Modeling and optimization of HVAC energy consumption
Energy Technology Data Exchange (ETDEWEB)
Kusiak, Andrew; Li, Mingyang; Tang, Fan [Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242 - 1527 (United States)
2010-10-15
A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan, and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the setpoint of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (author)
Optimization Models and Methods Developed at the Energy Systems Institute
N.I. Voropai; V.I. Zorkaltsev
2013-01-01
The paper presents shortly some optimization models of energy system operation and expansion that have been created at the Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences. Consideration is given to the optimization models of energy development in Russia, a software package intended for analysis of power system reliability, and model of flow distribution in hydraulic systems. A general idea of the optimization methods developed at the Energy Systems Institute...
Visual prosthesis wireless energy transfer system optimal modeling.
Li, Xueping; Yang, Yuan; Gao, Yong
2014-01-16
Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.
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.
Modeling and energy efficiency optimization of belt conveyors
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2011-01-01
Highlights: → We take optimization approach to improve operation efficiency of belt conveyors. → An analytical energy model, originating from ISO 5048, is proposed. → Then an off-line and an on-line parameter estimation schemes are investigated. → In a case study, six optimization problems are formulated with solutions in simulation. - Abstract: The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment and operation levels. Specifically, variable speed control, an equipment level intervention, is recommended to improve operation efficiency of belt conveyors. However, the current implementations mostly focus on lower level control loops without operational considerations at the system level. This paper intends to take a model based optimization approach to improve the efficiency of belt conveyors at the operational level. An analytical energy model, originating from ISO 5048, is firstly proposed, which lumps all the parameters into four coefficients. Subsequently, both an off-line and an on-line parameter estimation schemes are applied to identify the new energy model, respectively. Simulation results are presented for the estimates of the four coefficients. Finally, optimization is done to achieve the best operation efficiency of belt conveyors under various constraints. Six optimization problems of a typical belt conveyor system are formulated, respectively, with solutions in simulation for a case study.
A model of optimization for local energy infrastructure development
International Nuclear Information System (INIS)
Juroszek, Zbigniew; Kudelko, Mariusz
2016-01-01
The authors present a non-linear, optimization model supporting the planning of local energy systems development. The model considers two forms of final energy – heat and electricity. The model reflects both private and external costs and is designed to show the social perspective. It considers the variability of the marginal costs attributed to local renewable resources. In order to demonstrate the capacity of the model, the authors present a case study by modelling the development of the energy infrastructure in a municipality located in the south of Poland. The ensuing results show that a swift and significant shift in the local energy policy of typical central European municipalities is needed. The modelling is done in two scenarios – with and without the internalization of external environmental costs. The results confirm that the internalization of the external costs of energy production on a local scale leads to a significant improvement in the allocation of resources. - Highlights: • A model for municipal energy system development in Central European environment has been developed. • The variability of marginal costs of local, renewable fuels is considered. • External, environmental costs are considered. • The model reflects both network and individual energy infrastructure (e.g. individual housing boilers). • A swift change in Central European municipal energy infrastructure is necessary.
Protein homology model refinement by large-scale energy optimization.
Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David
2018-03-20
Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.
The case for repeatable analysis with energy economy optimization models
International Nuclear Information System (INIS)
DeCarolis, Joseph F.; Hunter, Kevin; Sreepathi, Sarat
2012-01-01
Energy economy optimization (EEO) models employ formal search techniques to explore the future decision space over several decades in order to deliver policy-relevant insights. EEO models are a critical tool for decision-makers who must make near-term decisions with long-term effects in the face of large future uncertainties. While the number of model-based analyses proliferates, insufficient attention is paid to transparency in model development and application. Given the complex, data-intensive nature of EEO models and the general lack of access to source code and data, many of the assumptions underlying model-based analysis are hidden from external observers. This paper discusses the simplifications and subjective judgments involved in the model building process, which cannot be fully articulated in journal papers, reports, or model documentation. In addition, we argue that for all practical purposes, EEO model-based insights cannot be validated through comparison to real world outcomes. As a result, modelers are left without credible metrics to assess a model's ability to deliver reliable insight. We assert that EEO models should be discoverable through interrogation of publicly available source code and data. In addition, third parties should be able to run a specific model instance in order to independently verify published results. Yet a review of twelve EEO models suggests that in most cases, replication of model results is currently impossible. We provide several recommendations to help develop and sustain a software framework for repeatable model analysis.
PEM fuel cell model suitable for energy optimization purposes
International Nuclear Information System (INIS)
Caux, S.; Hankache, W.; Fadel, M.; Hissel, D.
2010-01-01
Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms.
PEM fuel cell model suitable for energy optimization purposes
Energy Technology Data Exchange (ETDEWEB)
Caux, S.; Hankache, W.; Fadel, M. [LAPLACE/CODIASE: UMR CNRS 5213, Universite de Toulouse - INPT, UPS, - ENSEEIHT: 2 rue Camichel BP7122, 31071 Toulouse (France); CNRS, LAPLACE, F-31071 Toulouse (France); Hissel, D. [FEMTO-ST ENISYS/FCLAB, UMR CNRS 6174, University of Franche-Comte, Rue Thierry Mieg, 90010 Belfort (France)
2010-02-15
Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms. (author)
Modeling, hybridization, and optimal charging of electrical energy storage systems
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
Oneida Tribe of Indians of Wisconsin Energy Optimization Model
Energy Technology Data Exchange (ETDEWEB)
Troge, Michael [Little Bear Development Center, Oneida, WI (United States)
2014-12-01
Oneida Nation is located in Northeast Wisconsin. The reservation is approximately 96 square miles (8 miles x 12 miles), or 65,000 acres. The greater Green Bay area is east and adjacent to the reservation. A county line roughly splits the reservation in half; the west half is in Outagamie County and the east half is in Brown County. Land use is predominantly agriculture on the west 2/3 and suburban on the east 1/3 of the reservation. Nearly 5,000 tribally enrolled members live in the reservation with a total population of about 21,000. Tribal ownership is scattered across the reservation and is about 23,000 acres. Currently, the Oneida Tribe of Indians of Wisconsin (OTIW) community members and facilities receive the vast majority of electrical and natural gas services from two of the largest investor-owned utilities in the state, WE Energies and Wisconsin Public Service. All urban and suburban buildings have access to natural gas. About 15% of the population and five Tribal facilities are in rural locations and therefore use propane as a primary heating fuel. Wood and oil are also used as primary or supplemental heat sources for a small percent of the population. Very few renewable energy systems, used to generate electricity and heat, have been installed on the Oneida Reservation. This project was an effort to develop a reasonable renewable energy portfolio that will help Oneida to provide a leadership role in developing a clean energy economy. The Energy Optimization Model (EOM) is an exploration of energy opportunities available to the Tribe and it is intended to provide a decision framework to allow the Tribe to make the wisest choices in energy investment with an organizational desire to establish a renewable portfolio standard (RPS).
Electromagnetic Vibration Energy Harvesting Devices Architectures, Design, Modeling and Optimization
Spreemann, Dirk
2012-01-01
Electromagnetic vibration transducers are seen as an effective way of harvesting ambient energy for the supply of sensor monitoring systems. Different electromagnetic coupling architectures have been employed but no comprehensive comparison with respect to their output performance has been carried out up to now. Electromagnetic Vibration Energy Harvesting Devices introduces an optimization approach which is applied to determine optimal dimensions of the components (magnet, coil and back iron). Eight different commonly applied coupling architectures are investigated. The results show that correct dimensions are of great significance for maximizing the efficiency of the energy conversion. A comparison yields the architectures with the best output performance capability which should be preferably employed in applications. A prototype development is used to demonstrate how the optimization calculations can be integrated into the design–flow. Electromagnetic Vibration Energy Harvesting Devices targets the design...
Modeling and optimization of energy storage system for microgrid
Qiu, Xin
The vanadium redox flow battery (VRB) is well suited for the applications of microgrid and renewable energy. This thesis will have a practical analysis of the battery itself and its application in microgrid systems. The first paper analyzes the VRB use in a microgrid system. The first part of the paper develops a reduced order circuit model of the VRB and analyzes its experimental performance efficiency during deployment. The statistical methods and neural network approximation are used to estimate the system parameters. The second part of the paper addresses the implementation issues of the VRB application in a photovoltaic-based microgrid system. A new dc-dc converter was proposed to provide improved charging performance. The paper was published on IEEE Transactions on Smart Grid, Vol. 5, No. 4, July 2014. The second paper studies VRB use within a microgrid system from a practical perspective. A reduced order circuit model of the VRB is introduced that includes the losses from the balance of plant including system and environmental controls. The proposed model includes the circulation pumps and the HVAC system that regulates the environment of the VRB enclosure. In this paper, the VRB model is extended to include the ESS environmental controls to provide a model that provides a more realistic efficiency profile. The paper was submitted to IEEE Transactions on Sustainable Energy. Third paper discussed the optimal control strategy when VRB works with other type of battery in a microgird system. The work in first paper is extended. A high level control strategy is developed to coordinate a lead acid battery and a VRB with reinforcement learning. The paper is to be submitted to IEEE Transactions on Smart Grid.
Energy balance of forage consumption by phyllophagous insects: optimization model
Directory of Open Access Journals (Sweden)
O. V. Tarasova
2015-06-01
Full Text Available The model of optimal food consumption by phytophagous insects proposed, in which the metabolic costs are presented in the form of two components – the cost of food utilization and costs for proper metabolism of the individuals. Two measures were introduced – the «price» of food conversion and the «price» of biomass synthesis of individuals to assess the effectiveness of food consumption by caterpillars. The proposed approach to the description of food consumption by insects provides the exact solutions of the equation of energy balance of food consumption and determining the effectiveness of consumption and the risk of death of the individual. Experiments on larvae’s feeding in laboratory conditions were carried out to verify the model. Caterpillars of Aporia crataegi L. (Lepidoptera, Pieridae were the research subjects. Supplydemand balance, calculated value of the environmental price of consumption and efficiency of food consumption for each individual were determined from experimental data. It was found that the fertility of the female does not depend on the weight of food consumed by it, but is linearly dependent on the food consumption efficiency index. The greater the efficiency of food consumption by an individual, the higher its fertility. The data obtained in the course of experiments on the feeding caterpillars Aporia crataegi were compared with the data presented in the works of other authors and counted in the proposed model of consumption. Calculations allowed estimation of the critical value of food conversion price below which the energy balance is negative and the existence of an individual is not possible.
Effect of wind energy system performance on optimal renewable energy model - an analysis
International Nuclear Information System (INIS)
Iniyan, S.; Jagadeesan, T.R.
1998-01-01
The Optimal Renewable Energy Model (OREM) has been developed to determine the optimum level of renewable energy sources utilisation in India for the year 2020-21. The model aims at minimising cost/efficiency ratio and determines the optimum allocation of different renewable energy sources for various end-uses. The extent of social acceptance level, potential limit, demand and reliability will decide the renewable energy distribution pattern and are hence used as constraints in the model. In this paper, the performance and reliability of wind energy system and its effects on OREM model has been analysed. The demonstration windfarm (4 MW) which is situated in Muppandal, a village in the southern part of India, has been selected for the study. The windfarm has 20 wind turbine machines of 200 KW capacity . The average technical availability, real availability and capacity factor have been analysed from 1991 to 1995 and they are found to be 94.1%, 76.4% and 25.5% respectively. The reliability factor of wind energy systems is found to be 0.5 at 10,000 hours. The OREM model is analysed considering the above said factors for wind energy system, solar energy system and biomass energy systems. The model selects wind energy for pumping end-use to an extent of 0.3153 x10 15 KJ. (Author)
Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control
Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.
2016-02-01
A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
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...
Optimization of Experimental Model Parameter Identification for Energy Storage Systems
Directory of Open Access Journals (Sweden)
Rosario Morello
2013-09-01
Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
2017-07-04
This paper presents a stochastic multi-agent optimization model that supports energy infrastruc- : ture planning under uncertainty. The interdependence between dierent decision entities in the : system is captured in an energy supply chain network, w...
Domestic appliances energy optimization with model predictive control
International Nuclear Information System (INIS)
Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.
2017-01-01
Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new
An optimal control model for load shifting - With application in the energy management of a colliery
International Nuclear Information System (INIS)
Middelberg, Arno; Zhang Jiangfeng; Xia Xiaohua
2009-01-01
This paper presents an optimal control model for the load shifting problem in energy management and its application in a South African colliery. It is illustrated in the colliery scenario that how the optimal control model can be applied to optimize load shifting and improve energy efficiency through the control of conveyor belts. The time-of-use electricity tariff is used as an input to the objective function in order to obtain a solution that minimizes electricity costs and thus maximizes load shifting. The case study yields promising results that show the potential of applying this optimal control model to other industrial Demand Side Management initiatives
Optimal modeling and forecasting of the energy consumption and production in China
International Nuclear Information System (INIS)
Xiong, Ping-ping; Dang, Yao-guo; Yao, Tian-xiang; Wang, Zheng-xin
2014-01-01
Energy is of fundamental importance to a nation's economy. Accurate prediction of the energy consumption and production in China can play a guiding role in making the energy consumption plan, and facilitate timely and effective decision making of energy policy. This article proposes a novel GM (gray model) (1,1) model based on optimizing initial condition according to the principle of new information priority. The optimized model and five other GM (1,1) models are applied in the modeling of China's energy consumption and production. Both the simulation and prediction accuracy of the models are compared and analyzed. We obtain the result that the optimized model has higher prediction accuracy than the other five models. Therefore, the presented optimized model is further utilized to predict China's energy consumption and production from 2013 to 2017. The result indicates that China's energy consumption and production will keep increasing and the gap between the energy production and consumption will also be increasing. Finally, we predict Iran's and Argentina's energy consumption to further prove the effectiveness of the proposed model. - Highlights: • We proposed a novel GM (1,1) model based on optimizing initial condition. • The prediction accuracy of the proposed model is better than the other models. • We used the proposed model to predict China's energy consumption and production. • The proposed model can be used to predict other countries' energy consumption
A two-stage stochastic programming model for the optimal design of distributed energy systems
International Nuclear Information System (INIS)
Zhou, Zhe; Zhang, Jianyun; Liu, Pei; Li, Zheng; Georgiadis, Michael C.; Pistikopoulos, Efstratios N.
2013-01-01
Highlights: ► The optimal design of distributed energy systems under uncertainty is studied. ► A stochastic model is developed using genetic algorithm and Monte Carlo method. ► The proposed system possesses inherent robustness under uncertainty. ► The inherent robustness is due to energy storage facilities and grid connection. -- Abstract: A distributed energy system is a multi-input and multi-output energy system with substantial energy, economic and environmental benefits. The optimal design of such a complex system under energy demand and supply uncertainty poses significant challenges in terms of both modelling and corresponding solution strategies. This paper proposes a two-stage stochastic programming model for the optimal design of distributed energy systems. A two-stage decomposition based solution strategy is used to solve the optimization problem with genetic algorithm performing the search on the first stage variables and a Monte Carlo method dealing with uncertainty in the second stage. The model is applied to the planning of a distributed energy system in a hotel. Detailed computational results are presented and compared with those generated by a deterministic model. The impacts of demand and supply uncertainty on the optimal design of distributed energy systems are systematically investigated using proposed modelling framework and solution approach.
Energy-saving management modelling and optimization for lead-acid battery formation process
Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.
2017-11-01
In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.
A PSO–GA optimal model to estimate primary energy demand of China
International Nuclear Information System (INIS)
Yu Shiwei; Wei Yiming; Wang Ke
2012-01-01
To improve estimation efficiency for future projections, the present study has proposed a hybrid algorithm, Particle Swarm Optimization and Genetic Algorithm optimal Energy Demand Estimating (PSO–GA EDE) model, for China. The coefficients of the three forms of the model (linear, exponential, and quadratic) are optimized by PSO–GA using factors, such as GDP, population, economic structure, urbanization rate, and energy consumption structure, that affect demand. Based on 20-year historical data between 1990 and 2009, the simulation results of the proposed model have greater accuracy and reliability than other single optimization methods. Moreover, it can be used with optimal coefficients for the energy demand projections of China. The departure coefficient method is applied to get the weights of the three forms of the model to obtain a combinational prediction. The energy demand of China is going to be 4.79, 4.04, and 4.48 billion tce in 2015, and 6.91, 5.03, and 6.11 billion tce (“standard” tons coal equivalent) in 2020 under three different scenarios. Further, the projection results are compared with other estimating methods. - Highlights: ► A hybrid algorithm PSO–GA optimal energy demands estimating model for China. ► Energy demand of China is estimated by 2020 in three different scenarios. ► The projection results are compared with other estimating methods.
Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM
Directory of Open Access Journals (Sweden)
Egwunatum Samuel
2016-09-01
Full Text Available Given the ability of a Building Information Model (BIM to serve as a multi-disciplinary data repository, this paper seeks to explore and exploit the sustainability value of Building Information Modelling/models in delivering buildings that require less energy for their operation, emit less CO2 and at the same time provide a comfortable living environment for their occupants. This objective was achieved by a critical and extensive review of the literature covering: (1 building energy consumption, (2 building energy performance and analysis, and (3 building information modeling and energy assessment. The literature cited in this paper showed that linking an energy analysis tool with a BIM model helped project design teams to predict and create optimized energy consumption. To validate this finding, an in-depth analysis was carried out on a completed BIM integrated construction project using the Arboleda Project in the Dominican Republic. The findings showed that the BIM-based energy analysis helped the design team achieve the world’s first 103% positive energy building. From the research findings, the paper concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results as well as deliver energy-efficient buildings. The study further recommends that the adoption of a level 2 BIM and the integration of BIM in energy optimization analyse should be made compulsory for all projects irrespective of the method of procurement (government-funded or otherwise or its size.
Optimization model of energy mix taking into account the environmental impact
International Nuclear Information System (INIS)
Gruenwald, O.; Oprea, D.
2012-01-01
At present, the energy system in the Czech Republic needs to decide some important issues regarding limited fossil resources, greater efficiency in producing of electrical energy and reducing emission levels of pollutants. These problems can be decided only by formulating and implementing an energy mix that will meet these conditions: rational, reliable, sustainable and competitive. The aim of this article is to find a new way of determining an optimal mix for the energy system in the Czech Republic. To achieve the aim, the linear optimization model comprising several economics, environmental and technical aspects will be applied. (Authors)
Modeling and Optimization of an Electrostatic Energy Harvesting Device
DEFF Research Database (Denmark)
Crovetto, Andrea; Wang, Fei; Hansen, Ole
2014-01-01
that the electrostatic transducer force is related to the voltage output and cannot be approximated by viscous damping or a Coulomb force as reported previously. The coupled model with two simultaneous differential equations is numerically solved for the voltage output and transduction force with given parameters...
A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage
International Nuclear Information System (INIS)
Dominković, D.F.; Ćosić, B.; Bačelić Medić, Z.; Duić, N.
2015-01-01
Highlights: • Hybrid optimization model of biomass trigeneration system with PTES is developed. • Influence of premium feed-in tariffs on trigeneration systems is assessed. • Influence of total system efficiency on biomass trigeneration system with PTES is assessed. • Influence of energy savings on project economy is assessed. - Abstract: This paper provides a solution for managing excess heat production in trigeneration and thus, increases the power plant yearly efficiency. An optimization model for combining biomass trigeneration energy system and pit thermal energy storage has been developed. Furthermore, double piping district heating and cooling network in the residential area without industry consumers was assumed, thus allowing simultaneous flow of the heating and cooling energy. As a consequence, the model is easy to adopt in different regions. Degree-hour method was used for calculation of hourly heating and cooling energy demand. The system covers all the yearly heating and cooling energy needs, while it is assumed that all the electricity can be transferred to the grid due to its renewable origin. The system was modeled in Matlab© on hourly basis and hybrid optimization model was used to maximize the net present value (NPV), which was the objective function of the optimization. Economic figures become favorable if the economy-of-scale of both power plant and pit thermal energy storage can be utilized. The results show that the pit thermal energy storage was an excellent option for storing energy and shaving peaks in energy demand. Finally, possible switch from feed-in tariffs to feed-in premiums was assessed and possible subsidy savings have been calculated. The savings are potentially large and can be used for supporting other renewable energy projects
Global optimization of proteins using a dynamical lattice model: Ground states and energy landscapes
Dressel, F.; Kobe, S.
2004-01-01
A simple approach is proposed to investigate the protein structure. Using a low complexity model, a simple pairwise interaction and the concept of global optimization, we are able to calculate ground states of proteins, which are in agreement with experimental data. All possible model structures of small proteins are available below a certain energy threshold. The exact lowenergy landscapes for the trp cage protein (1L2Y) is presented showing the connectivity of all states and energy barriers.
Building Energy Modeling and Control Methods for Optimization and Renewables Integration
Burger, Eric M.
dynamics within a building by learning from sensor data. Control techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following. This dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.
Multi-objective optimization and simulation model for the design of distributed energy systems
International Nuclear Information System (INIS)
Falke, Tobias; Krengel, Stefan; Meinerzhagen, Ann-Kathrin; Schnettler, Armin
2016-01-01
Highlights: • Development of a model for the optimal design of district energy systems. • Multi-objective approach: integrated economic and ecological optimization. • Consideration of conventional conversion technologies, RES and district heating. • Decomposition of optimization problem to reduce computation complexity. • Approach enables the investigation of districts with more than 150 buildings. - Abstract: In this paper, a multi-objective optimization model for the investment planning and operation management of distributed heat and electricity supply systems is presented. Different energy efficiency measures and supply options are taken into account, including various distributed heat and power generation units, storage systems and energy-saving renovation measures. Furthermore, district heating networks are considered as an alternative to conventional, individual heat supply for each building. The optimization problem is decomposed into three subproblems to reduce the computational complexity. This enables a high level of detail in the optimization and simultaneously the comprehensive investigation of districts with more than 100 buildings. These capabilities distinguish the model from previous approaches in this field of research. The developed model is applied to a district in a medium-sized town in Germany in order to analyze the effects of different efficiency measures regarding total costs and emissions of CO 2 equivalents. Based on the Pareto efficient solutions, technologies and efficiency measures that can contribute most efficiently to reduce greenhouse gas emissions are identified.
A system-level cost-of-energy wind farm layout optimization with landowner modeling
International Nuclear Information System (INIS)
Chen, Le; MacDonald, Erin
2014-01-01
Highlights: • We model the role of landowners in determining the success of wind projects. • A cost-of-energy (COE) model with realistic landowner remittances is developed. • These models are included in a system-level wind farm layout optimization. • Basic verification indicates the optimal COE is in-line with real-world data. • Land plots crucial to a project’s success can be identified with the approach. - Abstract: This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustry. The system-level cost-of-energy (COE) optimization model is also tested under two land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability
A cost optimization model for 100% renewable residential energy supply systems
DEFF Research Database (Denmark)
Milan, Christian; Bojesen, Carsten; Nielsen, Mads Pagh
2012-01-01
The concept of net zero energy buildings (Net ZEB) has received increased attention throughout the last years. A well adapted and optimized design of the energy supply system is crucial for the performance of these buildings. To achieve this, a holistic approach is needed which accounts for the i......The concept of net zero energy buildings (Net ZEB) has received increased attention throughout the last years. A well adapted and optimized design of the energy supply system is crucial for the performance of these buildings. To achieve this, a holistic approach is needed which accounts......'s involving on-site production of heat and electricity in combination with electricity exchanged with the public grid. The model is based on linear programming and determines the optimal capacities for each relevant supply technology in terms of the overall system costs. It has been successfully applied...
International Nuclear Information System (INIS)
Maroufmashat, Azadeh; Elkamel, Ali; Fowler, Michael; Sattari, Sourena; Roshandel, Ramin; Hajimiragha, Amir; Walker, Sean; Entchev, Evgueniy
2015-01-01
Energy hubs that incorporate a variety of energy generation and energy transformation technologies can be used to provide the energy storage needed to enable the efficient operation of a ‘smart energy network’. When these hubs are combined as a network and allowed to exchange energy, they create efficiency advantages in both financial and environmental performance. Further, the interconnectedness of the energy network design provides an added layer of reliability. In this paper, a complex network of energy hubs is modeled and optimized under different scenarios to examine both the financial viability and potential reduction of greenhouse gas emissions. Two case studies consisting of two and three energy hubs within a network are considered. The modeling Scenarios vary according to the consideration of distributed energy systems and energy interaction between energy hubs. In the case of a network of two energy hubs, there is no significant economic or emissions benefit with only a 0.5% reduction in total cost and 3% reduction in CO_2 emission. In the case of a network of three energy hubs, there is a significant economic benefit ranging from 11% to 29%, and 11% emission reduction benefit, as well as a 13% reduction in natural gas consumption. - Highlights: • The generic form of the modified energy hub concept with network model is presented. • Two case studies are presented to demonstrate the benefits of energy hub network. • Distributed energy is shown to provide economic and environmental advantages. • Multi criteria optimization of the economic and environmental performance is done.
Energy Technology Data Exchange (ETDEWEB)
Mashhour, Elahe; Moghaddas-Tafreshi, S.M. [Faculty of Electrical Engineering, K.N. Toosi University of Technology, Seyd Khandan, P.O. Box 16315-1355, Shariati, Tehran (Iran)
2010-04-15
This paper develops a multiperiod optimization model for an interconnected micro grid with hierarchical control that participates in wholesale energy market to maximize its benefit (i.e. revenues-costs). In addition to the operational constraints of distributed energy resources (DER) including both inter-temporal and non-inter-temporal types, the adequacy and steady-state security constraints of micro grid and its power losses are incorporated in the optimization model. In the presented model, DER are integrated into low voltage grid considering both technical and economical aspects. This integration as a micro grid can participate in wholesale energy market as an entity with dual role including producer and consumer based on the direction of exchanged power. The developed model is evaluated by testing on a micro grid considering different cases and the results are analyzed. (author)
Analytic model for ultrasound energy receivers and their optimal electric loads
Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.
2017-08-01
In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.
Directory of Open Access Journals (Sweden)
Hye Yeon Kim
2016-03-01
Full Text Available This study suggests an optimization method for the life cycle cost (LCC in an economic feasibility analysis when applying energy saving techniques in the early design stage of a building. Literature and previous studies were reviewed to select appropriate optimization and LCC analysis techniques. The energy simulation (Energy Plus and computational program (MATLAB were linked to provide an automated optimization process. From the results, it is suggested that this process could outline the cost optimization model with which it is possible to minimize the LCC. To aid in understanding the model, a case study on an industrial building was performed to outline the operations of the cost optimization model including energy savings. An energy optimization model was also presented to illustrate the need for the cost optimization model.
DEFF Research Database (Denmark)
Guedes, J.M.; Rodrigues, H.C.; Bendsøe, Martin P.
2003-01-01
This paper describes a computational model, based on inverse homogenization and topology design, for approximating energy bounds for two-phase composites under multiple load cases. The approach allows for the identification of possible single-scale cellular materials that give rise to the optimal...
Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel
2014-01-01
The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.
Directory of Open Access Journals (Sweden)
Xiuli Zhao
2014-01-01
Full Text Available The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.
Model of a single mode energy harvester and properties for optimal power generation
International Nuclear Information System (INIS)
Liao Yabin; Sodano, Henry A
2008-01-01
The process of acquiring the energy surrounding a system and converting it into usable electrical energy is termed power harvesting. In the last few years, the field of power harvesting has experienced significant growth due to the ever increasing desire to produce portable and wireless electronics with extended life. Current portable and wireless devices must be designed to include electrochemical batteries as the power source. The use of batteries can be troublesome due to their finite energy supply, which necessitates their periodic replacement. In the case of wireless sensors that are to be placed in remote locations, the sensor must be easily accessible or of disposable nature to allow the device to function over extended periods of time. Energy scavenging devices are designed to capture the ambient energy surrounding the electronics and covert it into usable electrical energy. The concept of power harvesting works towards developing self-powered devices that do not require replaceable power supplies. The development of energy harvesting systems is greatly facilitated by an accurate model to assist in the design of the system. This paper will describe a theoretical model of a piezoelectric based energy harvesting system that is simple to apply yet provides an accurate prediction of the power generated around a single mode of vibration. Furthermore, this model will allow optimization of system parameters to be studied such that maximal performance can be achieved. Using this model an expression for the optimal resistance and a parameter describing the energy harvesting efficiency will be presented and evaluated through numerical simulations. The second part of this paper will present an experimental validation of the model and optimal parameters
Prediction of energy demands using neural network with model identification by global optimization
Energy Technology Data Exchange (ETDEWEB)
Yokoyama, Ryohei; Wakui, Tetsuya; Satake, Ryoichi [Department of Mechanical Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan)
2009-02-15
To operate energy supply plants properly from the viewpoints of stable energy supply, and energy and cost savings, it is important to predict energy demands accurately as basic conditions. Several methods of predicting energy demands have been proposed, and one of them is to use neural networks. Although local optimization methods such as gradient ones have conventionally been adopted in the back propagation procedure to identify the values of model parameters, they have the significant drawback that they can derive only local optimal solutions. In this paper, a global optimization method called ''Modal Trimming Method'' proposed for non-linear programming problems is adopted to identify the values of model parameters. In addition, the trend and periodic change are first removed from time series data on energy demand, and the converted data is used as the main input to a neural network. Furthermore, predicted values of air temperature and relative humidity are considered as additional inputs to the neural network, and their effect on the prediction of energy demand is investigated. This approach is applied to the prediction of the cooling demand in a building used for a bench mark test of a variety of prediction methods, and its validity and effectiveness are clarified. (author)
International Nuclear Information System (INIS)
Kuznetsova, Elizaveta; Li, Yan-Fu; Ruiz, Carlos; Zio, Enrico
2014-01-01
Highlights: • Microgrid composed of a train station, wind power plant and district is investigated. • Each player is modeled as an individual agent aiming at a particular goal. • Prediction Intervals quantify the uncertain operational and environmental parameters. • Optimal goal-directed actions planning is achieved with robust optimization. • Optimization framework improves system reliability and decreases power imbalances. - Abstract: A microgrid energy management framework for the optimization of individual objectives of microgrid stakeholders is proposed. The framework is exemplified by way of a microgrid that is connected to an external grid via a transformer and includes the following players: a middle-size train station with integrated photovoltaic power production system, a small energy production plant composed of urban wind turbines, and a surrounding district including residences and small businesses. The system is described by Agent-Based Modelling (ABM), in which each player is modelled as an individual agent aiming at a particular goal, (i) decreasing its expenses for power purchase or (ii) increasing its revenues from power selling. The context in which the agents operate is uncertain due to the stochasticity of operational and environmental parameters, and the technical failures of the renewable power generators. The uncertain operational and environmental parameters of the microgrid are quantified in terms of Prediction Intervals (PIs) by a Non-dominated Sorting Genetic Algorithm (NSGA-II) – trained Neural Network (NN). Under these uncertainties, each agent is seeking for optimal goal-directed actions planning by Robust Optimization (RO). The developed framework is shown to lead to an increase in system performance, evaluated in terms of typical reliability (adequacy) indicators for energy systems, such as Loss of Load Expectation (LOLE) and Loss of Expected Energy (LOEE), in comparison with optimal planning based on expected values of
Osman, Ayat E.
Energy use in commercial buildings constitutes a major proportion of the energy consumption and anthropogenic emissions in the USA. Cogeneration systems offer an opportunity to meet a building's electrical and thermal demands from a single energy source. To answer the question of what is the most beneficial and cost effective energy source(s) that can be used to meet the energy demands of the building, optimizations techniques have been implemented in some studies to find the optimum energy system based on reducing cost and maximizing revenues. Due to the significant environmental impacts that can result from meeting the energy demands in buildings, building design should incorporate environmental criteria in the decision making criteria. The objective of this research is to develop a framework and model to optimize a building's operation by integrating congregation systems and utility systems in order to meet the electrical, heating, and cooling demand by considering the potential life cycle environmental impact that might result from meeting those demands as well as the economical implications. Two LCA Optimization models have been developed within a framework that uses hourly building energy data, life cycle assessment (LCA), and mixed-integer linear programming (MILP). The objective functions that are used in the formulation of the problems include: (1) Minimizing life cycle primary energy consumption, (2) Minimizing global warming potential, (3) Minimizing tropospheric ozone precursor potential, (4) Minimizing acidification potential, (5) Minimizing NOx, SO 2 and CO2, and (6) Minimizing life cycle costs, considering a study period of ten years and the lifetime of equipment. The two LCA optimization models can be used for: (a) long term planning and operational analysis in buildings by analyzing the hourly energy use of a building during a day and (b) design and quick analysis of building operation based on periodic analysis of energy use of a building in a
Leśko, Michał; Bujalski, Wojciech
2017-12-01
The aim of this document is to present the topic of modeling district heating systems in order to enable optimization of their operation, with special focus on thermal energy storage in the pipelines. Two mathematical models for simulation of transient behavior of district heating networks have been described, and their results have been compared in a case study. The operational optimization in a DH system, especially if this system is supplied from a combined heat and power plant, is a difficult and complicated task. Finding a global financial optimum requires considering long periods of time and including thermal energy storage possibilities into consideration. One of the most interesting options for thermal energy storage is utilization of thermal inertia of the network itself. This approach requires no additional investment, while providing significant possibilities for heat load shifting. It is not feasible to use full topological models of the networks, comprising thousands of substations and network sections, for the purpose of operational optimization with thermal energy storage, because such models require long calculation times. In order to optimize planned thermal energy storage actions, it is necessary to model the transient behavior of the network in a very simple way - allowing for fast and reliable calculations. Two approaches to building such models have been presented. Both have been tested by comparing the results of simulation of the behavior of the same network. The characteristic features, advantages and disadvantages of both kinds of models have been identified. The results can prove useful for district heating system operators in the near future.
Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.
2017-10-01
In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.
External costs in the global energy optimization models. A tool in favour of sustain ability
International Nuclear Information System (INIS)
Cabal Cuesta, H.
2007-01-01
The aim of this work is the analysis of the effects of the GHG external costs internalization in the energy systems. This may provide a useful tool to support decision makers to help reaching the energy systems sustain ability. External costs internalization has been carried out using two methods. First, CO 2 externalities of different power generation technologies have been internalized to evaluate their effects on the economic competitiveness of these present and future technologies. The other method consisted of analysing and optimizing the global energy system, from an economic and environmental point of view, using the global energy optimization model generator, TIMES, with a time horizon of 50 years. Finally, some scenarios regarding environmental and economic strategic measures have been analysed. (Author)
A Model for Optimization and Analysis of Energy Flexible Boiler Plants for Building Heating Purposes
Energy Technology Data Exchange (ETDEWEB)
Nielsen, J R
1996-05-01
This doctoral thesis presents a model for optimization and analysis of boiler plants. The model optimizes a boiler plant with respect to the annual total costs or with respect to energy consumption. The optimum solution is identified for a given number of energy carriers and defined characteristics of the heat production units. The number of heat production units and the capacity of units related to each energy carrier or the capacity of units related to the same energy carrier can be found. For a problem comprising large variation during a defined analysis period the model gives the operating costs and energy consumption to be used in an extended optimization. The model can be used to analyse the consequences with respect to costs and energy consumption due to capacity margins and shifts in the boundary conditions. The model is based on a search approach comprising an operational simulator. The simulator is based on a marginal cost method and dynamic programming. The simulation is performed on an hourly basis. A general boiler characteristic representation is maintained by linear energy or cost functions. The heat pump characteristics are represented by tabulated performance and efficiency as function of state and nominal aggregate capacities. The simulation procedure requires a heat load profile on an hourly basis. The problem of the presence of capacity margins in boiler plants is studied for selected cases. The single-boiler, oil-fired plant is very sensitive to the magnitude of the losses present during burner off-time. For a plant comprising two oil-fired burners, the impact of a capacity margin can be dampened by the selected capacity configuration. The present incentive, in Norway, to install an electric element boiler in an oil-fired boiler plant is analysed. 77 refs., 74 figs., 12 tabs.
Escriva-Bou, A.; Lund, J. R.; Pulido-Velazquez, M.; Spang, E. S.; Loge, F. J.
2014-12-01
Although most freshwater resources are used in agriculture, a greater amount of energy is consumed per unit of water supply for urban areas. Therefore, efforts to reduce the carbon footprint of water in cities, including the energy embedded within household uses, can be an order of magnitude larger than for other water uses. This characteristic of urban water systems creates a promising opportunity to reduce global greenhouse gas emissions, particularly given rapidly growing urbanization worldwide. Based on a previous Water-Energy-CO2 emissions model for household water end uses, this research introduces a probabilistic two-stage optimization model considering technical and behavioral decision variables to obtain the most economical strategies to minimize household water and water-related energy bills given both water and energy price shocks. Results show that adoption rates to reduce energy intensive appliances increase significantly, resulting in an overall 20% growth in indoor water conservation if household dwellers include the energy cost of their water use. To analyze the consequences on a utility-scale, we develop an hourly water-energy model based on data from East Bay Municipal Utility District in California, including the residential consumption, obtaining that water end uses accounts for roughly 90% of total water-related energy, but the 10% that is managed by the utility is worth over 12 million annually. Once the entire end-use + utility model is completed, several demand-side management conservation strategies were simulated for the city of San Ramon. In this smaller water district, roughly 5% of total EBMUD water use, we found that the optimal household strategies can reduce total GHG emissions by 4% and utility's energy cost over 70,000/yr. Especially interesting from the utility perspective could be the "smoothing" of water use peaks by avoiding daytime irrigation that among other benefits might reduce utility energy costs by 0.5% according to our
State-of-The-Art of Modeling Methodologies and Optimization Operations in Integrated Energy System
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.
Compromises in energy policy-Using fuzzy optimization in an energy systems model
International Nuclear Information System (INIS)
Martinsen, Dag; Krey, Volker
2008-01-01
Over the last year in Germany a great many political discussions have centered around the future direction of energy and climate policy. Due to a number of events related to energy prices, security of supply and climate change, it has been necessary to develop cornerstones for a new integrated energy and climate policy. To supplement this decision process, model-based scenarios were used. In this paper we introduce fuzzy constraints to obtain a better representation of political decision processes, in particular, to find compromises between often contradictory targets (e.g. economic, environmentally friendly and secure energy supply). A number of policy aims derived from a review of the ongoing political discussions were formulated as fuzzy constraints to explicitly include trade-offs between various targets. The result is an overall satisfaction level of about 60% contingent upon the following restrictions: share of energy imports, share of biofuels, share of CHP electricity, CO 2 reduction target and use of domestic hard coal. The restrictions for the share of renewable electricity, share of renewable heat, energy efficiency and postponement of nuclear phase out have higher membership function values, i.e. they are not binding and therefore get done on the side
An approach to modeling and optimization of integrated renewable energy system (ires)
Maheshwari, Zeel
The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable strategy that can be employed to harness renewable energy resources to energize remote rural areas of developing countries. The resource- need matching, which is the basis for IRES makes it possible to provide energy in an efficient and cost effective manner. Modeling and optimization of IRES for a selected study area makes IRES more advantageous when compared to hybrid concepts. A remote rural area with a population of 700 in 120 households and 450 cattle is considered as an example for cost analysis and optimization. Mathematical models for key components of IRES such as biogas generator, hydropower generator, wind turbine, PV system and battery banks are developed. A discussion of the size of water reservoir required is also presented. Modeling of IRES on the basis of need to resource and resource to need matching is pursued to help in optimum use of resources for the needs. Fixed resources such as biogas and water are used in prioritized order whereas movable resources such as wind and solar can be used simultaneously for different priorities. IRES is cost optimized for electricity demand using HOMER software that is developed by the NREL (National Renewable Energy Laboratory). HOMER optimizes configuration for electrical demand only and does not consider other demands such as biogas for cooking and water for domestic and irrigation purposes. Hence an optimization program based on the need-resource modeling of IRES is performed in MATLAB. Optimization of the utilization of resources for several needs is performed. Results obtained from MATLAB clearly show that the available resources can fulfill the demand of the rural areas. Introduction of IRES in rural communities has many socio-economic implications. It brings about improvement in living
International Nuclear Information System (INIS)
Wu, Y.J.; Rosen, M.A.
1999-01-01
Energy equilibrium models can be valuable aids in energy planning and decision-making. In such models, supply is represented by a cost-minimizing linear submodel and demand by a smooth vector-valued function of prices. In this paper, we use the energy equilibrium model to study conventional systems and cogeneration-based district energy (DE) systems for providing heating, cooling and electrical services, not only to assess the potential economic and environmental benefits of cogeneration-based DE systems, but also to develop optimal configurations while accounting for such factors as economics and environmental impact. The energy equilibrium model is formulated and solved with software called WATEMS, which uses sequential non-linear programming to calculate the intertemporal equilibrium of energy supplies and demands. The methods of analysis and evaluation for the economic and environmental impacts are carefully explored. An illustrative energy equilibrium model of conventional and cogeneration-based DE systems is developed within WATEMS to compare quantitatively the economic and environmental impacts of those systems for various scenarios. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
Multistage Stochastic Programming and its Applications in Energy Systems Modeling and Optimization
Golari, Mehdi
Electric energy constitutes one of the most crucial elements to almost every aspect of life of people. The modern electric power systems face several challenges such as efficiency, economics, sustainability, and reliability. Increase in electrical energy demand, distributed generations, integration of uncertain renewable energy resources, and demand side management are among the main underlying reasons of such growing complexity. Additionally, the elements of power systems are often vulnerable to failures because of many reasons, such as system limits, weak conditions, unexpected events, hidden failures, human errors, terrorist attacks, and natural disasters. One common factor complicating the operation of electrical power systems is the underlying uncertainties from the demands, supplies and failures of system components. Stochastic programming provides a mathematical framework for decision making under uncertainty. It enables a decision maker to incorporate some knowledge of the intrinsic uncertainty into the decision making process. In this dissertation, we focus on application of two-stage and multistage stochastic programming approaches to electric energy systems modeling and optimization. Particularly, we develop models and algorithms addressing the sustainability and reliability issues in power systems. First, we consider how to improve the reliability of power systems under severe failures or contingencies prone to cascading blackouts by so called islanding operations. We present a two-stage stochastic mixed-integer model to find optimal islanding operations as a powerful preventive action against cascading failures in case of extreme contingencies. Further, we study the properties of this problem and propose efficient solution methods to solve this problem for large-scale power systems. We present the numerical results showing the effectiveness of the model and investigate the performance of the solution methods. Next, we address the sustainability issue
DEFF Research Database (Denmark)
Karlsson, Kenneth Bernard; Meibom, Peter
2008-01-01
that with an oil price at 100 $/barrel, a CO2 price at40 €/ton and the assumed penetration of hydrogen in the transport sector, it is economically optimal to cover more than 95% of the primary energy consumption for electricity and district heat by renewables in 2050. When the transport sector is converted......: A model for analyses of the electricity and CHP markets in the Baltic Sea Region. 〈www.Balmorel.com〉; 2001. [1
The Model of Optimization of Micro Energy; HOMER: El Modelo de Optimizacin de Micro energa
Energy Technology Data Exchange (ETDEWEB)
2004-05-01
HOMER, the model of optimization of micro energy, helps to disear systems out of the network and interconnected to the network. You can use HOMER to carry out the analysis to explore an extensive rank of questions of diseo. HOMER, el modelo de optimizacin de micro energa, le ayuda a disear sistemas fuera de la red e interconectados a la red. Usted puede usar HOMER para llevar a cabo el anlisis para explorar un amplio rango de preguntas de diseo.
Formulating an optimal long-term energy supply strategy for Syria using MESSAGE model
International Nuclear Information System (INIS)
Hainoun, A.; Seif Aldin, M.; Almoustafa, S.
2010-01-01
An optimal long-term energy supply strategy has been formulated based on minimizing the total system costs for the entire study period 2003-2030. The national energy chain was modelled covering all energy levels and conversion technologies. The results indicate that the primary energy will grow at annual average rate of 4.8% arriving 68 Mtoe in 2030. The total installed electric capacity will be optimally expanded from 6885 to 19500 MW in 2030. Furthermore, to ensure supply security the future national energy system will rely mainly upon oil and natural gas (NG) with limited contribution of renewables and nuclear to the end of study period. The share of NG will increase gradually up to 2020 and then retreat. Owing to the continuous decrease of oil production, oil export is expected to vanish in 2012 and the country will import about 63% of its primary energy demand in 2030. Thus, the expected long-term development of national energy sector indicates a hard challenge for the future national economy. The employing of sensitivity analysis clarifies the importance of wind turbines operation time and discount rate. The analysis proves that nuclear option is insensitive to overnight cost increase up to 85% of the reference case value.
Energy Technology Data Exchange (ETDEWEB)
Didriksen, H.; Sandvig Nielsen, J.; Weel Hansen, M.
2001-06-01
The aim of the project is to present a procedure to optimize existing drying processes. The optimization deals with energy consumption, capacity utilization and product quality. Other factors can also be included in the optimization, e.g. minimization of volume of discharged air. The optimization of existing drying processes will use calculation tool based on a mathematical simulation model for the process to calculate the most optimum operation situation on the basis of given conditions. In the project mathematical models have been developed precisely with this aim. The calculation tools have been developed with a user interface so that the tools can be used by technical staff in industrial companies and by consultants. The project also illustrates control of drying processes. Based on the developed models, the effect of using different types of control strategies by means of model simulations is illustrated. Three types of drying processes are treated: drum dryers, disc dryers and drying chambers. The work with the development of the simulation models has been very central in the project, as these have to be the basis for the optimization of the processes. The work is based on a large amount of information from academical literature and knowledge and experience about modelling thermal processes at dk-TEKNIK. The models constitute the core in the simulation programmes. The models describe the most important physical effects in connection with mass and energy transfer and transport under the drying for the three treated drying technologies. (EHS)
Yang, Sam
The dissertation presents the mathematical formulation, experimental validation, and application of a volume element model (VEM) devised for modeling, simulation, and optimization of energy systems in their early design stages. The proposed model combines existing modeling techniques and experimental adjustment to formulate a reduced-order model, while retaining sufficient accuracy to serve as a practical system-level design analysis and optimization tool. In the VEM, the physical domain under consideration is discretized in space using lumped hexahedral elements (i.e., volume elements), and the governing equations for the variable of interest are applied to each element to quantify diverse types of flows that cross it. Subsequently, a system of algebraic and ordinary differential equations is solved with respect to time and scalar (e.g., temperature, relative humidity, etc.) fields are obtained in both spatial and temporal domains. The VEM is capable of capturing and predicting dynamic physical behaviors in the entire system domain (i.e., at system level), including mutual interactions among system constituents, as well as with their respective surroundings and cooling systems, if any. The VEM is also generalizable; that is, the model can be easily adapted to simulate and optimize diverse systems of different scales and complexity and attain numerical convergence with sufficient accuracy. Both the capability and generalizability of the VEM are demonstrated in the dissertation via thermal modeling and simulation of an Off-Grid Zero Emissions Building, an all-electric ship, and a vapor compression refrigeration (VCR) system. Furthermore, the potential of the VEM as an optimization tool is presented through the integrative thermodynamic optimization of a VCR system, whose results are used to evaluate the trade-offs between various objective functions, namely, coefficient of performance, second law efficiency, pull-down time, and refrigerated space temperature, in
International Nuclear Information System (INIS)
Ibrahim, Oussama; Fardoun, Farouk; Younes, Rafic; Louahlia-Gualous, Hasna
2014-01-01
This paper presents a dynamic simulation model to predict the performance of an ASHPWH (air source heat pump water heater). The developed model is used to assess its performance in the Lebanese context. It is shown that for the four Lebanese climatic zones, the expected monthly values of the average COP (coefficient of performance) varies from 2.9 to 5, leading to high efficiencies compared with conventional electric water heaters. The energy savings and GHG (greenhouse gas) emissions reduction are investigated for each zone. Furthermore, it is recommended to use the ASHPWH during the period of highest daily ambient temperatures (noon or afternoon), assuming that the electricity tariff and hot water loads are constant. In addition, an optimal management model for the ASHPWH is developed and applied for a typical winter day of Beirut. Moreover, the developed dynamic model of ASHPWH is used to compare the performance of three similar systems that differ only with the condenser geometry, where results show that using mini-condenser geometries increase the COP (coefficient of performance) and consequently, more energy is saved as well as more GHG emissions are reduced. In addition, the condenser “surface compactness” is increased giving rise to an efficient compact heat exchanger. - Highlights: • Numerical modeling and experimental validation for ASHPWH (air source heat pump water heater). • Optimization of the ASHPWH-condenser length. • Comparison of the ASHPWH with conventional electric water heater according to energy efficiency and green gas house emissions. • Development of an energetic-economic optimal management model for ASHPWH. • Energetic and environmental assessment of ASHPWH with mini-tubes condensers
Integrating rooftop solar into a multi-source energy planning optimization model
International Nuclear Information System (INIS)
Arnette, Andrew N.
2013-01-01
Highlights: • There is significant technical capacity for rooftop solar installations. • Rooftop solar generation is heavily dependent on key parameters. • Rooftop solar should be one of several options for increasing renewable energy. • Renewable energy planning should consider both cost and benefits. - Abstract: This research uses an optimization model to compare the role of rooftop solar generation versus large-scale solar and wind farm installations in renewable energy planning. The model consists of competing objectives, minimizing annual generation costs and minimizing annual greenhouse gas emissions. Rather than focus on the individual consumer’s investment decision, over 20 scenarios were developed which explored key input parameters such as the maximum penetration level of rooftop solar installations, pricing of equipment, tax credits, and net-metering policy to determine what role rooftop solar plays in renewable energy investment at an aggregate level. The research finds that at lower levels of penetration, such as those currently found in the United States, other renewable energy sources remain viable options, thus rooftop solar should be just one option considered when increasing development of renewable energy sources. The research also shows that a balanced approach taking into account both of the opposing objectives will lead to greater levels of rooftop solar generation than focusing solely on cost or emissions. Therefore, rooftop solar should be considered as part of an overall balanced approach to increasing renewable energy generation
Evaluating biomass energy strategies for a UK eco-town with an MILP optimization model
International Nuclear Information System (INIS)
Keirstead, James; Samsatli, Nouri; Pantaleo, A. Marco; Shah, Nilay
2012-01-01
Recent years have shown a marked interest in the construction of eco-towns, showcase developments intended to demonstrate the best in ecologically-sensitive and energy-efficient construction. This paper examines one such development in the UK and considers the role of biomass energy systems. We present an integrated resource modelling framework that identifies an optimized low-cost energy supply system including the choice of conversion technologies, fuel sources, and distribution networks. Our analysis shows that strategies based on imported wood chips, rather than locally converted forestry residues, burned in a mix of ICE and ORC combined heat and power facilities offer the most promise. While there are uncertainties surrounding the precise environmental impacts of these solutions, it is clear that such biomass systems can help eco-towns to meet their target of an 80% reduction in greenhouse gas emissions. -- Highlights: ► An optimization model for urban biomass energy system design is presented. ► Tool selects technologies, operating rates, supply infrastructures. ► Five technology scenarios evaluated for a UK eco-town proposal. ► Results show ICE and ORC CHP units, fed by wood chips, promising. ► Results show biomass can help eco-towns achieve 80% GHG emission reductions.
Jayaweera, H. M. P. C.; Muhtaroğlu, Ali
2016-11-01
A novel model based methodology is presented to determine optimal device parameters for the fully integrated ultra low voltage DC-DC converter for energy harvesting applications. The proposed model feasibly contributes to determine the maximum efficient number of charge pump stages to fulfill the voltage requirement of the energy harvester application. The proposed DC-DC converter based power consumption model enables the analytical derivation of the charge pump efficiency when utilized simultaneously with the known LC tank oscillator behavior under resonant conditions, and voltage step up characteristics of the cross-coupled charge pump topology. The verification of the model has been done using a circuit simulator. The optimized system through the established model achieves more than 40% maximum efficiency yielding 0.45 V output with single stage, 0.75 V output with two stages, and 0.9 V with three stages for 2.5 kΩ, 3.5 kΩ and 5 kΩ loads respectively using 0.2 V input.
Optimal energy-utilization ratio for long-distance cruising of a model fish
Liu, Geng; Yu, Yong-Liang; Tong, Bing-Gang
2012-07-01
The efficiency of total energy utilization and its optimization for long-distance migration of fish have attracted much attention in the past. This paper presents theoretical and computational research, clarifying the above well-known classic questions. Here, we specify the energy-utilization ratio (fη) as a scale of cruising efficiency, which consists of the swimming speed over the sum of the standard metabolic rate and the energy consumption rate of muscle activities per unit mass. Theoretical formulation of the function fη is made and it is shown that based on a basic dimensional analysis, the main dimensionless parameters for our simplified model are the Reynolds number (Re) and the dimensionless quantity of the standard metabolic rate per unit mass (Rpm). The swimming speed and the hydrodynamic power output in various conditions can be computed by solving the coupled Navier-Stokes equations and the fish locomotion dynamic equations. Again, the energy consumption rate of muscle activities can be estimated by the quotient of dividing the hydrodynamic power by the muscle efficiency studied by previous researchers. The present results show the following: (1) When the value of fη attains a maximum, the dimensionless parameter Rpm keeps almost constant for the same fish species in different sizes. (2) In the above cases, the tail beat period is an exponential function of the fish body length when cruising is optimal, e.g., the optimal tail beat period of Sockeye salmon is approximately proportional to the body length to the power of 0.78. Again, the larger fish's ability of long-distance cruising is more excellent than that of smaller fish. (3) The optimal swimming speed we obtained is consistent with previous researchers’ estimations.
International Nuclear Information System (INIS)
Chen, Xiao; Wang, Qian; Srebric, Jelena
2016-01-01
Highlights: • This study evaluates an occupant-feedback driven Model Predictive Controller (MPC). • The MPC adjusts indoor temperature based on a dynamic thermal sensation (DTS) model. • A chamber model for predicting chamber air temperature is developed and validated. • Experiments show that MPC using DTS performs better than using Predicted Mean Vote. - Abstract: In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants’ votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.
Modeling the optimal energy mix in 2030 : Impact of the integration of renewable energy sources
Arthur, Camu
2016-01-01
The European Council has recently set objectives in the matter of energy and climate policies and thus the interest in renewable energies is more than ever at stake. However, the introduction of renewable energies in an energy mix is also accelerated and altered by political targets. The two most widespread renewable technologies, photovoltaic and wind farms, have specific characteristics - decentralized, intermittency, uncertain production forecast up until a few hours ahead - that oblige to...
Active surface model improvement by energy function optimization for 3D segmentation.
Azimifar, Zohreh; Mohaddesi, Mahsa
2015-04-01
This paper proposes an optimized and efficient active surface model by improving the energy functions, searching method, neighborhood definition and resampling criterion. Extracting an accurate surface of the desired object from a number of 3D images using active surface and deformable models plays an important role in computer vision especially medical image processing. Different powerful segmentation algorithms have been suggested to address the limitations associated with the model initialization, poor convergence to surface concavities and slow convergence rate. This paper proposes a method to improve one of the strongest and recent segmentation algorithms, namely the Decoupled Active Surface (DAS) method. We consider a gradient of wavelet edge extracted image and local phase coherence as external energy to extract more information from images and we use curvature integral as internal energy to focus on high curvature region extraction. Similarly, we use resampling of points and a line search for point selection to improve the accuracy of the algorithm. We further employ an estimation of the desired object as an initialization for the active surface model. A number of tests and experiments have been done and the results show the improvements with regards to the extracted surface accuracy and computational time of the presented algorithm compared with the best and recent active surface models. Copyright © 2015 Elsevier Ltd. All rights reserved.
Optimization models to reduce CO2 emissions and energy consumption of transport in open pit mines
Energy Technology Data Exchange (ETDEWEB)
Alpizar, Maria J.; Morales, Nelson; Wiertz, Jaques [Universidad de Chile (Chile)
2010-07-01
In the mining industry, approximately 20% of total cost corresponds to material transportation and, in the case of copper, 25% of the total energy consumed for extraction. These high values, together with growing concerns over excess CO2 emissions, have motivated the development of the optimization models discussed in this paper. The objective was to introduce energy and environmental variables into production planning and scheduling. The methodology includes variables that can save transportation energy and models that decrease material rehandling and hence, the cost of transportation. Two types of variables were adapted in the model: environmental and energetic. The advantage, leaving aside the costs and mileage of transportation, was a reduction in emissions of CO2 and in the amount of diesel used. With the inclusion of blending constraints, this model could be used in milling or other such processes. The results are shown using graphs. It worth noting that rehandling decreased, Cu production increased, and the model was able to calculate the extraction sequence over all time horizons.
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
Integrated modeling approach for optimal management of water, energy and food security nexus
Zhang, Xiaodong; Vesselinov, Velimir V.
2017-03-01
Water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-period socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. The obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.
Yang, Jing; Zhang, Da-hai; Chen, Ying; Liang, Hui; Tan, Ming; Li, Wei; Ma, Xian-dong
2017-10-01
A novel floating pendulum wave energy converter (WEC) with the ability of tide adaptation is designed and presented in this paper. Aiming to a high efficiency, the buoy's hydrodynamic shape is optimized by enumeration and comparison. Furthermore, in order to keep the buoy's well-designed leading edge always facing the incoming wave straightly, a novel transmission mechanism is then adopted, which is called the tidal adaptation mechanism in this paper. Time domain numerical models of a floating pendulum WEC with or without tide adaptation mechanism are built to compare their performance on various water levels. When comparing these two WECs in terms of their average output based on the linear passive control strategy, the output power of WEC with the tide adaptation mechanism is much steadier with the change of the water level and always larger than that without the tide adaptation mechanism.
Weijermars, R.; Taylor, P.; Bahn, O.; Das, S.R.; Wei, Y.M.
2011-01-01
Organizational behavior and stakeholder processes continually influence energy strategy choices and decisions. Although theoretical optimizations can provide guidance for energy mix decisions from a pure physical systems engineering point of view, these solutions might not be optimal from a
Model-Based Energy Efficiency Optimization of a Low-Temperature Adsorption Dryer
Atuonwu, J.C.; Straten, G. van; Deventer, H.C. van; Boxtel, A.J.B. van
2011-01-01
Low-temperature drying is important for heat-sensitive products, but at these temperatures conventional convective dryers have low energy efficiencies. To overcome this challenge, an energy efficiency optimization procedure is applied to a zeolite adsorption dryer subject to product quality. The
Xia, Li
2014-11-20
This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.
Xia, Li; Shihada, Basem
2014-01-01
This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.
Directory of Open Access Journals (Sweden)
Junlian Gao
2018-05-01
Full Text Available Across the world, human activity is approaching planetary boundaries. In northwest China, in particular, the coal industry and agriculture are competing for key limited inputs of land and water. In this situation, the traditional approach to planning the development of each sector independently fails to deliver sustainable solutions, as solutions made in sectorial ‘silos’ are often suboptimal for the entire economy. We propose a spatially detailed cost-minimizing model for coal and agricultural production in a region under constraints on land and water availability. We apply the model to the case study of Shanxi province, China. We show how such an integrated optimization, which takes maximum advantage of the spatial heterogeneity in resource abundance, could help resolve the conflicts around the water–food–energy (WFE nexus and assist in its management. We quantify the production-possibility frontiers under different water-availability scenarios and demonstrate that in water-scarce regions, like Shanxi, the production capacity and corresponding production solutions are highly sensitive to water constraints. The shadow prices estimated in the model could be the basis for intelligent differentiated water pricing, not only to enable the water-resource transfer between agriculture and the coal industry, and across regions, but also to achieve cost-effective WFE management.
Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters
Fusco, Francesco; Ringwood, John
2010-01-01
Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if ...
MOBE: Final report; Modelling and Optimization of Biomass-based Energy production
Energy Technology Data Exchange (ETDEWEB)
Trangbaek, K [Aalborg Univ., Institut for Elektroniske Systemer, Aalborg (Denmark); Elmegaard, B [Danmarks Tekniske Univ., Institut for Mekanisk Teknologi, Kgs. Lyngby (Denmark)
2008-07-01
The present report is the documentation of the work in the PSO-project MOBE, ''Modelling and Optimization of biomass-based Energy production''. The aim of the project is to develop better control methods for boilers in central power plant units, so the plant will achieve better controllability with respect to load changes. in particular focus is on the low load operation near and below the Benson point. The introduction of the report includes a description of the challenges the central power stations see in the modern electricity market where wind power delivers a significant prioritized production, and thus, in connection with consumption variations, contributes to the load requirements of the central units. The report documents the work on development of a common simulation platform for the partners in the project and for future model work. The result of this is an integration between the DTU simulation code DNA and Matlab. Other possible tools are suggested. The modelling work in the project has resulted in preliminary studies of time constants of evaporator tubes, an analysis that shows that Ledinegg instabilities do not occur in modern boilers even at low load, development of a validated evaporator model that can be coupled to tools for control system development, and an analysis of two different configurations at the low load system of Benson boilers. Based in a validated power plant model different control strategies have been studied. Because constraints on control signals and temperature gradients are dominating, it is recommended to use model predictive control. It is demonstrated, how such a simulator can handle large low gradients without violating the constraints. By switching between different linearized models the whole load range may be covered. The project indicates that Model predictive control can improve the control in low low significantly. This should be studied further in future projects by realistic tests. At first these should be done with
MOBE: Final report; Modelling and Optimization of Biomass-based Energy production
Energy Technology Data Exchange (ETDEWEB)
Trangbaek, K. (Aalborg Univ., Institut for Elektroniske Systemer, Aalborg (Denmark)); Elmegaard, B. (Danmarks Tekniske Univ., Institut for Mekanisk Teknologi, Kgs. Lyngby (Denmark))
2008-07-01
The present report is the documentation of the work in the PSO-project MOBE, ''Modelling and Optimization of biomass-based Energy production''. The aim of the project is to develop better control methods for boilers in central power plant units, so the plant will achieve better controllability with respect to load changes. in particular focus is on the low load operation near and below the Benson point. The introduction of the report includes a description of the challenges the central power stations see in the modern electricity market where wind power delivers a significant prioritized production, and thus, in connection with consumption variations, contributes to the load requirements of the central units. The report documents the work on development of a common simulation platform for the partners in the project and for future model work. The result of this is an integration between the DTU simulation code DNA and Matlab. Other possible tools are suggested. The modelling work in the project has resulted in preliminary studies of time constants of evaporator tubes, an analysis that shows that Ledinegg instabilities do not occur in modern boilers even at low load, development of a validated evaporator model that can be coupled to tools for control system development, and an analysis of two different configurations at the low load system of Benson boilers. Based in a validated power plant model different control strategies have been studied. Because constraints on control signals and temperature gradients are dominating, it is recommended to use model predictive control. It is demonstrated, how such a simulator can handle large low gradients without violating the constraints. By switching between different linearized models the whole load range may be covered. The project indicates that Model predictive control can improve the control in low low significantly. This should be studied further in future projects by realistic tests. At first these
Directory of Open Access Journals (Sweden)
Shuai Su
2016-02-01
Full Text Available Increasing attention is being paid to the energy efficiency in metro systems to reduce the operational cost and to advocate the sustainability of railway systems. Classical research has studied the energy-efficient operational strategy and the energy-efficient system design separately to reduce the traction energy consumption. This paper aims to combine the operational strategies and the system design by analyzing how the infrastructure and vehicle parameters of metro systems influence the operational traction energy consumption. Firstly, a solution approach to the optimal train control model is introduced, which is used to design the Optimal Train Control Simulator(OTCS. Then, based on the OTCS, the performance of some important energy-efficient system design strategies is investigated to reduce the trains’ traction energy consumption, including reduction of the train mass, improvement of the kinematic resistance, the design of the energy-saving gradient, increasing the maximum traction and braking forces, introducing regenerative braking and timetable optimization. As for these energy-efficient strategies, the performances are finally evaluated using the OTCS with the practical operational data of the Beijing Yizhuang metro line. The proposed approach gives an example to quantitatively analyze the energy reduction of different strategies in the system design procedure, which may help the decision makers to have an overview of the energy-efficient performances and then to make decisions by balancing the costs and the benefits.
International Nuclear Information System (INIS)
Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong; Seon Park, Hyo
2014-01-01
The number of multi-family housing complexes (MFHCs) over 15 yr old in South Korea is expected to exceed 5 million by 2015. Accordingly, the demand for energy retrofit in the deteriorating MFHCs is rapidly increasing. This study aimed to develop a decision support model for establishing the optimal energy retrofit strategy for existing MFHCs. It can provide clear criteria for establishing the carbon emissions reduction target (CERT) and allow efficient budget allocation for conducting the energy retrofit. The CERT for “S” MFHC, one of MFHCs located in Seoul, as a case study, was set at 23.0% (electricity) and 27.9% (gas energy). In the economic and environmental assessment, it was determined that scenario #12 was the optimal scenario (ranked second with regard to NPV 40 (net present value at year 40) and third with regard to SIR 40 (saving to investment ratio at year 40). The proposed model could be useful for owners, construction managers, or policymakers in charge of establishing energy retrofit strategy for existing MFHCs. It could allow contractors in a competitive bidding process to rationally establish the CERT and select the optimal energy retrofit strategy. It can be also applied to any other country or sector in a global environment. - Highlights: • The proposed model was developed to establish the optimal energy retrofit strategy. • Advanced case-based reasoning was applied to establish the community-based CERT. • Energy simulation was conducted to analyze the effects of energy retrofit strategy. • The optimal strategy can be finally selected based on the LCC and LCCO 2 analysis. • It could be extended to any other country or sector in the global environment
International Nuclear Information System (INIS)
Almansoori, Ali; Betancourt-Torcat, Alberto
2015-01-01
Highlights: • A design optimization model for the power sector has been developed. • We examine the influence of exogenous variables in the UAE power infrastructure. • Subsidizing fuel prices will stimulate fossil-based electricity generation. • Carbon tax and higher fuel prices are suitable options to decrease air emissions. • Accounting the social benefits of emissions avoidance incentivizes diversification. - Abstract: A Mixed Integer Linear Programming (MILP) formulation is presented for the optimal design of the United Arab Emirates’ (UAE) power system. The model was formulated in the General Algebraic Modeling System (GAMS), which is a mathematical modeling language for programming and optimization. Previous studies have either focused on the estimation of the UAE’s energy demands or the simulation of the operation of power technologies to plan future electricity supply. However, these studies have used international simulation tools such as “MARKAL” and “MESSAGE”; whereas the present work presents an optimization model. The proposed design optimization model can be used to estimate the most suitable combination of power plants under CO 2 emission and alternative energy targets, carbon tax, and social benefits of air emissions avoidance. Although the proposed model was used to estimate the future power infrastructure in the UAE, the model includes several standard power technologies; thus, it can be extended to other countries. The proposed optimization model was verified using historical data of the UAE power sector operation in the year 2011. Likewise, the proposed model was used to study the 2020 UAE power sector operations under three scenarios: domestic vs. international natural gas prices (considering different carbon tax levels), social benefits of using low emission power technologies (e.g., renewable and nuclear), and CO 2 emission constraints. The results show that the optimization model is a practical tool for designing the
Application of optimization techniques on lumped HVAC models for energy conservation
Energy Technology Data Exchange (ETDEWEB)
Wemhoff, A.P. [Department of Mechanical Engineering, Villanova University, Villanova, PA 19085 (United States)
2010-12-15
Heating, ventilating, and air conditioning (HVAC) systems comprise nearly one third of annual household energy consumption in the United States. HVAC energy use can be reduced by applying controls. This study applies a novel control method on a system with arbitrary steady-state and transient load distributions. The new method uses multi-dimensional interpolation between optimized control configurations for various steady-state load distributions. Demonstration of the new method on a two-room HVAC system predicts power savings for an arbitrary steady load that is nearly equivalent to that using a Variable-Air-Volume (VAV) with chiller modulation. However, the new method provides better energy savings for arbitrary transient loads: 19% energy savings over an uncontrolled system compared to energy savings of 6% for a VAV with chiller modulation. The average transient temperature deviation from setpoint using the new method is slightly better than that using VAV with chiller modulation. (author)
Directory of Open Access Journals (Sweden)
Huan-huan Li
2015-01-01
Full Text Available Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.
Optimal Energy Consumption in Refrigeration Systems - Modelling and Non-Convex Optimisation
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Skovrup, Morten J.
2012-01-01
Supermarket refrigeration consumes substantial amounts of energy. However, due to the thermal capacity of the refrigerated goods, parts of the cooling capacity delivered can be shifted in time without deteriorating the food quality. In this study, we develop a realistic model for the energy...... consumption in super market refrigeration systems. This model is used in a Nonlinear Model Predictive Controller (NMPC) to minimise the energy used by operation of a supermarket refrigeration system. The model is non-convex and we develop a computational efficient algorithm tailored to this problem...
Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
International Nuclear Information System (INIS)
Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.
2014-01-01
Highlights: • Solar data was analyzed in the location under consideration. • A program was developed to simulate operation of the PV hybrid system. • Genetic algorithm was used to optimize the sizes of the hybrid system components. • The costs of the pollutant emissions were considered in the optimization. • It is cost effective to power houses in remote areas with such hybrid systems. - Abstract: A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. A scenario that depends on a standalone PV, and another one that depends on a backup source alone were analyzed in this study. The optimization was achieved via the usage of genetic algorithm. The objective function minimizes the COE while covering the load demand with a specified value for the loss of load probability (LLP). The global warming emissions costs have been taken into account in this optimization analysis. Solar radiation data is firstly analyzed, and the tilt angle of the PV panels is then optimized. It was discovered that powering a small rural community using this hybrid system is cost-effective and extremely beneficial when compared to extending the utility grid to supply these remote areas, or just using conventional sources for this purpose. This hybrid system decreases both operating costs and the emission of pollutants. The hybrid system that realized these optimization purposes is the one constructed from a combination of these sources
International Nuclear Information System (INIS)
Perković, Luka; Novosel, Tomislav; Pukšec, Tomislav; Ćosić, Boris; Mustafa, Manal; Krajačić, Goran; Duić, Neven
2016-01-01
Highlights: • A new methodology for optimal management of energy systems is proposed. • Critical excess of electricity production is reduced by optimizing the energy flows. • At the same time, the curtailment from the RES can be decreased. - Abstract: This paper presents a new approach for modeling energy flows in complex energy systems with parallel supply of fresh water and electricity. Such systems consist of renewable energy sources (RES), desalination plant, conventional power plants and the residual brine storage which is used as energy storage. The presented method is treating energy vectors in the system as control variables to provide the optimal solution in terms of the lowest critical excess of electricity production (CEEP) and highest possible share of RES in the supply mix. The optimal solution for supplying the demands for fresh water and electricity is always found within the framework of model constraints which are derived from the physical limitations of the system. The presented method enables the optimization of energy flows for a larger period of time. This increases the role of energy storage when higher integration of RES in the supply mix. The method is tested on a hypothetical case of Jordan for different levels of installed wind and PV capacities, as well as different sizes of the brine storage. Results show that increasing the optimization horizon from one hour to 24 h can reduce the CEEP by 80% and allow the increase of RES in the supply mix by more than 5% without violating the CEEP threshold limit of 5%. The activity of the energy (brine) storage is crucial for achieving this goal.
Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad
2018-02-01
The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Optimization in the energy sector
International Nuclear Information System (INIS)
2015-01-01
The implementation of the energy transition and the developments in the national and international Energy markets constantly require sound analysis and new answers. The symposium ''optimization in the energy sector'' gives an overview of methods and models that can be practically used for decision support. Storage and electromobility as demand flexibility are important factors for the long-term design of the German and European energy system. But methodological aspects such as the consideration of uncertainties at the conference an important place is given. A key issue is also the short and medium term further development of the electricity market design. Not only broadly but also in detail e.g. the standard benefit and intraday markets there is considerable potential for optimization, which will be discussed in the context of technical presentations. And in view of challenging market environment is also new approaches to portfolio management a great importance for the practice. Therefore we are convinced that the Conference and its results for energy companies, public services and new entrants in the energy industry as well are of interest as for consultants, authorities, associations and energy economic research institutes. [de
Energy Technology Data Exchange (ETDEWEB)
Stetter, Daniel
2014-04-10
As electricity generation based on volatile renewable resources is subject to fluctuations, data with high temporal and spatial resolution on their availability is indispensable for integrating large shares of renewable capacities into energy infrastructures. The scope of the present doctoral thesis is to enhance the existing energy modelling environment REMix in terms of (i.) extending the geographic coverage of the potential assessment tool REMix-EnDaT from a European to a global scale, (ii.) adding a new plant siting optimization module REMix-PlaSMo, capable of assessing siting effects of renewable power plants on the portfolio output and (iii.) adding a new alternating current power transmission model between 30 European countries and CSP electricity imports from power plants located in North Africa and the Middle East via high voltage direct current links into the module REMix-OptiMo. With respect to the global potential assessment tool, a thorough investigation is carried out creating an hourly global inventory of the theoretical potentials of the major renewable resources solar irradiance, wind speed and river discharge at a spatial resolution of 0.45°x0.45°. A detailed global land use analysis determines eligible sites for the installation of renewable power plants. Detailed power plant models for PV, CSP, wind and hydro power allow for the assessment of power output, cost per kWh and respective full load hours taking into account the theoretical potentials, technological as well as economic data. The so-obtined tool REMix-EnDaT can be used as follows: First, as an assessment tool for arbitrary geographic locations, countries or world regions, deriving either site-specific or aggregated installable capacities, cost as well as full load hour potentials. Second, as a tool providing input data such as installable capacities and hourly renewable electricity generation for further assessments using the modules REMix-PlasMo and OptiMo. The plant siting tool
International Nuclear Information System (INIS)
Stetter, Daniel
2014-01-01
As electricity generation based on volatile renewable resources is subject to fluctuations, data with high temporal and spatial resolution on their availability is indispensable for integrating large shares of renewable capacities into energy infrastructures. The scope of the present doctoral thesis is to enhance the existing energy modelling environment REMix in terms of (i.) extending the geographic coverage of the potential assessment tool REMix-EnDaT from a European to a global scale, (ii.) adding a new plant siting optimization module REMix-PlaSMo, capable of assessing siting effects of renewable power plants on the portfolio output and (iii.) adding a new alternating current power transmission model between 30 European countries and CSP electricity imports from power plants located in North Africa and the Middle East via high voltage direct current links into the module REMix-OptiMo. With respect to the global potential assessment tool, a thorough investigation is carried out creating an hourly global inventory of the theoretical potentials of the major renewable resources solar irradiance, wind speed and river discharge at a spatial resolution of 0.45°x0.45°. A detailed global land use analysis determines eligible sites for the installation of renewable power plants. Detailed power plant models for PV, CSP, wind and hydro power allow for the assessment of power output, cost per kWh and respective full load hours taking into account the theoretical potentials, technological as well as economic data. The so-obtined tool REMix-EnDaT can be used as follows: First, as an assessment tool for arbitrary geographic locations, countries or world regions, deriving either site-specific or aggregated installable capacities, cost as well as full load hour potentials. Second, as a tool providing input data such as installable capacities and hourly renewable electricity generation for further assessments using the modules REMix-PlasMo and OptiMo. The plant siting tool
International Nuclear Information System (INIS)
Ghatrehsamani, Shirin; Ebrahimi, Rahim; Kazi, Salim Newaz; Badarudin Badry, Ahmad; Sadeghinezhad, Emad
2016-01-01
The aim of this study was to determine the amount of input–output energy used in peach production and to develop an optimal model of production in Chaharmahal va Bakhtiari province, Iran. Data were collected from 100 producers by administering a questionnaire in face-to-face interviews. Farms were selected based on random sampling method. Results revealed that the total energy of production is 47,951.52 MJ/ha and the highest share of energy consumption belongs to chemical fertilizers (35.37%). Consumption of direct energy was 47.4% while indirect energy was 52.6%. Also, Total energy consumption was divided into two groups; renewable and non-renewable (19.2% and 80.8% respectively). Energy use efficiency, Energy productivity, Specific energy and Net energy were calculated as 0.433, 0.228 (kg/MJ), 4.38 (MJ/kg) and −27,161.722 (MJ/ha), respectively. According to the negative sign for Net energy, if special strategy is used, energy dismiss will decrease and negative effect of some parameters could be omitted. In the present case the amount is indicating decimate of production energy. In addition, energy efficiency was not high enough. Some of the input energies were applied to machinery, chemical fertilizer, water irrigation and electricity which had significant effect on increasing production and MPP (marginal physical productivity) was determined for variables. This parameter was positive for energy groups namely; machinery, diesel fuel, chemical fertilizer, water irrigation and electricity while it was negative for other kind of energy such as chemical pesticides and human labor. Finally, there is a need to pursue a new policy to force producers to undertake energy-efficient practices to establish sustainable production systems without disrupting the natural resources. In addition, extension activities are needed to improve the efficiency of energy consumption and to sustain the natural resources. - Highlights: • Replacing non-renewable energy with renewable
Directory of Open Access Journals (Sweden)
Farong Kou
2018-01-01
Full Text Available In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of a vehicle semi-active energy regenerative suspension with an electro-hydraulic actuator (EHA. In light of the proposed concept, a specific energy regenerative scheme is designed and a mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using a recursive least squares algorithm. On the basis of the system principle, the nonlinear model of the semi-active energy regenerative suspension with an EHA is built. Meanwhile, linear-quadratic-Gaussian control strategy of the system is designed. Then, the influence of the main parameters of the EHA on the damping performance and energy regenerative performance of the suspension is analyzed. Finally, the main parameters of the EHA are optimized via the genetic algorithm. The test results show that when a sinusoidal is input at the frequency of 2 Hz and the amplitude of 30 mm, the spring mass acceleration root meam square value of the optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and the energy regenerative power RMS value is increased by 40.51%, which means that while meeting the requirements of vehicle ride comfort and driving safety, the energy regenerative performance is improved significantly.
Modeling and optimization of energy consumption in multipurpose batch plants - 2006 Annual report
Energy Technology Data Exchange (ETDEWEB)
Szijjarto, A.
2006-12-15
This annual report for the Swiss Federal Office of Energy (SFOE) takes a look at the work done in 2006 on the development of a model that is able to make prognoses concerning the energy consumption of chemical batch processes and thus enable these to be optimised. In the year under review, reliable models and software modelling tools were developed. The tools are based on commercially available simulation software. The authors note that the bottom-up model presented in the previous reports is powerful and robust enough to treat a significant amount of the process data in reasonable time. The model was tested for the modelling of energy consumption in the case-study plant during a period of two months. Up to 30 batches of 9 different products were produced in this period. The resolution of the model is discussed, which is very useful for identification of the process steps with the highest energy consumption. Energy-saving potential is noted. Based on these results, one product was chosen which is to be investigated in the final stage of the project in order to optimise the energy consumption of the case-study plant. The authors note that the methodology and software tools developed can be later applied for other products or chemical batch plants.
Optimization modeling with spreadsheets
Baker, Kenneth R
2015-01-01
An accessible introduction to optimization analysis using spreadsheets Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft® Office Excel® Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software. The Third Edition includes many practical applications of optimization models as well as a systematic framework that il
Directory of Open Access Journals (Sweden)
Daniel J. Garcia
2015-07-01
Full Text Available The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water, and maximization of energy output per liter of water consumed (energy efficiency of water. A mixed integer, multiobjective nonlinear fractional programming (MINLFP model is formulated. A mixed integer linear programing (MILP-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline. A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers.
International Nuclear Information System (INIS)
Bakr, A.A.; Dal Santo, D.J.; Smalley, R.C.; Phillips, E.C.
1988-01-01
This paper outlines and explores the fundamentals of the current strategies for groundwater hydraulic and quality management modeling and presents a scheme for the application of such strategies to DOE facilities. The discussion focuses on the DOE-Savannah River Operations (DOE-SR) facility. Remediation of contaminated groundwater at active and abandoned waste disposal sites has become a major element of environmental programs. Traditional groundwater remediation programs (e.g., pumping and treatment) may not represent optimal water quality management strategies at sites to be remediated. Complex, interrelated environmental (geologic/geohydrologic), institutional, engineering, and economic conditions at a site may require a more comprehensive management strategy. Groundwater management models based on the principles of operations research have been developed and used to determine optimal management strategies for water resources needs and for hypothetical remediation programs. Strategies for groundwater remediation programs have ranged from the simple removal of groundwater to complex, hydraulic gradient control programs involving groundwater removal, treatment, and recharge
Energy Technology Data Exchange (ETDEWEB)
Schuetz, Daniel; Vogel-Heuser, Birgit [Technische Univ. Muenchen (Germany). Lehrstuhl fuer Informationstechnik im Maschinenwesen
2011-01-15
In this Paper a modelling approach is presented that merges the operation characteristics and the energy aspects of automation modules into one model. A characteristic of this approach is the state-based behavior model. An example is used to demonstrate how the information in the model can be used for an energy-optimized operation controlled by software agents. (orig.)
An optimization model for energy generation and distribution in a dynamic facility
Lansing, F. L.
1981-01-01
An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai
2016-01-01
This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...
Holistic energy system modeling combining multi-objective optimization and life cycle assessment
Rauner, Sebastian; Budzinski, Maik
2017-12-01
Making the global energy system more sustainable has emerged as a major societal concern and policy objective. This transition comes with various challenges and opportunities for a sustainable evolution affecting most of the UN’s Sustainable Development Goals. We therefore propose broadening the current metrics for sustainability in the energy system modeling field by using industrial ecology techniques to account for a conclusive set of indicators. This is pursued by including a life cycle based sustainability assessment into an energy system model considering all relevant products and processes of the global supply chain. We identify three pronounced features: (i) the low-hanging fruit of impact mitigation requiring manageable economic effort; (ii) embodied emissions of renewables cause increasing spatial redistribution of impact from direct emissions, the place of burning fuel, to indirect emissions, the location of the energy infrastructure production; (iii) certain impact categories, in which more overall sustainable systems perform worse than the cost minimal system, require a closer look. In essence, this study makes the case for future energy system modeling to include the increasingly important global supply chain and broaden the metrics of sustainability further than cost and climate change relevant emissions.
Energy models characterize the energy system, its evolution, and its interactions with the broader economy. The energy system consists of primary resources, including both fossil fuels and renewables; power plants, refineries, and other technologies to process and convert these r...
International Nuclear Information System (INIS)
Komiyama, Ryoichi; Otsuki, Takashi; Fujii, Yasumasa
2015-01-01
Although the extensive introduction of VRs (variable renewables) will play an essential role to resolve energy and environmental issues in Japan after the Fukushima nuclear accident, its large-scale integration would pose a technical challenge in the grid management; as one of technical countermeasures, hydrogen storage receives much attention, as well as rechargeable battery, for controlling the intermittency of VR power output. For properly planning renewable energy policies, energy system modeling is important to quantify and qualitatively understand its potential benefits and impacts. This paper analyzes the optimal grid integration of large-scale VRs using hydrogen storage in Japan by developing a high time-resolution optimal power generation mix model. Simulation results suggest that the installation of hydrogen storage is promoted by both its cost reduction and CO 2 regulation policy. In addition, hydrogen storage turns out to be suitable for storing VR energy in a long period of time. Finally, through a sensitivity analysis of rechargeable battery cost, hydrogen storage is economically competitive with rechargeable battery; the cost of both technologies should be more elaborately recognized for formulating effective energy policies to integrate massive VRs into the country's power system in an economical manner. - Highlights: • Authors analyze hydrogen storage coupled with VRs (variable renewables). • Simulation analysis is done by developing an optimal power generation mix model. • Hydrogen storage installation is promoted by its cost decline and CO 2 regulation. • Hydrogen storage is suitable for storing VR energy in a long period of time. • Hydrogen storage is economically competitive with rechargeable battery
International Nuclear Information System (INIS)
Karmellos, M.; Kiprakis, A.; Mavrotas, G.
2015-01-01
Highlights: • We provide a model for prioritization of energy efficiency measures in buildings. • We examine the case of a new building and one under renovation. • Objective functions are total primary energy consumption and total investment cost. • We provide a software tool that solves this multi-objective optimization problem. • Primary energy consumption and investment cost are inversely proportional. - Abstract: Buildings are responsible for some 40% of the total final energy consumption in the European Union and about 40% of the world’s primary energy consumption. Hence, the reduction of primary energy consumption is important for the overall energy chain. The scope of the current work is to assess the energy efficiency measures in the residential and small commercial sector and to develop a methodology and a software tool for their optimal prioritization. The criteria used for the prioritization of energy efficiency measures in this article are the primary energy consumption and the initial investment cost. The developed methodology used is generic and could be implemented in the case of a new building or retrofitting an existing building. A multi-objective mixed-integer non-linear problem (MINLP) needs to be solved and the weighted sum method is used. Moreover, the novelty of this work is that a software tool has been developed using ‘Matlab®’ which is generic, very simple and time efficient and can be used by a Decision Maker (DM). Two case studies have been developed, one for a new building and one for retrofitting an existing one, in two cities with different climate characteristics. The building was placed in Edinburgh in the UK and Athens in Greece and the analysis showed that the primary energy consumption and the initial investment cost are inversely proportional
A risk-averse optimization model for trading wind energy in a market environment under uncertainty
International Nuclear Information System (INIS)
Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.
2011-01-01
In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. -- Highlights: → We model uncertainties on energy market prices and wind power production. → A hybrid intelligent approach generates price-wind power scenarios. → Risk aversion is also incorporated in the proposed stochastic programming approach. → A realistic case study, based on a wind farm in Portugal, is provided. → Our approach allows selecting the best solution according to the desired risk exposure level.
Performance Modeling and Optimization of a High Energy CollidingBeam Simulation Code
Energy Technology Data Exchange (ETDEWEB)
Shan, Hongzhang; Strohmaier, Erich; Qiang, Ji; Bailey, David H.; Yelick, Kathy
2006-06-01
An accurate modeling of the beam-beam interaction is essential to maximizing the luminosity in existing and future colliders. BeamBeam3D was the first parallel code that can be used to study this interaction fully self-consistently on high-performance computing platforms. Various all-to-all personalized communication (AAPC) algorithms dominate its communication patterns, for which we developed a sequence of performance models using a series of micro-benchmarks. We find that for SMP based systems the most important performance constraint is node-adapter contention, while for 3D-Torus topologies good performance models are not possible without considering link contention. The best average model prediction error is very low on SMP based systems with of 3% to 7%. On torus based systems errors of 29% are higher but optimized performance can again be predicted within 8% in some cases. These excellent results across five different systems indicate that this methodology for performance modeling can be applied to a large class of algorithms.
Performance Modeling and Optimization of a High Energy Colliding Beam Simulation Code
International Nuclear Information System (INIS)
Shan, Hongzhang; Strohmaier, Erich; Qiang, Ji; Bailey, David H.; Yelick, Kathy
2006-01-01
An accurate modeling of the beam-beam interaction is essential to maximizing the luminosity in existing and future colliders. BeamBeam3D was the first parallel code that can be used to study this interaction fully self-consistently on high-performance computing platforms. Various all-to-all personalized communication (AAPC) algorithms dominate its communication patterns, for which we developed a sequence of performance models using a series of micro-benchmarks. We find that for SMP based systems the most important performance constraint is node-adapter contention, while for 3D-Torus topologies good performance models are not possible without considering link contention. The best average model prediction error is very low on SMP based systems with of 3% to 7%. On torus based systems errors of 29% are higher but optimized performance can again be predicted within 8% in some cases. These excellent results across five different systems indicate that this methodology for performance modeling can be applied to a large class of algorithms
International Nuclear Information System (INIS)
Martini, N; Koukou, V; Sotiropoulou, P; Nikiforidis, G; Kalyvas, N; Michail, C; Valais, I; Kandarakis, I; Fountos, G; Bakas, A
2015-01-01
Dual Energy imaging is a promising method for visualizing masses and microcalcifications in digital mammography. The advent of two X-ray energies (low and high) requires a suitable detector. The scope of this work is to determine optimum detector parameters for dual energy applications. The detector was modeled through the linear cascaded (LCS) theory. It was assumed that a phosphor material was coupled to a CMOS photodetector (indirect detection). The pixel size was 22.5 μm. The phosphor thickness was allowed to vary between 20mg/cm 2 and 160mg/cm 2 The phosphor materials examined where Gd 2 O 2 S:Tb and Gd 2 O 2 S:Eu. Two Tungsten (W) anode X-ray spectra at 35 kV (filtered with 100 μm Palladium (Pd)) and 70 kV (filtered with 800 pm Ytterbium (Yb)), corresponding to low and high energy respectively, were considered to be incident on the detector. For each combination the contrast- to-noise ratio (CNR) and the detector optical gain (DOG), showing the sensitivity of the detector, were calculated. The 40 mg/cm 2 and 70 mg/cm 2 Gd 2 O 2 S:Tb exhibited the higher DOG values for the low and high energy correspondingly. Higher CNR between microcalcification and mammary gland exhibited the 70mg/cm 2 and the 100mg/cm 2 Gd 2 O 2 S:Tb for the low and the high energy correspondingly
Energy Optimization in Dyehouse
African Journals Online (AJOL)
2012r
2014-12-04
Dec 4, 2014 ... escalating cost of energy (electricity and fuel); hence conserving .... difficult to predict the behaviour of the fabric inside the DM, for instance .... This discounted cash flow is added to the initial investment (which is negative.
International Nuclear Information System (INIS)
Filkoski, Risto V.
2004-01-01
The investigation accomplished in the framework of this work is concerned with the thermal processes in the furnaces of modern steam and hot-water boilers on fossil fuels. Aerodynamic and thermal conditions in the furnaces are described and models for separate processes and phenomena that occur there are presented. By using proper CFD technique, three-dimensional models of furnaces of coal-fired power boiler, hot-water boiler with circulating fluidized bed combustion and steam boiler on liquid/gaseous fuel are created. Graphical pre-processor is used for geometry creation and mesh generation of the investigated boiler plants. Mathematical model for the gas-solids mixture flow is based on Lagrange approach for the discrete phase simulations, in addition to the transport equations for the gas phase. A standard steady semi-empirical k-E model is employed for description of the turbulent flow. Coupling of velocity and pressure is achieved by the SIMPLEC method. Coal combustion is modelled as non-premixed kinetics/diffusion-limited process by the mixture fraction/probability density function approach for the reaction chemistry, with equilibrium assumption applied for description of the system chemistry. Radiation heat transfer is computed by means of the P-1 model, which is simplified variance of the P-N model, based on the expansion of the radiation intensity into an orthogonal series of spherical harmonics. Presence of discrete solid phase in the main gas stream is effectively taken into consideration through additional terms in the radiation energy transfer equation and in other model equations. Variable emissivity coefficient of the combustion products is modelled with the weighted-sum-of-grey gases-model. A model for NO x formation and reduction is included in the computations. Numerical simulations provide results concerning the boilers operation in several regimes. A methodology for optimisation of energetic-ecological characteristics of boiler plants is proposed
DEFF Research Database (Denmark)
Tattini, Jacopo; Ramea, Kalai; Gargiulo, Maurizio
2018-01-01
and mathematical expressions required to develop the approach. This study develops MoCho-TIMES in the standalone transportation sector of TIMES-DK, the integrated energy system model for Denmark. The model is tested for the Business as Usual scenario and for four alternative scenarios that imply diverse......This study presents MoCho-TIMES, an original methodology for incorporating modal choice into energy-economy-environment-engineering (E4) system models. MoCho-TIMES addresses the scarce ability of E4 models to realistically depict behaviour in transport and allows for modal shift towards transit...
International Nuclear Information System (INIS)
Sood, Yog Raj; Singh, Randhir
2010-01-01
In the competitive electricity market it becomes very much important to give special consideration for development of renewable energy sources (RESs) due to environmental and other social problems related with conventional generations. So this paper presents an optimal model of congestion management with special emphasis for promotion of RES in competitive electricity market. This paper presents a generalized optimal model of congestion management for deregulated power sector that dispatches the pool in combination with privately negotiated bilateral and multilateral contracts while maximizing social benefit. This model determines the locational marginal pricing (LMP) based on marginal cost theory. It also determines the size of non-firm transactions as well as pool demand and generations. Both firms as well as non-firm transactions are considered in this model. The proposed model has been applied to IEEE-30 bus test system with addition of some RES for analysis of the proposed model. The RES supplies its power to load either through the firm transaction or through power pool. The power from RES is not subjected to any curtailment in proposed model of congestion management. (author)
Directory of Open Access Journals (Sweden)
Zhongfu Tan
2014-11-01
Full Text Available To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs and energy storage systems (ESSs are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users’ demand elasticity, thermal units’ startup-shutdown, thermal units’ output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.
Optimal Allocation of Renewable Energy Sources for Energy Loss Minimization
Directory of Open Access Journals (Sweden)
Vaiju Kalkhambkar
2017-03-01
Full Text Available Optimal allocation of renewable distributed generation (RDG, i.e., solar and the wind in a distribution system becomes challenging due to intermittent generation and uncertainty of loads. This paper proposes an optimal allocation methodology for single and hybrid RDGs for energy loss minimization. The deterministic generation-load model integrated with optimal power flow provides optimal solutions for single and hybrid RDG. Considering the complexity of the proposed nonlinear, constrained optimization problem, it is solved by a robust and high performance meta-heuristic, Symbiotic Organisms Search (SOS algorithm. Results obtained from SOS algorithm offer optimal solutions than Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Firefly Algorithm (FFA. Economic analysis is carried out to quantify the economic benefits of energy loss minimization over the life span of RDGs.
Original Framework for Optimizing Hybrid Energy Supply
Directory of Open Access Journals (Sweden)
Amevi Acakpovi
2016-01-01
Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.
Directory of Open Access Journals (Sweden)
Hung-Ju Shih
2018-02-01
Full Text Available A 12-year sea-state hindcast for Taiwanese waters, covering the period from 2005 to 2016, was conducted using a fully coupled tide-surge-wave model. The hindcasts of significant wave height and peak period were employed to estimate the wave power resources in the waters surrounding Taiwan. Numerical simulations based on unstructured grids were converted to structured grids with a resolution of 25 × 25 km. The spatial distribution maps of offshore annual mean wave power were created for each year and for the 12-year period. Waters with higher wave power density were observed off the northern, northeastern, southeastern (south of Green Island and southeast of Lanyu and southern coasts of Taiwan. Five energetic sea areas with spatial average annual total wave energy density of 60–90 MWh/m were selected for further analysis. The 25 × 25 km square grids were then downscaled to resolutions of 5 × 5 km, and five 5 × 5 km optimal areas were identified for wave energy converter deployments. The spatial average annual total wave energy yields at the five optimal areas (S1–(S5 were estimated to be 64.3, 84.1, 84.5, 111.0 and 99.3 MWh/m, respectively. The prevailing wave directions for these five areas lie between east and northeast.
International Nuclear Information System (INIS)
Undarmaa, Baatarkhuu; Horio, Kenta; Fujii, Yasumasa; Komiyama, Ryoichi
2017-01-01
In order to sustain long-term energy security and to mitigate the climate change, nuclear power remains an important baseload option for the global power generation mix. To utilize nuclear power in long-term, some important concerns such as economics, stability of fuel supply and spent fuel amount should be evaluated. Model developed in this study optimizes the global use nuclear power considering such issues. The Model is based on linear programming and calculates the best mix of nuclear reactor types by minimizing the current value of total power generation cost within the target period (next 100 years). Possibility of fuel cycle options such as reprocessing, seawater uranium and thorium utilization are also taken in to account, along with remaining spent fuel and plutonium stock. As result. reprocessing and uranium from seawater become essential part of nuclear fuel cycle in the long run. Amount of stored spent fuel is reduced following the deployment of Fast Breeder Reactor. Also, as an extension of current model, a baseload power generation mix model, which estimates the optimal mix of nuclear and coal-fired power generation will be introduced. (author)
Wu, C B; Huang, G H; Liu, Z P; Zhen, J L; Yin, J G
2017-03-01
In this study, an inexact multistage stochastic mixed-integer programming (IMSMP) method was developed for supporting regional-scale energy system planning (EPS) associated with multiple uncertainties presented as discrete intervals, probability distributions and their combinations. An IMSMP-based energy system planning (IMSMP-ESP) model was formulated for Qingdao to demonstrate its applicability. Solutions which can provide optimal patterns of energy resources generation, conversion, transmission, allocation and facility capacity expansion schemes have been obtained. The results can help local decision makers generate cost-effective energy system management schemes and gain a comprehensive tradeoff between economic objectives and environmental requirements. Moreover, taking the CO 2 emissions scenarios mentioned in Part I into consideration, the anti-driving effect of carbon emissions on energy structure adjustment was studied based on the developed model and scenario analysis. Several suggestions can be concluded from the results: (a) to ensure the smooth realization of low-carbon and sustainable development, appropriate price control and fiscal subsidy on high-cost energy resources should be considered by the decision-makers; (b) compared with coal, natural gas utilization should be strongly encouraged in order to insure that Qingdao could reach the carbon discharges peak value in 2020; (c) to guarantee Qingdao's power supply security in the future, the construction of new power plants should be emphasised instead of enhancing the transmission capacity of grid infrastructure. Copyright © 2016 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Grahovac, Milica
2012-11-29
The thermal conditioning systems are responsible for almost half of the energy consump-tion by commercial buildings. In many European countries and in the USA, buildings account for around 40% of primary energy consumption and it is therefore vital to explore further ways to reduce the HVAC (Heating, Ventilation and Air Conditioning) system energy consumption. This thesis investigates the relationship between the energy genera-tion and storage systems for thermal conditioning of buildings (shorter: primary HVAC systems) and the conceptual building design. Certain building design decisions irreversibly influence a building's energy performance and, conversely, many generation and storage components impose restrictions on building design and, by their nature, cannot be introduced at a later design stage. The objective is, firstly, to develop a method to quantify this influence, in terms of primary HVAC system dimensions, its cost, emissions and energy consumption and, secondly, to enable the use of the developed method by architects during the conceptual design. In order to account for the non-stationary effects of the intermittent renewable energy sources (RES), thermal storage and for the component part load efficiencies, a time domain system simulation is required. An abstract system simulation method is proposed based on seven pre-configured primary HVAC system models, including components such as boil-ers, chillers and cooling towers, thermal storage, solar thermal collectors, and photovoltaic modules. A control strategy is developed for each of the models and their annual quasi-stationary simulation is performed. The performance profiles obtained are then used to calculate the energy consumption, carbon emissions and costs. The annuity method has been employed to calculate the cost. Optimization is used to automatically size the HVAC systems, based on their simulation performance. Its purpose is to identify the system component dimensions that provide
Energy Technology Data Exchange (ETDEWEB)
Grahovac, Milica
2012-11-29
The thermal conditioning systems are responsible for almost half of the energy consump-tion by commercial buildings. In many European countries and in the USA, buildings account for around 40% of primary energy consumption and it is therefore vital to explore further ways to reduce the HVAC (Heating, Ventilation and Air Conditioning) system energy consumption. This thesis investigates the relationship between the energy genera-tion and storage systems for thermal conditioning of buildings (shorter: primary HVAC systems) and the conceptual building design. Certain building design decisions irreversibly influence a building's energy performance and, conversely, many generation and storage components impose restrictions on building design and, by their nature, cannot be introduced at a later design stage. The objective is, firstly, to develop a method to quantify this influence, in terms of primary HVAC system dimensions, its cost, emissions and energy consumption and, secondly, to enable the use of the developed method by architects during the conceptual design. In order to account for the non-stationary effects of the intermittent renewable energy sources (RES), thermal storage and for the component part load efficiencies, a time domain system simulation is required. An abstract system simulation method is proposed based on seven pre-configured primary HVAC system models, including components such as boil-ers, chillers and cooling towers, thermal storage, solar thermal collectors, and photovoltaic modules. A control strategy is developed for each of the models and their annual quasi-stationary simulation is performed. The performance profiles obtained are then used to calculate the energy consumption, carbon emissions and costs. The annuity method has been employed to calculate the cost. Optimization is used to automatically size the HVAC systems, based on their simulation performance. Its purpose is to identify the system component dimensions that provide minimal
Jin, S W; Li, Y P; Nie, S
2018-05-15
In this study, an interval chance-constrained bi-level programming (ICBP) method is developed for air quality management of municipal energy system under uncertainty. ICBP can deal with uncertainties presented as interval values and probability distributions as well as examine the risk of violating constraints. Besides, a leader-follower decision strategy is incorporated into the optimization process where two decision makers with different goals and preferences are involved. To solve the proposed model, a bi-level interactive algorithm based on satisfactory degree is introduced into the decision-making processes. Then, an ICBP based energy and environmental systems (ICBP-EES) model is formulated for Beijing, in which air quality index (AQI) is used for evaluating the integrated air quality of multiple pollutants. Result analysis can help different stakeholders adjust their tolerances to achieve the overall satisfaction of EES planning for the study city. Results reveal that natural gas is the main source for electricity-generation and heating that could lead to a potentially increment of imported energy for Beijing in future. Results also disclose that PM 10 is the major contributor to AQI. These findings can help decision makers to identify desired alternatives for EES planning and provide useful information for regional air quality management under uncertainty. Copyright © 2018 Elsevier B.V. All rights reserved.
Optimal utilization of energy resources
Energy Technology Data Exchange (ETDEWEB)
Hudson, E. A.
1977-10-15
General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.
Optimal utilization of energy resources
Energy Technology Data Exchange (ETDEWEB)
Hudson, E.A.
1977-10-15
General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.
Integrated solar energy system optimization
Young, S. K.
1982-11-01
The computer program SYSOPT, intended as a tool for optimizing the subsystem sizing, performance, and economics of integrated wind and solar energy systems, is presented. The modular structure of the methodology additionally allows simulations when the solar subsystems are combined with conventional technologies, e.g., a utility grid. Hourly energy/mass flow balances are computed for interconnection points, yielding optimized sizing and time-dependent operation of various subsystems. The program requires meteorological data, such as insolation, diurnal and seasonal variations, and wind speed at the hub height of a wind turbine, all of which can be taken from simulations like the TRNSYS program. Examples are provided for optimization of a solar-powered (wind turbine and parabolic trough-Rankine generator) desalinization plant, and a design analysis for a solar powered greenhouse.
OPTIMIZATION OF AEOLIAN ENERGY CONVERSION ...
African Journals Online (AJOL)
30 juin 2010 ... wind energy based on a criterion optimization that must maintain specific speed of the turbine at optimum speed which corresponds to the maximum power ... ainsi que la structure et les méthodes de contrôle-commande ...
Optimal development of the future Danish energy system – insights from TIMES-DTU model
DEFF Research Database (Denmark)
Petrovic, Stefan; Karlsson, Kenneth Bernard; Balyk, Olexandr
2015-01-01
After a long period of transition, Danish energy system is half-way towards completely renewable in 2050. Drastic changes happened in the last forty years – the imported oil has been replaced by a mix of coal and natural gas, energy efficiency and conservation have been improved by extensive use...... of CHP-based district heating and heat saving measures. In the same period Denmark became well-known by integration and export of wind turbines. In line with the changes in the past, Denmark currently has very ambitious renewable energy targets, most ambitious being the 100 % renewable energy system......) WLP with the constraint that 50 % of electricity production should come from wind starting from 2020, and (iii) WLP-NFE scenario with the constraint that power and heat sector should be fossil fuel-free starting from 2035 and Denmark should be 100 % renewable starting from 2050. In all scenarios...
Hemmati, Reza; Saboori, Hedayat
2016-05-01
Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.
Hemmati, Reza; Saboori, Hedayat
2016-01-01
Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741
Energy network dispatch optimization under emergency of local energy shortage
International Nuclear Information System (INIS)
Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang
2012-01-01
The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.
Nguyen, Gia Luong Huu
obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.
Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel
2014-01-01
The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use...
Belgasam, Tarek M.; Zbib, Hussein M.
2018-06-01
The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.
Quad-rotor flight path energy optimization
Kemper, Edward
Quad-Rotor unmanned areal vehicles (UAVs) have been a popular area of research and development in the last decade, especially with the advent of affordable microcontrollers like the MSP 430 and the Raspberry Pi. Path-Energy Optimization is an area that is well developed for linear systems. In this thesis, this idea of path-energy optimization is extended to the nonlinear model of the Quad-rotor UAV. The classical optimization technique is adapted to the nonlinear model that is derived for the problem at hand, coming up with a set of partial differential equations and boundary value conditions to solve these equations. Then, different techniques to implement energy optimization algorithms are tested using simulations in Python. First, a purely nonlinear approach is used. This method is shown to be computationally intensive, with no practical solution available in a reasonable amount of time. Second, heuristic techniques to minimize the energy of the flight path are tested, using Ziegler-Nichols' proportional integral derivative (PID) controller tuning technique. Finally, a brute force look-up table based PID controller is used. Simulation results of the heuristic method show that both reliable control of the system and path-energy optimization are achieved in a reasonable amount of time.
Directory of Open Access Journals (Sweden)
Iole Nardi
2016-08-01
Full Text Available The reduction of building energy consumption requires appropriate planning and design of the building’s envelope. In the last years, new innovative materials and construction technologies used in new or refurbished buildings have been developed in order to achieve this objective, which are also needed for reducing greenhouse gases emissions and building maintenance costs. In this work, the thermal conductance of a brick, made of wood and cement, used in a low-rise building, was investigated with a heat flow meter (HFM and with numerical simulation using the Ansys® software package (Canonsburg, PA, USA. Due to their influence on the buildings’ thermal efficiency, it is important to choose an appropriate design for the building blocks. Results obtained by the finite element modeling of the construction material and by in-situ analysis conducted on a real building are compared, and furthermore a thermal optimization of the shape of the material is suggested.
Optimizing RF energy transport : channel modelling and transmit antenna and rectenna design
Visser, H.J.
2012-01-01
For powering wireless sensors in buildings rechargeable batteries may be used, being charged remotely by dedicated RF sources. RF energy transport suffers from path loss and therefore the RF power available on a rectenna will be very low. As a consequence, the RF-to-DC conversion efficiency will
An optimal renewable energy mix for Indonesia
Leduc, Sylvain; Patrizio, Piera; Yowargana, Ping; Kraxner, Florian
2016-04-01
Indonesia has experienced a constant increase of the use of petroleum and coal in the power sector, while the share of renewable sources has remained stable at 6% of the total energy production during the last decade. As its domestic energy demand undeniably continues to grow, Indonesia is committed to increase the production of renewable energy. Mainly to decrease its dependency on fossil fuel-based resources, and to decrease the anthropogenic emissions, the government of Indonesia has established a 23 percent target for renewable energy by 2025, along with a 100 percent electrification target by 2020 (the current rate is 80.4 percent). In that respect, Indonesia has abundant resources to meet these targets, but there is - inter alia - a lack of proper integrated planning, regulatory support, investment, distribution in remote areas of the Archipelago, and missing data to back the planning. To support the government of Indonesia in its sustainable energy system planning, a geographic explicit energy modeling approach is applied. This approach is based on the energy systems optimization model BeWhere, which identifies the optimal location of energy conversion sites based on the minimization of the costs of the supply chain. The model will incorporate the existing fossil fuel-based infrastructures, and evaluate the optimal costs, potentials and locations for the development of renewable energy technologies (i.e., wind, solar, hydro, biomass and geothermal based technologies), as well as the development of biomass co-firing in existing coal plants. With the help of the model, an optimally adapted renewable energy mix - vis-à-vis the competing fossil fuel based resources and applicable policies in order to promote the development of those renewable energy technologies - will be identified. The development of the optimal renewable energy technologies is carried out with special focus on nature protection and cultural heritage areas, where feedstock (e.g., biomass
Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control
DEFF Research Database (Denmark)
Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller
2017-01-01
For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated...... and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm....
Energy Technology Data Exchange (ETDEWEB)
Brigantic, Robert T.; Papatyi, Anthony F.; Perkins, Casey J.
2010-09-30
This report summarizes a study and corresponding model development conducted in support of the United States Pacific Command (USPACOM) as part of the Federal Energy Management Program (FEMP) American Reinvestment and Recovery Act (ARRA). This research was aimed at developing a mathematical programming framework and accompanying optimization methodology in order to simultaneously evaluate energy efficiency (EE) and renewable energy (RE) opportunities. Once developed, this research then demonstrated this methodology at a USPACOM installation - Camp H.M. Smith, Hawaii. We believe this is the first time such an integrated, joint EE and RE optimization methodology has been constructed and demonstrated.
International Nuclear Information System (INIS)
Rout, Ullash K.; Fahl, Ulrich; Remme, Uwe; Blesl, Markus; Voss, Alfred
2009-01-01
Evaluation of global diffusion potential of learning technologies and their timely specific cost development across regions is always a challenging issue for the future technology policy preparation. Further the process of evaluation gains interest especially by endogenous treatment of energy technologies under uncertainty in learning rates with technology gap across the regions in global regional cluster learning approach. This work devised, implemented, and examined new methodologies on technology gaps (a practical problem), using two broad concepts of knowledge deficit and time lag approaches in global learning, applying the floor cost approach methodology. The study was executed in a multi-regional, technology-rich and long horizon bottom-up linear energy system model on The Integrated MARKAL EFOM System (TIMES) framework. Global learning selects highest learning technologies in maximum uncertainty of learning rate scenario, whereas any form of technology gap retards the global learning process and discourages the technologies deployment. Time lag notions of technology gaps prefer heavy utilization of learning technologies in developed economies for early reduction of specific cost. Technology gaps of any kind should be reduced among economies through the promotion and enactment of various policies by governments, in order to utilize the technological resources by mass deployment to combat ongoing climate change.
Energy Technology Data Exchange (ETDEWEB)
Nogueira, Carlos E.C. [UNIOESTE, Cascavel, PR (Brazil). Centro de Ciencias Exatas e Tecnologicas]. E-mail: cecn@correios.net.br; Zuern, Hans H. [Santa Catarina Univ., Florianopolis, SC (Brazil). Dept. de Engenharia Eletrica
2005-05-15
The purpose of this research was to develop a methodology for sizing integrated renewable energy systems, useful for rural areas, using simulation and optimization tools developed in MATLAB 6.0. The sizing model produces a system with minimum cost and high reliability level, based on the concept of loss of power supply probability (LPSP) for consecutive hours. An optimization model is presented and three different sizing scenarios are calculated and compared, showing flexibility in the elaboration of different project conceptions. The obtained results show a complete sizing of the energy conversion devices and a long-term cost evaluation. (author)
Optimization Modeling with Spreadsheets
Baker, Kenneth R
2011-01-01
This introductory book on optimization (mathematical programming) includes coverage on linear programming, nonlinear programming, integer programming and heuristic programming; as well as an emphasis on model building using Excel and Solver. The emphasis on model building (rather than algorithms) is one of the features that makes this book distinctive. Most books devote more space to algorithmic details than to formulation principles. These days, however, it is not necessary to know a great deal about algorithms in order to apply optimization tools, especially when relying on the sp
Optimization of finances into regional energy
Directory of Open Access Journals (Sweden)
Alexey Yuryevich Domnikov
2014-06-01
Full Text Available The development of modern Russian energy collides with the need for major investments in the modernization and renewal of generation and transmission capacity. In terms of attracting sufficient financial resources and find ways to increase, energy sector profitability and investment attractiveness of particular importance is the problem of investment financing optimizing aimed at minimizing the cost of financing while maintaining financial stability of the power companies and the goals and objectives of Russian energy system long-term development. The article discusses the problem of investment projects financing in power generation from the point of view of the need to achieve optimal investment budget. Presents the author’s approach to the investment financing optimization of power generation company that will achieve the minimum cost of resources involved, taking into account the impact of the funding structure for the power generating company financial sustainability. The developed model is applied to the problem of investment budget optimizing, for example, regional power generating company. The results can improve the efficiency of investment in energy, sustainable and competitive development of regional energy systems.
International Nuclear Information System (INIS)
Lu, Zhijian; Shao, Shuai
2016-01-01
Highlights: • An ESCO optimal decision model considering governmental subsidies is proposed. • Optimal price and performance level are deduced via a two-stage model. • Demand, profit, and performance level increase with increasing subsidies. • ESCO’s market strategy should firstly focus on high energy consumption industries. • Governmental subsidies standard in different industries should be differentiated. - Abstract: Government subsidies generally play a crucial role in pricing and the choice of performance levels in Energy Performance Contracting (EPC). However, the existing studies pay little attention to how the Energy Service Company (ESCO) prices and chooses performance levels for EPC with government subsidies. To fill such a gap, we propose a joint optimal decision model of pricing and performance level in EPC considering government subsidies. The optimization of the model is achieved via a two-stage process. At the first stage, given a performance level, ESCOs choose the best price; and at the second stage, ESCOs choose the optimal performance level for the optimal price. Furthermore, we carry out a numerical analysis to illuminate such an optimal decision mechanism. The results show that both price sensitivity and performance level sensitivity have significant effects on the choice of performance levels with government subsidies. Government subsidies can induce higher performance levels of EPC, the demand for EPC, and the profit of ESCO. We suggest that ESCO’s market strategy should firstly focus on high energy consumption industries with government subsidies and that government subsidies standard adopted in different industries should be differentiated according to the market characteristics and energy efficiency levels of various industries.
Subthreshold SPICE Model Optimization
Lum, Gregory; Au, Henry; Neff, Joseph; Bozeman, Eric; Kamin, Nick; Shimabukuro, Randy
2011-04-01
The first step in integrated circuit design is the simulation of said design in software to verify proper functionally and design requirements. Properties of the process are provided by fabrication foundries in the form of SPICE models. These SPICE models contain the electrical data and physical properties of the basic circuit elements. A limitation of these models is that the data collected by the foundry only accurately model the saturation region. This is fine for most users, but when operating devices in the subthreshold region they are inadequate for accurate simulation results. This is why optimizing the current SPICE models to characterize the subthreshold region is so important. In order to accurately simulate this region of operation, MOSFETs of varying widths and lengths are fabricated and the electrical test data is collected. From the data collected the parameters of the model files are optimized through parameter extraction rather than curve fitting. With the completed optimized models the circuit designer is able to simulate circuit designs for the sub threshold region accurately.
Directory of Open Access Journals (Sweden)
Meng Xiong
2015-08-01
Full Text Available Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.
International Nuclear Information System (INIS)
Fan, Yuling; Xia, Xiaohua
2017-01-01
Highlights: • A multi-objective optimization model for building envelope retrofit is presented. • Facility performance degradation and maintenance is built into the model. • A rooftop PV system is introduced to produce electricity. • Economic factors including net present value and payback period are considered. - Abstract: Retrofitting existing buildings with energy-efficient facilities is an effective method to improve their energy efficiency, especially for old buildings. A multi-objective optimization model for building envelope retrofitting is presented. Envelope components including windows, external walls and roofs are considered to be retrofitted. Installation of a rooftop solar panel system is also taken into consideration in this study. Rooftop solar panels are modeled with their degradation and a maintenance scheme is studied for sustainability of energy and its long-term effect on the retrofitting plan. The purpose is to make the best use of financial investment to maximize energy savings and economic benefits. In particular, net present value, the payback period and energy savings are taken as the main performance indicators of the retrofitting plan. The multi-objective optimization problem is formulated as a non-linear integer programming problem and solved by a weighted sum method. Results of applying the designed retrofitting plan to a 50-year-old building consisting of 66 apartments demonstrated the effectiveness of the proposed model.
International Nuclear Information System (INIS)
Gergaud, Olivier
2002-01-01
This thesis deals of the production of photovoltaic and wind electricity connected to the grid and having a storage. The principal interests of such a system are the clean production on the place of consumption, the mutualization of resources and energy storage, and the security of supply. Models are developed and compared successfully with reality thanks to an experimental device instrumented completion (2 kWp PV, 2 x 750 Wp wind generators, 15 kWh lead-acid battery). We obtain then a model that proves both accurate enough to distinguish energy transfers and fast enough to enable optimizing the sizing and handling of the system's energy transfers. Having energy, economic models and tools of dimensioning and management, we carried out a study of optimization based on simple cases of systems multi-production. To tackle this difficult problem, we then placed ourselves within the framework of a producer-consumer whose conditions weather with the site of production as its own consumption are supposed to be known, therefore deterministic. The problems were then the search for strategies of management of flows of energy and the fundamental characteristics of the elements of the installation optimal allowing the minimization of the energy cost. (author) [fr
Pareto optimality in organelle energy metabolism analysis.
Angione, Claudio; Carapezza, Giovanni; Costanza, Jole; Lió, Pietro; Nicosia, Giuseppe
2013-01-01
In low and high eukaryotes, energy is collected or transformed in compartments, the organelles. The rich variety of size, characteristics, and density of the organelles makes it difficult to build a general picture. In this paper, we make use of the Pareto-front analysis to investigate the optimization of energy metabolism in mitochondria and chloroplasts. Using the Pareto optimality principle, we compare models of organelle metabolism on the basis of single- and multiobjective optimization, approximation techniques (the Bayesian Automatic Relevance Determination), robustness, and pathway sensitivity analysis. Finally, we report the first analysis of the metabolic model for the hydrogenosome of Trichomonas vaginalis, which is found in several protozoan parasites. Our analysis has shown the importance of the Pareto optimality for such comparison and for insights into the evolution of the metabolism from cytoplasmic to organelle bound, involving a model order reduction. We report that Pareto fronts represent an asymptotic analysis useful to describe the metabolism of an organism aimed at maximizing concurrently two or more metabolite concentrations.
Energy optimization in mobile sensor networks
Yu, Shengwei
consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.
Energy Technology Data Exchange (ETDEWEB)
Correia, Paulo de Barros
1988-12-01
A multi-sectorial model for energy supply optimization is presented including the following main issues: energetic models general scenery; multi-sectorial energetic model; multi-sectorial operation coordinate; flows optimization in graphs generalized; optimization extension in graphs generalized; computational implementation; and case study of energetic system of Southeast Brazil.
Energy-economical optimization of industrial sites
International Nuclear Information System (INIS)
Berthold, A.; Saliba, S.; Franke, R.
2015-01-01
The holistic optimization of an industrial estate networks all electrical components of a location and combines energy trading, energy management and production processes. This allows to minimize the energy consumption from the supply network and to relieve the power grid and to maximize the profitability of the industrial self-generation. By analyzing the potential is detected and the cost of optimization solution is estimated. The generation-side optimization is supported through demand-side optimization (demand response). Through a real-time optimization the of Use of fuels is managed, controlled and optimized. [de
Gabrielli, Paolo; Gazzani, Matteo; Mazzotti, Marco
2018-01-01
The design and operation of integrated multi-energy systems require models that adequately describe the behavior of conversion and storage technologies. Typically, linear conversion performance or fixed data from technology manufacturers are employed, especially for new or advanced technologies.
Moser, Elke; Grass, Dieter; Tragler, Gernot
Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.
Energy optimization of bread baking process undergoing quality constraints
International Nuclear Information System (INIS)
Papasidero, Davide; Pierucci, Sauro; Manenti, Flavio
2016-01-01
International home energy rating regulations are forcing to use efficient cooking equipment and processes towards energy saving and sustainability. For this reason gas ovens are replaced by the electric ones, to get the highest energy rating. Due to this fact, the study of the technologies related to the energy efficiency in cooking is increasingly developing. Indeed, big industries are working to the energy optimization of their processes since decades, while there is still a lot of room in energy optimization of single household appliances. The achievement of a higher efficiency can have a big impact on the society only if the use of modern equipment gets widespread. The combination of several energy sources (e.g. forced convection, irradiation, microwave, etc.) and their optimization is an emerging target for oven manufacturers towards optimal oven design. In this work, an energy consumption analysis and optimization is applied to the case of bread baking. Each source of energy gets the due importance and the process conditions are compared. A basic quality standard is guaranteed by taking into account some quality markers, which are relevant based on a consumer viewpoint. - Highlights: • Energy optimization is based on a validated finite-element model for bread baking. • Quality parameters for the product acceptability are introduced as constraints. • Dynamic optimization leads to 20% energy saving compared to non-optimized case. • The approach is applicable to many products, quality parameters, thermal processes. • Other heating processes can be easily integrated in the presented model.
Control Methods Utilizing Energy Optimizing Schemes in Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, L.S; Thybo, C.; Stoustrup, Jakob
2003-01-01
The potential energy savings in refrigeration systems using energy optimal control has been proved to be substantial. This however requires an intelligent control that drives the refrigeration systems towards the energy optimal state. This paper proposes an approach for a control, which drives th...... the condenser pressure towards an optimal state. The objective of this is to present a feasible method that can be used for energy optimizing control. A simulation model of a simple refrigeration system will be used as basis for testing the control method....
Directory of Open Access Journals (Sweden)
Douglas Halamay
2014-09-01
Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.
Directory of Open Access Journals (Sweden)
Yongxiu He
2014-04-01
Full Text Available In Beijing, China, the rational consumption of energy is affected by the insufficient linkage mechanism of the energy pricing system, the unreasonable price ratio and other issues. This paper combines the characteristics of Beijing’s energy market, putting forward the society-economy equilibrium indicator R maximization taking into consideration the mitigation cost to determine a reasonable price ratio range. Based on the computable general equilibrium (CGE model, and dividing four kinds of energy sources into three groups, the impact of price fluctuations of electricity and natural gas on the Gross Domestic Product (GDP, Consumer Price Index (CPI, energy consumption and CO2 and SO2 emissions can be simulated for various scenarios. On this basis, the integrated effects of electricity and natural gas price shocks on the Beijing economy and environment can be calculated. The results show that relative to the coal prices, the electricity and natural gas prices in Beijing are currently below reasonable levels; the solution to these unreasonable energy price ratios should begin by improving the energy pricing mechanism, through means such as the establishment of a sound dynamic adjustment mechanism between regulated prices and market prices. This provides a new idea for exploring the rationality of energy price ratios in imperfect competitive energy markets.
Directory of Open Access Journals (Sweden)
Daeho Kim
2014-08-01
Full Text Available Considerable effort is being made to reduce the primary energy consumption in buildings. As part of this effort, fuel cell systems are attracting attention as a new/renewable energy systems for several reasons: (i distributed generation system; (ii combined heat and power system; and (iii availability of various sources of hydrogen in the future. Therefore, this study aimed to develop an economic and environmental assessment model for selecting the optimal implementation strategy of the fuel cell system, focusing on building energy policy. This study selected two types of buildings (i.e., residential buildings and non-residential buildings as the target buildings and considered two types of building energy policies (i.e., the standard of energy cost calculation and the standard of a government subsidy. This study established the optimal implementation strategy of the fuel cell system in terms of the life cycle cost and life cycle CO2 emissions. For the residential building, it is recommended that the subsidy level and the system marginal price level be increased. For the non-residential building, it is recommended that gas energy cost be decreased and the system marginal price level be increased. The developed model could be applied to any other country or any other type of building according to building energy policy.
Optimal Energy Taxation for Environment and Efficiency
Energy Technology Data Exchange (ETDEWEB)
Pak, Y.D. [Korea Energy Economics Institute, Euiwang (Korea)
2001-11-01
Main purpose of this research is to investigate about how to use energy tax system to reconcile environmental protection and economic growth, and promote sustainable development with the emphasis of double dividend hypothesis. As preliminary work to attain this target, in this limited study I will investigate the specific conditions under which double dividend hypothesis can be valid, and set up the model for optimal energy taxation. The model will be used in the simulation process in the next project. As the beginning part in this research, I provide a brief review about energy taxation policies in Sweden, Netherlands, and the United States. From this review it can be asserted that European countries are more aggressive in the application of environmental taxes like energy taxes for a cleaner environment than the United States. In next part I examined the rationale for optimal environmental taxation in the first-best and the second-best setting. Then I investigated energy taxation how it can provoke various distortions in markets and be connected to the marginal environmental damages and environmental taxation. In the next chapter, I examined the environmentally motivated taxation in the point of optimal commodity taxation view. Also I identified the impacts of environmental taxation in various circumstances intensively to find out when the environment tax can yield double dividend after taking into account of even tax-interaction effects. Then it can be found that even though in general the environmental tax exacerbates the distortion in the market rather than alleviates, it can also improve the welfare and the employment under several specific circumstances which are classified as various inefficiencies in the existing tax system. (author). 30 refs.
Software for industrial consumers electrical energy tariff optimal selection
Simona Ardelean; A. Ceclan; L. Czumbil; D. D. Micu; E. Simion
2008-01-01
This paper briefly presents someelectrical energy management techniques andproposes a software product dedicated forautomatic choose of the optimal tariff structure forindustrial consumers. The optimal choose ofelectrical energy invoicing model proves to be anefficient way to bring quality and economies in anycompanies administration. Advanced description ofthe proposed software is also presented.
International Nuclear Information System (INIS)
Fakehi, Amir Hossein; Ahmadi, Somayeh; Mirghaed, Mohammad Rezaie
2015-01-01
Highlights: • The exergy analysis of a hybrid system of a wind turbine and PEM electrolyzer/fuel-cell has been performed. • Effects of various operating parameters on the exergy efficiency have been investigated. • The exergy and energy efficiency in each of hybrid system’s components have been compared. - Abstract: In this study, hybrid renewable energy system based on wind/electrolyzer/PEM fuel cell are conceptually modeled, and also, exergy and energy analysis are performed. The energy and exergy flows are investigated by the proposed model for Khaf region-Iran with high average wind speed and monsoon. Exergy and energy analysis framework is made based on thermodynamic, electro-chemical and mechanical model of the different component of hybrid system. Also, the effects of various operating parameters in exergy efficiency are calculated. The results show an optimum wind speed where the exergy efficiency and power coefficient is at maximum level, and also, when the ambient temperature start to be increased in wind turbine, the efficiencies decrease by a great deal for constant wind speeds. Also, the optimum temperature is calculated by exergy analysis in electrolyzer and fuel cell as 353 and the exergy efficiency of electrolyzer decreases by increasing the membrane thickness. Furthermore, pressure changes affect exergy and energy efficiency in PEM fuel cell. Finally, the electrolyzer and fuel cell efficiencies are calculated as 68.5% and 47% respectively.
International Nuclear Information System (INIS)
Soheyli, Saman; Mehrjoo, Mehri; Shafiei Mayam, Mohamad Hossein
2017-01-01
Highlights: • Considering renewable resources as the main prime movers in tri-generation systems. • Using EDM and TDM strategies simultaneously by defining probability functions. • Using an area function to evaluate the practical implementation of the system. • Reducing fuel consumption and pollution up to 154 and 207 times more than SP system. • Reducing the need to power grid and other auxiliary systems to less than 1%. - Abstract: Tri-generation systems with the aim of recycling heat dissipation of equipment and importing the heat into the energy production cycle have been considered by researchers recently because of increasing energy efficiency and decreasing environmental pollution. Many studies have been done in the field of tri-generation systems, but the studies have been more focused on centralized energy sources, such as, steam and gas turbines. Thus, required researches to move the sources of tri-generation systems toward renewable energy resources are not perfect enough. Moreover, the type of operation strategy, which is one of the important issues in investigating tri-generation system, is usually depended on assistant resources, such as, local power grid. In this paper, a novel tri-generation system based on wind and solar renewable energy resources and natural gas as the system prime movers is evaluated. Furthermore, a different operation strategy is considered to minimize the need to auxiliary sources and so the ability to use the system in remote regions, independently. Hence, wind turbines, photovoltaic (PV) modules, and solid oxide fuel cells (SOFCs) are considered as prime movers of the system. Moreover, a battery bank and heat storage tanks (HSTs) are deployed to balance the fluctuations in produced energy by wind and solar renewable resources. Hence, thermal demand management (TDM) and electrical demand management (EDM) operation strategies are considered simultaneously and defined as two possible functions to achieve a system with
International Nuclear Information System (INIS)
Sadeghi, Mehdi; Ameli, Ahmad
2012-01-01
This paper presents an analytical hierarchy process (AHP) decision model for sectoral allocation of energy subsidy based on several criteria. With determination of priorities for these criteria through questionnaire and AHP method, the overall rank of these criteria that have the most influence on distribution of energy subsidy among socio-economic sub-sectors, are as the following: inflation, economic growth, labor intensity, distribution of energy subsidy among socio-economic levels, energy intensity and social cost of air pollution. According to the model, the first priority for allocation of energy subsidy is commercial sector and the last priority is related to transportation sector. Investigating the impact of changing priority of the criteria on overall results indicates that the socio-economic sub sectors’ ranking in receiving subsidy have little sensitivity for changing priority of the subsidy criteria. - Highlights: ► Commerce subsector is the best sub sector with an overall priority score of 0.331. ► The first priority for allocation of energy subsidy is commercial sector. ► When we increase the priority of each criterion first time, then overall rank of the outcome has little changing. ► The socio-economic sub sectors' ranking in receiving subsidy have little sensitivity for changing priority of the subsidy criteria.
Surrogate Modeling for Geometry Optimization
DEFF Research Database (Denmark)
Rojas Larrazabal, Marielba de la Caridad; Abraham, Yonas; Holzwarth, Natalie
2009-01-01
A new approach for optimizing the nuclear geometry of an atomic system is described. Instead of the original expensive objective function (energy functional), a small number of simpler surrogates is used.......A new approach for optimizing the nuclear geometry of an atomic system is described. Instead of the original expensive objective function (energy functional), a small number of simpler surrogates is used....
Optimal control of a wave energy converter
Hendrikx, R.W.M.; Leth, J.; Andersen, P; Heemels, W.P.M.H.
2017-01-01
The optimal control strategy for a wave energy converter (WEC) with constraints on the control torque is investigated. The goal is to optimize the total energy delivered to the electricity grid. Using Pontryagin's maximum principle, the solution is found to be singular-bang. Using higher order
Coordinated Optimal Operation Method of the Regional Energy Internet
Directory of Open Access Journals (Sweden)
Rishang Long
2017-05-01
Full Text Available The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized.
CSIR Research Space (South Africa)
Osburn, L
2010-01-01
Full Text Available The construction industry has turned to energy modelling in order to assist them in reducing the amount of energy consumed by buildings. However, while the energy loads of buildings can be accurately modelled, energy models often under...
Energy-optimal electrical excitation of nerve fibers.
Jezernik, Saso; Morari, Manfred
2005-04-01
We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.
Development of Optimal Stressor Scenarios for New Operational Energy Systems
2017-12-01
OPTIMAL STRESSOR SCENARIOS FOR NEW OPERATIONAL ENERGY SYSTEMS by Geoffrey E. Fastabend December 2017 Thesis Advisor: Alejandro S... ENERGY SYSTEMS 5. FUNDING NUMBERS 6. AUTHOR(S) Geoffrey E. Fastabend 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School...developed and tested simulation model for operational energy related systems in order to develop better stressor scenarios for acceptance testing
Tyurina, E. A.; Mednikov, A. S.
2017-11-01
The paper presents the results of studies on the perspective technologies of natural gas conversion to synthetic liquid fuel (SLF) at energy-technology installations for combined production of SLF and electricity based on their detailed mathematical models. The technologies of the long-distance transport of energy of natural gas from large fields to final consumers are compared in terms of their efficiency. This work was carried out at Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences and supported by Russian Science Foundation via grant No 16-19-10174
Interactive Cosegmentation Using Global and Local Energy Optimization
Xingping Dong,; Jianbing Shen,; Shao, Ling; Yang, Ming-Hsuan
2015-01-01
We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles to build the Gaussian mixture model and improve the cosegmentation performance. The second one is a global constraint, which attempts to match the histograms of common objects. To minimize the local energy, we apply the spline regression to learn the smoothne...
Optimizing refiner operation with statistical modelling
Energy Technology Data Exchange (ETDEWEB)
Broderick, G [Noranda Research Centre, Pointe Claire, PQ (Canada)
1997-02-01
The impact of refining conditions on the energy efficiency of the process and on the handsheet quality of a chemi-mechanical pulp was studied as part of a series of pilot scale refining trials. Statistical models of refiner performance were constructed from these results and non-linear optimization of process conditions were conducted. Optimization results indicated that increasing the ratio of specific energy applied in the first stage led to a reduction of some 15 per cent in the total energy requirement. The strategy can also be used to obtain significant increases in pulp quality for a given energy input. 20 refs., 6 tabs.
Simulation-based optimization of sustainable national energy systems
International Nuclear Information System (INIS)
Batas Bjelić, Ilija; Rajaković, Nikola
2015-01-01
The goals of the EU2030 energy policy should be achieved cost-effectively by employing the optimal mix of supply and demand side technical measures, including energy efficiency, renewable energy and structural measures. In this paper, the achievement of these goals is modeled by introducing an innovative method of soft-linking of EnergyPLAN with the generic optimization program (GenOpt). This soft-link enables simulation-based optimization, guided with the chosen optimization algorithm, rather than manual adjustments of the decision vectors. In order to obtain EnergyPLAN simulations within the optimization loop of GenOpt, the decision vectors should be chosen and explained in GenOpt for scenarios created in EnergyPLAN. The result of the optimization loop is an optimal national energy master plan (as a case study, energy policy in Serbia was taken), followed with sensitivity analysis of the exogenous assumptions and with focus on the contribution of the smart electricity grid to the achievement of EU2030 goals. It is shown that the increase in the policy-induced total costs of less than 3% is not significant. This general method could be further improved and used worldwide in the optimal planning of sustainable national energy systems. - Highlights: • Innovative method of soft-linking of EnergyPLAN with GenOpt has been introduced. • Optimal national energy master plan has been developed (the case study for Serbia). • Sensitivity analysis on the exogenous world energy and emission price development outlook. • Focus on the contribution of smart energy systems to the EU2030 goals. • Innovative soft-linking methodology could be further improved and used worldwide.
International Nuclear Information System (INIS)
Rong Xing; Du Yong; Frey, Eric C
2012-01-01
Quantitative Yttrium-90 ( 90 Y) bremsstrahlung single photon emission computed tomography (SPECT) imaging has shown great potential to provide reliable estimates of 90 Y activity distribution for targeted radionuclide therapy dosimetry applications. One factor that potentially affects the reliability of the activity estimates is the choice of the acquisition energy window. In contrast to imaging conventional gamma photon emitters where the acquisition energy windows are usually placed around photopeaks, there has been great variation in the choice of the acquisition energy window for 90 Y imaging due to the continuous and broad energy distribution of the bremsstrahlung photons. In quantitative imaging of conventional gamma photon emitters, previous methods for optimizing the acquisition energy window assumed unbiased estimators and used the variance in the estimates as a figure of merit (FOM). However, for situations, such as 90 Y imaging, where there are errors in the modeling of the image formation process used in the reconstruction there will be bias in the activity estimates. In 90 Y bremsstrahlung imaging this will be especially important due to the high levels of scatter, multiple scatter, and collimator septal penetration and scatter. Thus variance will not be a complete measure of reliability of the estimates and thus is not a complete FOM. To address this, we first aimed to develop a new method to optimize the energy window that accounts for both the bias due to model-mismatch and the variance of the activity estimates. We applied this method to optimize the acquisition energy window for quantitative 90 Y bremsstrahlung SPECT imaging in microsphere brachytherapy. Since absorbed dose is defined as the absorbed energy from the radiation per unit mass of tissues in this new method we proposed a mass-weighted root mean squared error of the volume of interest (VOI) activity estimates as the FOM. To calculate this FOM, two analytical expressions were derived for
Rong, Xing; Du, Yong; Frey, Eric C
2012-06-21
Quantitative Yttrium-90 ((90)Y) bremsstrahlung single photon emission computed tomography (SPECT) imaging has shown great potential to provide reliable estimates of (90)Y activity distribution for targeted radionuclide therapy dosimetry applications. One factor that potentially affects the reliability of the activity estimates is the choice of the acquisition energy window. In contrast to imaging conventional gamma photon emitters where the acquisition energy windows are usually placed around photopeaks, there has been great variation in the choice of the acquisition energy window for (90)Y imaging due to the continuous and broad energy distribution of the bremsstrahlung photons. In quantitative imaging of conventional gamma photon emitters, previous methods for optimizing the acquisition energy window assumed unbiased estimators and used the variance in the estimates as a figure of merit (FOM). However, for situations, such as (90)Y imaging, where there are errors in the modeling of the image formation process used in the reconstruction there will be bias in the activity estimates. In (90)Y bremsstrahlung imaging this will be especially important due to the high levels of scatter, multiple scatter, and collimator septal penetration and scatter. Thus variance will not be a complete measure of reliability of the estimates and thus is not a complete FOM. To address this, we first aimed to develop a new method to optimize the energy window that accounts for both the bias due to model-mismatch and the variance of the activity estimates. We applied this method to optimize the acquisition energy window for quantitative (90)Y bremsstrahlung SPECT imaging in microsphere brachytherapy. Since absorbed dose is defined as the absorbed energy from the radiation per unit mass of tissues in this new method we proposed a mass-weighted root mean squared error of the volume of interest (VOI) activity estimates as the FOM. To calculate this FOM, two analytical expressions were
REopt: A Platform for Energy System Integration and Optimization
Energy Technology Data Exchange (ETDEWEB)
Anderson, Katherine H. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cutler, Dylan S. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Olis, Daniel R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Elgqvist, Emma M. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Li, Xiangkun [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Laws, Nicholas D. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); DiOrio, Nicholas A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Walker, H. A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-09-22
REopt is a techno-economic decision support model used to optimize energy systems for buildings, campuses, communities, and microgrids. The primary application of the model is for optimizing the integration and operation of behind-the-meter energy assets. This report provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible, and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.
Energy Technology Data Exchange (ETDEWEB)
Lovley, Derek R
2012-12-28
The goal of this research was to provide computational tools to predictively model the behavior of two microbial communities of direct relevance to Department of Energy interests: 1) the microbial community responsible for in situ bioremediation of uranium in contaminated subsurface environments; and 2) the microbial community capable of harvesting electricity from waste organic matter and renewable biomass. During this project the concept of microbial electrosynthesis, a novel form of artificial photosynthesis for the direct production of fuels and other organic commodities from carbon dioxide and water was also developed and research was expanded into this area as well.
Optimizing Storage and Renewable Energy Systems with REopt
Energy Technology Data Exchange (ETDEWEB)
Elgqvist, Emma M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, Katherine H. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Cutler, Dylan S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); DiOrio, Nicholas A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Laws, Nicholas D. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olis, Daniel R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Walker, H. A. [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2017-12-27
Under the right conditions, behind the meter (BTM) storage combined with renewable energy (RE) technologies can provide both cost savings and resiliency. Storage economics depend not only on technology costs and avoided utility rates, but also on how the technology is operated. REopt, a model developed at NREL, can be used to determine the optimal size and dispatch strategy for BTM or off-grid applications. This poster gives an overview of three applications of REopt: Optimizing BTM Storage and RE to Extend Probability of Surviving Outage, Optimizing Off-Grid Energy System Operation, and Optimizing Residential BTM Solar 'Plus'.
Analysis and Optimization of Building Energy Consumption
Chuah, Jun Wei
Energy is one of the most important resources required by modern human society. In 2010, energy expenditures represented 10% of global gross domestic product (GDP). By 2035, global energy consumption is expected to increase by more than 50% from current levels. The increased pace of global energy consumption leads to significant environmental and socioeconomic issues: (i) carbon emissions, from the burning of fossil fuels for energy, contribute to global warming, and (ii) increased energy expenditures lead to reduced standard of living. Efficient use of energy, through energy conservation measures, is an important step toward mitigating these effects. Residential and commercial buildings represent a prime target for energy conservation, comprising 21% of global energy consumption and 40% of the total energy consumption in the United States. This thesis describes techniques for the analysis and optimization of building energy consumption. The thesis focuses on building retrofits and building energy simulation as key areas in building energy optimization and analysis. The thesis first discusses and evaluates building-level renewable energy generation as a solution toward building energy optimization. The thesis next describes a novel heating system, called localized heating. Under localized heating, building occupants are heated individually by directed radiant heaters, resulting in a considerably reduced heated space and significant heating energy savings. To support localized heating, a minimally-intrusive indoor occupant positioning system is described. The thesis then discusses occupant-level sensing (OLS) as the next frontier in building energy optimization. OLS captures the exact environmental conditions faced by each building occupant, using sensors that are carried by all building occupants. The information provided by OLS enables fine-grained optimization for unprecedented levels of energy efficiency and occupant comfort. The thesis also describes a retrofit
Optimized design of low energy buildings
DEFF Research Database (Denmark)
Rudbeck, Claus Christian; Esbensen, Peter Kjær; Svendsen, Sv Aa Højgaard
1999-01-01
concern which can be seen during the construction of new buildings. People want energy-friendly solutions, but they should be economical optimized. An exonomical optimized building design with respect to energy consumption is the design with the lowest total cost (investment plus operational cost over its...... to evaluate different separate solutions when they interact in the building.When trying to optimize several parameters there is a need for a method, which will show the correct price-performance of each part of a building under design. The problem with not having such a method will first be showed...
Integrated energy optimization with smart home energy management systems
Asare-Bediako, B.; Ribeiro, P.F.; Kling, W.L.
2012-01-01
Optimization of energy use is a vital concept in providing solutions to many of the energy challenges in our world today. Large chemical, mechanical, pneumatic, hydraulic, and electrical systems require energy efficiency as one of the important aspects of operating systems. At the micro-scale, the
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Energy Optimal Control of Induction Motor Drives
DEFF Research Database (Denmark)
Abrahamsen, Flemming
This thesis deals with energy optimal control of small and medium-size variable speed induction motor drives for especially Heating, Ventilation and Air-Condition (HVAC) applications. Optimized efficiency is achieved by adapting the magnetization level in the motor to the load, and the basic...... demonstrated that energy optimal control will sometimes improve and sometimes deteriorate the stability. Comparison of small and medium-size induction motor drives with permanent magnet motor drives indicated why, and in which applications, PM motors are especially good. Calculations of economical aspects...... improvement by energy optimal control for any standard induction motor drive between 2.2 kW and 90 kW. A simple method to evaluate the robustness against load disturbances was developed and used to compare the robustness of different motor types and sizes. Calculation of the oscillatory behavior of a motor...
Multimodal piezoelectric devices optimization for energy harvesting
Directory of Open Access Journals (Sweden)
G Acciani
2016-09-01
Full Text Available The use of the piezoelectric effect to convert ambient vibration into useful electrical energy constitutes one of the most studied areas in Energy Harvesting (EH research. This paper presents a typical cantilevered Energy Harvester device, which relates the electrical outputs to the vibration mode shape easily. The dynamic strain induced in the piezoceramic layer results in an alternating voltage output. The first six modes of frequencies and the deformation pattern of the beam are carried out basing on an eigenfrequency analysis conducted by the MEMS modules of the COMSOL Multiphysic® v3.5a to perform the Finite Element Analysis of the model. Subsequently, the piezoelectric material is cut around the inflection points to minimize the voltage cancellation effect occurring when the sign changes in the material. This study shows that the voltage produced by the device, increases in as the dimensions of the cuts vary in the piezoelectric layer. Such voltage reaches the optimum amount of piezoelectric material and cuts positioning. This proves that the optimized piezoelectric layer is 16% more efficient than the whole piezoelectric layer.
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.
DEFF Research Database (Denmark)
Milan, Christian
, individual performance models are defined. For small scale residential systems the hot water tank is one of the main components, connecting supply and demand side and acting as a buffer during mismatch periods. For this reason, the developed hot water tank model is rather detailed accounting for three...... different temperature layers, two different supply and demand loops as well as individual heat losses. It is presented at the end of the technology chapter. Subsequently, the methodology is validated by investigating the output with one single technology at a time and thus the individual performance models......This work presents a methodology to identify and investigate the cost optimal design of supply systems for Low and Net Zero Energy Buildings with the focus on residential single family houses. A preliminary analysis investigating relevant literature and existing computer tools resulted...
Risk modelling in portfolio optimization
Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi
2013-09-01
Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.
Optimal planning of integrated multi-energy systems
DEFF Research Database (Denmark)
van Beuzekom, I.; Gibescu, M.; Pinson, Pierre
2017-01-01
In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration...... and sustainability goals for 2030 and 2045. Optimal green- and brownfield designs for a district's future integrated energy system are compared using a one-step, as well as a two-step planning approach. As expected, the greenfield designs are more cost efficient, as their results are not constrained by the existing...
Model Risk in Portfolio Optimization
Directory of Open Access Journals (Sweden)
David Stefanovits
2014-08-01
Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.
CLUSTER ENERGY OPTIMIZATION: A THEORETICAL APPROACH
Vikram Yadav; G. Sahoo
2013-01-01
The optimization of energy consumption in the cloud computing environment is the question how to use various energy conservation strategies to efficiently allocate resources. The need of differentresources in cloud environment is unpredictable. It is observed that load management in cloud is utmost needed in order to provide QOS. The jobs at over-loaded physical machine are shifted to under-loadedphysical machine and turning the idle machine off in order to provide green cloud. For energy opt...
Energy Technology Data Exchange (ETDEWEB)
Tomaschek, Jan
2013-12-11
The transport sector is seen as one of the key factors for driving future energy consumption and greenhouse gas (GHG) emissions. Especially in developing countries, significant growth in transport demand is expected. Gauteng province, as the economic centre of South Africa and transport hub for the whole of southern Africa, is one emerging urban region that faces rapid growth. However, the province is on its way to playing a leading role for supporting ways to adapt to climate change and mitigate GHG emissions. Conversely, there is a lack of scientific research on the promising measures for GHG mitigation in the transport sector. For the rapidly growing transport sector of the province in particular, research is focused primarily on extending and structuring the road infrastructure. Moreover, it is important that the transport sector is considered as part of the whole energy system, as significant contributions to GHG emissions and the associated costs arise from energy supply, provision and conversion. This research is the first application of an integrated energy system model (i.e. the TIMES-GEECO model) for the optimization of the transport sector of Gauteng. Optimizing energy system models allows finding least-cost measures for various scenarios, by considering dependencies and interlinkages in the energy system as well as environmental constraints. To do so, the transport sector and the energy supply sector had to be incorporated into the model application in terms of the characteristics of a developing urban region, which includes all relevant transport modes, vehicle technologies, fuel options, vehicle-to-grid energy storage, the consideration of road types as well as explicit expansions of the public transport system and income-dependent travel demand modelling. Additionally, GHG mitigation options outside the provincial boundaries were incorporated to allow for mitigation at least cost and to consider regional resource availability. Moreover, in TIMES
International Nuclear Information System (INIS)
Tomaschek, Jan
2013-01-01
The transport sector is seen as one of the key factors for driving future energy consumption and greenhouse gas (GHG) emissions. Especially in developing countries, significant growth in transport demand is expected. Gauteng province, as the economic centre of South Africa and transport hub for the whole of southern Africa, is one emerging urban region that faces rapid growth. However, the province is on its way to playing a leading role for supporting ways to adapt to climate change and mitigate GHG emissions. Conversely, there is a lack of scientific research on the promising measures for GHG mitigation in the transport sector. For the rapidly growing transport sector of the province in particular, research is focused primarily on extending and structuring the road infrastructure. Moreover, it is important that the transport sector is considered as part of the whole energy system, as significant contributions to GHG emissions and the associated costs arise from energy supply, provision and conversion. This research is the first application of an integrated energy system model (i.e. the TIMES-GEECO model) for the optimization of the transport sector of Gauteng. Optimizing energy system models allows finding least-cost measures for various scenarios, by considering dependencies and interlinkages in the energy system as well as environmental constraints. To do so, the transport sector and the energy supply sector had to be incorporated into the model application in terms of the characteristics of a developing urban region, which includes all relevant transport modes, vehicle technologies, fuel options, vehicle-to-grid energy storage, the consideration of road types as well as explicit expansions of the public transport system and income-dependent travel demand modelling. Additionally, GHG mitigation options outside the provincial boundaries were incorporated to allow for mitigation at least cost and to consider regional resource availability. Moreover, in TIMES
Optimal Energy Mix with Renewable Portfolio Standards in Korea
Directory of Open Access Journals (Sweden)
Zong Woo Geem
2016-05-01
Full Text Available Korea is a heavily energy-dependent country whose primary energy consumption ranks ninth in the world. However, at the same time, it promised to reduce carbon emission and planned to use more renewable energy. Thus, the objective of this study is to propose an optimal energy mix planning model in electricity generation from various energy sources, such as gas, coal, nuclear, hydro, wind, photovoltaic, and biomass, which considers more renewable and sustainable portions by imposing governmental regulation named renewable portfolio standard (RPS. This optimization model minimizes various costs such as construction cost, operation and management cost, fuel cost, and carbon emission cost while satisfying minimal demand requirement, maximal annual installation potential, and renewable portfolio standard constraints. Results showed that this optimization model could successfully generate energy mix plan from 2012 to 2030 while minimizing the objective costs and satisfying all the constraints. Therefore, this optimization model contributes more efficient and objective method to the complex decision-making process with a sustainability option. This proposed energy mix model is expected to be applied not only to Korea, but also to many other countries in the future for more economical planning of their electricity generation while affecting climate change less.
Optimization of joint energy micro-grid with cold storage
Xu, Bin; Luo, Simin; Tian, Yan; Chen, Xianda; Xiong, Botao; Zhou, Bowen
2018-02-01
To accommodate distributed photovoltaic (PV) curtailment, to make full use of the joint energy micro-grid with cold storage, and to reduce the high operating costs, the economic dispatch of joint energy micro-grid load is particularly important. Considering the different prices during the peak and valley durations, an optimization model is established, which takes the minimum production costs and PV curtailment fluctuations as the objectives. Linear weighted sum method and genetic-taboo Particle Swarm Optimization (PSO) algorithm are used to solve the optimization model, to obtain optimal power supply output. Taking the garlic market in Henan as an example, the simulation results show that considering distributed PV and different prices in different time durations, the optimization strategies are able to reduce the operating costs and accommodate PV power efficiently.
REopt: A Platform for Energy System Integration and Optimization: Preprint
Energy Technology Data Exchange (ETDEWEB)
Simpkins, T.; Cutler, D.; Anderson, K.; Olis, D.; Elgqvist, E.; Callahan, M.; Walker, A.
2014-08-01
REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.
International Nuclear Information System (INIS)
Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui
2016-01-01
Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could
International Nuclear Information System (INIS)
Chen, Yizhong; He, Li; Li, Jing; Cheng, Xi; Lu, Hongwei
2016-01-01
Highlights: • Detailed model developed for power generation and pollutants mitigation. • Dynamic integration of bi-level programming with uncertainty analyses. • Application of the novel bi-level model for EPS in Fengtai District. • Development of renewable energy under different probability levels. - Abstract: In this study, an IBSOM (inexact bi-level simulation–optimization model) is developed for conjunctive regional renewable energy planning and air pollution control for EPS (electric power systems) under uncertainty. The IBSOM integrates techniques of CFMTVW (combined forecasting model with time-varying weights), ILP (interval linear programming), MIP (mixed integer programming), CCP (chance-constrained programming), as well as BLP (bi-level programming) into a general framework. In the IBSOM, uncertainties expressed as interval and stochastic parameters within multi-period and multi-option contexts can be effectively tackled. In addition, a leader-follower decision strategy is incorporated into the optimization process where two non-competitive objectives are sequentially proposed, with the environmental sector dominating the upper-level objective (leader’s one) and the energy sector providing the lower-level objective (follower’s one). To solve the proposed model, an improved bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for balancing to what extent the constraints are met and the objective reaches its optima. Then, the IBSOM is applied to a real-world case study of EPS in Fengtai District, Beijing, China. Interval solutions associated with renewable energy development, electricity generation, facility-expansion scheme, as well as pollutants mitigation can be obtained under different system-violation risk. Results indicate that a higher violation risk would lead to a decreased strictness of the constraints or an expanded decision space, which results in the decreased system
Champion, Billy Ray
Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. . Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. . The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM
Optimization theory for ballistic energy conversion
Xie, Yanbo; Versluis, Michel; Van Den Berg, Albert; Eijkel, Jan C.T.
2016-01-01
The growing demand of renewable energy stimulates the exploration of new materials and methods for clean energy. We recently demonstrated a high efficiency and power density energy conversion mechanism by using jetted charged microdroplets, termed as ballistic energy conversion. Hereby, we model and
Methods for Distributed Optimal Energy Management
DEFF Research Database (Denmark)
Brehm, Robert
The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast to convent......The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast...... to conventional centralised optimal energy flow management systems, here-in, focus is set on how optimal energy management can be achieved in a decentralised distributed architecture such as a multi-agent system. Distributed optimisation methods are introduced, targeting optimisation of energy flow in virtual......-consumption of renewable energy resources in low voltage grids. It can be shown that this method prevents mutual discharging of batteries and prevents peak loads, a supervisory control instance can dictate the level of autarchy from the utility grid. Further it is shown that the problem of optimal energy flow management...
Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.
Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T
2018-04-03
While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.
Energy mesh optimization for multi-level calculation schemes
International Nuclear Information System (INIS)
Mosca, P.; Taofiki, A.; Bellier, P.; Prevost, A.
2011-01-01
The industrial calculations of third generation nuclear reactors are based on sophisticated strategies of homogenization and collapsing at different spatial and energetic levels. An important issue to ensure the quality of these calculation models is the choice of the collapsing energy mesh. In this work, we show a new approach to generate optimized energy meshes starting from the SHEM 281-group library. The optimization model is applied on 1D cylindrical cells and consists of finding an energy mesh which minimizes the errors between two successive collision probability calculations. The former is realized over the fine SHEM mesh with Livolant-Jeanpierre self-shielded cross sections and the latter is performed with collapsed cross sections over the energy mesh being optimized. The optimization is done by the particle swarm algorithm implemented in the code AEMC and multigroup flux solutions are obtained from standard APOLLO2 solvers. By this new approach, a set of new optimized meshes which encompass from 10 to 50 groups has been defined for PWR and BWR calculations. This set will allow users to adapt the energy detail of the solution to the complexity of the calculation (assembly, multi-assembly, two-dimensional whole core). Some preliminary verifications, in which the accuracy of the new meshes is measured compared to a direct 281-group calculation, show that the 30-group optimized mesh offers a good compromise between simulation time and accuracy for a standard 17 x 17 UO 2 assembly with and without control rods. (author)
Energy modelling in sensor networks
Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.
2007-06-01
Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.
A Source-level Energy Optimization Framework for Mobile Applications
DEFF Research Database (Denmark)
Li, Xueliang; Gallagher, John Patrick
2016-01-01
strategies. The framework also lays a foundation for the code optimization by automatic tools. To the best of our knowledge, our work is the first that achieves this for a high-level language such as Java. In a case study, the experimental evaluation shows that our approach is able to save from 6.4% to 50...... process. The source code is the interface between the developer and hardware resources. In this paper, we propose an energy optimization framework guided by a source code energy model that allows developers to be aware of energy usage induced by the code and to apply very targeted source-level refactoring...
Energy Technology Data Exchange (ETDEWEB)
Akimoto, K.; Matsunaga, A.; Fujii, Y. [Yokohama National University, Yokohama (Japan); Yamaji, K. [The University of Tokyo, Tokyo (Japan)
1998-10-01
Carbon emissions which would cause global warming were agreed to be constrained at COP3 in Kyoto. In addition, carton emission permits trading was also approved to be introduced. The emission permits trading is expected to achieve efficient carbon emission reduction, equalizing the marginal costs of the emission reduction for the participating countries. In other words, the permits trading allows participants to reduce emissions where it is least expensive to do so. However, the inadequate introduction of the trading systems may impose unfairly greater burden on some countries, and therefore careful evaluation of the system would be indispensable for its implementation. In this paper, we attempt to analyze the emission permits trading. using the theory of cooperative games with a global energy model of optimization type. We assumed that seven world regions as players participate the permits trading system under the condition of the emission reduction target presented at COP3 and so on, and show the nucleolus of the grand coalition games, and the computational results of primary energy supplies and CO2 shadow prices. The insights of this research indicate that in order to stabilize the grand coalition, a noticeable amount of additional transfer of money would be needed besides the payments associated with the emission permits trading. 10 refs., 7 figs., 5 tabs.
Energy accounting and optimization for mobile systems
Dong, Mian
Energy accounting determines how much a software process contributes to the total system energy consumption. It is the foundation for evaluating software and has been widely used by operating system based energy management. While various energy accounting policies have been tried, there is no known way to evaluate them directly simply because it is hard to track every hardware use by software in a heterogeneous multi-core system like modern smartphones and tablets. In this thesis, we provide the ground truth for energy accounting based on multi-player game theory and offer the first evaluation of existing energy accounting policies, revealing their important flaws. The proposed ground truth is based on Shapley value, a single value solution to multi-player games of which four axiomatic properties are natural and self-evident to energy accounting. To obtain the Shapley value-based ground truth, one only needs to know if a process is active during the time under question and the system energy consumption during the same time. We further provide a utility optimization formulation of energy management and show, surprisingly, that energy accounting does not matter for existing energy management solutions that control the energy use of a process by giving it an energy budget, or budget based energy management (BEM). We show an optimal energy management (OEM) framework can always outperform BEM. While OEM does not require any form of energy accounting, it is related to Shapley value in that both require the system energy consumption for all possible combination of processes under question. We provide a novel system solution that meet this requirement by acquiring system energy consumption in situ for an OS scheduler period, i.e.,10 ms. We report a prototype implementation of both Shapley value-based energy accounting and OEM based scheduling. Using this prototype and smartphone workload, we experimentally demonstrate how erroneous existing energy accounting policies can
METHOD FOR OPTIMIZING THE ENERGY OF PUMPS
Skovmose Kallesøe, Carsten; De Persis, Claudio
2013-01-01
The device for energy-optimization on operation of several centrifugal pumps controlled in rotational speed, in a hydraulic installation, begins firstly with determining which pumps as pilot pumps are assigned directly to a consumer and which pumps are hydraulically connected in series upstream of
Cost optimal levels for energy performance requirements
DEFF Research Database (Denmark)
Thomsen, Kirsten Engelund; Aggerholm, Søren; Kluttig-Erhorn, Heike
This report summarises the work done within the Concerted Action EPBD from December 2010 to April 2011 in order to feed into the European Commission's proposal for a common European procedure for a Cost-Optimal methodology under the Directive on the Energy Performance of Buildings (recast) 2010/3...
Application of Strain Energy on BIW Mode Optimization
Directory of Open Access Journals (Sweden)
Chang Guangbao
2015-01-01
Full Text Available This paper takes the BIW model as the research object, completes modal analysis, and verifies the finite element model by comparing the simulation results with the test results. In order to improve the frequency of BIW, the weak structure of D pillar is found and then optimized by the method of strain energy, and the frequency of BIW is changed from 28.80Hz to 32.15Hz. Finally, the method of strain energy has great positive effects on modal optimization.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
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
Optimal Scheduling of a Multi-Carrier Energy Hub Supplemented By Battery Energy Storage Systems
DEFF Research Database (Denmark)
Javadi, Mohammad Sadegh; Anvari-Moghaddam, Amjad; Guerrero, Josep M.
2017-01-01
This paper introduces a management model for optimal scheduling of a multi-carrier energy hub. In the proposed hub, three types of assets are considered: dispersed generating systems (DGs) such as micro-combined heat and power (mCHP) units, storage devices such as battery-based electrical storage...... systems (ESSs), and heating/cooling devices such as electrical heater, heat-pumps and absorption chillers. The optimal scheduling and management of the examined energy hub assets in line with electrical transactions with distribution network is modeled as a mixed-integer non-linear optimization problem....... In this regard, optimal operating points of DG units as well as ESSs are calculated based on a cost-effective strategy. Degradation cost of ESSs is also taken into consideration for short-term scheduling. Simulation results demonstrate that including well-planned energy storage options together with optimal...
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.
International Nuclear Information System (INIS)
Carton, Ann-Katherine; Ullberg, Christer; Lindman, Karin; Acciavatti, Raymond; Francke, Tom; Maidment, Andrew D. A.
2010-01-01
Purpose: Dual-energy (DE) iodine contrast-enhanced x-ray imaging of the breast has been shown to identify cancers that would otherwise be mammographically occult. In this article, theoretical modeling was performed to obtain optimally enhanced iodine images for a photon-counting digital breast tomosynthesis (DBT) system using a DE acquisition technique. Methods: In the system examined, the breast is scanned with a multislit prepatient collimator aligned with a multidetector camera. Each detector collects a projection image at a unique angle during the scan. Low-energy (LE) and high-energy (HE) projection images are acquired simultaneously in a single scan by covering alternate collimator slits with Sn and Cu filters, respectively. Sn filters ranging from 0.08 to 0.22 mm thickness and Cu filters from 0.11 to 0.27 mm thickness were investigated. A tube voltage of 49 kV was selected. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. Iodine-enhanced DBT images were acquired by performing a weighted logarithmic subtraction of the HE and LE DBT images. The DE technique was evaluated for 20-80 mm thick breasts. Weighting factors, w t , that optimally cancel breast tissue were computed. Signal-difference-to-noise ratios (SDNRs) between iodine-enhanced and nonenhanced breast tissue normalized to the square root of the mean glandular dose (MGD) were computed as a function of the fraction of the MGD allocated to the HE images. Peak SDNR/√(MGD) and optimal dose allocations were identified. SDNR/√(MGD) and dose allocations were computed for several practical feasible system configurations (i.e., determined by the number of collimator slits covered by Sn and Cu). A practical system configuration and Sn-Cu filter pair that accounts for the trade-off between SDNR, tube-output, and MGD were selected. Results: w t depends on the Sn-Cu filter combination used, as well as on the breast thickness; to optimally cancel 0
Pyomo optimization modeling in Python
Hart, William E; Watson, Jean-Paul; Woodruff, David L; Hackebeil, Gabriel A; Nicholson, Bethany L; Siirola, John D
2017-01-01
This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. Pyomo is an open source software package fo...
Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs
Directory of Open Access Journals (Sweden)
Jiajun Liu
2017-10-01
Full Text Available Energy storage systems (ESS play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs and supercapacitors (SCs is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS of 14-ton underground load-haul-dump vehicles (LHDs. Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.
Venturi scrubber modelling and optimization
Energy Technology Data Exchange (ETDEWEB)
Viswanathan, S [National Univ., La Jolla, CA (United States). School of Engineering and Technology; Ananthanarayanan, N.V. [National Univ. of Singapore (Singapore). Dept. of Chemical and Environmental Engineering; Azzopardi, B.J. [Nottingham Univ., Nottingham (United Kingdom). Dept. of Chemical Engineering
2005-04-01
This study presented a method to maintain the efficiency of venturi scrubbers in removing fine particulates during gas clean operations while minimizing pressure drop. Venturi scrubbers meet stringent emission standards. In order to choose the optimal method for predicting pressure drop, 4 established models were compared for their accuracy of prediction and simplicity in application. The enhanced algorithm optimizes Pease-Anthony type venturi scrubber performance by predicting the minimum pressure drop required to achieve the desired collection efficiency. This was accomplished by optimizing the key operating and design parameters such as liquid-to-gas ratio, throat gas velocity, number of nozzles, nozzle diameter and throat aspect ratio. Two of the 4 established models were expanded by providing an empirical algorithm to better predict pressure drop in the venturi throat. Model results were validated with experimental data. The optimization algorithm considers the non-uniformity in liquid distribution. It can be applied to cylindrical and rectangular Pease-Anthony type scrubbers. It offers an effective, systematic and accurate method to optimize the performance of new and existing scrubbers. 54 refs., 5 figs.
Optimal satisfaction degree in energy harvesting cognitive radio networks
International Nuclear Information System (INIS)
Li Zan; Liu Bo-Yang; Si Jiang-Bo; Zhou Fu-Hui
2015-01-01
A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. (paper)
Optimal satisfaction degree in energy harvesting cognitive radio networks
Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui
2015-12-01
A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).
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...
Optimal energy management for a flywheel-based hybrid vehicle
Berkel, van K.; Hofman, T.; Vroemen, B.G.; Steinbuch, M.
2011-01-01
This paper presents the modeling and design of an optimal Energy Management Strategy (EMS) for a flywheel-based hybrid vehicle, that does not use any electrical motor/generator, or a battery, for its hybrid functionalities. The hybrid drive train consists of only low-cost components, such as a
Potential Energy Savings in Refrigeration Systems Using Optimal Setpoints
DEFF Research Database (Denmark)
Larsen, Lars Finn Slot; Thybo, Claus
2004-01-01
Energy efficiency of refrigeration systems has gradually been improved with help of control schemes utilizing the more flexible components. This paper proposes an approach in line with this trend, where a suboptimal condenser pressure is found in order to minimize the energy consumption. The obje......Energy efficiency of refrigeration systems has gradually been improved with help of control schemes utilizing the more flexible components. This paper proposes an approach in line with this trend, where a suboptimal condenser pressure is found in order to minimize the energy consumption....... The objective is to give an idea of how this optimization scheme works as well as to show what amount of energy it is possible to save. A steady state model of a simple refrigeration system will be used as a basis for the optimization....
Complex energy system management using optimization techniques
Energy Technology Data Exchange (ETDEWEB)
Bridgeman, Stuart; Hurdowar-Castro, Diana; Allen, Rick; Olason, Tryggvi; Welt, Francois
2010-09-15
Modern energy systems are often very complex with respect to the mix of generation sources, energy storage, transmission, and avenues to market. Historically, power was provided by government organizations to load centers, and pricing was provided in a regulatory manner. In recent years, this process has been displaced by the independent system operator (ISO). This complexity makes the operation of these systems very difficult, since the components of the system are interdependent. Consequently, computer-based large-scale simulation and optimization methods like Decision Support Systems are now being used. This paper discusses the application of a DSS to operations and planning systems.
Modeling and Optimization : Theory and Applications Conference
Terlaky, Tamás
2017-01-01
This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 17-19, 2016. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.
Modeling and Optimization : Theory and Applications Conference
Terlaky, Tamás
2015-01-01
This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 13-15, 2014. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, healthcare, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.
Agreement Technologies for Energy Optimization at Home.
González-Briones, Alfonso; Chamoso, Pablo; De La Prieta, Fernando; Demazeau, Yves; Corchado, Juan M
2018-05-19
Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.
Simultaneous integrated optimal energy flow of electricity, gas, and heat
International Nuclear Information System (INIS)
Shabanpour-Haghighi, Amin; Seifi, Ali Reza
2015-01-01
Highlights: • Integration of electrical, natural gas, and district heating networks is studied. • Part-load performances of units are considered in modeling. • A modified teaching–learning based optimization is used to solve the problem. • Results show the advantages of the integrated optimization approach. - Abstract: In this paper, an integrated approach to optimize electrical, natural gas, and district heating networks simultaneously is studied. Several interdependencies between these infrastructures are considered in details including a nonlinear part-load performance for boilers and CHPs besides the valve-point effect for generators. A novel approach based on selecting an appropriate set of state-variables for the problem is proposed that eliminates the addition of any new variable to convert irregular equations into a regular set while the optimization problem is still solvable. As a large optimization problem, the optimal solution cannot be achieved by conventional mathematical techniques. Hence, it is better to use evolutionary algorithms instead. In this paper, the well-known modified teaching–learning based optimization algorithm is utilized to solve the multi-period optimal power flow problem of multi-carrier energy networks. The proposed scheme is implemented and applied to a typical multi-carrier energy network. Results are compared with some other conventional heuristic algorithms and the applicability and superiority of the proposed methodology is verified
Site specific optimization of wind turbines energy cost: Iterative approach
International Nuclear Information System (INIS)
Rezaei Mirghaed, Mohammad; Roshandel, Ramin
2013-01-01
Highlights: • Optimization model of wind turbine parameters plus rectangular farm layout is developed. • Results show that levelized cost for single turbine fluctuates between 46.6 and 54.5 $/MW h. • Modeling results for two specific farms reported optimal sizing and farm layout. • Results show that levelized cost of the wind farms fluctuates between 45.8 and 67.2 $/MW h. - Abstract: The present study was aimed at developing a model to optimize the sizing parameters and farm layout of wind turbines according to the wind resource and economic aspects. The proposed model, including aerodynamic, economic and optimization sub-models, is used to achieve minimum levelized cost of electricity. The blade element momentum theory is utilized for aerodynamic modeling of pitch-regulated horizontal axis wind turbines. Also, a comprehensive cost model including capital costs of all turbine components is considered. An iterative approach is used to develop the optimization model. The modeling results are presented for three potential regions in Iran: Khaf, Ahar and Manjil. The optimum configurations and sizing for a single turbine with minimum levelized cost of electricity are presented. The optimal cost of energy for one turbine is calculated about 46.7, 54.5 and 46.6 dollars per MW h in the studied sites, respectively. In addition, optimal size of turbines, annual electricity production, capital cost, and wind farm layout for two different rectangular and square shaped farms in the proposed areas have been recognized. According to the results, optimal system configuration corresponds to minimum levelized cost of electricity about 45.8 to 67.2 dollars per MW h in the studied wind farms
A model of optimal voluntary muscular control.
FitzHugh, R
1977-07-19
In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.
Optimal Energy Consumption Analysis of Natural Gas Pipeline
Liu, Enbin; Li, Changjun; Yang, Yi
2014-01-01
There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent. PMID:24955410
Optimal sizing of energy storage system for microgrids
Indian Academy of Sciences (India)
strategies and optimal allocation methods of the ESS devices are required for the MG. ... for the optimal design of systems managed optimally according to different .... Energy storage hourly operating and maintenance cost is defined as a ...
Optimal Operation of Energy Storage in Power Transmission and Distribution
Akhavan Hejazi, Seyed Hossein
In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider
Di Cosmo, Valeri; Hyland, Marie
2012-01-01
PUBLISHED In Ireland, the energy sector has undergone significant change in the last forty years. In this period, there has been a significant increase in the demand for energy. This increase has been driven by economic and demographic factors. Although the current deep recession has quelled the upward trend in the demand for energy, a future economic recovery will bring these issues back into focus. This paper documents a model of the Irish energy sector which relates energy demand to re...
A robust optimization approach for energy generation scheduling in microgrids
International Nuclear Information System (INIS)
Wang, Ran; Wang, Ping; Xiao, Gaoxi
2015-01-01
Highlights: • A new uncertainty model is proposed for better describing unstable energy demands. • An optimization problem is formulated to minimize the cost of microgrid operations. • Robust optimization algorithms are developed to transform and solve the problem. • The proposed scheme can prominently reduce energy expenses. • Numerical results provide useful insights for future investment policy making. - Abstract: In this paper, a cost minimization problem is formulated to intelligently schedule energy generations for microgrids equipped with unstable renewable sources and combined heat and power (CHP) generators. In such systems, the fluctuant net demands (i.e., the electricity demands not balanced by renewable energies) and heat demands impose unprecedented challenges. To cope with the uncertainty nature of net demand and heat demand, a new flexible uncertainty model is developed. Specifically, we introduce reference distributions according to predictions and field measurements and then define uncertainty sets to confine net and heat demands. The model allows the net demand and heat demand distributions to fluctuate around their reference distributions. Another difficulty existing in this problem is the indeterminate electricity market prices. We develop chance constraint approximations and robust optimization approaches to firstly transform and then solve the prime problem. Numerical results based on real-world data evaluate the impacts of different parameters. It is shown that our energy generation scheduling strategy performs well and the integration of combined heat and power (CHP) generators effectively reduces the system expenditure. Our research also helps shed some illuminations on the investment policy making for microgrids.
1981-05-01
A summary of the energy situation in Brazil is presented. Energy consumption rates, reserves of primary energy, and the basic needs and strategies for meeting energy self sufficiency are discussed. Conserving energy, increasing petroleum production, and utilizing other domestic energy products and petroleum by-products are discussed. Specific programs are described for the development and use of alcohol fuels, wood and charcoal, coal, schist, solar and geothermal energy, power from the sea, fresh biomass, special batteries, hydrogen, vegetable oil, and electric energy from water power, nuclear, and coal. Details of the energy model for 1985 are given. Attention is also given to the energy demands and the structure of global energy from 1975 to 1985.
Energy Technology Data Exchange (ETDEWEB)
Beard, J.N. Jr.; Rice, W.T. Jr.
1980-01-01
A project to develop a mathematical model capable of simulating the activities in a typical batch dyeing process in the textile industry is described. The model could be used to study the effects of changes in dye-house operations, and to determine effective guidelines for optimal dyehouse performance. The computer model is of a hypothetical dyehouse. The appendices contain a listing of the computer program, sample computer inputs and outputs, and instructions for using the model. (MCW)
Optimization of Hybrid Renewable Energy Systems
Contreras Cordero, Francisco Jose
Use of diesel generators in remote communities is economically and environmentally unsustainable. Consequently, researchers have focussed on designing hybrid renewable energy systems (HRES) for distributed electricity generation in remote communities. However, the cost-effectiveness of interconnecting multiple remote communities (microgrids) has not been explored. The main objective of this thesis is to develop a methodology for optimal design of HRES and microgrids for remote communities. A set of case studies was developed to test this methodology and it was determined that a combination of stand-alone decentralized HRES and microgrids is the most cost-effective power generation scheme when studying a group of remote communities.
Optimal energy management in pulp and paper mills
International Nuclear Information System (INIS)
Sarimveis, H.K.; Angelou, A.S.; Retsina, T.R.; Rutherford, S.R.; Bafas, G.V.
2003-01-01
In this paper, we examine the utilization of mathematical programming tools for optimum energy management of the power plant in pulp and paper mills. The objective is the fulfillment of the total plant requirements in energy and steam with the minimum possible cost. The proposed methodology is based on the development of a detailed model of the power plant using mass and energy balances and a mathematical formulation of the electrical purchase contract, which can be translated into a rigorous mixed integer linear programming optimization problem. The results show that the method can be a very useful tool for the reduction of production cost due to minimization of the fuel and electricity costs
Optimal Investment Planning of Bulk Energy Storage Systems
Directory of Open Access Journals (Sweden)
Dina Khastieva
2018-02-01
Full Text Available Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonia...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
Energy efficiency improvement by gear shifting optimization
Directory of Open Access Journals (Sweden)
Blagojevic Ivan A.
2013-01-01
Full Text Available Many studies have proved that elements of driver’s behavior related to gear selection have considerable influence on the fuel consumption. Optimal gear shifting is a complex task, especially for inexperienced drivers. This paper presents an implemented idea for gear shifting optimization with the aim of fuel consumption minimization with more efficient engine working regimes. Optimized gear shifting enables the best possible relation between vehicle motion regimes and engine working regimes. New theoretical-experimental approach has been developed using On-Board Diagnostic technology which so far has not been used for this purpose. The matrix of driving modes according to which tests were performed is obtained and special data acquisition system and analysis process have been developed. Functional relations between experimental test modes and adequate engine working parameters have been obtained and all necessary operations have been conducted to enable their use as inputs for the designed algorithm. The created Model has been tested in real exploitation conditions on passenger car with Otto fuel injection engine and On-Board Diagnostic connection without any changes on it. The conducted tests have shown that the presented Model has significantly positive effects on fuel consumption which is an important ecological aspect. Further development and testing of the Model allows implementation in wide range of motor vehicles with various types of internal combustion engines.
Energy Technology Data Exchange (ETDEWEB)
Palzer, Andreas
2016-07-01
With the aim of reducing greenhouse gas emissions, comprehensive climate protection measures have already been adopted both nationally and internationally. This raises the question of how economically and ecologically useful system infrastructure looks, which at the same time ensures the supply reliability of all consumers. The regenerative energy model (REMod) presented in this book has been developed to provide answers. The sectors electricity, heat, transport and industry are considered for the first time simultaneous in an energy system model. In particular, in order to satisfy the criterion of reliability of supply, the model calculates the energy flows in hourly resolution for the period from today (2015) to 2050. The system is optimized with regard to minimum overall costs and under the boundary condition that a maximum set quantity of permitted greenhouse gas emissions is not exceed. On the example of Germany (REMod-D), the results show that, in particular, the interaction of the sectors can lead to strong differences in the design of the system infrastructure. [German] Mit dem Ziel den Ausstoss der Treibhausgase zu reduzieren, wurden bereits national wie international umfangreiche Klimaschutzmassnahmen verabschiedet. Hieraus ergibt sich die Frage wie eine oekonomisch und oekologisch sinnvolle Systeminfrastruktur aussieht, die gleichzeitig die Versorgungssicherheit aller Verbraucher gewaehrleistet. Das in diesem Buch vorgestellte Regenerative Energien Modell (REMod) wurde entwickelt um hierauf Antworten zu liefern. Beruecksichtigt werden erstmalig in einem Energiesystemmodell die Sektoren Strom, Waerme, Verkehr und Industrie gleichzeitig. Insbesondere um dem Kriterium der Versorgungssicherheit gerecht zu werden, berechnet das Modell die Energiefluesse in stuendlicher Aufloesung fuer den Zeitraum von heute (2015) bis 2050. Optimiert wird das System hinsichtlich minimaler Gesamtkosten und unter der Randbedingung, dass eine maximal vorgegebene Menge erlaubter
Optimal portfolio selection between different kinds of Renewable energy sources
Energy Technology Data Exchange (ETDEWEB)
Zakerinia, MohammadSaleh; Piltan, Mehdi; Ghaderi, Farid
2010-09-15
In this paper, selection of the optimal energy supply system in an industrial unit is taken into consideration. This study takes environmental, economical and social parameters into consideration in modeling along with technical factors. Several alternatives which include renewable energy sources, micro-CHP systems and conventional system has been compared by means of an integrated model of linear programming and three multi-criteria approaches (AHP, TOPSIS and ELECTRE III). New parameters like availability of sources, fuels' price volatility, besides traditional factors are considered in different scenarios. Results show with environmental preferences, renewable sources and micro-CHP are good alternatives for conventional systems.
OPTIMIZATION OF AEOLIAN ENERGY CONVERSION OPTIMISATION DE LA CONVERSION DE L’ENERGIE EOLIENNE
Directory of Open Access Journals (Sweden)
Y. Soufi
2015-08-01
Full Text Available The use of renewable energy increases, because people are increasingly concerned with environmental issues. Among renewable, wind power is now widely used. Their study showed that a value of wind speed, there is a maximum mechanical power supplied by the turbine. So, power is supplied are particularly changes with maximum speed.However, the objective of this paper is to present an algorithm for optimal conversion of wind energy based on a criterion optimization that must maintain specific speed of the turbine at optimum speed which corresponds to the maximum power provided by the steady wind turbine. To this end, the object is to preserve the position of any static operating point on the characteristic of optimal.To validate the model and algorithm for optimal conversion of wind energy, a series of numerical simulations carried out using the software MatLab Simulink will be presented is discussed.
Optimization of use of waste in the future energy system
International Nuclear Information System (INIS)
Muenster, Marie; Meibom, Peter
2011-01-01
Alternative uses of waste for energy production become increasingly interesting when considered from two perspectives, that of waste management and the energy system perspective. This paper presents the results of an enquiry into the use of waste in a future energy system. The analysis was performed using the energy system analysis model, Balmorel. The study is focused on Germany and the Nordic countries and demonstrates the optimization of both investments and production within the energy systems. The results present cost optimization excluding taxation concerning the use of waste for energy production in Denmark in a 2025 scenario with 48% renewable energy. Investments in a range of waste conversion technologies are facilitated, including waste incineration, co-combustion with coal, anaerobic digestion, and gasification. The most economically feasible solutions are found to be incineration of mixed waste, anaerobic digestion of organic waste, and gasification of part of the potential RDF (refuse derived fuel) for CHP (combined heat and power) production, while the remaining part is co-combusted with coal. Co-combustion mainly takes place in new coal-fired power plants, allowing investments to increase in comparison with a situation where only investments in waste incineration are allowed. -- Highlights: → The analysis is based on hourly chronological time steps, thereby taking dynamic properties of the energy system into account. → The system analyzed includes both the heat and the electricity market, which is important when analyzing e.g. CHP technologies. → The surrounding countries, which form part of the same electricity market, are included in the analysis. → New innovative Waste-to-Energy production plants have been modeled to allow for a more efficient and flexible use of waste. → The analysis includes economical optimization of operation and of investments in production and transmission of both electricity and heat.
UES: an optimization software package for power and energy
International Nuclear Information System (INIS)
Vohryzek, J.; Havlena, V.; Findejs, J.; Jech, J.
2004-01-01
Unified Energy Solutions components are designed to meet specific requirements of the electric utilities, industrial power units, and district heating (combined heat and power) plants. The optimization objective is to operate the plant with maximum process efficiency and operational profit under the constraints imposed by technology and environmental impacts. Software applications for advanced control real-time optimization may provide a low-cost, high return alternative to expensive boiler retrofits for improving operational profit as well as reducing emissions. Unified Energy Solutions (UES) software package is a portfolio of advanced control and optimization components running on top of the standard process regulatory and control system. The objective of the UES is to operate the plant with maximum achievable profit (maximum efficiency) under the constraints imposed by technology (life-time consumption, asset health) and environmental impacts (CO and NO x emissions). Fast responsiveness to varying economic conditions and integration of real-time optimization and operator decision support (off-line) features are critical for operation in real-time economy. Optimization Features are targeted to combustion process, heat and power load allocation to parallel resources, electric power delivery and ancillary services. Optimization Criteria include increased boiler thermal efficiency, maintaining emission limits, economic load allocation of the heat and generation sources. State-of-the-art advanced control algorithms use model based predictive control principles and provide superior response in transient states. Individual software modules support open control platforms and communication protocols. UES can be implemented on a wide range of distributed control systems. Typical achievable benefits include heat and power production costs savings, increased effective boiler operation range, optimized flue gas emissions, optimized production capacity utilization, optimized
The optimal time path of clean energy R&D policy when patents have finite lifetime
Gerlagh, R.; Kverndokk, S.; Rosendahl, K.E.
We study the optimal time path for clean energy innovation policy. In a model with emission reduction through clean energy deployment, and with R&D increasing the overall productivity of clean energy, we describe optimal R&D policies jointly with emission pricing policies. We find that while
MODELLING, SIMULATING AND OPTIMIZING BOILERS
DEFF Research Database (Denmark)
Sørensen, Kim; Condra, Thomas Joseph; Houbak, Niels
2004-01-01
In the present work a framework for optimizing the design of boilers for dynamic operation has been developed. A cost function to be minimized during the optimization has been formulated and for the present design variables related to the Boiler Volume and the Boiler load Gradient (i.e. ring rate...... on the boiler) have been dened. Furthermore a number of constraints related to: minimum and maximum boiler load gradient, minimum boiler size, Shrinking and Swelling and Steam Space Load have been dened. For dening the constraints related to the required boiler volume a dynamic model for simulating the boiler...... performance has been developed. Outputs from the simulations are shrinking and swelling of water level in the drum during for example a start-up of the boiler, these gures combined with the requirements with respect to allowable water level uctuations in the drum denes the requirements with respect to drum...
A dynamic optimization on economic energy efficiency in development: A numerical case of China
International Nuclear Information System (INIS)
Wang, Dong
2014-01-01
This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved. - Highlights: • A new definition on economic energy efficiency is proposed mathematically. • A dynamic optimization modelling links economic energy efficiency with other macroeconomic variables in long run. • Economic energy efficiency is determined by capital stock level and energy consumption. • Energy saving is a key solution for improving economic energy efficiency
Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Yuan Zou
2013-01-01
Full Text Available A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.
Optimizing Existing Multistory Building Designs towards Net-Zero Energy
Directory of Open Access Journals (Sweden)
Mohammad Y. AbuGrain
2017-03-01
Full Text Available Recent global developments in awareness and concerns about environmental problems have led to reconsidering built environment approaches and construction techniques. One of the alternatives is the principle of low/zero-energy buildings. This study investigates the potentials of energy savings in an existing multi-story building in the Mediterranean region in order to achieve net-zero energy as a solution to increasing fossil fuel prices. The Colored building at the Faculty of Architecture, Eastern Mediterranean University, Cyprus was chosen as a target of this study to be investigated and analyzed in order to know how energy efficiency strategies could be applied to the building to reduce annual energy consumption. Since this research objective is to develop a strategy to achieve net-zero energy in existing buildings, case study and problem solving methodologies were applied in this research in order to evaluate the building design in a qualitative manner through observations, in addition to a quantitative method through an energy modeling simulation to achieve desirable results which address the problems. After optimizing the building energy performance, an alternative energy simulation was made of the building in order to make an energy comparison analysis, which leads to reliable conclusions. These methodologies and the strategies used in this research can be applied to similar buildings in order to achieve net-zero energy goals.
Optimal design of compressed air energy storage systems
Energy Technology Data Exchange (ETDEWEB)
Ahrens, F. W.; Sharma, A.; Ragsdell, K. M.
1979-01-01
Compressed air energy storage (CAES) power systems are currently being considered by various electric utilities for load-leveling applications. Models of CAES systems which employ natural underground aquifer formations, and present an optimal design methodology which demonstrates their economic viability are developed. This approach is based upon a decomposition of the CAES plant and utility grid system into three partially-decoupled subsystems. Numerical results are given for a plant employing the Media, Illinois Galesville aquifer formation.
Optimized Free Energies from Bidirectional Single-Molecule Force Spectroscopy
Minh, David D. L.; Adib, Artur B.
2008-05-01
An optimized method for estimating path-ensemble averages using data from processes driven in opposite directions is presented. Based on this estimator, bidirectional expressions for reconstructing free energies and potentials of mean force from single-molecule force spectroscopy—valid for biasing potentials of arbitrary stiffness—are developed. Numerical simulations on a model potential indicate that these methods perform better than unidirectional strategies.
MODELLING, SIMULATING AND OPTIMIZING BOILERS
DEFF Research Database (Denmark)
Sørensen, K.; Condra, T.; Houbak, Niels
2003-01-01
, and the total stress level (i.e. stresses introduced due to internal pressure plus stresses introduced due to temperature gradients) must always be kept below the allowable stress level. In this way, the increased water-/steam space that should allow for better dynamic performance, in the end causes limited...... freedom with respect to dynamic operation of the plant. By means of an objective function including as well the price of the plant as a quantification of the value of dynamic operation of the plant an optimization is carried out. The dynamic model of the boiler plant is applied to define parts...
Energy group structure determination using particle swarm optimization
International Nuclear Information System (INIS)
Yi, Ce; Sjoden, Glenn
2013-01-01
Highlights: ► Particle swarm optimization is applied to determine broad group structure. ► A graph representation of the broad group structure problem is introduced. ► The approach is tested on a fuel-pin model. - Abstract: Multi-group theory is widely applied for the energy domain discretization when solving the Linear Boltzmann Equation. To reduce the computational cost, fine group cross libraries are often down-sampled into broad group cross section libraries. Cross section data collapsing generally involves two steps: Firstly, the broad group structure has to be determined; secondly, a weighting scheme is used to evaluate the broad cross section library based on the fine group cross section data and the broad group structure. A common scheme is to average the fine group cross section weighted by the fine group flux. Cross section collapsing techniques have been intensively researched. However, most studies use a pre-determined group structure, open based on experience, to divide the neutron energy spectrum into thermal, epi-thermal, fast, etc. energy range. In this paper, a swarm intelligence algorithm, particle swarm optimization (PSO), is applied to optimize the broad group structure. A graph representation of the broad group structure determination problem is introduced. And the swarm intelligence algorithm is used to solve the graph model. The effectiveness of the approach is demonstrated using a fuel-pin model
Optimal transportation networks models and theory
Bernot, Marc; Morel, Jean-Michel
2009-01-01
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
Aerodynamic modelling and optimization of axial fans
Energy Technology Data Exchange (ETDEWEB)
Noertoft Soerensen, Dan
1998-01-01
A numerically efficient mathematical model for the aerodynamics of low speed axial fans of the arbitrary vortex flow type has been developed. The model is based on a blade-element principle, whereby the rotor is divided into a number of annular stream tubes. For each of these stream tubes relations for velocity, pressure and radial position are derived from the conservation laws for mass, tangential momentum and energy. The equations are solved using the Newton-Raphson methods, and solutions converged to machine accuracy are found at small computing costs. The model has been validated against published measurements on various fan configurations, comprising two rotor-only fan stages, a counter-rotating fan unit and a stator-rotor stator stage. Comparisons of local and integrated properties show that the computed results agree well with the measurements. Optimizations have been performed to maximize the mean value of fan efficiency in a design interval of flow rates, thus designing a fan which operates well over a range of different flow conditions. The optimization scheme was used to investigate the dependence of maximum efficiency on 1: the number of blades, 2: the width of the design interval and 3: the hub radius. The degree of freedom in the choice of design variable and constraints, combined with the design interval concept, provides a valuable design-tool for axial fans. To further investigate the use of design optimization, a model for the vortex shedding noise from the trailing edge of the blades has been incorporated into the optimization scheme. The noise emission from the blades was minimized in a flow rate design point. Optimizations were performed to investigate the dependence of the noise on 1: the number of blades, 2: a constraint imposed on efficiency and 3: the hub radius. The investigations showed, that a significant reduction of noise could be achieved, at the expense of a small reduction in fan efficiency. (EG) 66 refs.
Modelling smart energy systems in tropical regions
DEFF Research Database (Denmark)
Dominkovic, D. F.; Dobravec, V.; Jiang, Y.
2018-01-01
and water desalination sectors. Five different large scale storages were modelled, too. The developed linear optimization model further included endogenous decisions about the share of district versus individual cooling, implementation of energy efficiency solutions and implementation of demand response...... emissions, 15% higher particulate matter emissions and 2% larger primary energy consumption compared to a business-as-usual case....
Optimization design of energy deposition on single expansion ramp nozzle
Ju, Shengjun; Yan, Chao; Wang, Xiaoyong; Qin, Yupei; Ye, Zhifei
2017-11-01
Optimization design has been widely used in the aerodynamic design process of scramjets. The single expansion ramp nozzle is an important component for scramjets to produces most of thrust force. A new concept of increasing the aerodynamics of the scramjet nozzle with energy deposition is presented. The essence of the method is to create a heated region in the inner flow field of the scramjet nozzle. In the current study, the two-dimensional coupled implicit compressible Reynolds Averaged Navier-Stokes and Menter's shear stress transport turbulence model have been applied to numerically simulate the flow fields of the single expansion ramp nozzle with and without energy deposition. The numerical results show that the proposal of energy deposition can be an effective method to increase force characteristics of the scramjet nozzle, the thrust coefficient CT increase by 6.94% and lift coefficient CN decrease by 26.89%. Further, the non-dominated sorting genetic algorithm coupled with the Radial Basis Function neural network surrogate model has been employed to determine optimum location and density of the energy deposition. The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method. The optimized thrust coefficient CT further increase by 1.94%, meanwhile, the optimized lift coefficient CN further decrease by 15.02% respectively. At the same time, the optimized performances are in good and reasonable agreement with the numerical predictions. The findings suggest that scramjet nozzle design and performance can benefit from the application of energy deposition.
A Method for Determining Optimal Residential Energy Efficiency Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gestwick, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bianchi, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Horowitz, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Christensen, C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Judkoff, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2011-04-01
This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location.
International Nuclear Information System (INIS)
Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.
2016-01-01
This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.
Optimal energy management strategy for self-reconfigurable batteries
International Nuclear Information System (INIS)
Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter
2017-01-01
This paper proposes a novel energy management strategy for multi-cell high voltage batteries where the current through each cell can be controlled, called self-reconfigurable batteries. An optimized control strategy further enhances the energy efficiency gained by the hardware architecture of those batteries. Currently, achieving cell equalization by using the active balancing circuits is considered as the best way to optimize the energy efficiency of the battery pack. This study demonstrates that optimizing the energy efficiency of self-reconfigurable batteries is no more strongly correlated to the cell balancing. According to the features of this novel battery architecture, the energy management strategy is formulated as nonlinear dynamic optimization problem. To solve this optimal control, an optimization algorithm that generates the optimal discharge policy for a given driving cycle is developed based on dynamic programming and code vectorization. The simulation results show that the designed energy management strategy maximizes the system efficiency across the battery lifetime over conventional approaches. Furthermore, the present energy management strategy can be implemented online due to the reduced complexity of the optimization algorithm. - Highlights: • The energy efficiency of self-reconfigurable batteries is maximized. • The energy management strategy for the battery is formulated as optimal control problem. • Developing an optimization algorithm using dynamic programming techniques and code vectorization. • Simulation studies are conducted to validate the proposed optimal strategy.
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.
Leila Torkaman; Nasser Ghassembaglou
2015-01-01
Significant quota of Municipal Electrical Energy consumption is related to Decentralized Air Conditioning which is mostly provided by evaporative coolers. So the aim is to optimize design of air conditioners to increase their efficiencies. To achieve this goal, results of practical standardized tests for 40 evaporative coolers in different types collected and simultaneously results for same coolers based on one of EER (Energy Efficiency Ratio) modeling styles are figured ...
Multiobjective Optimization Model for Wind Power Allocation
Directory of Open Access Journals (Sweden)
Juan Alemany
2017-01-01
Full Text Available There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solutions for the location of new wind power resources. It is based on the augmented ε-constrained methodology. Two competitive objectives are considered: maximization of preexisting energy injection and maximization of new wind energy injection, both embedded, in the maximization of load supply. The results show that the location of new renewable generation units affects considerably the transmission network flows, the load supply, and the preexisting energy injection. Moreover, there are diverse opportunities to benefit the preexisting generation, contrarily to the expected effect where renewable generation displaces conventional power. The proposed methodology produces a diverse range of equivalent solutions, expanding and enriching the horizon of options and giving flexibility to the decision-making process.
Optimal Time to Invest Energy Storage System under Uncertainty Conditions
Directory of Open Access Journals (Sweden)
Yongma Moon
2014-04-01
Full Text Available This paper proposes a model to determine the optimal investment time for energy storage systems (ESSs in a price arbitrage trade application under conditions of uncertainty over future profits. The adoption of ESSs can generate profits from price arbitrage trade, which are uncertain because the future marginal prices of electricity will change depending on supply and demand. In addition, since the investment is optional, an investor can delay adopting an ESS until it becomes profitable, and can decide the optimal time. Thus, when we evaluate this investment, we need to incorporate the investor’s option which is not captured by traditional evaluation methods. In order to incorporate these aspects, we applied real option theory to our proposed model, which provides an optimal investment threshold. Our results concerning the optimal time to invest show that if future profits that are expected to be obtained from arbitrage trade become more uncertain, an investor needs to wait longer to invest. Also, improvement in efficiency of ESSs can reduce the uncertainty of arbitrage profit and, consequently, the reduced uncertainty enables earlier ESS investment, even for the same power capacity. Besides, when a higher rate of profits is expected and ESS costs are higher, an investor needs to wait longer. Also, by comparing a widely used net present value model to our real option model, we show that the net present value method underestimates the value for ESS investment and misleads the investor to make an investment earlier.
Development of optimized segmentation map in dual energy computed tomography
Yamakawa, Keisuke; Ueki, Hironori
2012-03-01
Dual energy computed tomography (DECT) has been widely used in clinical practice and has been particularly effective for tissue diagnosis. In DECT the difference of two attenuation coefficients acquired by two kinds of X-ray energy enables tissue segmentation. One problem in conventional DECT is that the segmentation deteriorates in some cases, such as bone removal. This is due to two reasons. Firstly, the segmentation map is optimized without considering the Xray condition (tube voltage and current). If we consider the tube voltage, it is possible to create an optimized map, but unfortunately we cannot consider the tube current. Secondly, the X-ray condition is not optimized. The condition can be set empirically, but this means that the optimized condition is not used correctly. To solve these problems, we have developed methods for optimizing the map (Method-1) and the condition (Method-2). In Method-1, the map is optimized to minimize segmentation errors. The distribution of the attenuation coefficient is modeled by considering the tube current. In Method-2, the optimized condition is decided to minimize segmentation errors depending on tube voltagecurrent combinations while keeping the total exposure constant. We evaluated the effectiveness of Method-1 by performing a phantom experiment under the fixed condition and of Method-2 by performing a phantom experiment under different combinations calculated from the total exposure constant. When Method-1 was followed with Method-2, the segmentation error was reduced from 37.8 to 13.5 %. These results demonstrate that our developed methods can achieve highly accurate segmentation while keeping the total exposure constant.
Linear energy transfer incorporated intensity modulated proton therapy optimization
Cao, Wenhua; Khabazian, Azin; Yepes, Pablo P.; Lim, Gino; Poenisch, Falk; Grosshans, David R.; Mohan, Radhe
2018-01-01
The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the
Energy Resource Planning. Optimal utilization of energy resources
International Nuclear Information System (INIS)
Miclescu, T.; Domschke, W.; Bazacliu, G.; Dumbrava, V.
1996-01-01
For a thermal power plants system, the primary energy resources cost constitutes a significant percentage of the total system operational cost. Therefore a small percentage saving in primary energy resource allocation cost for a long term, often turns out to be a significant monetary value. In recent years, with a rapidly changing fuel supply situation, including the impact of energy policies changing, this area has become extremely sensitive. Natural gas availability has been restricted in many areas, coal production and transportation cost have risen while productivity has decreased, oil imports have increased and refinery capacity failed to meet demand. The paper presents a mathematical model and a practical procedure to solve the primary energy resource allocation. The objectives is to minimise the total energy cost over the planning period subject to constraints with regards to primary energy resource, transportation and energy consumption. Various aspects of the proposed approach are discussed, and its application to a power system is illustrated.(author) 2 figs., 1 tab., 3 refs
Directory of Open Access Journals (Sweden)
Sama Amid
2016-06-01
Full Text Available A literature review shows that energy consumption in agricultural production in Iran is not efficient and a high degree of inefficiency in broiler production exists in Iran. Energy consumption of broiler production in Ardabil province of Iran was studied and the non-parametric method of data envelopment analysis (DEA was used to analyze energy efficiency, separate efficient from inefficient broiler producers, and calculate wasteful use of energy to optimize energy. Data was collected using face-to-face questionnaires from 70 broiler farmers in the study area. Constant returns to scale (CCR and variable returns to scale (BCC models of DEA were applied to assess the technical efficiency of broiler production. The results indicated that total energy use was 154,283 MJ (1000 bird−1 and the share of fuel at 61.4% was the highest of all inputs. The indices of energy efficiency, energy productivity, specific energy, and net energy were found to be 0.18, 0.02 kg MJ−1, 59.56 MJ kg−1, and −126,836 MJ (1000 bird−1, respectively. The DEA results revealed that 40% and 22.86% of total units were efficient based on the CCR and BCC models, respectively. The average technical, pure technical, and scale efficiency of broiler farmers was 0.88, 0.93, and 0.95, respectively. The results showed that 14.53% of total energy use could be saved by converting the present units to optimal conditions. The contribution of fuel input to total energy savings was 72% and was the largest share, followed by feed and electricity energy inputs. The results of this study indicate that there is good potential for increasing energy efficiency of broiler production in Iran by following the recommendations for efficient energy use.
Environmental Multiobjective Optimization of the Use of Biomass Resources for Energy
DEFF Research Database (Denmark)
Vadenbo, Carl; Tonini, Davide; Astrup, Thomas Fruergaard
2017-01-01
of the optimization model is exemplified by a case aimed at determining the environmentally optimal use of biomass in the Danish energy system in 2025. A multiobjective formulation based on fuzzy intervals for six environmental impact categories resulted in impact reductions of 13-43% compared to the baseline...... environmental consequences. To circumvent the limitations of scenario-based life cycle assessment (LCA), we develop a multiobjective optimization model to systematically identify the environmentally optimal use of biomass for energy under given system constraints. Besides satisfying annual final energy demand...
Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics
Energy Technology Data Exchange (ETDEWEB)
Liu, Guodong [ORNL; Li, Zhi [ORNL; Starke, Michael R. [ORNL; Ollis, Ben [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)
2017-07-01
This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.
Optimal power flow management for distributed energy resources with batteries
International Nuclear Information System (INIS)
Tazvinga, Henerica; Zhu, Bing; Xia, Xiaohua
2015-01-01
Highlights: • A PV-diesel-battery hybrid system is proposed. • Model minimizes fuel and battery wear costs. • Power flows are analysed in a 24-h period. • Results provide a practical platform for decision making. - Abstract: This paper presents an optimal energy management model of a solar photovoltaic-diesel-battery hybrid power supply system for off-grid applications. The aim is to meet the load demand completely while satisfying the system constraints. The proposed model minimizes fuel and battery wear costs and finds the optimal power flow, taking into account photovoltaic power availability, battery bank state of charge and load power demand. The optimal solutions are compared for cases when the objectives are weighted equally and when a larger weight is assigned to battery wear. A considerable increase in system operational cost is observed in the latter case owing to the increased usage of the diesel generator. The results are important for decision makers, as they depict the optimal decisions considered in the presence of trade-offs between conflicting objectives
Clean coal technology optimization model
International Nuclear Information System (INIS)
Laseke, B.A.; Hance, S.B.
1992-01-01
Title IV of the Clean Air Act Amendments (CAAA) of 1990 contains provisions for the mitigation of acid rain precipitation through reductions in the annual emission of the acid rain precursors of sulfur dioxide (SO 2 ) and nitrogen oxide (NO x ). These provisions will affect primarily existing coal-fired power-generating plants by requiring nominal reductions of 5 millon and 10 million tons of SO 2 by the years 1995 and 2000, respectively, and 2 million tons of NO x by the year 2000 relative to the 1980 and 1985-87 reference period. The 1990 CAAA Title IV provisions are extremely complex in that they establish phased regulatory milestones, unit-level emission allowances and caps, a mechanism for inter-utility trading of emission allowances, and a system of emission allowance credits based on selection of control option and timing of its implementation. The net result of Title IV of the 1990 CAAA is that approximately 147 gigawatts (GW) of generating capacity is eligible to retrofit SO 2 controls by the year 2000. A number of options are available to bring affected boilers into compliance with Title IV. Market sharewill be influenced by technology performance and costs. These characteristics can be modeled through a bottom-up technology cost and performance optimization exercise to show their impact on the technology's potential market share. Such a model exists in the form of an integrated data base-model software system. This microcomputer (PC)-based software system consists of a unit (boiler)-level data base (ACIDBASE), a cost and performance engineering model (IAPCS), and a market forecast model (ICEMAN)
Model for optimum design of standalone hybrid renewable energy ...
African Journals Online (AJOL)
An optimization model for the design of a hybrid renewable energy microgrid ... and increasing the rated power of the wind energy conversion system (WECS) or solar ... a 70% reduction in gas emissions and an 80% reduction in energy costs.
Energy Cost Optimization in a Water Supply System Case Study
Directory of Open Access Journals (Sweden)
Daniel F. Moreira
2013-01-01
Full Text Available The majority of the life cycle costs (LCC of a pump are related to the energy spent in pumping, with the rest being related to the purchase and maintenance of the equipment. Any optimizations in the energy efficiency of the pumps result in a considerable reduction of the total operational cost. The Fátima water supply system in Portugal was analyzed in order to minimize its operational energy costs. Different pump characteristic curves were analyzed and modeled in order to achieve the most efficient operation point. To determine the best daily pumping operational scheduling pattern, genetic algorithm (GA optimization embedded in the modeling software was considered in contrast with a manual override (MO approach. The main goal was to determine which pumps and what daily scheduling allowed the best economical solution. At the end of the analysis it was possible to reduce the original daily energy costs by 43.7%. This was achieved by introducing more appropriate pumps and by intelligent programming of their operation. Given the heuristic nature of GAs, different approaches were employed and the most common errors were pinpointed, whereby this investigation can be used as a reference for similar future developments.
Novel optimization technique of isolated microgrid with hydrogen energy storage.
Beshr, Eman Hassan; Abdelghany, Hazem; Eteiba, Mahmoud
2018-01-01
This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.
Novel optimization technique of isolated microgrid with hydrogen energy storage.
Directory of Open Access Journals (Sweden)
Eman Hassan Beshr
Full Text Available This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs, Diesel Generator (DG, a Wind Turbine Generator (WTG, Photovoltaic (PV arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.
Directory of Open Access Journals (Sweden)
Yongli Wang
2018-06-01
Full Text Available Integrated energy systems (IESs are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA. The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data.
Optimization of Renewable Energy Hybrid System for Grid Connected Application
Directory of Open Access Journals (Sweden)
Mustaqimah Mustaqimah
2012-10-01
Full Text Available ABSTRACT. Hybrid energy systems are pollution free, takes low cost and less gestation period, user and social friendly. Such systems are important sources of energy for shops, schools, and clinics in village communities especially in remote areas. Hybrid systems can provide electricity at a comparatively economic price in many remote areas. This paper presents a method to jointly determine the sizing and operation control of hybrid energy systems. The model, PV wind hydro and biomass hybrid system connects to grid. The system configuration of the hybrid is derived based on a theoretical domestic load at a typical location and local solar radiation, wind and water flow rate data and biomass availability. The hybrid energy system is proposed for 10 of teacher’s houses of Industrial Training Institute, Mersing. It is predicted 10 kW load consumption per house. The hybrid energy system consists of wind, solar, biomass, hydro, and grid power. Approximately energy consumption is 860 kWh/day with a 105 kW peak demand load. The proposed hybrid renewable consists of solar photovoltaic (PV panels, wind turbine, hydro turbine and biomass. Battery and inverter are included as part of back-up and storage system. It provides the economic sensitivity of hybridization and the economic and environmental benefits of using a blend of technologies. It also presents the trade off that is involved in optimizing a hybrid energy system to harness and utilize the available renewable energy resources efficiently.
Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.
Sohn, Insoo; Liu, Huaping; Ansari, Nirwan
2015-01-01
An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.
Directory of Open Access Journals (Sweden)
E. C. Chukwuma
2015-08-01
Full Text Available Poor waste management strategy in abattoir in the the study area has needs a major attention considering it negative impacts on man land and water. Sitting of centralized biogas plant in a strategic location in the state would be the major means of combating the environmental challenges of increase in abattoir waste generation as result of population explosion in the state. This study investigates optimal location for sitting central abattoir waste treatment facility in Anambra State of Nigeria using facility location models with hotspot analysis in GIS environment. The result of the study shows that Using centre of gravity model the central location was estimated to be at Xc Yc 6.900953016 6.110157865. Based on inadequacy of the model hotspot analysis operation was done the hotspot analysis delineated clusters of abattoirs significantly higher in bio-wastes production than the overall study area. The hotspot analysis shows that the West regions of the study area has many abattoir that is classified as hotspot abattoirs. Using the hotspot abattoirs as proposed sites for load-distance model three abattoirs were identified as proposed sites- Obosi slaugher house Nkpor Private slaughter house and Oye-olise Ogbunike slaugher house. Their load distance values are 17250.40058 16299.24005 and 18210.14631 respectively. The optimal location for construction of central abattoir bio-waste treatment facility based on the application of these location facility models and hotspot analysis is Nkpor private slaughter house or its environs.
Energy Technology Data Exchange (ETDEWEB)
Pasonen, R.
2011-09-15
A simulation model of Energy centre microgrid made with PSCAD simulation software version 4.2.1 has been built in SGEM Smart Grids and Energy Markets (SGEM) work package 6.6. Microgrid is an autonomous electric power system which can operate separate from common distribution system. The idea of energy centre microgrid concept was considered in Master of Science thesis 'Community Microgrid - A Building block of Finnish Smart Grid'. The name of energy centre microgrid comes from a fact that production and storage units are concentrated into a single location, an energy centre. This centre feeds the loads which can be households or industrial loads. Power direction flow on the demand side remains same compared to the current distribution system and allows to the use of standard fuse protection in the system. The model consists of photovoltaic solar array, battery unit, variable frequency boost converter, inverter, isolation transformer and demand side (load) model. The model is capable to automatically switch to islanded mode when there is a fault in outside grid and back to parallel operation mode when fault is removed. The modelled system responses well to load changes and total harmonic distortion related to 50Hz base frequency is kept under 1.5% while operating and feeding passive load. (orig.)
Micro thermal energy harvester design optimization
International Nuclear Information System (INIS)
Trioux, E; Basrour, S; Monfray, S
2017-01-01
This paper reports the recent progress of a new technology to scavenge thermal energy, implying a double-step transduction through the thermal buckling of a bilayer aluminum nitride/aluminum bridge and piezoelectric transduction. A completely new scavenger design is presented, with improved performance. The butterfly shape reduces the overall device mechanical rigidity, which leads to a decrease in buckling temperatures compared to previously studied rectangular plates. Firstly, an analytical model exposes the basic principle of the presented device. Then a numerical model completes the explanations by introducing a butterfly shaped structure. Finally the fabrication process is briefly described and both the rectangular and butterfly harvesters are characterized. We compare their performances with an equal thickness of Al and AlN. Secondly, with a thicker Al layer than AlN layer, we will characterize only the butterfly structure in terms of output power and buckling temperatures, and compare it to the previous stack. (paper)
International Nuclear Information System (INIS)
Ohkubo, Hiroo; Suzuki, Atsuyuki; Kiyose, Ryohei
1983-01-01
This is an extension of the Suzuki model (base model) on optimal transition from resource-limited energy (oil) to advanced energy with virtually unlimited resource. The finite length of plant life, fuel cost, technological progress factor of advanced energy and the upper limit upon annual consumption rate of oil are taken into account for such an extension. The difference in optimal solutions obtained from extended and base models is shown by an application of the maximum principle. The implication of advanced energy R and D andenergy conservation effort is also discussed. (author)
Optimal Scheduling of Residential Microgrids Considering Virtual Energy Storage System
Directory of Open Access Journals (Sweden)
Weiliang Liu
2018-04-01
Full Text Available The increasingly complex residential microgrids (r-microgrid consisting of renewable generation, energy storage systems, and residential buildings require a more intelligent scheduling method. Firstly, aiming at the radiant floor heating/cooling system widely utilized in residential buildings, the mathematical relationship between the operative temperature and heating/cooling demand is established based on the equivalent thermodynamic parameters (ETP model, by which the thermal storage capacity is analyzed. Secondly, the radiant floor heating/cooling system is treated as virtual energy storage system (VESS, and an optimization model based on mixed-integer nonlinear programming (MINLP for r-microgrid scheduling is established which takes thermal comfort level and economy as the optimization objectives. Finally, the optimal scheduling results of two typical r-microgrids are analyzed. Case studies demonstrate that the proposed scheduling method can effectively employ the thermal storage capacity of radiant floor heating/cooling system, thus lowering the operating cost of the r-microgrid effectively while ensuring the thermal comfort level of users.
A model for optimization of process integration investments under uncertainty
International Nuclear Information System (INIS)
Svensson, Elin; Stroemberg, Ann-Brith; Patriksson, Michael
2011-01-01
The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency. -- Highlights: → Stochastic programming approach to long-term planning of process integration investments. → Extensive mathematical model formulation. → Multi-stage investment decisions and scenario-based modelling of uncertain energy prices. → Results illustrate how investments made now affect later investment and operation opportunities. → Approach for evaluation of robustness with respect to variations in probability distribution.
Economical optimization of building elements for use in design of nearly zero energy buildings
DEFF Research Database (Denmark)
Hansen, Sanne
2012-01-01
Nearly zero energy buildings are to become a requirement as part of the European energy policy. There are many ways of designing nearly zero energy buildings, but there is a lack of knowledge on how to end up with the most economical optimal solution. Therefore this paper present a method...... for finding the economical optimal solutions based on the use of the cost of conserved energy for each main building envelope part and building service system and cost of produced energy for each energy producing system. By use of information on construction cost and developed models of the yearly energy use...
Energy optimization methodology of multi-chiller plant in commercial buildings
International Nuclear Information System (INIS)
Thangavelu, Sundar Raj; Myat, Aung; Khambadkone, Ashwin
2017-01-01
This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions. - Highlights: • Energy optimization methodology improves the performance of multi-chiller plant. • Overall energy model of chiller plant accounts all equipment and the interactions. • Operation decisions are derived at regular interval based on time-varying factors. • Three case studies confirmed 20 to 40% of energy savings than conventional method.
Cowell, Martin Andrew
The world already hosts more internet connected devices than people, and that ratio is only increasing. These devices seamlessly integrate with peoples lives to collect rich data and give immediate feedback about complex systems from business, health care, transportation, and security. As every aspect of global economies integrate distributed computing into their industrial systems and these systems benefit from rich datasets. Managing the power demands of these distributed computers will be paramount to ensure the continued operation of these networks, and is elegantly addressed by including local energy harvesting and storage on a per-node basis. By replacing non-rechargeable batteries with energy harvesting, wireless sensor nodes will increase their lifetimes by an order of magnitude. This work investigates the coupling of high power energy storage with energy harvesting technologies to power wireless sensor nodes; with sections covering device manufacturing, system integration, and mathematical modeling. First we consider the energy storage mechanism of supercapacitors and batteries, and identify favorable characteristics in both reservoir types. We then discuss experimental methods used to manufacture high power supercapacitors in our labs. We go on to detail the integration of our fabricated devices with collaborating labs to create functional sensor node demonstrations. With the practical knowledge gained through in-lab manufacturing and system integration, we build mathematical models to aid in device and system design. First, we model the mechanism of energy storage in porous graphene supercapacitors to aid in component architecture optimization. We then model the operation of entire sensor nodes for the purpose of optimally sizing the energy harvesting and energy reservoir components. In consideration of deploying these sensor nodes in real-world environments, we model the operation of our energy harvesting and power management systems subject to
Energy optimization for a wind DFIG with flywheel energy storage
Energy Technology Data Exchange (ETDEWEB)
Hamzaoui, Ihssen, E-mail: hamzaoui-ihssen2000@yahoo.fr [Laboratory of Instrumentation, Faculty of Electronics and Computer, University of Sciences and Technology Houari Boumediene, BP 32 El-Alia 16111 Bab-Ezzouar (Algeria); Laboratory of Instrumentation, Faculty of Electronics and Computer, University of Khemis Miliana, Ain Defla (Algeria); Bouchafaa, Farid, E-mail: fbouchafa@gmail.com [Laboratory of Instrumentation, Faculty of Electronics and Computer, University of Sciences and Technology Houari Boumediene, BP 32 El-Alia 16111 Bab-Ezzouar (Algeria)
2016-07-25
The type of distributed generation unit that is the subject of this paper relates to renewable energy sources, especially wind power. The wind generator used is based on a double fed induction Generator (DFIG). The stator of the DFIG is connected directly to the network and the rotor is connected to the network through the power converter with three levels. The objective of this work is to study the association a Flywheel Energy Storage System (FESS) in wind generator. This system is used to improve the quality of electricity provided by wind generator. It is composed of a flywheel; an induction machine (IM) and a power electronic converter. A maximum power tracking technique « Maximum Power Point Tracking » (MPPT) and a strategy for controlling the pitch angle is presented. The model of the complete system is developed in Matlab/Simulink environment / to analyze the results from simulation the integration of wind chain to networks.
Method for Determining Optimal Residential Energy Efficiency Retrofit Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B.; Gestwick, M.; Bianchi, M.; Anderson, R.; Horowitz, S.; Christensen, C.; Judkoff, R.
2011-04-01
Businesses, government agencies, consumers, policy makers, and utilities currently have limited access to occupant-, building-, and location-specific recommendations for optimal energy retrofit packages, as defined by estimated costs and energy savings. This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location. Energy savings and incremental costs are calculated relative to a minimum upgrade reference scenario, which accounts for efficiency upgrades that would occur in the absence of a retrofit because of equipment wear-out and replacement with current minimum standards.
Optimization of the Public Buildings Energy Supply
DEFF Research Database (Denmark)
Filipović, P.; Dominkovic, Dominik Franjo; Ćosić, B.
2016-01-01
There is a rising interest in the improvement of energy efficiency in public buildings nowadays atthe EU level. Increasing energy efficiency can lead to both better thermal comfort, as well as netsavings on energy bills. Furthermore, the right choice of energy source can lead to large savings inC...
Scheduling home-appliances to optimize energy consumption
DEFF Research Database (Denmark)
Rossello Busquet, Ana
In order to optimize the energy consumption, energy demand peaks should be avoided, and energy consumption should be smoothly distributed over time. This can be achieved by setting a maximum energy consumption per user’s household. In other words, the overall consumption of the user’s appliances...
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.
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...
Intelligent structural optimization: Concept, Model and Methods
International Nuclear Information System (INIS)
Lu, Dagang; Wang, Guangyuan; Peng, Zhang
2002-01-01
Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented
ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS
Directory of Open Access Journals (Sweden)
T. SHANKAR
2014-04-01
Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.
International Nuclear Information System (INIS)
Richardson, David B.; Harvey, L.D. Danny
2015-01-01
Electricity systems with high penetrations of renewable energy require a mix of resources to balance supply with demand, and to maintain safe levels of system reliability. A load balancing methodology is developed to determine the optimal lowest-cost mix of renewable energy resources, demand response, and energy storage to replace conventional fuels in the Province of Ontario, Canada. Three successive cumulative scenarios are considered: the displacement of fossil fuel generation, the planned retirement of an existing nuclear reactor, and the electrification of the passenger vehicle fleet. The results show that each of these scenarios is achievable with energy generation costs that are not out of line with current and projected electricity generation costs. These transitions, especially that which proposes the electrification of the vehicle fleet, require significant investment in new generation, with installed capacities much higher than that of the current system. Transitions to mainly renewable energy systems require changes in our conceptualization of, and approach to, energy system planning. - Highlights: • Model three scenarios to replace conventional fuels with renewables, storage and DR (demand response). • Determine optimal low-cost mix of resources for each scenario. • Scenarios require much higher installed capacities than current system. • Energy transitions require changes in approach to energy system planning.
Şoimoşan, Teodora M.; Danku, Gelu; Felseghi, Raluca A.
2017-12-01
Within the thermo-energy optimization process of an existing heating system, the increase of the system's energy efficiency and speeding-up the transition to green energy use are pursued. The concept of multi-energy district heating system, with high harnessing levels of the renewable energy sources (RES) in order to produce heat, is expected to be the key-element in the future urban energy infrastructure, due to the important role it can have in the strategies of optimizing and decarbonizing the existing district heating systems. The issues that arise are related to the efficient integration of different technologies of harnessing renewable energy sources in the energy mix and to the increase of the participation levels of RES, respectively. For the holistic modeling of the district heating system, the concept of the energy hub was used, where the synergy of different primary forms of entered energy provides the system a high degree energy security and flexibility in operation. The optimization of energy flows within the energy hub allows the optimization of the thermo-energy district system in order to approach the dual concept of smart city & smart energy.
Energy Optimized Envelope for Cold Climate Indoor Agricultural Growing Center
Directory of Open Access Journals (Sweden)
Caroline Hachem-Vermette
2017-07-01
Full Text Available This paper presents a study of the development of building envelope design for improved energy performance of a controlled indoor agricultural growing center in a cold climate zone (Canada, 54° N. A parametric study is applied to analyze the effects of envelope parameters on the building energy loads for heating, cooling and lighting, required for maintaining growing requirement as obtained in the literature. A base case building of rectangular layout, incorporating conventionally applied insulation and glazing components, is initially analyzed, employing the EnergyPlus simulation program. Insulation and glazing parameters are then modified to minimize energy loads under assumed minimal lighting requirement. This enhanced design forms a base case for analyzing effects of additional design parameters—solar radiation control, air infiltration rate, sky-lighting and the addition of phase change materials—to obtain an enhanced design that minimizes energy loads. A second stage of the investigation applies a high lighting level to the enhanced design and modifies the design parameters to improve performance. A final part of the study is an investigation of the mechanical systems and renewable energy generation. Through the enhancement of building envelope components and day-lighting design, combined heating and cooling load of the low level lighting configuration is reduced by 65% and lighting load by 10%, relative to the base case design. Employing building integrated PV (BIPV system, this optimized model can achieve energy positive status. Solid Oxide Fuel Cells (SOFC, are discussed, as potential means to offset increased energy consumption associated with the high-level lighting model.
Optimal Power Flow in Microgrids with Energy Storage
DEFF Research Database (Denmark)
Levron, Yoash; Guerrero, Josep M.; Beck, Yuval
2013-01-01
Energy storage may improve power management in microgrids that include renewable energy sources. The storage devices match energy generation to consumption, facilitating a smooth and robust energy balance within the microgrid. This paper addresses the optimal control of the microgrid’s energy...... storage devices. Stored energy is controlled to balance power generation of renewable sources to optimize overall power consumption at the microgrid point of common coupling. Recent works emphasize constraints imposed by the storage device itself, such as limited capacity and internal losses. However...
Investigations of a Cost-Optimal Zero Energy Balance
DEFF Research Database (Denmark)
Marszal, Anna Joanna; Nørgaard, Jesper; Heiselberg, Per
2012-01-01
The Net Zero Energy Building (Net ZEB) concept is worldwide recognised as a promising solution for decreasing buildings’ energy use. Nevertheless, a consistent definition of the Net ZEB concept is constantly under discussion. One of the points on the Net ZEB agenda is the zero energy balance...... and taken a view point of private building owner to investigate what types of energy uses should be included in the cost-optimal zero energy balance. The analysis is conducted for five renewable energy supply systems and five user profiles with a study case of a multi-storey residential Net ZEB. The results...... have indicated that with current energy prices and technology, a cost-optimal Net ZEB zero energy balance accounts for only the building related energy use. Moreover, with high user related energy use is even more in favour of excluding appliances from the zero energy balance....
Optimization in engineering models and algorithms
Sioshansi, Ramteen
2017-01-01
This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering ...
Directory of Open Access Journals (Sweden)
Zhihao Zhao
2016-08-01
Full Text Available In this paper, an optimization method is proposed for the energy link in a wireless power transfer grid, which is a regional smart microgrid comprised of distributed devices equipped with wireless power transfer technology in a certain area. The relevant optimization model of the energy link is established by considering the wireless power transfer characteristics and the grid characteristics brought in by the device repeaters. Then, a concentration adaptive genetic algorithm (CAGA is proposed to optimize the energy link. The algorithm avoided the unification trend by introducing the concentration mechanism and a new crossover method named forward order crossover, as well as the adaptive parameter mechanism, which are utilized together to keep the diversity of the optimization solution groups. The results show that CAGA is feasible and competitive for the energy link optimization in different situations. This proposed algorithm performs better than its counterparts in the global convergence ability and the algorithm robustness.
Directory of Open Access Journals (Sweden)
Hengrui Ma
2018-01-01
Full Text Available Ancillary services are critical to maintaining the safe and stable operation of power systems that contain a high penetration level of renewable energy resources. As a high-quality regulation resource, the regional integrated energy system (RIES with energy storage system (ESS can effectively adjust the non-negligible frequency offset caused by the renewable energy integration into the power system, and help solve the problem of power system frequency stability. In this paper, the optimization model aiming at regional integrated energy system as a participant in the regulation market based on pay-for-performance is established. Meanwhile YALMIP + CPLEX is used to simulate and analyze the total operating cost under different dispatch modes. This paper uses the actual operation model of the PJM regulation market to guide the optimal allocation of regulation resource in the regional integrated energy system, and provides a balance between the power trading revenue and regulation market revenue in order to achieve the maximum profit.
Energy Capture Optimization for an Adaptive Wave Energy Converter
Barradas Berglind, Jose de Jesus; Meijer, Harmen; van Rooij, Marijn; Clemente Pinol, Silvia; Galvan Garcia, Bruno; Prins, Wouter; Vakis, Antonis I.; Jayawardhana, Bayu
2016-01-01
Wave energy has great potential as a renewable energy source, and can therefore contribute significantly to the proportion of renewable energy in the global energy mix. This is especially important since energy mixes with high renewable penetration have become a worldwide priority. One solution to
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 Placement of Energy Storage and Wind Power under Uncertainty
Directory of Open Access Journals (Sweden)
Pilar Meneses de Quevedo
2016-07-01
Full Text Available Due to the rapid growth in the amount of wind energy connected to distribution grids, they are exposed to higher network constraints, which poses additional challenges to system operation. Based on regulation, the system operator has the right to curtail wind energy in order to avoid any violation of system constraints. Energy storage systems (ESS are considered to be a viable solution to solve this problem. The aim of this paper is to provide the best locations of both ESS and wind power by optimizing distribution system costs taking into account network constraints and the uncertainty associated to the nature of wind, load and price. To do that, we use a mixed integer linear programming (MILP approach consisting of loss reduction, voltage improvement and minimization of generation costs. An alternative current (AC linear optimal power flow (OPF, which employs binary variables to define the location of the generation, is implemented. The proposed stochastic MILP approach has been applied to the IEEE 69-bus distribution network and the results show the performance of the model under different values of installed capacities of ESS and wind power.
Optimal Hedging with the Vector Autoregressive Model
L. Gatarek (Lukasz); S.G. Johansen (Soren)
2014-01-01
markdownabstract__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be
Optimal energy control of a crushing process based on vertical shaft impactor
International Nuclear Information System (INIS)
Numbi, B.P.; Xia, X.
2016-01-01
Highlights: • Energy optimal control strategy of a VSI crushing process is modeled. • Potential of a daily energy cost saving of about 49.7% is shown. • Potential of a daily energy saving of about 15.3% is shown. • Most of energy cost saving is due to the optimal load shifting under time-of-use tariff. • Energy saving is due to the operation of the process at the boundary of the admissible region. - Abstract: This paper presents an optimal control model to improve the operation energy efficiency of a vertical shaft impact (VSI) crushing process. The optimal control model takes the energy cost as the performance index to be minimized by accounting for the time-of-use tariff and process constraints such as storage capacity of the VSI crusher hopper, capacity of the main storage system, flow rate limits, cascade ratio setting, production requirement and product quality requirement. The control variables in the developed model are the belt conveyor feed rate, the material feed rate into the VSI crusher rotor, the bi-flow or cascade feed rate and the rotor tip speed of the crusher. These four control variables are optimally coordinated in order to improve the operation energy efficiency of the VSI crushing process. Simulation results based on a crushing process in a coal-fired power plant demonstrate a potential of a daily energy cost saving of about 49.7% and energy saving of about 15.3% in a high-demand season weekday.
Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.
Cherchi, Carla; Badruzzaman, Mohammad; Gordon, Matthew; Bunn, Simon; Jacangelo, Joseph G
2015-11-17
Holistic management of water and energy resources through energy and water quality management systems (EWQMSs) have traditionally aimed at energy cost reduction with limited or no emphasis on energy efficiency or greenhouse gas minimization. This study expanded the existing EWQMS framework and determined the impact of different management strategies for energy cost and energy consumption (e.g., carbon footprint) reduction on system performance at two drinking water utilities in California (United States). The results showed that optimizing for cost led to cost reductions of 4% (Utility B, summer) to 48% (Utility A, winter). The energy optimization strategy was successfully able to find the lowest energy use operation and achieved energy usage reductions of 3% (Utility B, summer) to 10% (Utility A, winter). The findings of this study revealed that there may be a trade-off between cost optimization (dollars) and energy use (kilowatt-hours), particularly in the summer, when optimizing the system for the reduction of energy use to a minimum incurred cost increases of 64% and 184% compared with the cost optimization scenario. Water age simulations through hydraulic modeling did not reveal any adverse effects on the water quality in the distribution system or in tanks from pump schedule optimization targeting either cost or energy minimization.
Optimal dimensioning model of water distribution systems | Gomes ...
African Journals Online (AJOL)
This study is aimed at developing a pipe-sizing model for a water distribution system. The optimal solution minimises the system's total cost, which comprises the hydraulic network capital cost, plus the capitalised cost of pumping energy. The developed model, called Lenhsnet, may also be used for economical design when ...
International Nuclear Information System (INIS)
Chen, Syuan-Yi; Hung, Yi-Hsuan; Wu, Chien-Hsun; Huang, Siang-Ting
2015-01-01
Highlights: • Online sub-optimal energy management using IPSO. • A second-order HEV model with 5 major segments was built. • IPSO with equivalent-fuel fitness function using 5 particles. • Engine, rule-based control, PSO, IPSO and ECMS are compared. • Max. 31+% fuel economy and 56+% energy consumption improved. - Abstract: This study developed an online suboptimal energy management system by using improved particle swarm optimization (IPSO) for engine/motor hybrid electric vehicles. The vehicle was modeled on the basis of second-order dynamics, and featured five major segments: a battery, a spark ignition engine, a lithium battery, transmission and vehicle dynamics, and a driver model. To manage the power distribution of dual power sources, the IPSO was equipped with three inputs (rotational speed, battery state-of-charge, and demanded torque) and one output (power split ratio). Five steps were developed for IPSO: (1) initialization; (2) determination of the fitness function; (3) selection and memorization; (4) modification of position and velocity; and (5) a stopping rule. Equivalent fuel consumption by the engine and motor was used as the fitness function with five particles, and the IPSO-based vehicle control unit was completed and integrated with the vehicle simulator. To quantify the energy improvement of IPSO, a four-mode rule-based control (system ready, motor only, engine only, and hybrid modes) was designed according to the engine efficiency and rotational speed. A three-loop Equivalent Consumption Minimization Strategy (ECMS) was coded as the best case. The simulation results revealed that IPSO searches the optimal solution more efficiently than conventional PSO does. In two standard driving cycles, ECE and FTP, the improvements in the equivalent fuel consumption and energy consumption compared to baseline were (24.25%, 45.27%) and (31.85%, 56.41%), respectively, for the IPSO. The CO_2 emission for all five cases (pure engine, rule-based, PSO
Directory of Open Access Journals (Sweden)
B. Shank
2014-11-01
Full Text Available We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs connected to quasiparticle (qp traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
Rethinking exchange market models as optimization algorithms
Luquini, Evandro; Omar, Nizam
2018-02-01
The exchange market model has mainly been used to study the inequality problem. Although the human society inequality problem is very important, the exchange market models dynamics until stationary state and its capability of ranking individuals is interesting in itself. This study considers the hypothesis that the exchange market model could be understood as an optimization procedure. We present herein the implications for algorithmic optimization and also the possibility of a new family of exchange market models
Problems of future energy market planning and optimization
International Nuclear Information System (INIS)
Vladimir Lelek; David Jaluvka
2007-01-01
Problems of future energy supply in the form, which is demanded - heat, liquid fuel, electricity - are described. There are several factors, which probably could be studied separately: technology and its sustain ability with respect to the raw materials resources, long time for capacity construction, for some form of energy even absence of sufficiently deep technology knowledge and model of prices. Prices are specially peculiar problem - they could be very different from the standard approach (investment, operation and maintenance, fuel, profit), if there are market instabilities and you are not able to supply market by the demanded amount form of energy with the consequences on production. Expected effect will be jump in prices or regulated supply to equalize supply and use. Such situation will be until the new capacities are put into operation or new technologies of production are established - it could be time about ten or more years and this can completely change our standard consideration of profit. The main profit will be to avoid losses and unemployment. Also concept of local or domestic raw material resources could be changed - in the free market your resources will be sold to those paying more. Probable development of energy market is described in the article and special attention is devoted to the nuclear energy, which not only consume, but also produce raw material and how to proceed to avoid crises in supply. Contemporary understanding of the problem does not enable to formulate it strictly as mathematical optimization task (Authors)
Energy models for commercial energy prediction and substitution of renewable energy sources
International Nuclear Information System (INIS)
Iniyan, S.; Suganthi, L.; Samuel, Anand A.
2006-01-01
In this paper, three models have been projected namely Modified Econometric Mathematical (MEM) model, Mathematical Programming Energy-Economy-Environment (MPEEE) model, and Optimal Renewable Energy Mathematical (OREM) model. The actual demand for coal, oil and electricity is predicted using the MEM model based on economic, technological and environmental factors. The results were used in the MPEEE model, which determines the optimum allocation of commercial energy sources based on environmental limitations. The gap between the actual energy demand from the MEM model and optimal energy use from the MPEEE model, has to be met by the renewable energy sources. The study develops an OREM model that would facilitate effective utilization of renewable energy sources in India, based on cost, efficiency, social acceptance, reliability, potential and demand. The economic variations in solar energy systems and inclusion of environmental constraint are also analyzed with OREM model. The OREM model will help policy makers in the formulation and implementation of strategies concerning renewable energy sources in India for the next two decades
3D-mapping optimization of embodied energy of transportation
Energy Technology Data Exchange (ETDEWEB)
Pearce, Joshua M.; Johnson, Sara J. [Clarion University of Pennsylvania, Physics Department, Clarion, PA 16214 (United States); Grant, Gabriel B. [Purdue University, West Lafayette, IN (United States)
2007-08-15
The recent development of Google Earth, an information service that provides imagery and three-dimensional data depicting the entire Earth, provides an opportunity to use a new method of navigating information to save energy in the real world. Google Earth uses Keyhole Markup Language (KML) for modeling and storing geographic features and information for display in the Google Earth Client. This paper will analyze the potential of this novel and free geographic mapping service to reduce embodied energy of transportation in two ways. First, at the consumer level, Google Earth will be studied to map the automobile route that uses the least fuel and maintains vehicle velocities at their individual maximum fuel efficiency. The same analysis for single destination trips could be used to optimize fleet vehicle routes such as garbage or recycling collection trucks. The secondary benefit of ecological education will also be explored. Fuel used could be converted into monetary units based on the current price of gas, pollution/greenhouse gas emissions, or ecological footprints to improve driving habits. Secondly, KML overlays will be analyzed for use of determining: (1) raw material and products availability as a function of location, and (2) modes of transportation as a function of emissions. These overlays would enable manufacturers access to an easily navigable method to optimize the life cycle of their products by minimizing embodied energy of transportation. The most efficient transportation methods and travel routes could be calculated. This same tool would be useful for architects to obtain Leadership in Energy and Environmental Design rating points for the green design of buildings. Overall, the analysis completed finds that the flexibility and visual display of quantitative information made available by Google Earth could have a significant impact at conserving fuel resources by reducing the embodied energy of transportation on a global scale. (author)
Optimization of directional elastic energy propagation
DEFF Research Database (Denmark)
Andreassen, Erik; Chang, Hannah R.; Ruzzene, Massimo
2016-01-01
The aim of this paper is to demonstrate how topology optimization can be used to design a periodically perforated plate, in order to obtain a tailored anisotropic group velocity profile. The main method is demonstrated on both low and high frequency bending wave propagation in an aluminum plate......, but is general in the sense that it could be used to design periodic structures with frequency dependent group velocity profiles for any kind of elastic wave propagation. With the proposed method the resulting design is manufacturable. Measurements on an optimized design compare excellently with the numerical...
DEFF Research Database (Denmark)
Ghiglino, Christian; Tvede, Mich
for generations, through fiscal policy, i.e. monetary transfers and taxes. Both situations with and without time discounting are considered. It is shown that if the discount factor is suffciently close to one then the optimal policy stabilizes the economy, i.e. the equilibrium path has the turnpike property...
DEFF Research Database (Denmark)
Ghiglino, Christian; Tvede, Mich
2000-01-01
for generations, through fiscal policy, i.e., monetary transfers and taxes. Situations both with and without time discounting are considered. It is shown that if the discount factor is sufficiently close to one then the optimal policy stabilizes the economy, i.e. the equilibrium path has the turnpike property...
DEFF Research Database (Denmark)
Baldini, Mattia; Klinge Jacobsen, Henrik
2016-01-01
the improvements made in the energy saving field. Indeed, little attention has been paid to implement energy efficiency measures, which has resulted in scenarios where expedients for a wise use of energy (e.g. energy savings and renewables share) are unbalanced. The aim of this paper is to review and evaluate...... international experiences on finding the optimal trade-off between efficiency improvements and additional renewable energy supply. A critical review of each technique, focusing on purposes, methodology and outcomes, is provided along with a review of tools adopted for the analyses. The models are categorized...... trade-off between renewables and energy efficiency measures in energy-systems under different objectives....
Optimal Scheduling for Energy Harvesting Transmitters with Hybrid Energy Storage
Ozel, Omur; Shahzad, Khurram; Ulukus, Sennur
2013-01-01
We consider data transmission with an energy harvesting transmitter which has a hybrid energy storage unit composed of a perfectly efficient super-capacitor (SC) and an inefficient battery. The SC has finite space for energy storage while the battery has unlimited space. The transmitter can choose to store the harvested energy in the SC or in the battery. The energy is drained from the SC and the battery simultaneously. In this setting, we consider the offline throughput maximization problem ...
Hybrid vehicle energy management: singular optimal control
Delprat, S.; Hofman, T.; Paganelli, S.
2017-01-01
Hybrid vehicle energymanagement is often studied in simulation as an optimal control problem. Under strict convexity assumptions, a solution can be developed using Pontryagin’s minimum principle. In practice, however, many engineers do not formally check these assumptions resulting in the possible
Optimization of airborne wind energy generators
Fagiano, L.; Milanese, M.; Piga, D.
2012-01-01
This paper presents novel results related to an innovative airborne wind energy technology, named Kitenergy, for the conversion of high-altitude wind energy into electricity. The research activities carried out in the last five years, including theoretical analyses, numerical simulations, and
Optimization of energy planning strategies in municipalities
DEFF Research Database (Denmark)
Petersen, Jens-Phillip
approach, suffers from insufficient information, tools and resources. Municipalities are often unable to take on a steering role in community energy planning. To overcome these barriers and guide municipalities in the pre-project phase, a decision-support methodology, based on community energy profiles...
Handbook on modelling for discrete optimization
Pitsoulis, Leonidas; Williams, H
2006-01-01
The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...
Portfolio optimization with mean-variance model
Hoe, Lam Weng; Siew, Lam Weng
2016-06-01
Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.
Energy based optimization of viscous–friction dampers on cables
International Nuclear Information System (INIS)
Weber, F; Boston, C
2010-01-01
This investigation optimizes numerically a viscous–friction damper connected to a cable close to one cable anchor for fastest reduction of the total mechanical cable energy during a free vibration decay test. The optimization parameters are the viscous coefficient of the viscous part and the ratio between the friction force and displacement amplitude of the friction part of the transverse damper. Results demonstrate that an almost pure friction damper with negligibly small viscous damping generates fastest cable energy reduction over the entire decay. The ratio between the friction force and displacement amplitude of the optimal friction damper differs from that derived from the energy equivalent optimal viscous damper. The reason for this is that the nonlinearity of the friction damper causes energy spillover from the excited to higher modes of the order of 10%, i.e. cables with attached friction dampers vibrate at several frequencies. This explains why the energy equivalent approach does not yield the optimal friction damper. Analysis of the simulation data demonstrates that the optimally tuned friction damper dissipates the same energy per cycle as if each modal component of the cable were damped by its corresponding optimal linear viscous damper
The Optimal Use of Renewable Energy Sources-The Case of Lemnos Island
DEFF Research Database (Denmark)
Koroneos, C.; Xydis, George; Polyzakis, A.
2012-01-01
The efficient use of Renewable Energy Sources (RES) is one of the major issues in the modern energy sector. The objective of this work was to examine the potential of wind energy, solar energy (e.g. photovoltaics), biomass energy sources to meet the current energy use in the island of Lemnos...... in Greece. An optimisation methodology was applied to the energy system of the island, where various Renewable Energy Sources are abundant and could be exploited to satisfy part of the island's energy needs. An optimization model has been developed having as an objective the satisfaction of Lemnos Island...... energy needs from Renewable Energy Sources taking into consideration a multiplicity of criteria such as environmental impacts, energy demand, energy cost, and resources availability. A series of solutions have resulted, based on deterministic model runs, providing decision makers the flexibility...
DEFF Research Database (Denmark)
Zheng, Yingying; Jenkins, Bryan M.; Kornbluth, Kurt
2018-01-01
Deterministic constrained optimization and stochastic optimization approaches were used to evaluate uncertainties in biomass-integrated microgrids supplying both electricity and heat. An economic linear programming model with a sliding time window was developed to assess design and scheduling...... of biomass combined heat and power (BCHP) based microgrid systems. Other available technologies considered within the microgrid were small-scale wind turbines, photovoltaic modules (PV), producer gas storage, battery storage, thermal energy storage and heat-only boilers. As an illustrative example, a case...... study was examined for a conceptual utility grid-connected microgrid application in Davis, California. The results show that for the assumptions used, a BCHP/PV with battery storage combination is the most cost effective design based on the assumed energy load profile, local climate data, utility tariff...
Integrated IDA–ANN–DEA for assessment and optimization of energy consumption in industrial sectors
International Nuclear Information System (INIS)
Olanrewaju, O.A.; Jimoh, A.A.; Kholopane, P.A.
2012-01-01
This paper puts forward an integrated approach, based on logarithmic mean divisia index (LMDI) – an index decomposition analysis (IDA) method, an artificial neural network (ANN) and a data envelopment analysis (DEA) for the analysis of total energy efficiency and optimization in an industrial sector. The energy efficiency assessment and the optimization of the proposed model use LMDI to decompose energy consumption into activity, structural and intensity indicators, which serve as inputs to the ANN. The ANN model is verified and validated by performing a linear regression comparison between the specifically measured energy consumption and the corresponding predicted energy consumption. The proposed approach utilizes the measure-specific, super-efficient DEA model for sensitivity analysis to determine the critical measured energy consumption and its optimization reductions. The proposed method is validated by its application to determine the efficiency computation and an analysis of historical data as well as the prediction and optimization capability of the Canadian industrial sector. -- Highlights: ► An integrated IDA–ANN–DEA model for energy management is proposed. ► The model relies on aggregate energy and GDP data. ► The model explains how energy can be managed in the Canadian Industrial sector.
International Nuclear Information System (INIS)
Chae, Kyu Nam
1995-02-01
An energy demand and supply analysis is carried out to establish the future nuclear energy system of Korea in the situation of environmental restriction and resource depletion. Based on the useful energy intensity concept, a long-term energy demand forecasting model FIN2USE is developed to integrate with a supply model. The energy supply optimization model MESSAGE is improved to evaluate the role of nuclear energy system in Korean long-term energy supply strategy. Long-term demand for useful energy used as an exogeneous input of the energy supply model is derived from the trend of useful energy intensity by sectors and energy carriers. Supply-side optimization is performed for the overall energy system linked with the reactor and nuclear fuel cycle strategy. The limitation of fossil fuel resources and the CO 2 emission constraints are reflected as determinants of the future energy system. As a result of optimization of energy system using linear programming with the objective of total discounted system cost, the optimal energy system is obtained with detailed results on the nuclear sector for various scenarios. It is shown that the relative importance of nuclear energy would increase especially in the cases of CO 2 emission constraint. It is concluded that nuclear reactor strategy and fuel cycle strategy should be incorporated with national energy strategy and be changed according to environmental restriction and energy demand scenarios. It is shown that this modelling approach is suitable for a decision support system of nuclear energy policy
Design optimization of superconducting magnetic energy storage coil
Energy Technology Data Exchange (ETDEWEB)
Bhunia, Uttam, E-mail: ubhunia@vecc.gov.in; Saha, Subimal; Chakrabarti, Alok
2014-05-15
Highlights: • We modeled the optimization formulation that minimizes overall refrigeration load into the SMES cryostat. • Higher the operating current reduces the dynamic load but increases static heat load into the cryostat. • Higher allowable hoop stress reduces both coil volume and refrigeration load. • The formulation can be in general be utilized for any arbitrary specification of SMES coil and conductor type. - Abstract: An optimization formulation has been developed for a superconducting magnetic energy storage (SMES) solenoid-type coil with niobium titanium (Nb–Ti) based Rutherford-type cable that minimizes the cryogenic refrigeration load into the cryostat. Minimization of refrigeration load reduces the operating cost and opens up the possibility to adopt helium re-condensing system using cryo-cooler especially for small-scale SMES system. Dynamic refrigeration load during charging or discharging operational mode of the coil dominates over steady state load. The paper outlines design optimization with practical design constraints like actual critical characteristics of the superconducting cable, maximum allowable hoop stress on winding, etc., with the objective to minimize refrigeration load into the SMES cryostat. Effect of design parameters on refrigeration load is also investigated.
Making optimal investment decisions for energy service companies under uncertainty: A case study
International Nuclear Information System (INIS)
Deng, Qianli; Jiang, Xianglin; Zhang, Limao; Cui, Qingbin
2015-01-01
Varied initial energy efficiency investments would result in different annual energy savings achievements. In order to balance the savings revenue and the potential capital loss through EPC (Energy Performance Contracting), a cost-effective investment decision is needed when selecting energy efficiency technologies. In this research, an approach is developed for the ESCO (Energy Service Company) to evaluate the potential energy savings profit, and thus make the optimal investment decisions. The energy savings revenue under uncertainties, which are derived from energy efficiency performance variation and energy price fluctuation, are first modeled as stochastic processes. Then, the derived energy savings profit is shared by the owner and the ESCO according to the contract specification. A simulation-based model is thus built to maximize the owner's profit, and at the same time, satisfy the ESCO's expected rate of return. In order to demonstrate the applicability of the proposed approach, the University of Maryland campus case is also presented. The proposed method could not only help the ESCO determine the optimal energy efficiency investments, but also assist the owner's decision in the bidding selection. - Highlights: • An optimization model is built for determining energy efficiency investment for ESCO. • Evolution of the energy savings revenue is modeled as a stochastic process. • Simulation is adopted to calculate investment balancing the owner and the ESCO's profit. • A campus case is presented to demonstrate applicability of the proposed approach
International Nuclear Information System (INIS)
Suzuki, Atsuyuki
1980-01-01
The paper is aimed at making a theoretical analysis on optimal shift from finite energy resources like presently used oil toward advanced energy sources like nuclear and solar. First, the value of conventional energy as a finite resource is derived based on the variational principle. Second, a simplified model on macroeconomy is used to obtain and optimal relationship between energy production and consumption and thereby the optimality on energy price is provided. Third, the meaning of research and development of advanced energy is shown by taking into account resource constraints and technological progress. Finally, an optimal timing of the shift from conventional to advanced energies is determined by making use of the maximum principle. The methematical model employed there is much simplified but can be used to conclude that in order to make an optimal shift some policy-oriented decision must be made prior to when an economically competitive condition comes and that, even with that decision made, some recession of energy demand is inevitable during the transitional phase. (author)
Optimization of sources for focusing wave energy in targeted formations
Jeong, C; Kallivokas, L F; Huh, C; Lake, L W
2010-01-01
that will maximize the kinetic energy in the target zone, while keeping silent the neighbouring zones. To this end, we cast the problem as an inverse-source problem, and use a partial-differential- equation-constrained optimization approach to arrive at an optimized
Optimization of HTS superconducting magnetic energy storage magnet volume
Korpela, Aki; Lehtonen, Jorma; Mikkonen, Risto
2003-08-01
Nonlinear optimization problems in the field of electromagnetics have been successfully solved by means of sequential quadratic programming (SQP) and the finite element method (FEM). For example, the combination of SQP and FEM has been proven to be an efficient tool in the optimization of low temperature superconductors (LTS) superconducting magnetic energy storage (SMES) magnets. The procedure can also be applied for the optimization of HTS magnets. However, due to a strongly anisotropic material and a slanted electric field, current density characteristic high temperature superconductors HTS optimization is quite different from that of the LTS. In this paper the volumes of solenoidal conduction-cooled Bi-2223/Ag SMES magnets have been optimized at the operation temperature of 20 K. In addition to the electromagnetic constraints the stress caused by the tape bending has also been taken into account. Several optimization runs with different initial geometries were performed in order to find the best possible solution for a certain energy requirement. The optimization constraints describe the steady-state operation, thus the presented coil geometries are designed for slow ramping rates. Different energy requirements were investigated in order to find the energy dependence of the design parameters of optimized solenoidal HTS coils. According to the results, these dependences can be described with polynomial expressions.
Energy Technology Data Exchange (ETDEWEB)
Liu, Pei; Pistikopoulos, Efstratios N. [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Li, Zheng [Department of Thermal Engineering, Tsinghua University, Beijing 100084 (China)
2010-08-15
Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach. (author)
International Nuclear Information System (INIS)
Liu Pei; Pistikopoulos, Efstratios N.; Li Zheng
2010-01-01
Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach.
Energy Technology Data Exchange (ETDEWEB)
Liu Pei [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Pistikopoulos, Efstratios N., E-mail: e.pistikopoulos@imperial.ac.u [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Li Zheng [Department of Thermal Engineering, Tsinghua University, Beijing 100084 (China)
2010-08-15
Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach.
Modeling investor optimism with fuzzy connectives
Lovric, M.; Almeida, R.J.; Kaymak, U.; Spronk, J.; Carvalho, J.P.; Dubois, D.; Kaymak, U.; Sousa, J.M.C.
2009-01-01
Optimism or pessimism of investors is one of the important characteristics that determine the investment behavior in financial markets. In this paper, we propose a model of investor optimism based on a fuzzy connective. The advantage of the proposed approach is that the influence of different levels
DEFF Research Database (Denmark)
Khoobi, Saeed; Halvaei, Abolfazl; Hajizadeh, Amin
2016-01-01
Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management...... of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy...
International Nuclear Information System (INIS)
Baldi, Simone; Karagevrekis, Athanasios; Michailidis, Iakovos T.; Kosmatopoulos, Elias B.
2015-01-01
Highlights: • Energy efficient operation of photovoltaic-equipped interconnected microgrids. • Optimized energy demand for a block of heterogeneous buildings with different sizes. • Multiobjective optimization: matching demand and supply taking into account thermal comfort. • Intelligent control mechanism for heating, ventilating, and air conditioning units. • Optimization of energy consumption and thermal comfort at the aggregate microgrid level. - Abstract: Electrical smart microgrids equipped with small-scale renewable-energy generation systems are emerging progressively as an alternative or an enhancement to the central electrical grid: due to the intermittent nature of the renewable energy sources, appropriate algorithms are required to integrate these two typologies of grids and, in particular, to perform efficiently dynamic energy demand and distributed generation management, while guaranteeing satisfactory thermal comfort for the occupants. This paper presents a novel control algorithm for joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids. Energy demand shaping is achieved via an intelligent control mechanism for heating, ventilating, and air conditioning units. The intelligent control mechanism takes into account the available solar energy, the building dynamics and the thermal comfort of the buildings’ occupants. The control design is accomplished in a simulation-based fashion using an energy simulation model, developed in EnergyPlus, of an interconnected microgrid. Rather than focusing only on how each building behaves individually, the optimization algorithm employs a central controller that allows interaction among the buildings of the microgrid. The control objective is to optimize the aggregate microgrid performance. Simulation results demonstrate that the optimization algorithm efficiently integrates the microgrid with the photovoltaic system that provides free electric energy: in
Image processing to optimize wave energy converters
Bailey, Kyle Marc-Anthony
The world is turning to renewable energies as a means of ensuring the planet's future and well-being. There have been a few attempts in the past to utilize wave power as a means of generating electricity through the use of Wave Energy Converters (WEC), but only recently are they becoming a focal point in the renewable energy field. Over the past few years there has been a global drive to advance the efficiency of WEC. Placing a mechanical device either onshore or offshore that captures the energy within ocean surface waves to drive a mechanical device is how wave power is produced. This paper seeks to provide a novel and innovative way to estimate ocean wave frequency through the use of image processing. This will be achieved by applying a complex modulated lapped orthogonal transform filter bank to satellite images of ocean waves. The complex modulated lapped orthogonal transform filterbank provides an equal subband decomposition of the Nyquist bounded discrete time Fourier Transform spectrum. The maximum energy of the 2D complex modulated lapped transform subband is used to determine the horizontal and vertical frequency, which subsequently can be used to determine the wave frequency in the direction of the WEC by a simple trigonometric scaling. The robustness of the proposed method is provided by the applications to simulated and real satellite images where the frequency is known.
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
Optimization in the energy sector; Optimierung in der Energiewirtschaft
Energy Technology Data Exchange (ETDEWEB)
NONE
2015-07-01
The implementation of the energy transition and the developments in the national and international Energy markets constantly require sound analysis and new answers. The symposium ''optimization in the energy sector'' gives an overview of methods and models that can be practically used for decision support. Storage and electromobility as demand flexibility are important factors for the long-term design of the German and European energy system. But methodological aspects such as the consideration of uncertainties at the conference an important place is given. A key issue is also the short and medium term further development of the electricity market design. Not only broadly but also in detail e.g. the standard benefit and intraday markets there is considerable potential for optimization, which will be discussed in the context of technical presentations. And in view of challenging market environment is also new approaches to portfolio management a great importance for the practice. Therefore we are convinced that the Conference and its results for energy companies, public services and new entrants in the energy industry as well are of interest as for consultants, authorities, associations and energy economic research institutes. [German] Die Umsetzung der Energiewende und die Entwicklungen auf den nationalen und internationalen Energiemaerkten erfordern immer wieder fundierte Analysen und neue Antworten. Die Fachtagung ''Optimierung in der Energiewirtschaft'' gibt hier einen Ueberblick ueber Methoden und Modelle, die praxisnah zur Entscheidungsunterstuetzung eingesetzt werden koennen. Speicher und Elektromobilitaet ebenso wie Nachfrageflexibilitaet sind wichtige Faktoren fuer die langfristige Gestaltung des deutschen und europaeischen Energiesystems. Aber auch methodischen Aspekten wie die Beruecksichtigung von Unsicherheiten wird im Rahmen der Tagung ein wichtiger Platz eingeraeumt. Ein zentrales Thema ist zudem die kurz- und
National Energy Outlook Modelling System
Energy Technology Data Exchange (ETDEWEB)
Volkers, C.M. [ECN Policy Studies, Petten (Netherlands)
2013-12-15
For over 20 years, the Energy research Centre of the Netherlands (ECN) has been developing the National Energy Outlook Modelling System (NEOMS) for Energy projections and policy evaluations. NEOMS enables 12 energy models of ECN to exchange data and produce consistent and detailed results.
Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.
D'Agostino, Delia; Parker, Danny
2018-04-01
This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs) in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO 2 emissions, envelope, materials, lighting, appliances and systems.
Data on cost-optimal Nearly Zero Energy Buildings (NZEBs across Europe
Directory of Open Access Journals (Sweden)
Delia D'Agostino
2018-04-01
Full Text Available This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO2 emissions, envelope, materials, lighting, appliances and systems.
Iterative free-energy optimization for recurrent neural networks (INFERNO)
2017-01-01
The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework based on the free-energy principle, we propose to see the problem of spikes’ synchrony as an optimization problem of the neurons sub-threshold activity for the generation of long neuronal chains. Using a stochastic gradient descent, a reinforcement signal (presumably dopaminergic) evaluates the quality of one input vector to move the recurrent neural network to a desired activity; depending on the error made, this input vector is strengthened to hill-climb the gradient or elicited to search for another solution. This vector can be learned then by one associative memory as a model of the basal-ganglia to control the recurrent neural network. Experiments on habit learning and on sequence retrieving demonstrate the capabilities of the dual system to generate very long and precise spatio-temporal sequences, above two hundred iterations. Its features are applied then to the sequential planning of arm movements. In line with neurobiological theories, we discuss its relevance for modeling the cortico-basal working memory to initiate flexible goal-directed neuronal chains of causation and its relation to novel architectures such as Deep Networks, Neural Turing Machines and the Free-Energy Principle. PMID:28282439
Modeling and optimization of laser cutting operations
Directory of Open Access Journals (Sweden)
Gadallah Mohamed Hassan
2015-01-01
Full Text Available Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta, surface roughness (Ra and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.
Mathematical modeling and optimization of complex structures
Repin, Sergey; Tuovinen, Tero
2016-01-01
This volume contains selected papers in three closely related areas: mathematical modeling in mechanics, numerical analysis, and optimization methods. The papers are based upon talks presented on the International Conference for Mathematical Modeling and Optimization in Mechanics, held in Jyväskylä, Finland, March 6-7, 2014 dedicated to Prof. N. Banichuk on the occasion of his 70th birthday. The articles are written by well-known scientists working in computational mechanics and in optimization of complicated technical models. Also, the volume contains papers discussing the historical development, the state of the art, new ideas, and open problems arising in modern continuum mechanics and applied optimization problems. Several papers are concerned with mathematical problems in numerical analysis, which are also closely related to important mechanical models. The main topics treated include: * Computer simulation methods in mechanics, physics, and biology; * Variational problems and methods; minimiz...
Stochastic search, optimization and regression with energy applications
Hannah, Lauren A.
Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression
International Nuclear Information System (INIS)
Tsvetkov, Pavel Valeryevich; Rodriguez, Salvador B.; Ames, David E. II; Rochau, Gary Eugene
2009-01-01
The impact associated with energy generation and utilization is immeasurable due to the immense, widespread, and myriad effects it has on the world and its inhabitants. The polar extremes are demonstrated on the one hand, by the high quality of life enjoyed by individuals with access to abundant reliable energy sources, and on the other hand by the global-scale environmental degradation attributed to the affects of energy production and use. Thus, nations strive to increase their energy generation, but are faced with the challenge of doing so with a minimal impact on the environment and in a manner that is self-reliant. Consequently, a revival of interest in nuclear energy has followed, with much focus placed on technologies for transmuting nuclear spent fuel. The performed research investigates nuclear energy systems that optimize the destruction of nuclear waste. In the context of this effort, nuclear energy system is defined as a configuration of nuclear reactors and corresponding fuel cycle components. The proposed system has unique characteristics that set it apart from other systems. Most notably the dedicated High-Energy External Source Transmuter (HEST), which is envisioned as an advanced incinerator used in combination with thermal reactors. The system is configured for examining environmentally benign fuel cycle options by focusing on minimization or elimination of high level waste inventories. Detailed high-fidelity exact-geometry models were developed for representative reactor configurations. They were used in preliminary calculations with Monte Carlo N-Particle eXtented (MCNPX) and Standardized Computer Analysis for Licensing Evaluation (SCALE) code systems. The reactor models have been benchmarked against existing experimental data and design data. Simulink(reg s ign), an extension of MATLAB(reg s ign), is envisioned as the interface environment for constructing the nuclear energy system model by linking the individual reactor and fuel component sub-models
Reliability-Based Structural Optimization of Wave Energy Converters
DEFF Research Database (Denmark)
Ambühl, Simon; Kramer, Morten; Sørensen, John Dalsgaard
2014-01-01
More and more wave energy converter (WEC) concepts are reaching prototype level. Once the prototype level is reached, the next step in order to further decrease the levelized cost of energy (LCOE) is optimizing the overall system with a focus on structural and maintenance (inspection) costs......, as well as on the harvested power from the waves. The target of a fully-developed WEC technology is not maximizing its power output, but minimizing the resulting LCOE. This paper presents a methodology to optimize the structural design of WECs based on a reliability-based optimization problem...
Online algorithms for optimal energy distribution in microgrids
Wang, Yu; Nelms, R Mark
2015-01-01
Presenting an optimal energy distribution strategy for microgrids in a smart grid environment, and featuring a detailed analysis of the mathematical techniques of convex optimization and online algorithms, this book provides readers with essential content on how to achieve multi-objective optimization that takes into consideration power subscribers, energy providers and grid smoothing in microgrids. Featuring detailed theoretical proofs and simulation results that demonstrate and evaluate the correctness and effectiveness of the algorithm, this text explains step-by-step how the problem can b
Desiccant wheel thermal performance modeling for indoor humidity optimal control
International Nuclear Information System (INIS)
Wang, Nan; Zhang, Jiangfeng; Xia, Xiaohua
2013-01-01
Highlights: • An optimal humidity control model is formulated to control the indoor humidity. • MPC strategy is used to implement the optimal operation solution. • Practical applications of the MPC strategy is illustrated by the case study. - Abstract: Thermal comfort is an important concern in the energy efficiency improvement of commercial buildings. Thermal comfort research focuses mostly on temperature control, but humidity control is an important aspect to maintain indoor comfort too. In this paper, an optimal humidity control model (OHCM) is presented. Model predictive control (MPC) strategy is applied to implement the optimal operation of the desiccant wheel during working hours of a commercial building. The OHCM is revised to apply the MPC strategy. A case is studied to illustrate the practical applications of the MPC strategy
International Nuclear Information System (INIS)
Feng, Lujia; Mears, Laine; Beaufort, Cleveland; Schulte, Joerg
2016-01-01
Highlights: • Single objective and multicriteria optimization approaches are proposed. • Objectives of energy, economy, and environment are proved conflicting. • 3-input-5-output energy supply system of an automotive plant is studied. - Abstract: Increasing attention has recently been drawn to energy consumption in manufacturing plants. Facing the challenges from reducing emissions coupled with rising raw material prices and energy costs, manufacturers are trying to balance the energy usage strategy among the total energy consumption, economy, and environment, which can be self-conflicting at times. In this paper, energy systems in manufacturing environments are reviewed, and the current status of onsite energy system and renewable energy usage are discussed. Single objective and multicriteria optimization approaches are effectively formulated for making the best use of energy delivered to the production processes. Energy supply operation suggestions based on the optimization results are obtained. Finally, an example from an automotive assembly manufacturer is described to demonstrate the energy usage in the current manufacturing plants and how the optimization approaches can be applied to satisfy the energy management objectives. According to the optimization results, in an energy oriented operation, it takes 35% more in monetary cost; while in an economy oriented operation, it takes 17% more in megawatt hour energy supply and tends to rely more on the inexpensive renewable energy.
International Nuclear Information System (INIS)
Wang, Ge; Zhang, Qi; Mclellan, Benjamin C.; Li, Hailong
2016-01-01
Renewable energy is expected to play much more important role in future low-carbon energy system, however, renewable energy has problems with regard to load-following and regional imbalance. This study aims to plan the deployment of intermittent renewable energy in multiple regions considering the impacts of regional natural conditions and generation capacity mix as well as interregional transmission capacity using a multi-region dynamic optimization model. The model was developed to find optimized development paths toward future smart electricity systems with high level penetration of intermittent renewable energy considering regional differences and interregional transmission at national scale. As a case study, the model was applied to plan power generation in nine interconnected regions in Japan out to 2030. Four scenarios were proposed with different supporting policies for the interregional power transmission infrastructures and different nuclear power phase-out scenarios. The analysis results show that (i) the government's support for power transmission infrastructures is vital important to develop more intermittent renewable energy in appropriate regions and utilize renewable energy more efficiently; (ii) nuclear and renewable can complement rather than replace each other if enough interregional transmission capacity is provided. - Highlights: • Plan the optimal deployment of intermittent renewable energy in multiple regions. • A multi-region dynamic optimization model was developed. • The impacts of natural conditions and interregional transmission are studied. • The government's support for transmission is vital important for renewable energy. • Nuclear and renewable can complement rather than replace each other.
Optimal control, investment and utilization schemes for energy storage under uncertainty
Mirhosseini, Niloufar Sadat
Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency
Maintenance Optimization of High Voltage Substation Model
Directory of Open Access Journals (Sweden)
Radim Bris
2008-01-01
Full Text Available The real system from practice is selected for optimization purpose in this paper. We describe the real scheme of a high voltage (HV substation in different work states. Model scheme of the HV substation 22 kV is demonstrated within the paper. The scheme serves as input model scheme for the maintenance optimization. The input reliability and cost parameters of all components are given: the preventive and corrective maintenance costs, the actual maintenance period (being optimized, the failure rate and mean time to repair - MTTR.
Optimized systems for energy efficient optical tweezing
Kampmann, R.; Kleindienst, R.; Grewe, A.; Bürger, Elisabeth; Oeder, A.; Sinzinger, S.
2013-03-01
Compared to conventional optics like singlet lenses or even microscope objectives advanced optical designs help to develop properties specifically useful for efficient optical tweezers. We present an optical setup providing a customized intensity distribution optimized with respect to large trapping forces. The optical design concept combines a refractive double axicon with a reflective parabolic focusing mirror. The axicon arrangement creates an annular field distribution and thus clears space for additional integrated observation optics in the center of the system. Finally the beam is focused to the desired intensity distribution by a parabolic ring mirror. The compact realization of the system potentially opens new fields of applications for optical tweezers such as in production industries and micro-nano assembly.
Economic analysis of alternatives for optimizing energy use in manufacturing companies
International Nuclear Information System (INIS)
Méndez-Piñero, Mayra Ivelisse; Colón-Vázquez, Melitza
2013-01-01
The manufacturing companies are one of the main consumers of energy. The increment in global warming and the instability in the petroleum oil market have motivated companies to find alternatives to reduce energy use. In the academic literature several researchers have demonstrated that optimization models can be successfully used to reduce energy use. This research presents the use of an optimization model to identify feasible economic alternatives to reduce energy use. The economic analysis methods used were the payback and the internal rate of return. The optimization model developed in this research was applied and validated using an electronic manufacturing company case study. The results demonstrate that the main variables affecting the economic feasibility of the alternatives are the economic analysis method and the initial implementation costs. Several scenarios were analyzed and the best results show that the manufacturing company could save up to $78,000 in three years if the recommendations based on the optimization model results are implemented. - Highlights: • Evaluate top consumers of energy in manufacturing: A/C, compressed air, and lighting • Economic analysis of alternatives to optimize energy used in manufacturing • Comparison of payback method and internal rate of return method with real data • Results demonstrate that the company could generate savings in energy use
A useful framework for optimal replacement models
International Nuclear Information System (INIS)
Aven, Terje; Dekker, Rommert
1997-01-01
In this note we present a general framework for optimization of replacement times. It covers a number of models, including various age and block replacement models, and allows a uniform analysis for all these models. A relation to the marginal cost concept is described
Multiobjective optimization of an extremal evolution model
International Nuclear Information System (INIS)
Elettreby, M.F.
2004-09-01
We propose a two-dimensional model for a co-evolving ecosystem that generalizes the extremal coupled map lattice model. The model takes into account the concept of multiobjective optimization. We find that the system self-organizes into a critical state. The distributions of the distances between subsequent mutations as well as the distribution of avalanches sizes follow power law. (author)
Optimizing Data Centre Energy and Environmental Costs
Aikema, David Hendrik
Data centres use an estimated 2% of US electrical power which accounts for much of their total cost of ownership. This consumption continues to grow, further straining power grids attempting to integrate more renewable energy. This dissertation focuses on assessing and reducing data centre environmental and financial costs. Emissions of projects undertaken to lower the data centre environmental footprints can be assessed and the emission reduction projects compared using an ISO-14064-2-compliant greenhouse gas reduction protocol outlined herein. I was closely involved with the development of the protocol. Full lifecycle analysis and verifying that projects exceed business-as-usual expectations are addressed, and a test project is described. Consuming power when it is low cost or when renewable energy is available can be used to reduce the financial and environmental costs of computing. Adaptation based on the power price showed 10--50% potential savings in typical cases, and local renewable energy use could be increased by 10--80%. Allowing a fraction of high-priority tasks to proceed unimpeded still allows significant savings. Power grid operators use mechanisms called ancillary services to address variation and system failures, paying organizations to alter power consumption on request. By bidding to offer these services, data centres may be able to lower their energy costs while reducing their environmental impact. If providing contingency reserves which require only infrequent action, savings of up to 12% were seen in simulations. Greater power cost savings are possible for those ceding more control to the power grid operator. Coordinating multiple data centres adds overhead, and altering at which data centre requests are processed based on changes in the financial or environmental costs of power is likely to increase this overhead. Tests of virtual machine migrations showed that in some cases there was no visible increase in power use while in others power use
A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting
International Nuclear Information System (INIS)
Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge
2014-01-01
Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily
Energy models: methods and trends
Energy Technology Data Exchange (ETDEWEB)
Reuter, A [Division of Energy Management and Planning, Verbundplan, Klagenfurt (Austria); Kuehner, R [IER Institute for Energy Economics and the Rational Use of Energy, University of Stuttgart, Stuttgart (Germany); Wohlgemuth, N [Department of Economy, University of Klagenfurt, Klagenfurt (Austria)
1997-12-31
Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of `energy models`, computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning. 2 figs., 19 refs.
Energy models: methods and trends
International Nuclear Information System (INIS)
Reuter, A.; Kuehner, R.; Wohlgemuth, N.
1996-01-01
Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of 'energy models', computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning
Optimal design of distributed energy resource systems based on two-stage stochastic programming
International Nuclear Information System (INIS)
Yang, Yun; Zhang, Shijie; Xiao, Yunhan
2017-01-01
Highlights: • A two-stage stochastic programming model is built to design DER systems under uncertainties. • Uncertain energy demands have a significant effect on the optimal design. • Uncertain energy prices and renewable energy intensity have little effect on the optimal design. • The economy is overestimated if the system is designed without considering the uncertainties. • The uncertainty in energy prices has the significant and greatest effect on the economy. - Abstract: Multiple uncertainties exist in the optimal design of distributed energy resource (DER) systems. The expected energy, economic, and environmental benefits may not be achieved and a deficit in energy supply may occur if the uncertainties are not handled properly. This study focuses on the optimal design of DER systems with consideration of the uncertainties. A two-stage stochastic programming model is built in consideration of the discreteness of equipment capacities, equipment partial load operation and output bounds as well as of the influence of ambient temperature on gas turbine performance. The stochastic model is then transformed into its deterministic equivalent and solved. For an illustrative example, the model is applied to a hospital in Lianyungang, China. Comparative studies are performed to evaluate the effect of the uncertainties in load demands, energy prices, and renewable energy intensity separately and simultaneously on the system’s economy and optimal design. Results show that the uncertainties in load demands have a significant effect on the optimal system design, whereas the uncertainties in energy prices and renewable energy intensity have almost no effect. Results regarding economy show that it is obviously overestimated if the system is designed without considering the uncertainties.
Optimization Models for Petroleum Field Exploitation
Energy Technology Data Exchange (ETDEWEB)
Jonsbraaten, Tore Wiig
1998-12-31
This thesis presents and discusses various models for optimal development of a petroleum field. The objective of these optimization models is to maximize, under many uncertain parameters, the project`s expected net present value. First, an overview of petroleum field optimization is given from the point of view of operations research. Reservoir equations for a simple reservoir system are derived and discretized and included in optimization models. Linear programming models for optimizing production decisions are discussed and extended to mixed integer programming models where decisions concerning platform, wells and production strategy are optimized. Then, optimal development decisions under uncertain oil prices are discussed. The uncertain oil price is estimated by a finite set of price scenarios with associated probabilities. The problem is one of stochastic mixed integer programming, and the solution approach is to use a scenario and policy aggregation technique developed by Rockafellar and Wets although this technique was developed for continuous variables. Stochastic optimization problems with focus on problems with decision dependent information discoveries are also discussed. A class of ``manageable`` problems is identified and an implicit enumeration algorithm for finding optimal decision policy is proposed. Problems involving uncertain reservoir properties but with a known initial probability distribution over possible reservoir realizations are discussed. Finally, a section on Nash-equilibrium and bargaining in an oil reservoir management game discusses the pool problem arising when two lease owners have access to the same underlying oil reservoir. Because the oil tends to migrate, both lease owners have incentive to drain oil from the competitors part of the reservoir. The discussion is based on a numerical example. 107 refs., 31 figs., 14 tabs.
Observer model optimization of a spectral mammography system
Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats
2010-04-01
Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.
Real options valuation and optimization of energy assets
Thompson, Matthew
In this thesis we present algorithms for the valuation and optimal operation of natural gas storage facilities, hydro-electric power plants and thermal power generators in competitive markets. Real options theory is used to derive nonlinear partial-integro-differential equations (PIDEs) for the valuation and optimal operating strategies of all types of facilities. The equations are designed to incorporate a wide class of spot price models that can exhibit the same time-dependent, mean-reverting dynamics and price spikes as those observed in most energy markets. Particular attention is paid to the operational characteristics of real energy assets. For natural gas storage facilities these characteristics include: working gas capacities, variable deliverability and injection rates and cycling limitations. For thermal power plants relevant operational characteristics include variable start-up times and costs, control response time lags, minimum generating levels, nonlinear output functions, structural limitations on ramp rates, and minimum up/down time restrictions. For hydro-electric units, head effects and environmental constraints are addressed. We illustrate the models with numerical examples of a gas storage facility, a hydro-electric pump storage facility and a thermal power plant. This PIDE framework is the first in the literature to achieve second order accuracy in characterizing the operating states of hydro-electric and hydro-thermal power plants. The continuous state space representation derived in this thesis can therefore achieve far greater realism in terms of operating state specification than any other method in the literature to date. This thesis is also the first and only to allow for any continuous time jump diffusion processes in order to account for price spikes.
Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.
2016-08-01
Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.
Enhanced index tracking modelling in portfolio optimization
Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin
2013-09-01
Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.
Optimal Real-time Dispatch for Integrated Energy Systems
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Guerrero, Josep M.; Rahimi-Kian, Ashkan
2016-01-01
With the emerging of small-scale integrated energy systems (IESs), there are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy and typical implementation of building-level distributed energy resources (DERs). By integrating DSM and DERs...... into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems, and integrated communications architectures, it is possible to efficiently manage energy and comfort at the end-use location. In this paper, an ontology-driven multi......-agent control system with intelligent optimizers is proposed for optimal real-time dispatch of an integrated building and microgrid system considering coordinated demand response (DR) and DERs management. The optimal dispatch problem is formulated as a mixed integer nonlinear programing problem (MINLP...
Optimization of the Energy Output of Osmotic Power Plants
Directory of Open Access Journals (Sweden)
Florian Dinger
2013-01-01
Full Text Available On the way to a completely renewable energy supply, additional alternatives to hydroelectric, wind, and solar power have to be investigated. Osmotic power is such an alternative with a theoretical global annual potential of up to 14400 TWh (70% of the global electricity consumption of 2008 per year. It utilizes the phenomenon that upon the mixing of fresh water and oceanic salt water (e.g., at a river mouth, around 2.88 MJ of energy per 1 m3 of fresh water is released. Here, we describe a new approach to derive operational parameter settings for osmotic power plants using a pressure exchanger for optimal performance, either with respect to maximum generated power or maximum extracted energy. Up to now, only power optimization is discussed in the literature, but when considering the fresh water supply as a limiting factor, the energy optimization appears as the challenging task.
Energy Optimization of Road Tunnel Lighting Systems
Directory of Open Access Journals (Sweden)
Ferdinando Salata
2015-07-01
Full Text Available A road tunnel is an enclosed and covered infrastructure for the vehicular traffic. Its lighting system provides 24 h of artificial sources only, with a higher amount of electric power used during the day. Due to safety reasons, when there is natural lighting outside the tunnel, the lighting levels in the stretches right after the entrance and before the exit must be high, in order to guide the driver’s eye towards the middle of the tunnel where the luminance must guarantee safe driving, avoid any over-dimensioning of the lighting systems, and produce energy savings. Such effects can be reached not only through the technological advances in the field of artificial lighting sources with high luminous efficiency, but also through new materials for road paving characterized by a higher reflection coefficient than other ordinary asphalts. This case study examines different technical scenarios, analyzing and comparing possible energy and economic savings. Traditional solutions are thus compared with scenarios suggesting the solutions previously mentioned. Special asphalts are interesting from an economic point of view, whereas the high costs of LED sources nowadays represent an obstacle for their implementation.
Energy optimization of integrated process plants
Energy Technology Data Exchange (ETDEWEB)
Sandvig Nielsen, J
1996-10-01
A general approach for viewing the process synthesis as an evolutionary process is proposed. Each step is taken according to the present level of information and knowledge. This is formulated in a Process Synthesis Cycle. Initially the synthesis is conducted at a high abstraction level maximizing use of heuristics (prior experience, rules of thumbs etc). When further knowledge and information are available, heuristics will gradually be replaced by exact problem formulations. The principles in the Process Synthesis Cycle, is used to develop a general procedure for energy synthesis, based on available tools. The procedure is based on efficient use of process simulators with integrated Pinch capabilities (energy targeting). The proposed general procedure is tailored to three specific problems (Humid Air Turbine power plant synthesis, Nitric Acid process synthesis and Sulphuric Acid synthesis). Using the procedure reduces the problem dimension considerable and thus allows for faster evaluation of more alternatives. At more detailed level a new framework for the Heat Exchanger Network synthesis problem is proposed. The new framework is object oriented based on a general functional description of all elements potentially present in the heat exchanger network (streams, exchangers, pumps, furnaces etc.). (LN) 116 refs.
Demand-Side Energy Management Based on Nonconvex Optimization in Smart Grid
Directory of Open Access Journals (Sweden)
Kai Ma
2017-10-01
Full Text Available Demand-side energy management is used for regulating the consumers’ energy usage in smart grid. With the guidance of the grid’s price policy, the consumers can change their energy consumption in response. The objective of this study is jointly optimizing the load status and electric supply, in order to make a tradeoff between the electric cost and the thermal comfort. The problem is formulated into a nonconvex optimization model. The multiplier method is used to solve the constrained optimization, and the objective function is transformed to the augmented Lagrangian function without constraints. Hence, the Powell direction acceleration method with advance and retreat is applied to solve the unconstrained optimization. Numerical results show that the proposed algorithm can achieve the balance between the electric supply and demand, and the optimization variables converge to the optimum.
A cognitive decision agent architecture for optimal energy management of microgrids
International Nuclear Information System (INIS)
Velik, Rosemarie; Nicolay, Pascal
2014-01-01
Highlights: • We propose an optimization approach for energy management in microgrids. • The optimizer emulates processes involved in human decision making. • Optimization objectives are energy self-consumption and financial gain maximization. • We gain improved optimization results in significantly reduced computation time. - Abstract: Via the integration of renewable energy and storage technologies, buildings have started to change from passive (electricity) consumers to active prosumer microgrids. Along with this development come a shift from centralized to distributed production and consumption models as well as discussions about the introduction of variable demand–supply-driven grid electricity prices. Together with upcoming ICT and automation technologies, these developments open space to a wide range of novel energy management and energy trading possibilities to optimally use available energy resources. However, what is considered as an optimal energy management and trading strategy heavily depends on the individual objectives and needs of a microgrid operator. Accordingly, elaborating the most suitable strategy for each particular system configuration and operator need can become quite a complex and time-consuming task, which can massively benefit from computational support. In this article, we introduce a bio-inspired cognitive decision agent architecture for optimized, goal-specific energy management in (interconnected) microgrids, which are additionally connected to the main electricity grid. For evaluating the performance of the architecture, a number of test cases are specified targeting objectives like local photovoltaic energy consumption maximization and financial gain maximization. Obtained outcomes are compared against a modified simulating annealing optimization approach in terms of objective achievement and computational effort. Results demonstrate that the cognitive decision agent architecture yields improved optimization results in
Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review
Directory of Open Access Journals (Sweden)
Maria Ferrara
2018-06-01
Full Text Available Since the introduction of the recast of the EPBD European Directive 2010/31/EU, many studies on the cost-effective feasibility of nearly zero-energy buildings (NZEBs were carried out either by academic research bodies and by national bodies. In particular, the introduction of the cost-optimal methodology has given a strong impulse to research in this field. This paper presents a comprehensive and significant review on scientific works based on the application of cost-optimal analysis applications in Europe since the EPBD recast entered into force, pointing out the differences in the analyzed studies and comparing their outcomes before the new recast of EPBD enters into force in 2018. The analysis is conducted with special regard to the methods used for the energy performance assessment, the global cost calculation, and for the selection of the energy efficiency measures leading to design optimization. A critical discussion about the assumptions on which the studies are based and the resulting gaps between the resulting cost-optimal performance and the zero energy target is provided together with a summary of the resulting cost-optimal set of technologies to be used for cost-optimal NZEB design in different contexts. It is shown that the cost-optimal approach results as an effective method for delineating the future of NZEB design throughout Europe while emerging criticalities and open research issues are presented.
Optimizing Energy Conversion: Magnetic Nano-materials
McIntyre, Dylan; Dann, Martin; Ilie, Carolina C.
2015-03-01
We present herein the work started at SUNY Oswego as a part of a SUNY 4E grant. The SUNY 4E Network of Excellence has awarded SUNY Oswego and collaborators a grant to carry out extensive studies on magnetic nanoparticles. The focus of the study is to develop cost effective rare-earth-free magnetic materials that will enhance energy transmission performance of various electrical devices (solar cells, electric cars, hard drives, etc.). The SUNY Oswego team has started the preliminary work for the project and graduate students from the rest of the SUNY 4E team (UB, Alfred College, Albany) will continue the project. The preliminary work concentrates on analyzing the properties of magnetic nanoparticle candidates, calculating molecular orbitals and band gap, and the fabrication of thin films. SUNY 4E Network of Excellence Grant.
Optimal energy management of HEVs with hybrid storage system
International Nuclear Information System (INIS)
Vinot, E.; Trigui, R.
2013-01-01
Highlights: • A battery and ultra-capacitor system for parallel hybrid vehicle is considered. • Optimal management using Pontryagin’s minimum principle is developed. • Battery stress limitation is taken into account by means of RMS current. • Rule based management approaching the optimal control is proposed. • Comparison between rule based and optimal management are proposed using Pareto front. - Abstract: Energy storage systems are a key point in the design and development of electric and hybrid vehicles. In order to reduce the battery size and its current stress, a hybrid storage system, where a battery is coupled with an electrical double-layer capacitor (EDLC) is considered in this paper. The energy management of such a configuration is not obvious and the optimal operation concerning the energy consumption and battery RMS current has to be identified. Most of the past work on the optimal energy management of HEVs only considered one additional power source. In this paper, the control of a hybrid vehicle with a hybrid storage system (HSS), where two additional power sources are used, is presented. Applying the Pontryagin’s minimum principle, an optimal energy management strategy is found and compared to a rule-based parameterized control strategy. Simulation results are shown and discussed. Applied on a small compact car, optimal and ruled-based methods show that gains of fuel consumption and/or a battery RMS current higher than 15% may be obtained. The paper also proves that a well tuned rule-based algorithm presents rather good performances when compared to the optimal strategy and remains relevant for different driving cycles. This rule-based algorithm may easily be implemented in a vehicle prototype or in an HIL test bench
Optimization under uncertainty of parallel nonlinear energy sinks
Boroson, Ethan; Missoum, Samy; Mattei, Pierre-Olivier; Vergez, Christophe
2017-04-01
Nonlinear Energy Sinks (NESs) are a promising technique for passively reducing the amplitude of vibrations. Through nonlinear stiffness properties, a NES is able to passively and irreversibly absorb energy. Unlike the traditional Tuned Mass Damper (TMD), NESs do not require a specific tuning and absorb energy over a wider range of frequencies. Nevertheless, they are still only efficient over a limited range of excitations. In order to mitigate this limitation and maximize the efficiency range, this work investigates the optimization of multiple NESs configured in parallel. It is well known that the efficiency of a NES is extremely sensitive to small perturbations in loading conditions or design parameters. In fact, the efficiency of a NES has been shown to be nearly discontinuous in the neighborhood of its activation threshold. For this reason, uncertainties must be taken into account in the design optimization of NESs. In addition, the discontinuities require a specific treatment during the optimization process. In this work, the objective of the optimization is to maximize the expected value of the efficiency of NESs in parallel. The optimization algorithm is able to tackle design variables with uncertainty (e.g., nonlinear stiffness coefficients) as well as aleatory variables such as the initial velocity of the main system. The optimal design of several parallel NES configurations for maximum mean efficiency is investigated. Specifically, NES nonlinear stiffness properties, considered random design variables, are optimized for cases with 1, 2, 3, 4, 5, and 10 NESs in parallel. The distributions of efficiency for the optimal parallel configurations are compared to distributions of efficiencies of non-optimized NESs. It is observed that the optimization enables a sharp increase in the mean value of efficiency while reducing the corresponding variance, thus leading to more robust NES designs.
Optimizing Power–Frequency Droop Characteristics of Distributed Energy Resources
Energy Technology Data Exchange (ETDEWEB)
Guggilam, Swaroop S.; Zhao, Changhong; Dall Anese, Emiliano; Chen, Yu Christine; Dhople, Sairaj V.
2018-05-01
This paper outlines a procedure to design power-frequency droop slopes for distributed energy resources (DERs) installed in distribution networks to optimally participate in primary frequency response. In particular, the droop slopes are engineered such that DERs respond in proportion to their power ratings and they are not unfairly penalized in power provisioning based on their location in the distribution network. The main contribution of our approach is that a guaranteed level of frequency regulation can be guaranteed at the feeder head, while ensuring that the outputs of individual DERs conform to some well-defined notion of fairness. The approach we adopt leverages an optimization-based perspective and suitable linearizations of the power-flow equations to embed notions of fairness and information regarding the physics of the power flows within the distribution network into the droop slopes. Time-domain simulations from a differential algebraic equation model of the 39-bus New England test-case system augmented with three instances of the IEEE 37-node distribution-network with frequency-sensitive DERs are provided to validate our approach.
International Nuclear Information System (INIS)
Wang, Jianxiao; Zhong, Haiwang; Tang, Wenyuan; Rajagopal, Ram; Xia, Qing; Kang, Chongqing; Wang, Yi
2017-01-01
Highlights: •Flexible ramping products are modelled in the framework of a microgrid. •Microgrids’ optimal bidding model is proposed in energy and ancillary service markets. •A hybrid stochastic and robust optimization approach is adopted. •The effectiveness of the proposed bidding model is verified based on real-world data. -- Abstract: Due to the volatile nature of wind and photovoltaic power, wind farms and solar stations are generally thought of as the consumers of ramping services. However, a microgrid (MG) is able to strategically integrate various distributed energy resources (DERs) to provide both energy and ancillary services (ASs) for the bulk power system. To evaluate the ramping capabilities of an MG in the joint energy and AS markets, an optimal bidding strategy is developed in this paper considering flexible ramping products (FRPs). By aggregating and coordinating various DERs, including wind turbines (WTs), photovoltaic systems (PVs), micro-turbines (MTs) and energy storage systems (ESSs), the MG is able to optimally allocate the capacities for energy, spinning reserve and ramping. Taking advantage of the synergy among DERs, the MG can maximize its revenues from different markets. Moreover, the flexibility of the MG for the bulk power system can be fully explored. To address the uncertainties introduced by renewable generation and market prices, a hybrid stochastic/robust optimization (RO) approach is adopted. Case studies based on a real-world MG with various DERs demonstrate the market behavior of the MG using the proposed bidding model.
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.
Velichkin, Vladimir A.; Zavyalov, Vladimir A.
2018-03-01
This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.
Integrating prediction, provenance, and optimization into high energy workflows
Energy Technology Data Exchange (ETDEWEB)
Schram, M.; Bansal, V.; Friese, R. D.; Tallent, N. R.; Yin, J.; Barker, K. J.; Stephan, E.; Halappanavar, M.; Kerbyson, D. J.
2017-10-01
We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.
Optimal foraging in marine ecosystem models: selectivity, profitability and switching
DEFF Research Database (Denmark)
Visser, Andre W.; Fiksen, Ø.
2013-01-01
ecological mechanics and evolutionary logic as a solution to diet selection in ecosystem models. When a predator can consume a range of prey items it has to choose which foraging mode to use, which prey to ignore and which ones to pursue, and animals are known to be particularly skilled in adapting...... to the preference functions commonly used in models today. Indeed, depending on prey class resolution, optimal foraging can yield feeding rates that are considerably different from the ‘switching functions’ often applied in marine ecosystem models. Dietary inclusion is dictated by two optimality choices: 1...... by letting predators maximize energy intake or more properly, some measure of fitness where predation risk and cost are also included. An optimal foraging or fitness maximizing approach will give marine ecosystem models a sound principle to determine trophic interactions...
Mathematical model of highways network optimization
Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.
2017-12-01
The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.
Fuzzy multiobjective models for optimal operation of a hydropower system
Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.
2013-06-01
Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.
International Nuclear Information System (INIS)
Cho, Jinkyun; Kim, Yundeok
2016-01-01
Highlights: • Energy-optimized data center’s cooling solutions were derived for four different climate zones. • We studied practical technologies of green data center that greatly improved energy efficiency. • We identified the relationship between mutually dependent factors in datacenter cooling systems. • We evaluated the effect of the dedicated cooling system applications. • Power Usage Effectiveness (PUE) was computed with energy simulation for data centers. - Abstract: Data centers are approximately 50 times more energy-intensive than general buildings. The rapidly increasing energy demand for data center operation has motivated efforts to better understand data center electricity use and to identify strategies that reduce the environmental impact. This research is presented analytical approach to the energy efficiency optimization of high density data center, in a synergy with relevant performance analysis of corresponding case study. This paper builds on data center energy modeling efforts by characterizing climate and cooling system differences among data centers and then evaluating their consequences for building energy use. Representative climate conditions for four regions are applied to data center energy models for several different prototypical cooling types. This includes cooling system, supplemental cooling solutions, design conditions and controlling the environment of ICT equipment were generally used for each climate zone, how these affect energy efficiency, and how the prioritization of system selection is derived. Based on the climate classification and the required operating environmental conditions for data centers suggested by the ASHRAE TC 9.9, a dedicated data center energy evaluation tool was taken to examine the potential energy savings of the cooling technology. Incorporating economizer use into the cooling systems would increase the variation in energy efficiency among geographic regions, indicating that as data centers
Statistical models for optimizing mineral exploration
International Nuclear Information System (INIS)
Wignall, T.K.; DeGeoffroy, J.
1987-01-01
The primary purpose of mineral exploration is to discover ore deposits. The emphasis of this volume is on the mathematical and computational aspects of optimizing mineral exploration. The seven chapters that make up the main body of the book are devoted to the description and application of various types of computerized geomathematical models. These chapters include: (1) the optimal selection of ore deposit types and regions of search, as well as prospecting selected areas, (2) designing airborne and ground field programs for the optimal coverage of prospecting areas, and (3) delineating and evaluating exploration targets within prospecting areas by means of statistical modeling. Many of these statistical programs are innovative and are designed to be useful for mineral exploration modeling. Examples of geomathematical models are applied to exploring for six main types of base and precious metal deposits, as well as other mineral resources (such as bauxite and uranium)
Dynamic optimization deterministic and stochastic models
Hinderer, Karl; Stieglitz, Michael
2016-01-01
This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Modeling and optimization of LCD optical performance
Yakovlev, Dmitry A; Kwok, Hoi-Sing
2015-01-01
The aim of this book is to present the theoretical foundations of modeling the optical characteristics of liquid crystal displays, critically reviewing modern modeling methods and examining areas of applicability. The modern matrix formalisms of optics of anisotropic stratified media, most convenient for solving problems of numerical modeling and optimization of LCD, will be considered in detail. The benefits of combined use of the matrix methods will be shown, which generally provides the best compromise between physical adequacy and accuracy with computational efficiency and optimization fac
Optimal synthesis and operation of advanced energy supply systems for standard and domotic home
International Nuclear Information System (INIS)
Buoro, Dario; Casisi, Melchiorre; Pinamonti, Piero; Reini, Mauro
2012-01-01
Highlights: ► Definition of an optimization model for a home energy supply system. ► Optimization of the energy supply system for standard and domotic home. ► Strong improvement can be achieved adopting the optimal system in standard and domotic home. ► The improvements are consistent if supply side and demand side strategies are applied together. ► Solutions with internal combustion engines are less sensible to market price of electricity and gas. - Abstract: The paper deals with the optimization of an advanced energy supply systems for two dwellings: a standard home and an advanced domotic home, where some demand side energy saving strategies have been implemented. In both cases the optimal synthesis, design and operation of the whole energy supply system have been obtained and a sensitivity analysis has been performed, by introducing different economic constraints. The optimization model is based on a Mixed Integer Linear Program (MILP) and includes different kinds of small-scale cogenerators, geothermal heat pumps, boilers, heat storages, solar thermal and photovoltaic panels. In addition, absorption machines, supplied with cogenerated heat, can be used instead of conventional electrical chiller to face the cooling demand. The aim of the analysis is to address the question if advanced demand strategies and supply strategies have to be regarded as alternatives, or if they have to be simultaneously applied, in order to obtain the maximum energy and economic benefit.
Optimal use of biomass for energy production
International Nuclear Information System (INIS)
Ruijgrok, W.; Cleijne, H.
2000-10-01
In addition to the EWAB programme, which is focused mainly on the application of waste and biomass for generating electricity, Novem is also working on behalf of the government on the development of a programme for gaseous and liquid energy carriers (GAVE). The Dutch ministries concerned have requested that Novem provide more insight concerning two aspects. The first aspect is the world-wide availability of biomass in the long term. A study group under the leadership of the University of Utrecht has elaborated this topic in greater detail in the GRAIN project. The second aspect is the question of whether the use of biomass for biofuels, as aimed at in the GAVE programme, can go hand in hand with the input for the electricity route. Novem has asked the Dutch research institute for the electric power industry (KEMA) to study the driving forces that determine the future use of biomass for electricity and biofuels, the competitive strength of each of the routes, and the possible future scenarios that emerge. The results of this report are presented in the form of copies of overhead sheets
Modelling and Optimizing Mathematics Learning in Children
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus
2013-01-01
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Optimization of a polygeneration system for energy demands of a livestock farm
Directory of Open Access Journals (Sweden)
Mančić Marko V.
2016-01-01
Full Text Available A polygeneration system is an energy system capable of providing multiple utility outputs to meet local demands by application of process integration. This paper addresses the problem of pinpointing the optimal polygeneration energy supply system for the local energy demands of a livestock farm in terms of optimal system configuration and optimal system capacity. The optimization problem is presented and solved for a case study of a pig farm in the paper. Energy demands of the farm, as well as the super-structure of the polygeneration system were modelled using TRNSYS software. Based on the locally available resources, the following polygeneration modules were chosen for the case study analysis: a biogas fired internal combustion engine co-generation module, a gas boiler, a chiller, a ground water source heat pump, solar thermal collectors, photovoltaic collectors, and heat and cold storage. Capacities of the polygeneration modules were used as optimization variables for the TRNSYS-GenOpt optimization, whereas net present value, system primary energy consumption, and CO2 emissions were used as goal functions for optimization. A hybrid system composed of biogas fired internal combustion engine based co-generation system, adsorption chiller solar thermal and photovoltaic collectors, and heat storage is found to be the best option. Optimal heating capacity of the biogas co-generation and adsorption units was found equal to the design loads, whereas the optimal surface of the solar thermal array is equal to the south office roof area, and the optimal surface of the PV array corresponds to the south facing animal housing building rooftop area. [Projekat Ministarstva nauke Republike Srbije, br. III 42006: Research and development of energy and environmentally highly effective polygeneration systems based on using renewable energy sources
Bio-Inspired Optimization of Sustainable Energy Systems: A Review
Directory of Open Access Journals (Sweden)
Yu-Jun Zheng
2013-01-01
Full Text Available Sustainable energy development always involves complex optimization problems of design, planning, and control, which are often computationally difficult for conventional optimization methods. Fortunately, the continuous advances in artificial intelligence have resulted in an increasing number of heuristic optimization methods for effectively handling those complicated problems. Particularly, algorithms that are inspired by the principles of natural biological evolution and/or collective behavior of social colonies have shown a promising performance and are becoming more and more popular nowadays. In this paper we summarize the recent advances in bio-inspired optimization methods, including artificial neural networks, evolutionary algorithms, swarm intelligence, and their hybridizations, which are applied to the field of sustainable energy development. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.
Automated Multivariate Optimization Tool for Energy Analysis: Preprint
Energy Technology Data Exchange (ETDEWEB)
Ellis, P. G.; Griffith, B. T.; Long, N.; Torcellini, P. A.; Crawley, D.
2006-07-01
Building energy simulations are often used for trial-and-error evaluation of ''what-if'' options in building design--a limited search for an optimal solution, or ''optimization''. Computerized searching has the potential to automate the input and output, evaluate many options, and perform enough simulations to account for the complex interactions among combinations of options. This paper describes ongoing efforts to develop such a tool. The optimization tool employs multiple modules, including a graphical user interface, a database, a preprocessor, the EnergyPlus simulation engine, an optimization engine, and a simulation run manager. Each module is described and the overall application architecture is summarized.
International Nuclear Information System (INIS)
Alavi, Seyed Arash; Ahmadian, Ali; Aliakbar-Golkar, Masoud
2015-01-01
Highlights: • Energy management is necessary in the active distribution network to reduce operation costs. • Uncertainty modeling is essential in energy management studies in active distribution networks. • Point estimate method is a suitable method for uncertainty modeling due to its lower computation time and acceptable accuracy. • In the absence of Probability Distribution Function (PDF) robust optimization has a good ability for uncertainty modeling. - Abstract: Uncertainty can be defined as the probability of difference between the forecasted value and the real value. As this probability is small, the operation cost of the power system will be less. This purpose necessitates modeling of system random variables (such as the output power of renewable resources and the load demand) with appropriate and practicable methods. In this paper, an adequate procedure is proposed in order to do an optimal energy management on a typical micro-grid with regard to the relevant uncertainties. The point estimate method is applied for modeling the wind power and solar power uncertainties, and robust optimization technique is utilized to model load demand uncertainty. Finally, a comparison is done between deterministic and probabilistic management in different scenarios and their results are analyzed and evaluated
Enhanced Multi-Objective Energy Optimization by a Signaling Method
Soares, João; Borges, Nuno; Vale, Zita; Oliveira, P.B.
2016-01-01
In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance of these methods with the use of multi-dimensi...
Italian energy scenarios: Markal model
International Nuclear Information System (INIS)
Gracceva, Francesco
2005-01-01
Energy scenarios carried out through formal models comply with scientific criteria such as internal coherence and transparency. Besides, Markal methodology allows a good understanding of the complex nature of the energy system. The business-as-usual scenario carried out through the Markal-Italy model shows that structural changes occurring in end-use sectors will continue to drive up energy consumption, in spite of the slow economic growth and the quite high energy prices [it
International Nuclear Information System (INIS)
Kim, Hyung Chul; Keoleian, Gregory A.; Horie, Yuhta A.
2006-01-01
Although the last decade witnessed dramatic progress in refrigerator efficiencies, inefficient, outdated refrigerators are still in operation, sometimes consuming more than twice as much electricity per year compared with modern, efficient models. Replacing old refrigerators before their designed lifetime could be a useful policy to conserve electric energy and greenhouse gas emissions. However, from a life cycle perspective, product replacement decisions also induce additional economic and environmental burdens associated with disposal of old models and production of new models. This paper discusses optimal lifetimes of mid-sized refrigerator models in the US, using a life cycle optimization model based on dynamic programming. Model runs were conducted to find optimal lifetimes that minimize energy, global warming potential (GWP), and cost objectives over a time horizon between 1985 and 2020. The baseline results show that depending on model years, optimal lifetimes range 2-7 years for the energy objective, and 2-11 years for the GWP objective. On the other hand, an 18-year of lifetime minimizes the economic cost incurred during the time horizon. Model runs with a time horizon between 2004 and 2020 show that current owners should replace refrigerators that consume more than 1000 kWh/year of electricity (typical mid-sized 1994 models and older) as an efficient strategy from both cost and energy perspectives
Multi-objective optimal dispatch of distributed energy resources
Longe, Ayomide
This thesis is composed of two papers which investigate the optimal dispatch for distributed energy resources. In the first paper, an economic dispatch problem for a community microgrid is studied. In this microgrid, each agent pursues an economic dispatch for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, a simple market structure is introduced as a framework for energy trades in a small community microgrid such as the Solar Village. It was found that both sellers and buyers benefited by participating in this market. In the second paper, Semidefinite Programming (SDP) for convex relaxation of power flow equations is used for optimal active and reactive dispatch for Distributed Energy Resources (DER). Various objective functions including voltage regulation, reduced transmission line power losses, and minimized reactive power charges for a microgrid are introduced. Combinations of these goals are attained by solving a multiobjective optimization for the proposed ORPD problem. Also, both centralized and distributed versions of this optimal dispatch are investigated. It was found that SDP made the optimal dispatch faster and distributed solution allowed for scalability.
Long-term optimal energy mix planning towards high energy security and low GHG emission
International Nuclear Information System (INIS)
Thangavelu, Sundar Raj; Khambadkone, Ashwin M.; Karimi, Iftekhar A.
2015-01-01
Highlights: • We develop long-term energy planning considering the future uncertain inputs. • We analyze the effect of uncertain inputs on the energy cost and energy security. • Conventional energy mix prone to cause high energy cost and energy security issues. • Stochastic and optimal energy mix show benefits over conventional energy planning. • Nuclear option consideration reduces the energy cost and carbon emissions. - Abstract: Conventional energy planning focused on energy cost, GHG emission and renewable contribution based on future energy demand, fuel price, etc. Uncertainty in the projected variables such as energy demand, volatile fuel price and evolution of renewable technologies will influence the cost of energy when projected over a period of 15–30 years. Inaccurate projected variables could affect energy security and lead to the risk of high energy cost, high emission and low energy security. The energy security is an ability of generation capacity to meet the future energy demand. In order to minimize the risks, a generic methodology is presented to determine an optimal energy mix for a period of around 15 years. The proposed optimal energy mix is a right combination of energy sources that minimize the risk caused due to future uncertainties related to the energy sources. The proposed methodology uses stochastic optimization to address future uncertainties over a planning horizon and minimize the variations in the desired performance criteria such as energy security and costs. The developed methodology is validated using a case study for a South East Asian region with diverse fuel sources consists of wind, solar, geothermal, coal, biomass and natural gas, etc. The derived optimal energy mix decision outperformed the conventional energy planning by remaining stable and feasible against 79% of future energy demand scenarios at the expense of 0–10% increase in the energy cost. Including the nuclear option in the energy mix resulted 26
Modeling, simulation and optimization of bipedal walking
Berns, Karsten
2013-01-01
The model-based investigation of motions of anthropomorphic systems is an important interdisciplinary research topic involving specialists from many fields such as Robotics, Biomechanics, Physiology, Orthopedics, Psychology, Neurosciences, Sports, Computer Graphics and Applied Mathematics. This book presents a study of basic locomotion forms such as walking and running is of particular interest due to the high demand on dynamic coordination, actuator efficiency and balance control. Mathematical models and numerical simulation and optimization techniques are explained, in combination with experimental data, which can help to better understand the basic underlying mechanisms of these motions and to improve them. Example topics treated in this book are Modeling techniques for anthropomorphic bipedal walking systems Optimized walking motions for different objective functions Identification of objective functions from measurements Simulation and optimization approaches for humanoid robots Biologically inspired con...
Cost-optimal levels for energy performance requirements
DEFF Research Database (Denmark)
Thomsen, Kirsten Engelund; Aggerholm, Søren; Kluttig-Erhorn, Heike
2011-01-01
The CA conducted a study on experiences and challenges for setting cost optimal levels for energy performance requirements. The results were used as input by the EU Commission in their work of establishing the Regulation on a comparative methodology framework for calculating cost optimal levels...... of minimum energy performance requirements. In addition to the summary report released in August 2011, the full detailed report on this study is now also made available, just as the EC is about to publish its proposed Regulation for MS to apply in their process to update national building requirements....
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
Techno-Economic Optimization of a Sustainable Energy System for a 100% Renewables Smart House
DEFF Research Database (Denmark)
Craciun, Vasile Simion; Blarke, Morten; Trifa, Viorel
2012-01-01
technical and economic challenges. One such challenge is the discontinuity, or intermittency, of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization strategies. This paper presents a model and optimization...... for a sustainable energy system for a 100% renewables based Smart House (SH). We have devised and analysed an innovative high-efficiency approach to residential energy supply. The analysis involves detailed technical specifications and considerations for providing optimal supply of electricity, heating, cooling......The continuous increasing negative effects of fossil fuel consumption on society and the environment, opens a major interest into environmentally friendly alternatives to sustain the increasing demand for energy services. Despite the obvious advantages of renewable energy, it presents important...
International Nuclear Information System (INIS)
Gao, Penghui; Dai, Yanjun; Tong, YenWah; Dong, Pengwei
2015-01-01
CCHP (combined cooling, heating and power) system as a poly-generation technology has received an increasing attention in field of small scale power systems for applications ranging from residence to utilities. It will also play an important role in waste to energy application for megacities. However, how to evaluate and manage energy utilization of CCHP scientifically remains unclear. In this paper, energy level and exergy analysis are implemented on energy conversion processes to reveal the variation of energy amount and quality in the operation of CCHP system. Moreover, based on the energy level analysis, the methodology of energy matching and optimization for the CCHP system is proposed. By this method, the operational parameters of CCHP system can be deduced to obtain an efficient performance and proper energy utilization. It will be beneficial to understand and operate the CCHP system, and to provide a guiding principle of the energy conversion and management for the CCHP system. - Highlights: • Energy level is implemented to reveal the energy variation of CCHP system. • A mathematical energy level analysis model of CCHP system is proposed. • By energy level analysis between supply and demand, optimal zone is obtained. • This study will be useful for energy matching and optimization of CCHP system
Low-carbon-oriented dynamic optimization of residential energy pricing in China
International Nuclear Information System (INIS)
He, Yongxiu; Liu, Yangyang; Wang, Jianhui; Xia, Tian; Zhao, Yushan
2014-01-01
In China, the energy pricing mechanism has an insufficient linkage with other energy prices. As a result of the unreasonable price level, it is impossible to exploit fully the substitution elasticity among energy resources and there is a negative impact on achieving energy conservation and energy efficiency. This paper proposes an optimized mechanism for residential energy prices in China, which maximizes the total social surplus subject to some related constraints. Three types of energy pricing mechanisms are designed based on China's low-carbon targets and the optimization of residential energy price policies through the dynamic CGE model. Compared with the energy price linkage method, the results show that the market netback value mechanism has a greater impact on the total social surplus. In order to achieve further low-carbon targets, the proportion of second and third tier residents can be expanded, while the energy prices could be deregulated to some degree. In addition, considering residential affordability, the government may take into account different electricity pricing mechanisms for different tiers of residents. Electricity pricing for the first tier, the second tier and the third tier should be based respectively on cost, the integration of energy price linkage and the market netback value mechanism. - Highlights: • Residential energy price mechanisms can be considered in the D-CGE model. • The maximization of total social surplus is the optimized objective. • The market netback value mechanism has a greater impact on the total social surplus. • Production cost and energy price conduction should be considered in price mechanisms. • Government should take the energy system as a whole to optimize energy prices
Models for efficient integration of solar energy
DEFF Research Database (Denmark)
Bacher, Peder
the available flexibility in the system. In the present thesis methods related to operation of solar energy systems and for optimal energy use in buildings are presented. Two approaches for forecasting of solar power based on numerical weather predictions (NWPs) are presented, they are applied to forecast......Efficient operation of energy systems with substantial amount of renewable energy production is becoming increasingly important. Renewables are dependent on the weather conditions and are therefore by nature volatile and uncontrollable, opposed to traditional energy production based on combustion....... The "smart grid" is a broad term for the technology for addressing the challenge of operating the grid with a large share of renewables. The "smart" part is formed by technologies, which models the properties of the systems and efficiently adapt the load to the volatile energy production, by using...
Optimization of thermal insulation to achieve energy savings in low energy house (refurbishment)
International Nuclear Information System (INIS)
Bojić, Milorad; Miletić, Marko; Bojić, Ljubiša
2014-01-01
Highlights: • For buildings that require heating, a thickness of their thermal insulation is optimized. • The objective was to improve energy efficiency of the building. • The optimization is performed by using EnergyPlus and Hooke–Jeeves method. • The embodied energy of thermal insulation and the entire life cycle of the house are taken into account. - Abstract: Due to the current environmental situation, saving energy and reducing CO 2 emission have become the leading drive in modern research. For buildings that require heating, one of the solutions is to optimize a thickness of their thermal insulation and thus improve energy efficiency and reduce energy needs. In this paper, for a small residential house in Serbia, an optimization in the thickness of its thermal insulation layer is investigated by using EnergyPlus software and Hooke–Jeeves direct search method. The embodied energy of thermal insulation is taken into account. The optimization is done for the entire life cycle of thermal insulation. The results show the optimal thickness of thermal insulation that yields the minimum primary energy consumption
International Nuclear Information System (INIS)
Voss, A.
1976-01-01
The development and application of energy models as helping factors in planning and decision making has gained more importance in all regions of energy economy and energy policy in recent times. This development not only covered models for the single branches and companies like, for example, for improving power plant systems, but also models showing the whole energy system. These models aim at analizing the possibilities of developing the energy supply with regard to aspects of the entire system, paying special attention to the integration of the energy system into economic and ecological side conditions. The following essay briefly explains the energy models developed for the Federal Republic of Germany after analizing the set of problems of energy and the demands on the energy planning methods arising from them. The energy model system developed by the programming team 'Systems research and technological development' of the nuclear research plant in Juelich is dealt with very intensively, explaining some model results as examples. Finally, the author gives his opinion on the problem of the integration and conversion of model studies in the process of decision making. (orig.) [de
Green smartphone GPUs: Optimizing energy consumption using GPUFreq scaling governors
Ahmad, Enas M.; Shihada, Basem
2015-01-01
and alternatives in controlling the power consumption and performance of their GPUs. We implemented and evaluated our model on a smartphone GPU and measured the energy performance using an external power monitor. The results show that the energy consumption
Energy - achieving an optimum through information. Energie - optimal durch Information
Energy Technology Data Exchange (ETDEWEB)
Gitt, W.
1986-01-01
What have computer programs in common with everyday human behaviour. Or the birds' passage, or photosynthesis, or the chemical reactions in a cell. They all primarily are information-controlled processes. The book under review deals with 'information' and 'energy', two main concepts in today's technological world. 'Energy' during the last few years has become a significant criterion with regard to technological progress. 'Information' is not only a main term in informatics terminology, but also a central concept for example in biology, linguistics, and communication science. The author shows that every 'information' is the result of an intellectual and purposeful process. The concept of information is taken as the red thread leading the author's journey through manifold strata of modern life, asking questions, finding answers, discussing problems. The wide spectrum of aspects discussed, including for instance a new approach to the Bible, and the remarkable examples presented by the author, make this book a treasure of knowledge, and of faith.
International Nuclear Information System (INIS)
Azadeh, A.; Amalnick, M.S.; Ghaderi, S.F.; Asadzadeh, S.M.
2007-01-01
This paper introduces an integrated approach based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT) for total energy efficiency assessment and optimization in energy intensive manufacturing sectors. Total energy efficiency assessment and optimization of the proposed approach considers structural indicators in addition conventional consumption and manufacturing sector output indicators. The validity of the DEA model is verified and validated by PCA and NT through Spearman correlation experiment. Moreover, the proposed approach uses the measure-specific super-efficiency DEA model for sensitivity analysis to determine the critical energy carriers. Four energy intensive manufacturing sectors are discussed in this paper: iron and steel, pulp and paper, petroleum refining and cement manufacturing sectors. To show superiority and applicability, the proposed approach has been applied to refinery sub-sectors of some OECD (Organization for Economic Cooperation and Development) countries. This study has several unique features which are: (1) a total approach which considers structural indicators in addition to conventional energy efficiency indicators; (2) a verification and validation mechanism for DEA by PCA and NT and (3) utilization of DEA for total energy efficiency assessment and consumption optimization of energy intensive manufacturing sectors
Optimal time points sampling in pathway modelling.
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.
Simplified ejector model for control and optimization
International Nuclear Information System (INIS)
Zhu Yinhai; Cai Wenjian; Wen Changyun; Li Yanzhong
2008-01-01
In this paper, a simple yet effective ejector model for a real time control and optimization of an ejector system is proposed. Firstly, a fundamental model for calculation of ejector entrainment ratio at critical working conditions is derived by one-dimensional analysis and the shock circle model. Then, based on thermodynamic principles and the lumped parameter method, the fundamental ejector model is simplified to result in a hybrid ejector model. The model is very simple, which only requires two or three parameters and measurement of two variables to determine the ejector performance. Furthermore, the procedures for on line identification of the model parameters using linear and non-linear least squares methods are also presented. Compared with existing ejector models, the solution of the proposed model is much easier without coupled equations and iterative computations. Finally, the effectiveness of the proposed model is validated by published experimental data. Results show that the model is accurate and robust and gives a better match to the real performances of ejectors over the entire operating range than the existing models. This model is expected to have wide applications in real time control and optimization of ejector systems
Optimal shaping and positioning of energy-efficient buildings
Directory of Open Access Journals (Sweden)
Barović Dušan D.
2017-01-01
Full Text Available Due to the number of variables and the complexity of objective functions, optimal design of an energy-efficient building is hard combinatorial problem of multi-objective optimisation. Therefore, it is necessary to describe structure and its position in surroundings precisely but by as few variables as possible. This paper presents methodology for finding adequate methodology for defining geometry and orientation of a given building, as well as its elements of importance for energy-efficiency analysis.
Environomic design of vehicle energy systems for optimal mobility service
Dimitrova, Zlatina Kirilova; Maréchal, François
2014-01-01
The main design criteria for the modern sustainable development of vehicle powertrains are the high energy efficiency of the conversion system, the competitive cost and the lowest possible environmental impacts. An innovative decision making methodology, using multi-objective optimization technics is currently under development. The idea is to obtain a population of possible design solutions corresponding to the most efficient energy system definition. These solutions meet technical, economic...
1st International Symposium on Energy System Optimization
Fichtner, Wolf; Heuveline, Vincent; Leibfried, Thomas
2017-01-01
The papers presented in this volume address diverse challenges in energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids and from theoretical considerations to data provision concerns and applied case studies. The International Symposium on Energy System Optimization (ISESO) was held on November 9th and 10th 2015 at the Heidelberg Institute for Theoretical Studies (HITS) and was organized by HITS, Heidelberg University and Karlsruhe Institute of Technology.
Optimal design of base isolation and energy dissipation system for nuclear power plant structures
International Nuclear Information System (INIS)
Zhou Fulin
1991-01-01
This paper suggests the method of optimal design of base isolation and energy dissipation system for earthquake resistant nuclear power plant structures. This method is based on dynamic analysis, shaking table tests for a 1/4 scale model, and a great number of low cycle fatigue failure tests for energy dissipating elements. A set of calculation formulas for optimal design of structures with base isolation and energy dissipation system were introduced, which are able to be used in engineering design for earthquake resistant nuclear power plant structures or other kinds of structures. (author)
Directory of Open Access Journals (Sweden)
Kangji Li
2017-02-01
Full Text Available Numerous conflicting criteria exist in building design optimization, such as energy consumption, greenhouse gas emission and indoor thermal performance. Different simulation-based optimization strategies and various optimization algorithms have been developed. A few of them are analyzed and compared in solving building design problems. This paper presents an efficient optimization framework to facilitate optimization designs with the aid of commercial simulation software and MATLAB. The performances of three optimization strategies, including the proposed approach, GenOpt method and artificial neural network (ANN method, are investigated using a case study of a simple building energy model. Results show that the proposed optimization framework has competitive performances compared with the GenOpt method. Further, in another practical case, four popular multi-objective algorithms, e.g., the non-dominated sorting genetic algorithm (NSGA-II, multi-objective particle swarm optimization (MOPSO, the multi-objective genetic algorithm (MOGA and multi-objective differential evolution (MODE, are realized using the propose optimization framework and compared with three criteria. Results indicate that MODE achieves close-to-optimal solutions with the best diversity and execution time. An uncompetitive result is achieved by the MOPSO in this case study.
International Nuclear Information System (INIS)
Tsvetkov, Pavel Valeryevich; Rodriguez, Salvador B.; Ames, David E. II; Rochau, Gary Eugene
2010-01-01
A new high-fidelity integrated system method and analysis approach was developed and implemented for consistent and comprehensive evaluations of advanced fuel cycles leading to minimized Transuranic (TRU) inventories. The method has been implemented in a developed code system integrating capabilities of Monte Carlo N - Particle Extended (MCNPX) for high-fidelity fuel cycle component simulations. In this report, a Nuclear Energy System (NES) configuration was developed to take advantage of used fuel recycling and transmutation capabilities in waste management scenarios leading to minimized TRU waste inventories, long-term activities, and radiotoxicities. The reactor systems and fuel cycle components that make up the NES were selected for their ability to perform in tandem to produce clean, safe, and dependable energy in an environmentally conscious manner. The diversity in performance and spectral characteristics were used to enhance TRU waste elimination while efficiently utilizing uranium resources and providing an abundant energy source. A computational modeling approach was developed for integrating the individual models of the NES. A general approach was utilized allowing for the Integrated System Model (ISM) to be modified in order to provide simulation for other systems with similar attributes. By utilizing this approach, the ISM is capable of performing system evaluations under many different design parameter options. Additionally, the predictive capabilities of the ISM and its computational time efficiency allow for system sensitivity/uncertainty analysis and the implementation of optimization techniques.
Energy Technology Data Exchange (ETDEWEB)
Tsvetkov, Pavel Valeryevich (Texas A& M University, College Station, TX); Rodriguez, Salvador B.; Ames, David E., II (Texas A& M University, College Station, TX); Rochau, Gary Eugene
2010-10-01
A new high-fidelity integrated system method and analysis approach was developed and implemented for consistent and comprehensive evaluations of advanced fuel cycles leading to minimized Transuranic (TRU) inventories. The method has been implemented in a developed code system integrating capabilities of Monte Carlo N - Particle Extended (MCNPX) for high-fidelity fuel cycle component simulations. In this report, a Nuclear Energy System (NES) configuration was developed to take advantage of used fuel recycling and transmutation capabilities in waste management scenarios leading to minimized TRU waste inventories, long-term activities, and radiotoxicities. The reactor systems and fuel cycle components that make up the NES were selected for their ability to perform in tandem to produce clean, safe, and dependable energy in an environmentally conscious manner. The diversity in performance and spectral characteristics were used to enhance TRU waste elimination while efficiently utilizing uranium resources and providing an abundant energy source. A computational modeling approach was developed for integrating the individual models of the NES. A general approach was utilized allowing for the Integrated System Model (ISM) to be modified in order to provide simulation for other systems with similar attributes. By utilizing this approach, the ISM is capable of performing system evaluations under many different design parameter options. Additionally, the predictive capabilities of the ISM and its computational time efficiency allow for system sensitivity/uncertainty analysis and the implementation of optimization techniques.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Optimal inventory management and order book modeling
Baradel, Nicolas
2018-02-16
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
To the Problem of Energy Security and Energy Objects Control Optimization
International Nuclear Information System (INIS)
Gotsiridze, A.; Abzianidze, D.
2004-01-01
One of the method of studying energy security of energy objects is evaluation of character and range of main safety risk influence with the help of indicator analysis. In the work is also reviewed an example of applying modern management theory to the group of tasks, connected with the optimal management of energy objects, which is the basis of their secure functioning. (authors)
Energy consumption optimization of a continuous ice cream process
International Nuclear Information System (INIS)
González-Ramírez, J.E.; Leducq, D.; Arellano, M.; Alvarez, G.
2013-01-01
Highlights: • This work investigates potential energy savings of an ice cream freezer. • From a full load compressor to a variable speed compressor one in freezer. • 30% less of energy consumption. • It is possible to save between 11 and 14 MWh per year by optimizing freezers. - Abstract: This work investigates potential energy saves in an ice cream freezer by using a variable speed compressor and optimization’s methodology for operating conditions during the process. Two configurations to control the refrigeration capacity were analyzed, the first one, modifies the pressure through the pilot control valve (conventional refrigeration system) and the second one with a variable speed compressor, both with a float expansion valve. Variable speed compressor configuration has showed the highest coefficient of performance and around of 30% less of energy consumption than the conventional one. The optimization of operating conditions in order to minimize the energy consumption is also presented. It was calculated only in France, for all ice cream and sorbet production, it is possible to save energy between 11 and 14 MWh per year by optimizing the operation of the refrigeration system through a variable speed compressor configuration
Economic optimization of waste treatment and energy production in Denmark
DEFF Research Database (Denmark)
Münster, Marie; Ravn, Hans; Hedegaard, Karsten
2013-01-01
This article presents an optimization model that incorporates LCA methodology and captures important characteristics of waste management systems. The most attractive waste management options are in the model identified as part the optimization. The model renders it possible to apply different...... optimization objectives such as minimizing costs or greenhouse gas emissions or to prioritise several objectives given different weights. An illustrative case is analyzed, covering alternative treatments of 1 tonne residual household waste: incineration of the full amount or sorting out organic waste...... for biogas production for either CHP generation or as fuel in vehicles. The case study illustrates, that what is the optimal solution depends on the objective and assumptions regarding the background system – here illustrated with different assumptions regarding displaced electricity production. The article...
Life Cycle Cost optimization of a BOLIG+ Zero Energy Building
Energy Technology Data Exchange (ETDEWEB)
Marszal, A.J.
2011-12-15
Buildings consume approximately 40% of the world's primary energy use. Considering the total energy consumption throughout the whole life cycle of a building, the energy performance and supply is an important issue in the context of climate change, scarcity of energy resources and reduction of global energy consumption. An energy consuming as well as producing building, labelled as the Zero Energy Building (ZEB) concept, is seen as one of the solutions that could change the picture of energy consumption in the building sector, and thus contribute to the reduction of the global energy use. However, before being fully implemented in the national building codes and international standards, the ZEB concept requires a clear understanding and a uniform definition. The ZEB concept is an energy-conservation solution, whose successful adaptation in real life depends significantly on private building owners' approach to it. For this particular target group, the cost is often an obstacle when investing money in environmental or climate friendly products. Therefore, this PhD project took the perspective of a future private ZEB owner to investigate the cost-optimal Net ZEB definition applicable in the Danish context. The review of the various ZEB approaches indicated a general concept of a Zero Energy Building as a building with significantly reduced energy demand that is balanced by an equivalent energy generation from renewable sources. And, with this as a general framework, each ZEB definition should further specify: (1) the connection or the lack of it to the energy infrastructure, (2) the unit of the balance, (3) the period of the balance, (4) the types of energy use included in the balance, (5) the minimum energy performance requirements (6) the renewable energy supply options, and if applicable (7) the requirements of the building-grid interaction. Moreover, the study revealed that the future ZEB definitions applied in Denmark should mostly be focused on grid
International Nuclear Information System (INIS)
Serre, S.
2010-01-01
This research thesis first describes the problematic of the effects of natural radiation on micro- and nano-electronic components, and the atmospheric-radiative stress of atmospheric neutrons from cosmic origin: issue of 'Single event upsets', present knowledge of the atmospheric radiative environment induced by cosmic rays. The author then presents the neutron-based detection and spectrometry by using the Bonner sphere technique: principle of moderating spheres, definition and mathematical formulation of neutron spectrometry using Bonner spheres, active sensors of thermal neutrons, response of a system to conventional Bonner spheres, extension to the range of high energies. Then, he reports the development of a Bonner sphere system extended to the high-energy range for the spectrometry of atmospheric neutrons: definition of a conventional system, Monte Carlo calculation of response functions, development of the response matrix, representation and semi-empirical verification of fluence response, uncertainty analysis, extension to high energies, and measurement tests of the spectrometer. He reports the use of a Monte Carlo simulation to characterize the spectrometer response in the high-energy range
An integrated optimization approach for a hybrid energy system in electric vehicles
International Nuclear Information System (INIS)
Hung, Yi-Hsuan; Wu, Chien-Hsun
2012-01-01
Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.
Optimization study on inductive-resistive circuit for broadband piezoelectric energy harvesters
Directory of Open Access Journals (Sweden)
Ting Tan
2017-03-01
Full Text Available The performance of cantilever-beam piezoelectric energy harvester is usually analyzed with pure resistive circuit. The optimal performance of such a vibration-based energy harvesting system is limited by narrow bandwidth around its modified natural frequency. For broadband piezoelectric energy harvesting, series and parallel inductive-resistive circuits are introduced. The electromechanical coupled distributed parameter models for such systems under harmonic base excitations are decoupled with modified natural frequency and electrical damping to consider the coupling effect. Analytical solutions of the harvested power and tip displacement for the electromechanical decoupled model are confirmed with numerical solutions for the coupled model. The optimal performance of piezoelectric energy harvesting with inductive-resistive circuits is revealed theoretically as constant maximal power at any excitation frequency. This is achieved by the scenarios of matching the modified natural frequency with the excitation frequency and equating the electrical damping to the mechanical damping. The inductance and load resistance should be simultaneously tuned to their optimal values, which may not be applicable for very high electromechanical coupling systems when the excitation frequency is higher than their natural frequencies. With identical optimal performance, the series inductive-resistive circuit is recommended for relatively small load resistance, while the parallel inductive-resistive circuit is suggested for relatively large load resistance. This study provides a simplified optimization method for broadband piezoelectric energy harvesters with inductive-resistive circuits.
Optimization study on inductive-resistive circuit for broadband piezoelectric energy harvesters
Tan, Ting; Yan, Zhimiao
2017-03-01
The performance of cantilever-beam piezoelectric energy harvester is usually analyzed with pure resistive circuit. The optimal performance of such a vibration-based energy harvesting system is limited by narrow bandwidth around its modified natural frequency. For broadband piezoelectric energy harvesting, series and parallel inductive-resistive circuits are introduced. The electromechanical coupled distributed parameter models for such systems under harmonic base excitations are decoupled with modified natural frequency and electrical damping to consider the coupling effect. Analytical solutions of the harvested power and tip displacement for the electromechanical decoupled model are confirmed with numerical solutions for the coupled model. The optimal performance of piezoelectric energy harvesting with inductive-resistive circuits is revealed theoretically as constant maximal power at any excitation frequency. This is achieved by the scenarios of matching the modified natural frequency with the excitation frequency and equating the electrical damping to the mechanical damping. The inductance and load resistance should be simultaneously tuned to their optimal values, which may not be applicable for very high electromechanical coupling systems when the excitation frequency is higher than their natural frequencies. With identical optimal performance, the series inductive-resistive circuit is recommended for relatively small load resistance, while the parallel inductive-resistive circuit is suggested for relatively large load resistance. This study provides a simplified optimization method for broadband piezoelectric energy harvesters with inductive-resistive circuits.
Stabilized quasi-Newton optimization of noisy potential energy surfaces
International Nuclear Information System (INIS)
Schaefer, Bastian; Goedecker, Stefan; Alireza Ghasemi, S.; Roy, Shantanu
2015-01-01
Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. To automatize these tasks, optimization algorithms must not only be efficient but also very reliable. Unfortunately, computational noise in forces and energies is inherent to electronic structure codes. This computational noise poses a severe problem to the stability of efficient optimization methods like the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. We here present a technique that allows obtaining significant curvature information of noisy potential energy surfaces. We use this technique to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. We demonstrate with the help of benchmarks that both the minimizer and the saddle finding approach are superior to comparable existing methods
Stabilized quasi-Newton optimization of noisy potential energy surfaces
Energy Technology Data Exchange (ETDEWEB)
Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch [Department of Physics, University of Basel, Klingelbergstrasse 82, CH-4056 Basel (Switzerland); Alireza Ghasemi, S. [Institute for Advanced Studies in Basic Sciences, P.O. Box 45195-1159, IR-Zanjan (Iran, Islamic Republic of); Roy, Shantanu [Computational and Systems Biology, Biozentrum, University of Basel, CH-4056 Basel (Switzerland)
2015-01-21
Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. To automatize these tasks, optimization algorithms must not only be efficient but also very reliable. Unfortunately, computational noise in forces and energies is inherent to electronic structure codes. This computational noise poses a severe problem to the stability of efficient optimization methods like the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. We here present a technique that allows obtaining significant curvature information of noisy potential energy surfaces. We use this technique to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. We demonstrate with the help of benchmarks that both the minimizer and the saddle finding approach are superior to comparable existing methods.
Energy and ancillary service dispatch through dynamic optimal power flow
International Nuclear Information System (INIS)
Costa, A.L.; Costa, A. Simoes
2007-01-01
This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system. (author)
Energy Optimization in Dyehouse | Jeetah | University of Mauritius ...
African Journals Online (AJOL)
... that the initial investment on the paint, whose shell life is 2 years, would be recuperated by the 11th month. The positive net present value (2411 MUR) and high internal rate of return (80%) obtained suggested that the project should go ahead. Keywords: Insulation paint, steam consumption, energy optimization, dyehouse ...
Exploiting variability for energy optimization of parallel programs
Energy Technology Data Exchange (ETDEWEB)
Lavrijsen, Wim [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Iancu, Costin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); de Jong, Wibe [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Xin [Georgia Inst. of Technology, Atlanta, GA (United States); Schwan, Karsten [Georgia Inst. of Technology, Atlanta, GA (United States)
2016-04-18
Here in this paper we present optimizations that use DVFS mechanisms to reduce the total energy usage in scientific applications. Our main insight is that noise is intrinsic to large scale parallel executions and it appears whenever shared resources are contended. The presence of noise allows us to identify and manipulate any program regions amenable to DVFS. When compared to previous energy optimizations that make per core decisions using predictions of the running time, our scheme uses a qualitative approach to recognize the signature of executions amenable to DVFS. By recognizing the "shape of variability" we can optimize codes with highly dynamic behavior, which pose challenges to all existing DVFS techniques. We validate our approach using offline and online analyses for one-sided and two-sided communication paradigms. We have applied our methods to NWChem, and we show best case improvements in energy use of 12% at no loss in performance when using online optimizations running on 720 Haswell cores with one-sided communication. With NWChem on MPI two-sided and offline analysis, capturing the initialization, we find energy savings of up to 20%, with less than 1% performance cost.
Optimal energy management strategy for battery powered electric vehicles
International Nuclear Information System (INIS)
Xi, Jiaqi; Li, Mian; Xu, Min
2014-01-01
Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios
Optimized design of total energy systems: The RETE project
Alia, P.; Dallavalle, F.; Denard, C.; Sanson, F.; Veneziani, S.; Spagni, G.
1980-05-01
The RETE (Reggio Emilia Total Energy) project is discussed. The total energy system (TES) was developed to achieve the maximum quality matching on the thermal energy side between plant and user and perform an open scheme on the electrical energy side by connection with the Italian electrical network. The most significant qualitative considerations at the basis of the plant economic energy optimization and the selection of the operating criterion most fitting the user consumption characteristics and the external system constraints are reported. The design methodology described results in a TES that: in energy terms achieves a total efficiency evaluated on a yearly basis to be equal to about 78 percent and a fuel saving of about 28 percent and in economic terms allows a recovery of the investment required as to conventional solutions, in about seven years.
Computing energy-optimal trajectories for an autonomous underwater vehicle using direct shooting
Directory of Open Access Journals (Sweden)
Inge Spangelo
1992-07-01
Full Text Available Energy-optimal trajectories for an autonomous underwater vehicle can be computed using a numerical solution of the optimal control problem. The vehicle is modeled with the six dimensional nonlinear and coupled equations of motion, controlled with DC-motors in all degrees of freedom. The actuators are modeled and controlled with velocity loops. The dissipated energy is expressed in terms of the control variables as a nonquadratic function. Direct shooting methods, including control vector parameterization (CVP arc used in this study. Numerical calculations are performed and good results are achieved.
Applied probability models with optimization applications
Ross, Sheldon M
1992-01-01
Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.
An Improved Genetic Algorithm for Optimal Stationary Energy Storage System Locating and Sizing
Directory of Open Access Journals (Sweden)
Bin Wang
2014-10-01
Full Text Available The application of a stationary ultra-capacitor energy storage system (ESS in urban rail transit allows for the recuperation of vehicle braking energy for increasing energy savings as well as for a better vehicle voltage profile. This paper aims to obtain the best energy savings and voltage profile by optimizing the location and size of ultra-capacitors. This paper firstly raises the optimization objective functions from the perspectives of energy savings, regenerative braking cancellation and installation cost, respectively. Then, proper mathematical models of the DC (direct current traction power supply system are established to simulate the electrical load-flow of the traction supply network, and the optimization objections are evaluated in the example of a Chinese metro line. Ultimately, a methodology for optimal ultra-capacitor energy storage system locating and sizing is put forward based on the improved genetic algorithm. The optimized result shows that certain preferable and compromised schemes of ESSs’ location and size can be obtained, acting as a compromise between satisfying better energy savings, voltage profile and lower installation cost.
Model averaging, optimal inference and habit formation
Directory of Open Access Journals (Sweden)
Thomas H B FitzGerald
2014-06-01
Full Text Available Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function – the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an additional challenge – that of determining which model or models of their environment are the best for guiding behaviour. Bayesian model averaging – which says that an agent should weight the predictions of different models according to their evidence – provides a principled way to solve this problem. Importantly, because model evidence is determined by both the accuracy and complexity of the model, optimal inference requires that these be traded off against one another. This means an agent’s behaviour should show an equivalent balance. We hypothesise that Bayesian model averaging plays an important role in cognition, given that it is both optimal and realisable within a plausible neuronal architecture. We outline model averaging and how it might be implemented, and then explore a number of implications for brain and behaviour. In particular, we propose that model averaging can explain a number of apparently suboptimal phenomena within the framework of approximate (bounded Bayesian inference, focussing particularly upon the relationship between goal-directed and habitual behaviour.
Procedural Optimization Models for Multiobjective Flexible JSSP
Directory of Open Access Journals (Sweden)
Elena Simona NICOARA
2013-01-01
Full Text Available The most challenging issues related to manufacturing efficiency occur if the jobs to be sched-uled are structurally different, if these jobs allow flexible routings on the equipments and mul-tiple objectives are required. This framework, called Multi-objective Flexible Job Shop Scheduling Problems (MOFJSSP, applicable to many real processes, has been less reported in the literature than the JSSP framework, which has been extensively formalized, modeled and analyzed from many perspectives. The MOFJSSP lie, as many other NP-hard problems, in a tedious place where the vast optimization theory meets the real world context. The paper brings to discussion the most optimization models suited to MOFJSSP and analyzes in detail the genetic algorithms and agent-based models as the most appropriate procedural models.
Computer models for optimizing radiation therapy
International Nuclear Information System (INIS)
Duechting, W.
1998-01-01
The aim of this contribution is to outline how methods of system analysis, control therapy and modelling can be applied to simulate normal and malignant cell growth and to optimize cancer treatment as for instance radiation therapy. Based on biological observations and cell kinetic data, several types of models have been developed describing the growth of tumor spheroids and the cell renewal of normal tissue. The irradiation model is represented by the so-called linear-quadratic model describing the survival fraction as a function of the dose. Based thereon, numerous simulation runs for different treatment schemes can be performed. Thus, it is possible to study the radiation effect on tumor and normal tissue separately. Finally, this method enables a computer-assisted recommendation for an optimal patient-specific treatment schedule prior to clinical therapy. (orig.) [de
Energy Technology Data Exchange (ETDEWEB)
Farenc, D.
1997-12-16
Technologies for Smart Power Integrated Circuits combine into a single chip Bipolar and CMOS transistors, plus power with lateral or vertical DMOS transistors. Complexity which has been increasing dramatically since the mid-80`s has allowed to integrate, into a single monolithic solution, entire systems. This thesis deals with the modelling, conception and test of the power integrated LDMOS transistor. The power LDMOS transistor is used as a switching device. It is characterized by two parameters which are the Specific On-resistance R{sub sp} and the breakdown voltage BV{sub DSS}. The LDMOS transistor developed for the new Smart Power technology exhibits a Specific On-resistance of 200 m{Omega}{sup *}mm{sup 2} and a breakdown voltage of 60 V. This device is dedicated to automotive applications. A reduction of the power device which is achieved with a low Specific On-resistance puts forward new issues such as the maximum Energy capability. When the power device is switched-off on an inductive load, a certain amount of energy is dissipated; if it is beyond a certain limit, the device is destroyed. Our goal is to determine the energy limits which are associated with our new Power integrated LDMOS transistor. (author) 28 refs.
New Energy Utility Business Models
International Nuclear Information System (INIS)
Potocnik, V.
2016-01-01
Recently a lot of big changes happened in the power sector: energy efficiency and renewable energy sources are quickly progressing, distributed or decentralised generation of electricity is expanding, climate change requires reduction of greenhouse gas emissions and price volatility and incertitude of fossil fuel supply is common. Those changes have led to obsolescence of vertically integrated business models which have dominated in energy utility organisations for a hundred years and new business models are being introduced. Those models take into account current changes in the power sector and enable a wider application of energy efficiency and renewable energy sources, especially for consumers, with the decentralisation of electricity generation and complying with the requirements of climate and environment preservation. New business models also solve the questions of financial compensations for utilities because of the reduction of centralised energy generation while contributing to local development and employment.(author).
Energy-Performance as a driver for optimal production planning
International Nuclear Information System (INIS)
Salahi, Niloofar; Jafari, Mohsen A.
2016-01-01
Highlights: • A 2-dimensional Energy-Performance measure is proposed for energy aware production. • This is a novel approach integrates energy efficiency with production requirements. • This approach simultaneously incorporates machine and process related specifications. • The problem is solved as stochastic MILP with constraints addressing risk averseness. • The optimization is illustrated for 2 cases of single and serial machining operation. • Impact of various electricity pricing schemes on proposed production plan is analyzed. - Abstract: In this paper, we present energy-aware production planning using a two-dimensional “Energy-Performance” measure. With this measure, the production plan explicitly takes into account machine-level requirements, process control strategies, product types and demand patterns. The “Energy-Performance” measure is developed based on an existing concept, namely, “Specific Energy” at machine level. It is further expanded to an “Energy-Performance” profile for a production line. A production planning problem is formulated as a stochastic MILP with risk-averse constraints to account for manufacturer’s risk averseness. The objective is to attain an optimal production plan that minimizes the total loss distribution subject to system throughput targets, probabilistic risk constraints and constraints imposed by the underlying “Energy-Performance” pattern. Electricity price and demand per unit time are assumed to be stochastic. Conditional Value at Risk (CVaR) of loss distributions is used as the manufacturer’s risk measure. Both single-machine and production lines are studied for different profiles and electricity pricing schemes. It is shown that the shape of “Energy-Performance” profile can change optimal plans.
Optimal policy of energy innovation in developing countries: Development of solar PV in Iran
International Nuclear Information System (INIS)
Shafiei, Ehsan; Saboohi, Yadollah; Ghofrani, Mohammad B.
2009-01-01
The purpose of this study is to apply managerial economics and methods of decision analysis to study the optimal pattern of innovation activities for development of new energy technologies in developing countries. For this purpose, a model of energy research and development (R and D) planning is developed and it is then linked to a bottom-up energy-systems model. The set of interlinked models provide a comprehensive analytical tool for assessment of energy technologies and innovation planning taking into account the specific conditions of developing countries. An energy-system model is used as a tool for the assessment and prioritization of new energy technologies. Based on the results of the technology assessment model, the optimal R and D resources allocation for new energy technologies is estimated with the help of the R and D planning model. The R and D planning model is based on maximization of the total net present value of resulting R and D benefits taking into account the dynamics of technological progress, knowledge and experience spillovers from advanced economies, technology adoption and R and D constraints. Application of the set of interlinked models is explained through the analysis of the development of solar PV in Iranian electricity supply system and then some important policy insights are concluded
Optimal Electrical Energy Slewing for Reaction Wheel Spacecraft
Marsh, Harleigh Christian
The results contained in this dissertation contribute to a deeper level of understanding to the energy required to slew a spacecraft using reaction wheels. This work addresses the fundamental manner in which spacecrafts are slewed (eigenaxis maneuvering), and demonstrates that this conventional maneuver can be dramatically improved upon in regards to reduction of energy, dissipative losses, as well as peak power. Energy is a fundamental resource that effects every asset, system, and subsystem upon a spacecraft, from the attitude control system which orients the spacecraft, to the communication subsystem to link with ground stations, to the payloads which collect scientific data. For a reaction wheel spacecraft, the attitude control system is a particularly heavy load on the power and energy resources on a spacecraft. The central focus of this dissertation is reducing the burden which the attitude control system places upon the spacecraft in regards to electrical energy, which is shown in this dissertation to be a challenging problem to computationally solve and analyze. Reducing power and energy demands can have a multitude of benefits, spanning from the initial design phase, to in-flight operations, to potentially extending the mission life of the spacecraft. This goal is approached from a practical standpoint apropos to an industry-flight setting. Metrics to measure electrical energy and power are developed which are in-line with the cost associated to operating reaction wheel based attitude control systems. These metrics are incorporated into multiple families of practical high-dimensional constrained nonlinear optimal control problems to reduce the electrical energy, as well as the instantaneous power burdens imposed by the attitude control system upon the spacecraft. Minimizing electrical energy is shown to be a problem in L1 optimal control which is nonsmooth in regards to state variables as well as the control. To overcome the challenge of nonsmoothness, a
An optimization model for metabolic pathways.
Planes, F J; Beasley, J E
2009-10-15
Different mathematical methods have emerged in the post-genomic era to determine metabolic pathways. These methods can be divided into stoichiometric methods and path finding methods. In this paper we detail a novel optimization model, based upon integer linear programming, to determine metabolic pathways. Our model links reaction stoichiometry with path finding in a single approach. We test the ability of our model to determine 40 annotated Escherichia coli metabolic pathways. We show that our model is able to determine 36 of these 40 pathways in a computationally effective manner.
Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy
Directory of Open Access Journals (Sweden)
Shunfu Jin
2016-01-01
Full Text Available The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy. In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs and then propose an appropriate pricing policy for secondary user (SU packets. We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline. With the help of a Quasi-Birth-Death (QBD process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS via the Matrix-Geometric Solution method. We assess the average latency of SU packets and the energy saving ratio of system. According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO method to search the socially optimal arrival rate of SU packets. By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets. Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
International Nuclear Information System (INIS)
Cheung, Brian C.; Carriveau, Rupp; Ting, David S.K.
2014-01-01
This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates. - Highlights: • UWCAES system configurations were developed using multi-objective optimization. • System was optimized for energy efficiency, exergy, and exergoeconomics • Pareto-optimal solution surfaces were developed at different interest rates. • Similar preferred system configurations were found at all interest rates studied
Optimization for energy consumption in drying section of fluting paper machine
Directory of Open Access Journals (Sweden)
Ghodbanan Shaaban
2017-01-01
Full Text Available Non-linear programming optimization method was used to optimize total steam and air consumption in the dryer section of multi-cylinder fluting paper machine. Equality constraints of the optimization model were obtained from specified process blocks considering mass and energy balance relationships in drying and heat recovery sections. Inequality constraints correspond to process parameters such as production capacity, operating conditions, and other limitations. Using the simulation, the process parameters can be optimized to improve the energy efficiency and heat recovery performance. For a corrugating machine, optimized parameters show the total steam use can be reduced by about 11% due to improvement of the heat recovery performance and optimization of the operating conditions such as inlet web dryness, evaporation rate, and exhaust air humidity, accordingly total steam consumption can be decreased from about 1.71 to 1.53 tonnes steam per tonne paper production. The humidity of the exhaust air should be kept as high as possible to optimize the energy performance and avoid condensation in the pocket dryers and hood exhaust air. So the simulation shows the supply air should be increased by about 10% to achieve optimal humidity level which was determined about 0.152 kgH2O/(kg dry air.
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik
2008-01-01
is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....
Optimization model for rotor blades of horizontal axis wind turbines
Institute of Scientific and Technical Information of China (English)
LIU Xiong; CHEN Yan; YE Zhiquan
2007-01-01
This paper presents an optimization model for rotor blades of horizontal axis wind turbines. The model refers to the wind speed distribution function on the specific wind site, with an objective to satisfy the maximum annual energy output. To speed up the search process and guarantee a global optimal result, the extended compact genetic algorithm (ECGA) is used to carry out the search process.Compared with the simple genetic algorithm, ECGA runs much faster and can get more accurate results with a much smaller population size and fewer function evaluations. Using the developed optimization program, blades of a 1.3 MW stall-regulated wind turbine are designed. Compared with the existing blades, the designed blades have obviously better aerodynamic performance.
Modeling of biological intelligence for SCM system optimization.
Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang
2012-01-01
This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and