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.

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

International Nuclear Information System (INIS)

Jing, Z.X.; Jiang, X.S.; Wu, Q.H.; Tang, W.H.; Hua, B.

2014-01-01

This paper presents a comprehensive model of a small-scale integrated energy based district heating and cooling (DHC) system located in a residential area of hot-summer and cold-winter zone, which makes joint use of wind energy, solar energy, natural gas and electric energy. The model includes an off-grid wind turbine generator, heat producers, chillers, a water supply network and terminal loads. This research also investigates an optimal operating strategy based on Group Search Optimizer (GSO), through which the daily running cost of the system is optimized in both the heating and cooling modes. The strategy can be used to find the optimal number of operating chillers, optimal outlet water temperature set points of boilers and optimal water flow set points of pumps, taking into account cost functions and various operating constraints. In order to verify the model and the optimal operating strategy, performance tests have been undertaken using MATLAB. The simulation results prove the validity of the model and show that the strategy is able to minimize the system operation cost. The proposed system is evaluated in comparison with a conventional separation production (SP) system. The feasibility of investment for the DHC system is also discussed. The comparative results demonstrate the investment feasibility, the significant energy saving and the cost reduction, achieved in daily operation in an environment, where there are varying heating loads, cooling loads, wind speeds, solar radiations and electricity prices. - Highlights: • A model of a small-scale integrated energy based DHC system is presented. • An off-grid wind generator used for water heating is embedded in the model. • An optimal control strategy is studied to optimize the running cost of the system. • The designed system is proved to be energy efficient and cost effective in operation

An approach to modeling and optimization of integrated renewable energy system (ires)

Science.gov (United States)

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

Energy-saving management modelling and optimization for lead-acid battery formation process

Science.gov (United States)

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.

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

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

Science.gov (United States)

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

Life cycle optimization model for integrated cogeneration and energy systems applications in buildings

Science.gov (United States)

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

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)

Analytic model for ultrasound energy receivers and their optimal electric loads

Science.gov (United States)

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.

Optimal urban water conservation strategies considering embedded energy: coupling end-use and utility water-energy models.

Science.gov (United States)

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

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

Modeling of District Heating Networks for the Purpose of Operational Optimization with Thermal Energy Storage

Science.gov (United States)

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.

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

Science.gov (United States)

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.

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China: A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

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.

An integrated framework of agent-based modelling and robust optimization for microgrid energy management

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

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

Science.gov (United States)

Zheng, Zhan; Zhang, Yongjun

2017-08-01

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

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

Directory of Open Access Journals (Sweden)

Thanh Tung Ha

2018-03-01

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

A stochastic multi-agent optimization model for energy infrastructure planning under uncertainty and competition.

Science.gov (United States)

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...

Decision support model for establishing the optimal energy retrofit strategy for existing multi-family housing complexes

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

Quad-rotor flight path energy optimization

Science.gov (United States)

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.

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.

Integration of distributed energy resources into low voltage grid: A market-based multiperiod optimization model

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)

Energy savings by optimization of drying processes through use of models and effective control; Energibesparelser ved optimering af toerreprocesser gennem anvendelse af modeller og effektiv regulering

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)

Modeling of optimal energy flows for systems with close integration of sea water desalination and renewable energy sources: Case study for Jordan

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.

Energy-optimal electrical excitation of nerve fibers.

Science.gov (United States)

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.

An optimal renewable energy mix for Indonesia

Science.gov (United States)

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

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.

Assessing and optimizing the economic and environmental impacts of cogeneration/district energy systems using an energy equilibrium model

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.)

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.

Model Based Optimization of Integrated Low Voltage DC-DC Converter for Energy Harvesting Applications

Science.gov (United States)

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 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.

Multistage Stochastic Programming and its Applications in Energy Systems Modeling and Optimization

Science.gov (United States)

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

Electromagnetic Vibration Energy Harvesting Devices Architectures, Design, Modeling and Optimization

CERN Document Server

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...

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.

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.

Modeling and optimization of a network of energy hubs to improve economic and emission considerations

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.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

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.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

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.

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....

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.

Global optimization of proteins using a dynamical lattice model: Ground states and energy landscapes

OpenAIRE

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.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

Science.gov (United States)

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.

Pareto optimality in organelle energy metabolism analysis.

Science.gov (United States)

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.

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...

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)

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.

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

Science.gov (United States)

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.

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...

Impacts of government subsidies on pricing and performance level choice in Energy Performance Contracting: A two-step optimal decision model

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.

Optimal energy-utilization ratio for long-distance cruising of a model fish

Science.gov (United States)

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.

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 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.

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.

A material optimization model to approximate energy bounds for cellular materials under multiload conditions

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...

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...

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)

Air source heat pump water heater: Dynamic modeling, optimal energy management and mini-tubes condensers

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

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

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

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.

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

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 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.

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.

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

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.

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

Science.gov (United States)

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.

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

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'.

Modeling and optimization of energy storage system for microgrid

Science.gov (United States)

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.

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.

Software for industrial consumers electrical energy tariff optimal selection

OpenAIRE

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.

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.

Observation on optimal transition from conventional energy with resource constraints to advanced energy with virtually unlimited resource

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)

A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance

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.

Optimization of joint energy micro-grid with cold storage

Science.gov (United States)

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.

Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

OpenAIRE

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 ...

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

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.

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).

Active surface model improvement by energy function optimization for 3D segmentation.

Science.gov (United States)

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.

Optimal control, investment and utilization schemes for energy storage under uncertainty

Science.gov (United States)

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

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 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.

Design optimization model for the integration of renewable and nuclear energy in the United Arab Emirates’ power system

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

Stochastic optimal charging of electric-drive vehicles with renewable energy

International Nuclear Information System (INIS)

Pantoš, Miloš

2011-01-01

The paper presents the stochastic optimization algorithm that may eventually be used by electric energy suppliers to coordinate charging of electric-drive vehicles (EDVs) in order to maximize the use of renewable energy in transportation. Due to the stochastic nature of transportation patterns, the Monte Carlo simulation is applied to model uncertainties presented by numerous scenarios. To reduce the problem complexity, the simulated driving patterns are not individually considered in the optimization but clustered into fleets using the GAMS/SCENRED tool. Uncertainties of production of renewable energy sources (RESs) are presented by statistical central moments that are further considered in Hong’s 2-point + 1 estimation method in order to define estimate points considered in the optimization. Case studies illustrate the application of the proposed optimization in achieving maximal exploitation of RESs in transportation by EDVs. -- Highlights: ► Optimization model for EDV charging applying linear programming. ► Formation of EDV fleets based on the driving patterns assessment applying the GAMS/SCENRED. ► Consideration of uncertainties of RES production and energy prices in the market. ► Stochastic optimization. ► Application of Hong’s 2-point + 1 estimation method.

Optimal Energy Consumption Analysis of Natural Gas Pipeline

Science.gov (United States)

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

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.

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

Energy modeling and economic optimization of a hybrid wind/photovoltaic system coupled with the grid and associated to an accumulator

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

Observation on optimal transition from conventional energy with resource constraints to advanced energy with virtually unlimited resource, (2)

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)

Energy modeling and analysis for optimal grid integration of large-scale variable renewables using hydrogen storage in Japan

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

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.

Nonlinear Modeling and Coordinate Optimization of a Semi-Active Energy Regenerative Suspension with an Electro-Hydraulic Actuator

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.

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

International Nuclear Information System (INIS)

Wang, Xinli; Cai, Wenjian; Lu, Jiangang; Sun, Youxian; Zhao, Lei

2015-01-01

This study presents a model-based optimization strategy for an actual chiller driven dehumidifier of liquid desiccant dehumidification system operating with lithium chloride solution. By analyzing the characteristics of the components, energy predictive models for the components in the dehumidifier are developed. To minimize the energy usage while maintaining the outlet air conditions at the pre-specified set-points, an optimization problem is formulated with an objective function, the constraints of mechanical limitations and components interactions. Model-based optimization strategy using genetic algorithm is proposed to obtain the optimal set-points for desiccant solution temperature and flow rate, to minimize the energy usage in the dehumidifier. Experimental studies on an actual system are carried out to compare energy consumption between the proposed optimization and the conventional strategies. The results demonstrate that energy consumption using the proposed optimization strategy can be reduced by 12.2% in the dehumidifier operation. - Highlights: • Present a model-based optimization strategy for energy saving in LDDS. • Energy predictive models for components in dehumidifier are developed. • The Optimization strategy are applied and tested in an actual LDDS. • Optimization strategy can achieve energy savings by 12% during operation

Energy optimization in mobile sensor networks

Science.gov (United States)

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.

Model-Based Energy Efficiency Optimization of a Low-Temperature Adsorption Dryer

NARCIS (Netherlands)

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

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.

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.

Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.

Science.gov (United States)

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.

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.

An Optimization Scheduling Model for Wind Power and Thermal Power with Energy Storage System considering Carbon Emission Trading

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.

Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

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.

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.

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

Directory of Open Access Journals (Sweden)

Fei Wang

2017-07-01

Full Text Available The optimized dispatch of different distributed generations (DGs in stand-alone microgrid (MG is of great significance to the operation’s reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL and combined cooling-heating-power (CCHP model of micro-gas turbine (MT, a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV, wind turbine (WT, fuel cell (FC, diesel engine (DE, MT and energy storage (ES. Four typical scenarios were designed according to different day types (work day or weekend and weather conditions (sunny or rainy in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers’ comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO to propose modified chaos particle swarm optimization (MCPSO whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.

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

Optimal Operation of Energy Storage in Power Transmission and Distribution

Science.gov (United States)

Akhavan Hejazi, Seyed Hossein

In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider

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

Science.gov (United States)

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.

Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.

Science.gov (United States)

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.

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

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.

Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method

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

Integrated modelling of module behavior and energy aspects in mechatronics. Energy optimization of production facilities based on model information; Modellintegration von Verhaltens- und energetischen Aspekten fuer mechatronische Module. Energieoptimierung von Produktionsanlagen auf Grundlage von Modellinformationen

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.)

The development of a volume element model for energy systems engineering and integrative thermodynamic optimization

Science.gov (United States)

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

Interactive Cosegmentation Using Global and Local Energy Optimization

OpenAIRE

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.

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

International Nuclear Information System (INIS)

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

2017-01-01

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

Multi-region optimal deployment of renewable energy considering different interregional transmission scenarios

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 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.

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.

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

The role of nuclear energy for Korean long-term energy supply strategy : application of energy demand-supply model

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

Optimal Scheduling of an Regional Integrated Energy System with Energy Storage Systems for Service Regulation

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.

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)

An Energy-Aware Trajectory Optimization Layer for sUAS

Science.gov (United States)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between

Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.

Science.gov (United States)

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.

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.

Review of models and actors in energy mix optimization – can leader visions and decisions align with optimum model strategies for our future energy systems?

NARCIS (Netherlands)

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

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

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...

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.

Optimized sizing model for renewable energy systems in rural areas; Modelo de dimensionamento otimizado para sistemas energeticos renovaveis em ambiente rurais

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)

Optimal investment paths for future renewable based energy systems - Using the optimisation model Balmorel

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

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....

Combined optimization model for sustainable energization strategy

Science.gov (United States)

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.

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.

Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

Science.gov (United States)

Shah, Rahul H.

Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the

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.

A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids

International Nuclear Information System (INIS)

Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel

2017-01-01

Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.

Integrated modeling approach for optimal management of water, energy and food security nexus

Science.gov (United States)

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.

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.

The assessment of global thermo-energy performances of existing district heating systems optimized by harnessing renewable energy sources

Science.gov (United States)

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.

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...

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

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

System optimization for HVAC energy management using the robust evolutionary algorithm

International Nuclear Information System (INIS)

Fong, K.F.; Hanby, V.I.; Chow, T.T.

2009-01-01

For an installed centralized heating, ventilating and air conditioning (HVAC) system, appropriate energy management measures would achieve energy conservation targets through the optimal control and operation. The performance optimization of conventional HVAC systems may be handled by operation experience, but it may not cover different optimization scenarios and parameters in response to a variety of load and weather conditions. In this regard, it is common to apply the suitable simulation-optimization technique to model the system then determine the required operation parameters. The particular plant simulation models can be built up by either using the available simulation programs or a system of mathematical expressions. To handle the simulation models, iterations would be involved in the numerical solution methods. Since the gradient information is not easily available due to the complex nature of equations, the traditional gradient-based optimization methods are not applicable for this kind of system models. For the heuristic optimization methods, the continual search is commonly necessary, and the system function call is required for each search. The frequency of simulation function calls would then be a time-determining step, and an efficient optimization method is crucial, in order to find the solution through a number of function calls in a reasonable computational period. In this paper, the robust evolutionary algorithm (REA) is presented to tackle this nature of the HVAC simulation models. REA is based on one of the paradigms of evolutionary algorithm, evolution strategy, which is a stochastic population-based searching technique emphasized on mutation. The REA, which incorporates the Cauchy deterministic mutation, tournament selection and arithmetic recombination, would provide a synergetic effect for optimal search. The REA is effective to cope with the complex simulation models, as well as those represented by explicit mathematical expressions of

Optimization model of peach production relevant to input energies – Yield function in Chaharmahal va Bakhtiari province, Iran

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

Optimal household refrigerator replacement policy for life cycle energy, greenhouse gas emissions, and cost

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

Feasibility and Optimal Design of a Stand-Alone Photovoltaic Energy System for the Orphanage

Directory of Open Access Journals (Sweden)

Vincent Anayochukwu Ani

2014-01-01

Full Text Available Access to electricity can have a positive psychological impact through a lessening of the sense of exclusion, and vulnerability often felt by the orphanages. This paper presented the simulation and optimization study of a stand-alone photovoltaic power system that produced the desired power needs of an orphanage. Solar resources for the design of the system were obtained from the National Aeronautics and Space Administration (NASA Surface Meteorology and Solar Energy website at a location of 6°51′N latitude and 7°35′E longitude, with annual average solar radiation of 4.92 kWh/m2/d. This study is based on modeling, simulation, and optimization of energy system in the orphanage. The patterns of load consumption within the orphanage were studied and suitably modeled for optimization. Hybrid Optimization Model for Electric Renewables (HOMER software was used to analyze and design the proposed stand-alone photovoltaic power system model. The model was designed to provide an optimal system configuration based on an hour-by-hour data for energy availability and demands. A detailed design, description, and expected performance of the system were presented in this paper.

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

Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries

Directory of Open Access Journals (Sweden)

Yan Li

2016-01-01

Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.

Optimization design of energy deposition on single expansion ramp nozzle

Science.gov (United States)

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.

Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm

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.

A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

Science.gov (United States)

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.

Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

International Nuclear Information System (INIS)

Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

2015-01-01

Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

Evaporative Air Coolers Optimization for Energy Consumption Reduction and Energy Efficiency Ratio Increment

OpenAIRE

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 ...

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

International Nuclear Information System (INIS)

Stadler, M.; Groissböck, M.; Cardoso, G.; Marnay, C.

2014-01-01

Highlights: • We model strategic investment decisions for distributed energy resources and passive measures. • Compare the demonstrated mixed integer optimization model with other existing tools. • Describe the mathematical formulation of the tool. • Demonstrate the capabilities at an Austrian University building. • Show the trade-off between cost and CO 2 reduction and report on the optimal investment decisions. - Abstract: The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables to 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This paper shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic

Optimal model of congestion management in deregulated environment of power sector with promotion of renewable energy sources

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)

An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors

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

Development of Optimal Stressor Scenarios for New Operational Energy Systems

Science.gov (United States)

2017-12-01

OPTIMAL STRESSOR SCENARIOS FOR NEW OPERATIONAL ENERGY SYSTEMS by Geoffrey E. Fastabend December 2017 Thesis Advisor: Alejandro S... ENERGY SYSTEMS 5. FUNDING NUMBERS 6. AUTHOR(S) Geoffrey E. Fastabend 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School...developed and tested simulation model for operational energy related systems in order to develop better stressor scenarios for acceptance testing

Joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids

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

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.

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.

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

Optimal satisfaction degree in energy harvesting cognitive radio networks

Science.gov (United States)

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).

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.

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.

The optimal time path of clean energy R&D policy when patents have finite lifetime

NARCIS (Netherlands)

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

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...

Energy matching and optimization analysis of waste to energy CCHP (combined cooling, heating and power) system with exergy and energy level

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

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.

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 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.

Integration and Optimization of Alternative Sources of Energy in a Remote Region

Science.gov (United States)

Berberi, Pellumb; Inodnorjani, Spiro; Aleti, Riza

2010-01-01

In a remote coastal region supply of energy from national grid is insufficient for a sustainable development. Integration and optimization of local alternative renewable energy sources is an optional solution of the problem. In this paper we have studied the energetic potential of local sources of renewable energy (water, solar, wind and biomass). A bottom-up energy system optimization model is proposed in order to support planning policies for promoting the use of renewable energy sources. A software, based on multiple factors and constrains analysis for optimization energy flow is proposed, which provides detailed information for exploitation each source of energy, power and heat generation, GHG emissions and end-use sectors. Economical analysis shows that with existing technologies both stand alone and regional facilities may be feasible. Improving specific legislation will foster investments from Central or Local Governments and also from individuals, private companies or small families. The study is carried on the frame work of a FP6 project "Integrated Renewable Energy System."

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.

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

The Role of Energy Reservoirs in Distributed Computing: Manufacturing, Implementing, and Optimizing Energy Storage in Energy-Autonomous Sensor Nodes

Science.gov (United States)

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

Optimal energy management of a hybrid electric powertrain system using improved particle swarm optimization

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

Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

KAUST Repository

Rached, Nadhir B.

2017-02-07

Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.

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

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.

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

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

An Optimal and Distributed Demand Response Strategy for Energy Internet Management

Directory of Open Access Journals (Sweden)

Qian Liu

2018-01-01

Full Text Available This study proposes a new model of demand response management for a future smart grid that consists of smart microgrids. The microgrids have energy storage units, responsive loads, controllable distributed generation units, and renewable energy resources. They can buy energy from the utility company when the power generation in themselves cannot satisfy the load demand, and sell extra power generation to the utility company. The goal is to optimize the operation schedule of microgrids to minimize the microgrids’ payments and the utility company’s operation cost. A parallel distributed optimization algorithm based on games theory is developed to solve the optimization problem, in which microgrids only need to send their aggregated purchasing/selling energy to the utility company, thus avoid infringing its privacy. Microgrids can update their operation schedule simultaneously. A case study is implemented, and the simulation results show that the proposed method is effective and efficient.

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

Science.gov (United States)

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.

Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g

Directory of Open Access Journals (Sweden)

Guozheng Li

2018-03-01

Full Text Available The integration of renewable energies into combined cooling, heating, and power (CCHP systems has become increasingly popular in recent years. However, the optimization of renewable energies integrated CCHP (RECCHP systems (i.e., optimal component configurations is far from being well addressed, especially in isolated mode. This study aims to fill this research gap. A multi-objective optimization model characterizing the system reliability, system cost, and environmental sustainability is constructed. In this model, the objectives include minimization of annual total cost (ATC, carbon dioxide emission (CDE, and loss of energy supply probability (LESP. The decision variables representing the configuration of the RECCHP system include the number of photovoltaic (PV panels and wind turbines (WTs, the tilt angle of PV panels, the height of WTs, the maximum fuel consumption, and the capacity of battery and heat storage tanks (HSTs. The multi-objective model is solved by a multi-objective evolutionary algorithm, namely, the preference-inspired coevolutionary algorithm (PICEA-g, resulting in a set of Pareto optimal (trade-off solutions. Then, a decision-making process is demonstrated, selecting a preferred solution amongst those trade-off solutions by further considering the decision-maker preferences. Furthermore, on the optimization of the RECCHP system, operational strategies (i.e., following electric load, FEL, and following thermal load, FTL are considered, respectively. Experimental results show that the FEL and FTL strategies lead to different optimal configurations. In general, the FTL is recommended in summer and winter, while the FEL is more suitable for spring and autumn. Compared with traditional energy systems, RECCHP has better economic and environmental advantages.

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.

Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center

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

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)

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.

Energy, economy, and environment analysis and optimization on manufacturing plant energy supply system

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.

Exploring the Environment/Energy Pareto Optimal Front of an Office Room Using Computational Fluid Dynamics-Based Interactive Optimization Method

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available This paper is concerned with the development of a high-resolution and control-friendly optimization framework in enclosed environments that helps improve thermal comfort, indoor air quality (IAQ, and energy costs of heating, ventilation and air conditioning (HVAC system simultaneously. A computational fluid dynamics (CFD-based optimization method which couples algorithms implemented in Matlab with CFD simulation is proposed. The key part of this method is a data interactive mechanism which efficiently passes parameters between CFD simulations and optimization functions. A two-person office room is modeled for the numerical optimization. The multi-objective evolutionary algorithm—non-dominated-and-crowding Sorting Genetic Algorithm II (NSGA-II—is realized to explore the environment/energy Pareto front of the enclosed space. Performance analysis will demonstrate the effectiveness of the presented optimization method.

Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

International Nuclear Information System (INIS)

Toksari, M. Duran

2009-01-01

This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

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

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 sampling plan for clean development mechanism energy efficiency lighting projects

International Nuclear Information System (INIS)

Ye, Xianming; Xia, Xiaohua; Zhang, Jiangfeng

2013-01-01

Highlights: • A metering cost minimisation model is built to assist the sampling plan for CDM projects. • The model minimises the total metering cost by the determination of optimal sample size. • The required 90/10 criterion sampling accuracy is maintained. • The proposed metering cost minimisation model is applicable to other CDM projects as well. - Abstract: Clean development mechanism (CDM) project developers are always interested in achieving required measurement accuracies with the least metering cost. In this paper, a metering cost minimisation model is proposed for the sampling plan of a specific CDM energy efficiency lighting project. The problem arises from the particular CDM sampling requirement of 90% confidence and 10% precision for the small-scale CDM energy efficiency projects, which is known as the 90/10 criterion. The 90/10 criterion can be met through solving the metering cost minimisation problem. All the lights in the project are classified into different groups according to uncertainties of the lighting energy consumption, which are characterised by their statistical coefficient of variance (CV). Samples from each group are randomly selected to install power meters. These meters include less expensive ones with less functionality and more expensive ones with greater functionality. The metering cost minimisation model will minimise the total metering cost through the determination of the optimal sample size at each group. The 90/10 criterion is formulated as constraints to the metering cost objective. The optimal solution to the minimisation problem will therefore minimise the metering cost whilst meeting the 90/10 criterion, and this is verified by a case study. Relationships between the optimal metering cost and the population sizes of the groups, CV values and the meter equipment cost are further explored in three simulations. The metering cost minimisation model proposed for lighting systems is applicable to other CDM projects as

A model of optimal voluntary muscular control.

Science.gov (United States)

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.

An optimization methodology for the design of renewable energy systems for residential net zero energy buildings with on-site heat production

DEFF Research Database (Denmark)

Milan, Christian; Bojesen, Carsten; Nielsen, Mads Pagh

2011-01-01

The concept of net zero energy buildings (NZEB) 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 such buildings. This paper aims at developing a method for the optimal sizing of renewable...... energy supply systems for residential NZEB 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...

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.

Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage

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...

Analysis and Optimization of Building Energy Consumption

Science.gov (United States)

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

Energy modelling in sensor networks

Science.gov (United States)

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.

Nonlinear optimal filter technique for analyzing energy depositions in TES sensors driven into saturation

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.

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....

Multi Dimensional Honey Bee Foraging Algorithm Based on Optimal Energy Consumption

Science.gov (United States)

Saritha, R.; Vinod Chandra, S. S.

2017-10-01

In this paper a new nature inspired algorithm is proposed based on natural foraging behavior of multi-dimensional honey bee colonies. This method handles issues that arise when food is shared from multiple sources by multiple swarms at multiple destinations. The self organizing nature of natural honey bee swarms in multiple colonies is based on the principle of energy consumption. Swarms of multiple colonies select a food source to optimally fulfill the requirements of its colonies. This is based on the energy requirement for transporting food between a source and destination. Minimum use of energy leads to maximizing profit in each colony. The mathematical model proposed here is based on this principle. This has been successfully evaluated by applying it on multi-objective transportation problem for optimizing cost and time. The algorithm optimizes the needs at each destination in linear time.

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

Multi-Train Energy Saving for Maximum Usage of Regenerative Energy by Dwell Time Optimization in Urban Rail Transit Using Genetic Algorithm

Directory of Open Access Journals (Sweden)

Fei Lin

2016-03-01

Full Text Available With its large capacity, the total urban rail transit energy consumption is very high; thus, energy saving operations are quite meaningful. The effective use of regenerative braking energy is the mainstream method for improving the efficiency of energy saving. This paper examines the optimization of train dwell time and builds a multiple train operation model for energy conservation of a power supply system. By changing the dwell time, the braking energy can be absorbed and utilized by other traction trains as efficiently as possible. The application of genetic algorithms is proposed for the optimization, based on the current schedule. Next, to validate the correctness and effectiveness of the optimization, a real case is studied. Actual data from the Beijing subway Yizhuang Line are employed to perform the simulation, and the results indicate that the optimization method of the dwell time is effective.

Combined Municipal Solid Waste and biomass system optimization for district energy applications

International Nuclear Information System (INIS)

Rentizelas, Athanasios A.; Tolis, Athanasios I.; Tatsiopoulos, Ilias P.

2014-01-01

Highlights: • Combined energy conversion of MSW and agricultural residue biomass is examined. • The model optimizes the financial yield of the investment. • Several system specifications are optimally defined by the optimization model. • The application to a case study in Greece shows positive financial yield. • The investment is mostly sensitive on the interest rate, the investment cost and the heating oil price. - Abstract: Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Energy Technology Data Exchange (ETDEWEB)

Rentizelas, Athanasios A., E-mail: arent@central.ntua.gr; Tolis, Athanasios I., E-mail: atol@central.ntua.gr; Tatsiopoulos, Ilias P., E-mail: itat@central.ntua.gr

2014-01-15

Highlights: • Combined energy conversion of MSW and agricultural residue biomass is examined. • The model optimizes the financial yield of the investment. • Several system specifications are optimally defined by the optimization model. • The application to a case study in Greece shows positive financial yield. • The investment is mostly sensitive on the interest rate, the investment cost and the heating oil price. - Abstract: Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers

Integrated energy optimization with smart home energy management systems

NARCIS (Netherlands)

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

Integrated solar energy system optimization

Science.gov (United States)

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.

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...

Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products

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.

Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation

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.

Generalizable occupant-driven optimization model for domestic hot water production in NZEB

International Nuclear Information System (INIS)

Kazmi, H.; D’Oca, S.; Delmastro, C.; Lodeweyckx, S.; Corgnati, S.P.

2016-01-01

Highlights: • Smart meter data for domestic hot water consumption is collected for 46 NZEB. • Reinforcement learning optimizes energy consumed while constrained on user comfort. • Online optimization models learn occupant behaviour and system thermodynamics. • Offline generalizable models calibrate dynamically the storage vessel operation. • Real world application of the active controls resulted in energy savings of 27%. - Abstract: The primary objective of this paper is to demonstrate improved energy efficiency for domestic hot water (DHW) production in residential buildings. This is done by deriving data-driven optimal heating schedules (used interchangeably with policies) automatically. The optimization leverages actively learnt occupant behaviour and models for thermodynamics of the storage vessel to operate the heating mechanism – an air-source heat pump (ASHP) in this case – at the highest possible efficiency. The proposed algorithm, while tested on an ASHP, is essentially decoupled from the heating mechanism making it sufficiently robust to generalize to other types of heating mechanisms as well. Simulation results for this optimization based on data from 46 Net-Zero Energy Buildings (NZEB) in the Netherlands are presented. These show a reduction of energy consumption for DHW by 20% using a computationally inexpensive heuristic approach, and 27% when using a more intensive hybrid ant colony optimization based method. The energy savings are strongly dependent on occupant comfort level. This is demonstrated in real-world settings for a low-consumption house where active control was performed using heuristics for 3.5 months and resulted in energy savings of 27% (61 kW h). It is straightforward to extend the same models to perform automatic demand side management (ADSM) by treating the DHW vessel as a flexibility bearing device.

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...

Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

Energy Technology Data Exchange (ETDEWEB)

Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Greenlots, San Francisco, CA (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovation Technologies (Austria); Yin, Rongxin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liu, Zhenhua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-11-29

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

Science.gov (United States)

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.

Optimal control of a wave energy converter

NARCIS (Netherlands)

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

Optimal energy management for a flywheel-based hybrid vehicle

NARCIS (Netherlands)

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

Optimization of piezoelectric cantilever energy harvesters including non-linear effects

International Nuclear Information System (INIS)

Patel, R; McWilliam, S; Popov, A A

2014-01-01

This paper proposes a versatile non-linear model for predicting piezoelectric energy harvester performance. The presented model includes (i) material non-linearity, for both substrate and piezoelectric layers, and (ii) geometric non-linearity incorporated by assuming inextensibility and accurately representing beam curvature. The addition of a sub-model, which utilizes the transfer matrix method to predict eigenfrequencies and eigenvectors for segmented beams, allows for accurate optimization of piezoelectric layer coverage. A validation of the overall theoretical model is performed through experimental testing on both uniform and non-uniform samples manufactured in-house. For the harvester composition used in this work, the magnitude of material non-linearity exhibited by the piezoelectric layer is 35 times greater than that of the substrate layer. It is also observed that material non-linearity, responsible for reductions in resonant frequency with increases in base acceleration, is dominant over geometric non-linearity for standard piezoelectric harvesting devices. Finally, over the tested range, energy loss due to damping is found to increase in a quasi-linear fashion with base acceleration. During an optimization study on piezoelectric layer coverage, results from the developed model were compared with those from a linear model. Unbiased comparisons between harvesters were realized by using devices with identical natural frequencies—created by adjusting the device substrate thickness. Results from three studies, each with a different assumption on mechanical damping variations, are presented. Findings showed that, depending on damping variation, a non-linear model is essential for such optimization studies with each model predicting vastly differing optimum configurations. (paper)

Cross-layer Energy Optimization Under Image Quality Constraints for Wireless Image Transmissions.

Science.gov (United States)

Yang, Na; Demirkol, Ilker; Heinzelman, Wendi

2012-01-01

Wireless image transmission is critical in many applications, such as surveillance and environment monitoring. In order to make the best use of the limited energy of the battery-operated cameras, while satisfying the application-level image quality constraints, cross-layer design is critical. In this paper, we develop an image transmission model that allows the application layer (e.g., the user) to specify an image quality constraint, and optimizes the lower layer parameters of transmit power and packet length, to minimize the energy dissipation in image transmission over a given distance. The effectiveness of this approach is evaluated by applying the proposed energy optimization to a reference ZigBee system and a WiFi system, and also by comparing to an energy optimization study that does not consider any image quality constraint. Evaluations show that our scheme outperforms the default settings of the investigated commercial devices and saves a significant amount of energy at middle-to-large transmission distances.

Modeling and optimization of energy generation and storage systems for thermal conditioning of buildings targeting conceptual building design

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

Modeling and optimization of energy generation and storage systems for thermal conditioning of buildings targeting conceptual building design

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

Optimal Active Power Control of A Wind Farm Equipped with Energy Storage System based on Distributed Model Predictive Control

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...

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.

Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

Directory of Open Access Journals (Sweden)

Shun Jia

2017-04-01

Full Text Available Energy demand modeling of machining processes is the foundation of energy optimization. Energy demand of machining state transition is integral to the energy requirements of the machining process. However, research focus on energy modeling of state transition is scarce. To fill this gap, an energy demand modeling methodology of key state transitions of the turning process is proposed. The establishment of an energy demand model of state transition could improve the accuracy of the energy model of the machining process, which also provides an accurate model and reliable data for energy optimization of the machining process. Finally, case studies were conducted on a CK6153i CNC lathe, the results demonstrating that predictive accuracy with the proposed method is generally above 90% for the state transition cases.

Online optimal control of variable refrigerant flow and variable air volume combined air conditioning system for energy saving

International Nuclear Information System (INIS)

Zhu, Yonghua; Jin, Xinqiao; Du, Zhimin; Fang, Xing

2015-01-01

The variable refrigerant flow (VRF) and variable air volume (VAV) combined air conditioning system can solve the problem of the VRF system in outdoor air ventilation while taking advantage of its high part load energy efficiency. Energy performance of the combined air conditioning system can also be optimized by joint control of both the VRF and the VAV parts. A model-based online optimal control strategy for the combined air conditioning system is presented. Simplified adaptive models of major components of the combined air conditioning system are firstly developed for predicting system performances. And a cost function in terms of energy consumption and thermal comfort is constructed. Genetic algorithm is used to search for the optimal control sets. The optimal control strategy is tested and evaluated through two case studies based on the simulation platform. Results show that the optimal strategy can effectively reduce energy consumption of the combined air conditioning system while maintaining acceptable thermal comfort. - Highlights: • A VRF and VAV combined system is proposed. • A model-based online optimal control strategy is proposed for the combined system. • The strategy can reduce energy consumption without sacrificing thermal comfort. • Novel simplified adaptive models are firstly developed for the VRF system

An Economic and Environmental Assessment Model for Selecting the Optimal Implementation Strategy of Fuel Cell Systems—A Focus on Building Energy Policy

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.

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.

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...

An Optimization Model for Large–Scale Wind Power Grid Connection Considering Demand Response and Energy Storage Systems

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.

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...

Energy use pattern and optimization of energy required for broiler production using data envelopment analysis

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.

Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles

International Nuclear Information System (INIS)

Prebeg, Pero; Gasparovic, Goran; Krajacic, Goran; Duic, Neven

2016-01-01

Highlights: • Optimization of supply side long-term energy planning of large power system. • Integration of renewable sources and electrical vehicles in large power system. • Multi-level, multi-objective optimization for a design of energy system. • Historical river flow data analysis for modeling of aggregated hydropower potential. - Abstract: Due to the stochastic nature and variability of renewable energy sources (RES), it is necessary to integrate still expensive storage capacities into an energy system with a high share of RES and to model appropriate energy market. The study presented here considers all energy carriers, however, only the electricity carrier is modeled in detail, with notion taken for the heating demand that is covered but without proper modeling of storage. A proposed two-level approach with multi-objective optimization on the global level, was used to design a Croatian Energy System (CES), where electric vehicles (EVs) are integrated to serve as battery storage in Vehicle-to-Grid (V2G) mode, for a scenario between 2015 and 2050. In addition, case study includes nine aggregated hydro power plants, one for each river basin in Croatia. Also, case study includes solar and wind power plants modeled for six locations in Croatia: Osijek, Zagreb, Rijeka, Sibenik, Split and Dubrovnik. The resulting Pareto front suggests that with assumed future costs of fuels and technology certain level of conventional energy sources will have to remain in the energy system to take into the account unfavourable weather conditions and to cover heating demand, which also results in significantly lower load factors for those power plants. Also, variants with more RES share have lower total energy system load factor and significantly higher installed capacity.

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

Comprehensive Energy Assessment: EE and RE Project Optimization Modeling for United States Pacific Command (USPACOM) American Recovery and Reinvestment Act (ARRA) FEMP Technical Assistance

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.

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...

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...

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

Institute of Scientific and Technical Information of China (English)

Feng Zhao; Chenghui Zhang; Bo Sun

2016-01-01

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

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

Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

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...

Optimal electricity price calculation model for retailers in a deregulated market

Energy Technology Data Exchange (ETDEWEB)

Yusta, J.M.; Dominguez-Navarro, J.A. [Zaragoza Univ., Dept. of Electrical Engineering, Zaragoza (Spain); Ramirez-Rosado, I.J. [La Rioja Univ., Dept. of Electrical Engineering, Logrono (Spain); Perez-Vidal, J.M. [McKinnon and Clarke, Energy Services Div., Zaragoza (Spain)

2005-07-01

The electricity retailing, a new business in deregulated electric power systems, needs the development of efficient tools to optimize its operation. This paper defines a technical-economic model of an electric energy service provider in the environment of the deregulated electricity market in Spain. This model results in an optimization problem, for calculating the optimal electric power and energy selling prices that maximize the economic profits obtained by the provider. This problem is applied to different cases, where the impact on the profits of several factors, such as the price strategy, the discount on tariffs and the elasticity of customer demand functions, is studied. (Author)

Optimal electricity price calculation model for retailers in a deregulated market

International Nuclear Information System (INIS)

Yusta, J.M.; Dominguez-Navarro, J.A.; Ramirez-Rosado, I.J.; Perez-Vidal, J.M.

2005-01-01

The electricity retailing, a new business in deregulated electric power systems, needs the development of efficient tools to optimize its operation. This paper defines a technical-economic model of an electric energy service provider in the environment of the deregulated electricity market in Spain. This model results in an optimization problem, for calculating the optimal electric power and energy selling prices that maximize the economic profits obtained by the provider. This problem is applied to different cases, where the impact on the profits of several factors, such as the price strategy, the discount on tariffs and the elasticity of customer demand functions, is studied. (Author)

Parallel algorithms for islanded microgrid with photovoltaic and energy storage systems planning optimization problem: Material selection and quantity demand optimization

Science.gov (United States)

Cao, Yang; Liu, Chun; Huang, Yuehui; Wang, Tieqiang; Sun, Chenjun; Yuan, Yue; Zhang, Xinsong; Wu, Shuyun

2017-02-01

With the development of roof photovoltaic power (PV) generation technology and the increasingly urgent need to improve supply reliability levels in remote areas, islanded microgrid with photovoltaic and energy storage systems (IMPE) is developing rapidly. The high costs of photovoltaic panel material and energy storage battery material have become the primary factors that hinder the development of IMPE. The advantages and disadvantages of different types of photovoltaic panel materials and energy storage battery materials are analyzed in this paper, and guidance is provided on material selection for IMPE planners. The time sequential simulation method is applied to optimize material demands of the IMPE. The model is solved by parallel algorithms that are provided by a commercial solver named CPLEX. Finally, to verify the model, an actual IMPE is selected as a case system. Simulation results on the case system indicate that the optimization model and corresponding algorithm is feasible. Guidance for material selection and quantity demand for IMPEs in remote areas is provided by this method.

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 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

A complex systems approach to planning, optimization and decision making for energy networks

International Nuclear Information System (INIS)

Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

2008-01-01

This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock

Optimization modeling with spreadsheets

CERN Document Server

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

Fast exploration of an optimal path on the multidimensional free energy surface

Science.gov (United States)

Chen, Changjun

2017-01-01

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475

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...

Optimizing renewable energy, demand response and energy storage to replace conventional fuels in Ontario, Canada

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.

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.

Modeling and Optimization : Theory and Applications Conference

CERN Document Server

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

CERN Document Server

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.

Novel optimization technique of isolated microgrid with hydrogen energy storage.

Science.gov (United States)

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.

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.

Real - time Optimization of Distributed Energy Storage System Operation Strategy Based on Peak Load Shifting

Science.gov (United States)

Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di

2018-01-01

To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.

Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

Directory of Open Access Journals (Sweden)

Changbin Hu

2015-02-01

Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

Identification of optimal strategies for energy management systems planning under multiple uncertainties

International Nuclear Information System (INIS)

Cai, Y.P.; Huang, G.H.; Yang, Z.F.; Tan, Q.

2009-01-01

Management of energy resources is crucial for many regions throughout the world. Many economic, environmental and political factors are having significant effects on energy management practices, leading to a variety of uncertainties in relevant decision making. The objective of this research is to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a fuzzy-random interval programming (FRIP) model. The method is based on an integration of the existing interval linear programming (ILP), superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP). Such a FRIP model allows multiple uncertainties presented as interval values, possibilistic and probabilistic distributions, as well as their combinations within a general optimization framework. It can also be used for facilitating capacity-expansion planning of energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term energy management planning for a region with three cities. Useful solutions for the planning of energy management systems were generated. Interval solutions associated with different risk levels of constraint violation were obtained. They could be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks could be successfully tackled, i.e., higher costs will increase system stability, while a desire for lower

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

Science.gov (United States)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

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.

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 ...

A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies

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

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....

Optimal allocation of energy storage in a co-optimized electricity market: Benefits assessment and deriving indicators for economic storage ventures

International Nuclear Information System (INIS)

Krishnan, Venkat; Das, Trishna

2015-01-01

This paper presents a framework for optimally allocating storage technologies in a power system. This decision support tool helps in quantitatively answering the questions on “where to and how much to install” considering the profits from arbitrage opportunities in a co-optimized electricity market. The developed framework is illustrated on a modified IEEE (Institute of Electrical and Electronics Engineers) 24 bus RTS (Reliability Test System), and the framework finds the optimal allocation solution and the revenues storage earns at each of these locations. Bulk energy storage, CAES (compressed air energy storage) is used as the representative storage technology, and the benefits of optimally allocated storage integration onto the grid are compared with transmission expansion solution. The paper also discusses about system-level indicators to identify candidate locations for economical storage ventures, which are derived based on the optimal storage allocation solution; and applies the market price based storage venture indicators on MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) electricity markets. - Highlights: • Storage optimal allocation framework based on high-fidelity storage dispatch model. • Storage with transmission addresses energy and ancillary issues under high renewables. • Bulk storage earns higher revenues from co-optimization (∼10× energy only market). • Grid offers distributed opportunities for investing in a strategic mix of storage. • Storage opportunities depend on cross-arbitrage, as seen from MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) markets

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

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 energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available 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 energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

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 energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Intelligent energy management of optimally located renewable energy systems incorporating PHEV

International Nuclear Information System (INIS)

El-Zonkoly, Amany

2014-01-01

Highlights: • The algorithm optimally selects the number, locations and sizes of DGs. • Wind units, PV units, diesel units and PHEV parking lots are considered as DGs. • The algorithm determines the corresponding energy scheduling of resources. • The problem is formulated as an optimization problem solved using ABC. • The objective is to minimize the overall energy cost of the system. - Abstract: The recent interest in plug-in-hybrid electric vehicles (PHEV) results in the increase in the utilization of vehicles batteries for grid support. In addition, the integration of renewable energy systems (RES) into electricity grid is a promising technique for addressing the environmental concerns. This paper presents a multi-objective algorithm to optimally allocate a number of renewable energy systems including parking lots for PHEV in a distribution system. The proposed algorithm determines the number, locations and sizes of the RES and parking lots. In addition, a rule based expert system is used to find the corresponding energy scheduling of the system resources. The objective of the proposed algorithm is to minimize the overall energy cost of the system. The problem is formulated as an optimization problem which is solved using artificial bee colony (ABC) algorithm taking into consideration the power system and PHEV operational constraints. The proposed algorithm is applied to a 45-bus distribution network of Alexandria, Egypt. The test results indicate an improvement in the operational conditions of the system

Energy Management Strategy in Consideration of Battery Health for PHEV via Stochastic Control and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Yuying Wang

2017-11-01

Full Text Available This paper presents an energy management strategy for plug-in hybrid electric vehicles (PHEVs that not only tries to minimize the energy consumption, but also considers the battery health. First, a battery model that can be applied to energy management optimization is given. In this model, battery health damage can be estimated in the different states of charge (SOC and temperature of the battery pack. Then, because of the inevitability that limiting the battery health degradation will increase energy consumption, a Pareto energy management optimization problem is formed. This multi-objective optimal control problem is solved numerically by using stochastic dynamic programming (SDP and particle swarm optimization (PSO for satisfying the vehicle power demand and considering the tradeoff between energy consumption and battery health at the same time. The optimization solution is obtained offline by utilizing real historical traffic data and formed as mappings on the system operating states so as to implement online in the actual driving conditions. Finally, the simulation results carried out on the GT-SUITE-based PHEV test platform are illustrated to demonstrate that the proposed multi-objective optimal control strategy would effectively yield benefits.

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.

A multi-sectorial model for energy supply optimization: electric power, natural gas, and cogeneration with biomass; Um modelo multisetorial para otimizacao do suprimento de energia: eletricidade, gas natural e cogeracao com biomassa

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.

Dynamic Optimal Energy Flow in the Integrated Natural Gas and Electrical Power Systems

DEFF Research Database (Denmark)

Fang, Jiakun; Zeng, Qing; Ai, Xiaomeng

2018-01-01

. Simulation on the test case illustrates the success of the modelling and the beneficial roles of the power-to-gas are analyzed. The proposed model can be used in the decision support for both planning and operation of the coordinated natural gas and electrical power systems.......This work focuses on the optimal operation of the integrated gas and electrical power system with bi-directional energy conversion. Considering the different response times of the gas and power systems, the transient gas flow and steady- state power flow are combined to formulate the dynamic...... optimal energy flow in the integrated gas and power systems. With proper assumptions and simplifications, the problem is transformed into a single stage linear programming. And only a single stage linear programming is needed to obtain the optimal operation strategy for both gas and power systems...

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-07-01

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

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

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...

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

Observer model optimization of a spectral mammography system

Science.gov (United States)

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.

Walking on a moving surface: energy-optimal walking motions on a shaky bridge and a shaking treadmill can reduce energy costs below normal.

Science.gov (United States)

Joshi, Varun; Srinivasan, Manoj

2015-02-08

Understanding how humans walk on a surface that can move might provide insights into, for instance, whether walking humans prioritize energy use or stability. Here, motivated by the famous human-driven oscillations observed in the London Millennium Bridge, we introduce a minimal mathematical model of a biped, walking on a platform (bridge or treadmill) capable of lateral movement. This biped model consists of a point-mass upper body with legs that can exert force and perform mechanical work on the upper body. Using numerical optimization, we obtain energy-optimal walking motions for this biped, deriving the periodic body and platform motions that minimize a simple metabolic energy cost. When the platform has an externally imposed sinusoidal displacement of appropriate frequency and amplitude, we predict that body motion entrained to platform motion consumes less energy than walking on a fixed surface. When the platform has finite inertia, a mass- spring-damper with similar parameters to the Millennium Bridge, we show that the optimal biped walking motion sustains a large lateral platform oscillation when sufficiently many people walk on the bridge. Here, the biped model reduces walking metabolic cost by storing and recovering energy from the platform, demonstrating energy benefits for two features observed for walking on the Millennium Bridge: crowd synchrony and large lateral oscillations.

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)

Combining gait optimization with passive system to increase the energy efficiency of a humanoid robot walking movement

International Nuclear Information System (INIS)

Pereira, Ana I.; Lima, José; Costa, Paulo

2015-01-01

There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Final results demonstrate that optimization is a valid gait planning technique

Combining gait optimization with passive system to increase the energy efficiency of a humanoid robot walking movement

Energy Technology Data Exchange (ETDEWEB)

Pereira, Ana I. [Polytechnic Institute of Bragança (Portugal); ALGORITMI,University of Minho (Portugal); Lima, José [Polytechnic Institute of Bragança (Portugal); INESC TEC (formerly INESC Porto) Porto (Portugal); Costa, Paulo [Faculty of Engineering, University of Porto (Portugal); INESC TEC (formerly INESC Porto) Porto (Portugal)

2015-03-10

There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Final results demonstrate that optimization is a valid gait planning technique.

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

Directory of Open Access Journals (Sweden)

Yuefei Wang

2016-10-01

Full Text Available As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

Optimized Free Energies from Bidirectional Single-Molecule Force Spectroscopy

Science.gov (United States)

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.

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...

Combining spatial modeling and choice experiments for the optimal spatial allocation of wind turbines

International Nuclear Information System (INIS)

Drechsler, Martin; Ohl, Cornelia; Meyerhoff, Juergen; Eichhorn, Marcus; Monsees, Jan

2011-01-01

Although wind power is currently the most efficient source of renewable energy, the installation of wind turbines (WT) in landscapes often leads to conflicts in the affected communities. We propose that such conflicts can be mitigated by a welfare-optimal spatial allocation of WT in the landscape so that a given energy target is reached at minimum social costs. The energy target is motivated by the fact that wind power production is associated with relatively low CO 2 emissions. Social costs comprise energy production costs as well as external costs caused by harmful impacts on humans and biodiversity. We present a modeling approach that combines spatially explicit ecological-economic modeling and choice experiments to determine the welfare-optimal spatial allocation of WT in West Saxony, Germany. The welfare-optimal sites balance production and external costs. Results indicate that in the welfare-optimal allocation the external costs represent about 14% of the total costs (production costs plus external costs). Optimizing wind power production without consideration of the external costs would lead to a very different allocation of WT that would marginally reduce the production costs but strongly increase the external costs and thus lead to substantial welfare losses. - Highlights: → We combine modeling and economic valuation to optimally allocate wind turbines. → Welfare-optimal allocation balances energy production costs and external costs. → External costs (impacts on the environment) can be substantial. → Ignoring external costs leads to suboptimal allocations and welfare losses.

Using a water-food-energy nexus approach for optimal irrigation management during drought events in Nebraska

Science.gov (United States)

Campana, P. E.; Zhang, J.; Yao, T.; Melton, F. S.; Yan, J.

2017-12-01

Climate change and drought have severe impacts on the agricultural sector affecting crop yields, water availability, and energy consumption for irrigation. Monitoring, assessing and mitigating the effects of climate change and drought on the agricultural and energy sectors are fundamental challenges that require investigation for water, food, and energy security issues. Using an integrated water-food-energy nexus approach, this study is developing a comprehensive drought management system through integration of real-time drought monitoring with real-time irrigation management. The spatially explicit model developed, GIS-OptiCE, can be used for simulation, multi-criteria optimization and generation of forecasts to support irrigation management. To demonstrate the value of the approach, the model has been applied to one major corn region in Nebraska to study the effects of the 2012 drought on crop yield and irrigation water/energy requirements as compared to a wet year such as 2009. The water-food-energy interrelationships evaluated show that significant water volumes and energy are required to halt the negative effects of drought on the crop yield. The multi-criteria optimization problem applied in this study indicates that the optimal solutions of irrigation do not necessarily correspond to those that would produce the maximum crop yields, depending on both water and economic constraints. In particular, crop pricing forecasts are extremely important to define the optimal irrigation management strategy. The model developed shows great potential in precision agriculture by providing near real-time data products including information on evapotranspiration, irrigation volumes, energy requirements, predicted crop growth, and nutrient requirements.

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 extended continuum model considering optimal velocity change with memory and numerical tests

Science.gov (United States)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading