Pub Date : 2016-10-01DOI: 10.4018/IJEOE.2016100104
Dipayan Guha, P. Roy, Subrata Banerjee
In this article, a novel optimization algorithm called grey wolf optimization GWO with the theory of quasi-oppositional based learning Q-OBL is proposed for the first time to solve load frequency control LFC problem. An equal two-area thermal power system equipped with classical PID-controller is considered for this study. The power system network is modeled with governor dead band and time delay nonlinearities to get better insight of LFC system. 1% load perturbation in area-1 is considered to appraise the dynamic behavior of concerned power system. Integral time absolute error and least average error based fitness functions are defined for fine tuning of PID-controller gains employing the proposed method. An extensive comparative analysis is performed to establish the superiority of proposed algorithm over other recently published algorithms. Finally, sensitivity analysis is performed to show the robustness of the designed controller with system uncertainties.
{"title":"Grey Wolf Optimization to Solve Load Frequency Control of an Interconnected Power System: GWO Used to Solve LFC Problem","authors":"Dipayan Guha, P. Roy, Subrata Banerjee","doi":"10.4018/IJEOE.2016100104","DOIUrl":"https://doi.org/10.4018/IJEOE.2016100104","url":null,"abstract":"In this article, a novel optimization algorithm called grey wolf optimization GWO with the theory of quasi-oppositional based learning Q-OBL is proposed for the first time to solve load frequency control LFC problem. An equal two-area thermal power system equipped with classical PID-controller is considered for this study. The power system network is modeled with governor dead band and time delay nonlinearities to get better insight of LFC system. 1% load perturbation in area-1 is considered to appraise the dynamic behavior of concerned power system. Integral time absolute error and least average error based fitness functions are defined for fine tuning of PID-controller gains employing the proposed method. An extensive comparative analysis is performed to establish the superiority of proposed algorithm over other recently published algorithms. Finally, sensitivity analysis is performed to show the robustness of the designed controller with system uncertainties.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121742300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-01DOI: 10.4018/IJEOE.2016070103
S. Dutta, P. Roy, Debashis Nandi
Static synchronous series compensator (SSSC) is one of the most effective flexible AC transmission systems (FACTS) devices used for enhancing power system security. In this paper, optimal location and sizing of SSSC are investigated for solving the optimal reactive power dispatch (ORPD) problem in order to minimize the active power loss in the transmission networks. A new and efficient chemical reaction optimization (CRO) is proposed to find the feasible optimal solution of the SSSC based optimal reactive power dispatch (ORPD) problem. The proposed approach is carried out on the standard IEEE 30 bus and IEEE 57 bus test systems. The optimization results obtained by the proposed CRO are analyzed and compared with the same obtained from genetic algorithm (GA), teaching learning based optimization (TLBO), quasi-oppositional TLBO (QOTLBO) and strength pareto evolutionary algorithm (SPEA). The results demonstrate the capabilities of the proposed approach to generate true and well-distributed optimal solutions.
{"title":"Optimal Allocation of Static Synchronous Series Compensator Controllers using Chemical Reaction Optimization for Reactive Power Dispatch","authors":"S. Dutta, P. Roy, Debashis Nandi","doi":"10.4018/IJEOE.2016070103","DOIUrl":"https://doi.org/10.4018/IJEOE.2016070103","url":null,"abstract":"Static synchronous series compensator (SSSC) is one of the most effective flexible AC transmission systems (FACTS) devices used for enhancing power system security. In this paper, optimal location and sizing of SSSC are investigated for solving the optimal reactive power dispatch (ORPD) problem in order to minimize the active power loss in the transmission networks. A new and efficient chemical reaction optimization (CRO) is proposed to find the feasible optimal solution of the SSSC based optimal reactive power dispatch (ORPD) problem. The proposed approach is carried out on the standard IEEE 30 bus and IEEE 57 bus test systems. The optimization results obtained by the proposed CRO are analyzed and compared with the same obtained from genetic algorithm (GA), teaching learning based optimization (TLBO), quasi-oppositional TLBO (QOTLBO) and strength pareto evolutionary algorithm (SPEA). The results demonstrate the capabilities of the proposed approach to generate true and well-distributed optimal solutions.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130746999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-01DOI: 10.4018/IJEOE.2016070101
Dipayan Guha, P. Roy, Subrata Banerjee
An attempt has been made for the effective application of biogeography based optimization and its modified version to solve load frequency control (LFC) problem. Two-area interconnected multi-unit multi-source power system having thermal, hydro and gas power plant without and with AC-DC link is considered for study. Proportional-integral-derivative controller is used as secondary controller in LFC system and its gains are tuned by proposed algorithms through minimization of integral time absolute error based objective function. The results confirm the effectiveness of proposed algorithms after comparing results with other evolutionary algorithms like differential evolution (DE), teaching learning based optimization (TLBO) for the similar test system. The robustness of proposed algorithm is checked with different objective functions like integral square error, integral absolute error, integral time square error criterions and under different loading conditions. Critical analysis of results reveals that proposed method gives better performance than that obtained with DE, TLBO.
{"title":"Application of Modified Biogeography Based Optimization in AGC of an Interconnected Multi-Unit Multi-Source AC-DC Linked Power System","authors":"Dipayan Guha, P. Roy, Subrata Banerjee","doi":"10.4018/IJEOE.2016070101","DOIUrl":"https://doi.org/10.4018/IJEOE.2016070101","url":null,"abstract":"An attempt has been made for the effective application of biogeography based optimization and its modified version to solve load frequency control (LFC) problem. Two-area interconnected multi-unit multi-source power system having thermal, hydro and gas power plant without and with AC-DC link is considered for study. Proportional-integral-derivative controller is used as secondary controller in LFC system and its gains are tuned by proposed algorithms through minimization of integral time absolute error based objective function. The results confirm the effectiveness of proposed algorithms after comparing results with other evolutionary algorithms like differential evolution (DE), teaching learning based optimization (TLBO) for the similar test system. The robustness of proposed algorithm is checked with different objective functions like integral square error, integral absolute error, integral time square error criterions and under different loading conditions. Critical analysis of results reveals that proposed method gives better performance than that obtained with DE, TLBO.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124780887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-01DOI: 10.4018/IJEOE.2016070102
Subhajit Roy
As it is known Microgrid is a miniature grid consist of one or more numbers of same or by different conventional or non-conventional generation sources. Here one can consider Microturbine (MT) as the main source of generation and it may or may not be connected with the main grid. The author discussed modeling of different types of Micro turbine during implementation of mathematical modeling of split-shaft type with the help of MATLAB® Simulink®. From developed models can be describe behavior of a MicroGrid (MG) under islanded mode as MT and SOFC as the sources. SOFC can change its electrical output power (30%) high or low, but take more time to response than MT (2-3 times more). It is demonstrated that Microturbines and fuel-cells are capable of providing a load-following service in the distributed generation system. Results prove the effectiveness of the two developed models in the studying and analysis of the transient dynamic response of MG.
{"title":"Implementation of Model to Analyse the Performance of Microturbine as in Microgrid Comparison with Fuel Cell","authors":"Subhajit Roy","doi":"10.4018/IJEOE.2016070102","DOIUrl":"https://doi.org/10.4018/IJEOE.2016070102","url":null,"abstract":"As it is known Microgrid is a miniature grid consist of one or more numbers of same or by different conventional or non-conventional generation sources. Here one can consider Microturbine (MT) as the main source of generation and it may or may not be connected with the main grid. The author discussed modeling of different types of Micro turbine during implementation of mathematical modeling of split-shaft type with the help of MATLAB® Simulink®. From developed models can be describe behavior of a MicroGrid (MG) under islanded mode as MT and SOFC as the sources. SOFC can change its electrical output power (30%) high or low, but take more time to response than MT (2-3 times more). It is demonstrated that Microturbines and fuel-cells are capable of providing a load-following service in the distributed generation system. Results prove the effectiveness of the two developed models in the studying and analysis of the transient dynamic response of MG.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130532294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-07-01DOI: 10.4018/IJEOE.2016070104
Mohammed Tamali, Bouzidi Boumedienne, Allali Ahmed
Industrial systems require reliable components. The interactions among components affect the system reliability. In this study, the electrical power system Robustness is evaluated among its sensitivity to potential changes in the intrinsic parameters. Reliability represents a state indicator. In this work, highlights are made on the importance of Maintenance in Sustaining the QoS of a System. Service, Usage, and Consumers are the three components that can seriously harm the System Reliability and especially in a southern regions conditions where temperatures can simply, reach high values. First, a model is proposed after which a series of tests follow for validation. System's Maintenance is a major factor that affects its Longevity within an acceptable Robustness. Therefore maintenance can be fatal to system operation. Maintenance means expected services with respect to recommended Usage and responding to Consumption Demand. For a given period t in time, the EN represents the indicator of the Electrical System Reliability.
{"title":"System Reliability-based Optimization Method to Solve Unavailability of Electrical Energy","authors":"Mohammed Tamali, Bouzidi Boumedienne, Allali Ahmed","doi":"10.4018/IJEOE.2016070104","DOIUrl":"https://doi.org/10.4018/IJEOE.2016070104","url":null,"abstract":"Industrial systems require reliable components. The interactions among components affect the system reliability. In this study, the electrical power system Robustness is evaluated among its sensitivity to potential changes in the intrinsic parameters. Reliability represents a state indicator. In this work, highlights are made on the importance of Maintenance in Sustaining the QoS of a System. Service, Usage, and Consumers are the three components that can seriously harm the System Reliability and especially in a southern regions conditions where temperatures can simply, reach high values. First, a model is proposed after which a series of tests follow for validation. System's Maintenance is a major factor that affects its Longevity within an acceptable Robustness. Therefore maintenance can be fatal to system operation. Maintenance means expected services with respect to recommended Usage and responding to Consumption Demand. For a given period t in time, the EN represents the indicator of the Electrical System Reliability.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128656137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.4018/IJEOE.2016040102
Saria Abed, T. Khir, A. Brahim
In this paper, thermodynamic study of simple and regenerative gas turbine cycles is exhibited. Firstly, thermodynamic models for both cycles are defined; thermal efficiencies of both cycles are determined, the overall heat transfer coefficient through the heat exchanger is calculated in order to determinate its performances and parametric study is carried out to investigate the effects of compressor inlet temperature, turbine inlet temperature and compressor pressure ratio on the parameters that measure cycles' performance. Subsequently, numerical optimization is established through EES software to determinate operating conditions. The results of parametric study have shown a significant impact of operating parameters on the performance of the cycle. According to this study, the regeneration technique improves the thermal efficiency by 10%. The studied regenerator has an important effectiveness (Eœ 82%) which improves the heat transfer exchange; also a high compressor pressure ratio and an important combustion temperature can increase thermal efficiency.
{"title":"Thermodynamic and Energy Study of a Regenerator in Gas Turbine Cycle and Optimization of Performances","authors":"Saria Abed, T. Khir, A. Brahim","doi":"10.4018/IJEOE.2016040102","DOIUrl":"https://doi.org/10.4018/IJEOE.2016040102","url":null,"abstract":"In this paper, thermodynamic study of simple and regenerative gas turbine cycles is exhibited. Firstly, thermodynamic models for both cycles are defined; thermal efficiencies of both cycles are determined, the overall heat transfer coefficient through the heat exchanger is calculated in order to determinate its performances and parametric study is carried out to investigate the effects of compressor inlet temperature, turbine inlet temperature and compressor pressure ratio on the parameters that measure cycles' performance. Subsequently, numerical optimization is established through EES software to determinate operating conditions. The results of parametric study have shown a significant impact of operating parameters on the performance of the cycle. According to this study, the regeneration technique improves the thermal efficiency by 10%. The studied regenerator has an important effectiveness (Eœ 82%) which improves the heat transfer exchange; also a high compressor pressure ratio and an important combustion temperature can increase thermal efficiency.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"629 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123341908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.4018/IJEOE.2016040103
Shabbir Uddin, A. Ray, K. Sherpa, S. Chakravorty
An expert system for distribution planning is proposed in this paper. Choosing a best location of a distribution substation and grouping the various load points to be fed from a particular distribution substation has always been a concern to the distribution planners. Here in this paper the authors present a hybridization of K-means clustering method with fuzzy context aware decision algorithm for choosing the optimum location of distribution substation and its feeder layout. K means clustering has been applied to various loads which are at different location to form a cluster with load points in closer proximity so that a substation could be placed for each cluster for the distribution of power. Fuzzy Context Aware Decision Algorithm based on the Analytical Hierarchy process (AHP) is then applied on each cluster to decide on the feeder layout connecting the load points in each cluster. The feeder layout is based on the various reliability factors and thus the result obtained will lead to optimum feeder path and will hence lower long range distribution expenses.
{"title":"Design of an Expert System for Distribution Planning System using Soft Computing Techniques","authors":"Shabbir Uddin, A. Ray, K. Sherpa, S. Chakravorty","doi":"10.4018/IJEOE.2016040103","DOIUrl":"https://doi.org/10.4018/IJEOE.2016040103","url":null,"abstract":"An expert system for distribution planning is proposed in this paper. Choosing a best location of a distribution substation and grouping the various load points to be fed from a particular distribution substation has always been a concern to the distribution planners. Here in this paper the authors present a hybridization of K-means clustering method with fuzzy context aware decision algorithm for choosing the optimum location of distribution substation and its feeder layout. K means clustering has been applied to various loads which are at different location to form a cluster with load points in closer proximity so that a substation could be placed for each cluster for the distribution of power. Fuzzy Context Aware Decision Algorithm based on the Analytical Hierarchy process (AHP) is then applied on each cluster to decide on the feeder layout connecting the load points in each cluster. The feeder layout is based on the various reliability factors and thus the result obtained will lead to optimum feeder path and will hence lower long range distribution expenses.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131004211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.4018/IJEOE.2016040104
S. Dutta, P. Roy, Debashis Nandi
In this paper, quasi-oppositional teaching-learning based optimization QOTLBO is introduced and successfully applied for solving an optimal power flow OPF problem in power system incorporating flexible AC transmission systems FACTS. The main drawback of the original teaching-learning based optimization TLBO is that it gives a local optimal solution rather than the near global optimal one in limited iteration cycles. In this paper, opposition based learning OBL concept is introduced to improve the convergence speed and simulation results of TLBO. The effectiveness of the proposed method implemented with MATLAB and tested on modified IEEE 30-bus system in four different cases. The simulation results show the effectiveness and accuracy of the proposed QOTLBO algorithm over other methods like conventional BBO and hybrid biogeography-based optimization HDE-BBO. This method gives better solution quality in finding the optimal parameter settings for FACTS devices to solve OPF problems. The simulation study also shows that using FACTS devices, it is possible to improve the quality of the electric power supply thereby providing an economically attractive solution to power system problems.
{"title":"Quasi Oppositional Teaching-Learning based Optimization for Optimal Power Flow Incorporating FACTS","authors":"S. Dutta, P. Roy, Debashis Nandi","doi":"10.4018/IJEOE.2016040104","DOIUrl":"https://doi.org/10.4018/IJEOE.2016040104","url":null,"abstract":"In this paper, quasi-oppositional teaching-learning based optimization QOTLBO is introduced and successfully applied for solving an optimal power flow OPF problem in power system incorporating flexible AC transmission systems FACTS. The main drawback of the original teaching-learning based optimization TLBO is that it gives a local optimal solution rather than the near global optimal one in limited iteration cycles. In this paper, opposition based learning OBL concept is introduced to improve the convergence speed and simulation results of TLBO. The effectiveness of the proposed method implemented with MATLAB and tested on modified IEEE 30-bus system in four different cases. The simulation results show the effectiveness and accuracy of the proposed QOTLBO algorithm over other methods like conventional BBO and hybrid biogeography-based optimization HDE-BBO. This method gives better solution quality in finding the optimal parameter settings for FACTS devices to solve OPF problems. The simulation study also shows that using FACTS devices, it is possible to improve the quality of the electric power supply thereby providing an economically attractive solution to power system problems.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122278566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.4018/IJEOE.2016040101
S. Joshi, D. Talange
In the last decade Autonomous Underwater Vehicles are used in large number. The control issue of these vehicles is very challenging due to uncertain underwater environment. Conventional controllers may fail during operations especially when changes in the system occur, since it is impossible to re tune the controller in water. Hence the autonomous underwater system must have controller capability to detect, identify and tolerate fault, abort the ongoing mission and return to water surface. In this paper fault tolerant control algorithm is designed and applied to fractional order model of AUV. While designing fault tolerant controller state observer feedback technique is used. It is observed that the fractional order system is stable for fractional order greater than 1 and less than 2 under normal and under actuator failure conditions. For gain optimization of feedback controller LMI approach is used.
{"title":"Fault Tolerant Control for a Fractional Order AUV System","authors":"S. Joshi, D. Talange","doi":"10.4018/IJEOE.2016040101","DOIUrl":"https://doi.org/10.4018/IJEOE.2016040101","url":null,"abstract":"In the last decade Autonomous Underwater Vehicles are used in large number. The control issue of these vehicles is very challenging due to uncertain underwater environment. Conventional controllers may fail during operations especially when changes in the system occur, since it is impossible to re tune the controller in water. Hence the autonomous underwater system must have controller capability to detect, identify and tolerate fault, abort the ongoing mission and return to water surface. In this paper fault tolerant control algorithm is designed and applied to fractional order model of AUV. While designing fault tolerant controller state observer feedback technique is used. It is observed that the fractional order system is stable for fractional order greater than 1 and less than 2 under normal and under actuator failure conditions. For gain optimization of feedback controller LMI approach is used.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133198615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-10-01DOI: 10.4018/IJEOE.2015100103
Karol Fabisz, A. Filipowska, T. Hossa
Nowadays, a lot of attention regarding smart grids' development is devoted to delivery of methods for estimation of the energy demand taking into account the behavior of network participants (being single prosumers or groups of prosumers). These methods take an advantage from an analysis of the ex-post data on energy consumption, usually with no additional data about profiles of prosumers. The goal of this paper is to present and validate a method for an energy demand forecasting based on profiling of prosumers that enables estimation of the energy demand for every user stereotype, every hour, every day of the year and even for every device. The paper presents possible scenarios on how the proposed approach can be used for the benefit of the microgrid.
{"title":"Profiling of Prosumers for the Needs of Electric Energy Demand Estimation in Microgrids","authors":"Karol Fabisz, A. Filipowska, T. Hossa","doi":"10.4018/IJEOE.2015100103","DOIUrl":"https://doi.org/10.4018/IJEOE.2015100103","url":null,"abstract":"Nowadays, a lot of attention regarding smart grids' development is devoted to delivery of methods for estimation of the energy demand taking into account the behavior of network participants (being single prosumers or groups of prosumers). These methods take an advantage from an analysis of the ex-post data on energy consumption, usually with no additional data about profiles of prosumers. The goal of this paper is to present and validate a method for an energy demand forecasting based on profiling of prosumers that enables estimation of the energy demand for every user stereotype, every hour, every day of the year and even for every device. The paper presents possible scenarios on how the proposed approach can be used for the benefit of the microgrid.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129291387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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