deliver satisfactory convergence for the SA method on data sets with high irregularity in their point distributions.

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)

Fixed-Point Configurable Hardware Components

Directory of Open Access Journals (Sweden)

Rocher Romuald

2006-01-01

Full Text Available To reduce the gap between the VLSI technology capability and the designer productivity, design reuse based on IP (intellectual properties is commonly used. In terms of arithmetic accuracy, the generated architecture can generally only be configured through the input and output word lengths. In this paper, a new kind of method to optimize fixed-point arithmetic IP has been proposed. The architecture cost is minimized under accuracy constraints defined by the user. Our approach allows exploring the fixed-point search space and the algorithm-level search space to select the optimized structure and fixed-point specification. To significantly reduce the optimization and design times, analytical models are used for the fixed-point optimization process.

Optimal design and operation of a thermal storage system for a chilled water plant serving pharmaceutical buildings

Energy Technology Data Exchange (ETDEWEB)

Henze, Gregor P. [University of Nebraska, Architectural Engineering, Omaha, NE 68182 (United States); Biffar, Bernd; Kohn, Dietmar [Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach D-88400 (Germany); Becker, Martin P. [University of Applied Sciences Biberach, Architectural Engineering, Biberach D-88400 (Germany)

2008-07-01

A group of buildings in the pharmaceutical industry located in Southern Germany is experiencing a trend of growing cooling loads to be met by the chilled water plant composed of 10 chillers of greatly varying cost effectiveness. With a capacity shortfall inevitable, the question arises whether to install an additional chiller or improve the utilization of the existing chillers, in particular those with low operating costs per unit cooling, through the addition of a chilled water thermal energy storage (TES) system. To provide decision support in this matter, an optimization environment was developed and validated that adopts mixed integer programming as the approach to optimizing the chiller dispatch for any load condition, while an overarching dynamic programming based optimization approach optimizes the charge/discharge strategy of the TES system. In this fashion, the chilled water plant optimization is decoupled but embedded in the TES control optimization. The approach was selected to allow for arbitrary constraints and optimization horizons, while ensuring a global optimum to the problem. Optimization scenarios have been defined that include current load conditions as well cooling loads that are elevated by 25% from current conditions in order to reflect the expected growth in cooling demand in the near future; both scenarios analyzed the impact of storage capacity by investigating several TES tank capacities. The annual optimization runs revealed that - based on the elevated cooling load scenario - the smallest TES system pays back the incremental investment necessary for the TES system in about three years; based on today's cooling loads the static payback is approximately six years. As the efficiency and cost of operating the existing chillers vary over a wide range, the TES system allows for a reduction in operating costs for the chilled water plant by avoiding the operation of inefficient chillers (such as the single-stage absorption type) and

Optimal Operation of Industrial Batch Crystallizers : A Nonlinear Model-based Control Approach

NARCIS (Netherlands)

Mesbah, A.

2010-01-01

Batch crystallization is extensively employed in the chemical, pharmaceutical, and food industries to separate and purify high value-added chemical substances. Despite their widespread application, optimal operation of batch crystallizers is particularly challenging. The difficulties primarily

Optimal Operation of Photovoltaic System with a DC-DC Boost Converter FED SAF Using ICosφ Algorithm

Directory of Open Access Journals (Sweden)

G.Vijayakumar

2014-07-01

Full Text Available This paper presents an optimal utilization of Photovoltaic (PV solar system based Shunt Active Filter (PV-SAF for harmonic mitigation, real and reactive power compensation at the point of common coupling (PCC throughout the day. This PV system operated SAF reduces the energy consumption by disconnecting the utility grid from the load through semiconductor switches, when the PV system generates excessive or equal real power to the required load demand. However, the reduction of energy consumption is always desirable for the reduction of panel tariff and global warming gasses. The PV module is connected to the DC side of SAF through the DC-DC converter with fuzzy based Perturb & Observe (P&O Maximum Power Point Tracking (MPPT algorithm to eliminate the drawback of the conventional PV system by tracking maximum power point of the PV array is presented. The reference currents extract by the Fuzzy logic controller based ICosΦ control strategy. This proposed PV-SAF, if connected at the terminals of a small industry or a home or a small enlightening institution can avoid interruptible power supply, use of individual stabilizer and potential panel tariff over a 12 hour period. A MATLAB simulink is presented to validate the advantage of the proposed system.

A Feedback Optimal Control Algorithm with Optimal Measurement Time Points

Directory of Open Access Journals (Sweden)

Felix Jost

2017-02-01

Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.

Dynamic Value Engineering Method Optimizing the Risk on Real Time Operating System

Directory of Open Access Journals (Sweden)

Prashant Kumar Patra

2014-04-01

Full Text Available The value engineering is the umbrella of the many more sub-system like quality assurance, quality control, quality function design and development for manufacturability. The system engineering & value engineering is two part of the coin. The value engineering is the high level of technology management for every aspect of engineering fields. The value engineering is the high utilization of System Product (i.e. Processor, Memory & Encryption key, Services, Business and Resources at minimal cost. The high end operating system providing highest services at optimal cost & time. The value engineering provides the maximum performance, accountability, reliability, integrity and availability of processor, memory, encryption key and other inter dependency sub-components. The value engineering is the ratio of the maximum functionality of individual components to the optimal cost. VE=k [(P, M, E, C, A]/optimal cost. Where k is the proportionality constant. The VE is directly proportional to performance of individual components and inversely proportional to the minimal cost. The VE is directly proportional to the risk assessment. The VE maximize the business throughput & decision process mean while minimize the risk and down time. We have to develop the dynamic value engineering model & mechanism for risk optimization over a complex real time operating system This proposed composition model definite will be resolve our objective at top high level. Product

The primary ion source for construction and optimization of operation parameters

International Nuclear Information System (INIS)

Synowiecki, A.; Gazda, E.

1986-01-01

The construction of primary ion source for SIMS has been presented. The influence of individual operation parameters on the properties of ion source has been investigated. Optimization of these parameters has allowed to appreciate usefulness of the ion source for SIMS study. 14 refs., 8 figs., 2 tabs. (author)

Hybrid Proximal-Point Methods for Zeros of Maximal Monotone Operators, Variational Inequalities and Mixed Equilibrium Problems

Directory of Open Access Journals (Sweden)

Kriengsak Wattanawitoon

2011-01-01

Full Text Available We prove strong and weak convergence theorems of modified hybrid proximal-point algorithms for finding a common element of the zero point of a maximal monotone operator, the set of solutions of equilibrium problems, and the set of solution of the variational inequality operators of an inverse strongly monotone in a Banach space under different conditions. Moreover, applications to complementarity problems are given. Our results modify and improve the recently announced ones by Li and Song (2008 and many authors.

Condenser design optimization and operation characteristics of a novel miniature loop heat pipe

International Nuclear Information System (INIS)

Wan Zhenping; Wang Xiaowu; Tang Yong

2012-01-01

Highlights: ► A novel miniature LHP (mLHP) system was presented. ► Optimal design of condenser was considered. ► The heat transfer performance was investigated experimentally. - Abstract: Loop heat pipe (LHP) is a promising means for electronics cooling since LHP is a exceptionally efficient heat transfer device. In this paper, a novel miniature LHP (mLHP) system is presented and optimal design of condenser is considered seeing that evaporators have been able to handle very high-heat fluxes with low-heat transfer resistances since most of the previous researchers focused on the evaporator of mLHP. The arrayed pins were designed and machined out on the bottom of condenser to enhance condensation heat transfer. The parameters of the arrayed pins, including layout, cross-section shape and area, were optimized by finite element analysis. Tests were carried out on the mLHP with a CPU thermal simulator using forced air convection condenser cooling to validate the optimization. The operation characteristics of the mLHP with optimal design parameters of condenser were investigated experimentally. The experimental results show that the mLHP can reject head load 200 W while maintaining the cooled object temperatures below 100 °C, and for a variable power applied to the evaporator, the system presents reliable startups and continuous operation.

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.

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.

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)

Families of optimal thermodynamic solutions for combined cycle gas turbine (CCGT) power plants

International Nuclear Information System (INIS)

Godoy, E.; Scenna, N.J.; Benz, S.J.

2010-01-01

Optimal designs of a CCGT power plant characterized by maximum second law efficiency values are determined for a wide range of power demands and different values of the available heat transfer area. These thermodynamic optimal solutions are found within a feasible operation region by means of a non-linear mathematical programming (NLP) model, where decision variables (i.e. transfer areas, power production, mass flow rates, temperatures and pressures) can vary freely. Technical relationships among them are used to systematize optimal values of design and operative variables of a CCGT power plant into optimal solution sets, named here as optimal solution families. From an operative and design point of view, the families of optimal solutions let knowing in advance optimal values of the CCGT variables when facing changes of power demand or adjusting the design to an available heat transfer area.

An algorithm to locate optimal bond breaking points on a potential energy surface for applications in mechanochemistry and catalysis.

Science.gov (United States)

Bofill, Josep Maria; Ribas-Ariño, Jordi; García, Sergio Pablo; Quapp, Wolfgang

2017-10-21

The reaction path of a mechanically induced chemical transformation changes under stress. It is well established that the force-induced structural changes of minima and saddle points, i.e., the movement of the stationary points on the original or stress-free potential energy surface, can be described by a Newton Trajectory (NT). Given a reactive molecular system, a well-fitted pulling direction, and a sufficiently large value of the force, the minimum configuration of the reactant and the saddle point configuration of a transition state collapse at a point on the corresponding NT trajectory. This point is called barrier breakdown point or bond breaking point (BBP). The Hessian matrix at the BBP has a zero eigenvector which coincides with the gradient. It indicates which force (both in magnitude and direction) should be applied to the system to induce the reaction in a barrierless process. Within the manifold of BBPs, there exist optimal BBPs which indicate what is the optimal pulling direction and what is the minimal magnitude of the force to be applied for a given mechanochemical transformation. Since these special points are very important in the context of mechanochemistry and catalysis, it is crucial to develop efficient algorithms for their location. Here, we propose a Gauss-Newton algorithm that is based on the minimization of a positively defined function (the so-called σ-function). The behavior and efficiency of the new algorithm are shown for 2D test functions and for a real chemical example.

Optimal Operation of a Josephson Parametric Amplifier for Vacuum Squeezing

Science.gov (United States)

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.

A Novel Optimization Method on Logistics Operation for Warehouse & Port Enterprises Based on Game Theory

Directory of Open Access Journals (Sweden)

Junyang Li

2013-09-01

Full Text Available Purpose: The following investigation aims to deal with the competitive relationship among different warehouses & ports in the same company. Design/methodology/approach: In this paper, Game Theory is used in carrying out the optimization model. Genetic Algorithm is used to solve the model. Findings: Unnecessary competition will rise up if there is little internal communication among different warehouses & ports in one company. This paper carries out a novel optimization method on warehouse & port logistics operation model. Originality/value: Warehouse logistics business is a combination of warehousing services and terminal services which is provided by port logistics through the existing port infrastructure on the basis of a port. The newly proposed method can help to optimize logistics operation model for warehouse & port enterprises effectively. We set Sinotrans Guangdong Company as an example to illustrate the newly proposed method. Finally, according to the case study, this paper gives some responses and suggestions on logistics operation in Sinotrans Guangdong warehouse & port for its future development.

Analytical design of proportional-integral controllers for the optimal control of first-order processes with operational constraints

Energy Technology Data Exchange (ETDEWEB)

Thu, Hien Cao Thi; Lee, Moonyong [Yeungnam University, Gyeongsan (Korea, Republic of)

2013-12-15

A novel analytical design method of industrial proportional-integral (PI) controllers was developed for the optimal control of first-order processes with operational constraints. The control objective was to minimize a weighted sum of the controlled variable error and the rate of change in the manipulated variable under the maximum allowable limits in the controlled variable, manipulated variable and the rate of change in the manipulated variable. The constrained optimal servo control problem was converted to an unconstrained optimization to obtain an analytical tuning formula. A practical shortcut procedure for obtaining optimal PI parameters was provided based on graphical analysis of global optimality. The proposed PI controller was found to guarantee global optimum and deal explicitly with the three important operational constraints.

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

Realization of universal optimal quantum machines by projective operators and stochastic maps

International Nuclear Information System (INIS)

Sciarrino, F.; Sias, C.; Ricci, M.; De Martini, F.

2004-01-01

Optimal quantum machines can be implemented by linear projective operations. In the present work a general qubit symmetrization theory is presented by investigating the close links to the qubit purification process and to the programmable teleportation of any generic optimal antiunitary map. In addition, the contextual realization of the N→M cloning map and of the teleportation of the N→(M-N) universal-NOT (UNOT) gate is analyzed by a very general angular momentum theory. An extended set of experimental realizations by state symmetrization linear optical procedures is reported. These include the 1→2 cloning process, the UNOT gate and the quantum tomographic characterization of the optimal partial transpose map of polarization encoded qubits

Optimizing Environmental Flow Operation Rules based on Explicit IHA Constraints

Science.gov (United States)

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.

Model-based minimization algorithm of a supercritical helium loop consumption subject to operational constraints

Science.gov (United States)

Bonne, F.; Bonnay, P.; Girard, A.; Hoa, C.; Lacroix, B.; Le Coz, Q.; Nicollet, S.; Poncet, J.-M.; Zani, L.

2017-12-01

Supercritical helium loops at 4.2 K are the baseline cooling strategy of tokamaks superconducting magnets (JT-60SA, ITER, DEMO, etc.). This loops work with cryogenic circulators that force a supercritical helium flow through the superconducting magnets in order that the temperature stay below the working range all along their length. This paper shows that a supercritical helium loop associated with a saturated liquid helium bath can satisfy temperature constraints in different ways (playing on bath temperature and on the supercritical flow), but that only one is optimal from an energy point of view (every Watt consumed at 4.2 K consumes at least 220 W of electrical power). To find the optimal operational conditions, an algorithm capable of minimizing an objective function (energy consumption at 5 bar, 5 K) subject to constraints has been written. This algorithm works with a supercritical loop model realized with the Simcryogenics [2] library. This article describes the model used and the results of constrained optimization. It will be possible to see that the changes in operating point on the temperature of the magnet (e.g. in case of a change in the plasma configuration) involves large changes on the cryodistribution optimal operating point. Recommendations will be made to ensure that the energetic consumption is kept as low as possible despite the changing operating point. This work is partially supported by EUROfusion Consortium through the Euratom Research and Training Program 20142018 under Grant 633053.

Operational Excellence through Schedule Optimization and Production Simulation of Application Specific Integrated Circuits.

Energy Technology Data Exchange (ETDEWEB)

Flory, John Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Padilla, Denise D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, Steven P [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-05-01

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performance evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.

Optimal pricing of non-utility generated electric power

International Nuclear Information System (INIS)

Siddiqi, S.N.; Baughman, M.L.

1994-01-01

The importance of an optimal pricing policy for pricing non-utility generated power is pointed out in this paper. An optimal pricing policy leads to benefits for all concerned: the utility, industry, and the utility's other customers. In this paper, it is shown that reliability differentiated real-time pricing provides an optimal non-utility generated power pricing policy, from a societal welfare point of view. Firm capacity purchase, and hence an optimal price for purchasing firm capacity, are an integral part of this pricing policy. A case study shows that real-time pricing without firm capacity purchase results in improper investment decisions and higher costs for the system as a whole. Without explicit firm capacity purchase, the utility makes greater investment in capacity addition in order to meet its reliability criteria than is socially optimal. It is concluded that the non-utility generated power pricing policy presented in this paper and implied by reliability differentiated pricing policy results in social welfare-maximizing investment and operation decisions

An optimal cut-off point for the calving interval may be used as an indicator of bovine abortions.

Science.gov (United States)

Bronner, Anne; Morignat, Eric; Gay, Emilie; Calavas, Didier

2015-10-01

The bovine abortion surveillance system in France aims to detect as early as possible any resurgence of bovine brucellosis, a disease of which the country has been declared free since 2005. It relies on the mandatory notification and testing of each aborting cow, but under-reporting is high. This research uses a new and simple approach which considers the calving interval (CI) as a "diagnostic test" to determine optimal cut-off point c and estimate diagnostic performance of the CI to identify aborting cows, and herds with multiple abortions (i.e. three or more aborting cows per calving season). The period between two artificial inseminations (AI) was considered as a "gold standard". During the 2006-2010 calving seasons, the mean optimal CI cut-off point for identifying aborting cows was 691 days for dairy cows and 703 days for beef cows. Depending on the calving season, production type and scale at which c was computed (individual or herd), the average sensitivity of the CI varied from 42.6% to 64.4%; its average specificity from 96.7% to 99.7%; its average positive predictive value from 27.6% to 65.4%; and its average negative predictive value from 98.7% to 99.8%. When applied to the French bovine population as a whole, this indicator identified 2-3% of cows suspected to have aborted, and 10-15% of herds suspected of multiple abortions. The optimal cut-off point and CI performance were consistent over calving seasons. By applying an optimal CI cut-off point to the cattle demographics database, it becomes possible to identify herds with multiple abortions, carry out retrospective investigations to find the cause of these abortions and monitor a posteriori compliance of farmers with their obligation to report abortions for brucellosis surveillance needs. Therefore, the CI could be used as an indicator of abortions to help improve the current mandatory notification surveillance system. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimal Operation and Stabilising Control of the Concentric Heat-Integrated Distillation Column

DEFF Research Database (Denmark)

Bisgaard, Thomas; Skogestad, Sigurd; Huusom, Jakob Kjøbsted

2016-01-01

A systematic control structure design method is applied on the concentric heat integrated distillation column (HIDiC) separating benzene and toluene. A degrees of freedom analysis is provided for identifying potential manipulated and controlled variables. Optimal operation is mapped and active...

Optimization of Control Points Number at Coordinate Measurements based on the Monte-Carlo Method

Science.gov (United States)

Korolev, A. A.; Kochetkov, A. V.; Zakharov, O. V.

2018-01-01

Improving the quality of products causes an increase in the requirements for the accuracy of the dimensions and shape of the surfaces of the workpieces. This, in turn, raises the requirements for accuracy and productivity of measuring of the workpieces. The use of coordinate measuring machines is currently the most effective measuring tool for solving similar problems. The article proposes a method for optimizing the number of control points using Monte Carlo simulation. Based on the measurement of a small sample from batches of workpieces, statistical modeling is performed, which allows one to obtain interval estimates of the measurement error. This approach is demonstrated by examples of applications for flatness, cylindricity and sphericity. Four options of uniform and uneven arrangement of control points are considered and their comparison is given. It is revealed that when the number of control points decreases, the arithmetic mean decreases, the standard deviation of the measurement error increases and the probability of the measurement α-error increases. In general, it has been established that it is possible to repeatedly reduce the number of control points while maintaining the required measurement accuracy.

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

Science.gov (United States)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their

Parallel algorithm for dominant points correspondences in robot binocular stereo vision

Science.gov (United States)

Al-Tammami, A.; Singh, B.

1993-01-01

a final decision tool when there is still more than one point in the search area. If there is no dominant point in the search area of if the points in the search area are below a correlation threshold, then the dominant point in the reference image is occluded and can not be corresponded. The algorithm has been modeled, implemented and shown to be fast, robust and parallel. The parallelism is created from three main features: locality of the operators; a memory optimization scheme; and the ability to fully parallelize the extraction phase which is the most computational intensive task in the algorithm. The last feature is achieved by performing the extraction phase on the two images simultaneously.