Pub Date : 2015-07-26DOI: 10.1109/PESGM.2015.7285651
S. Kolluri, J. Ramamurthy, S. Wong, M. Peterson, P. Yu, Mukund R. Chander
Fault-induced delayed voltage recovery (FIDVR) is a major concern in bulk electric systems, especially in high load growth areas of the system which may be limited in generation and transmission. As part of an overall emergency plan to manage exposure to low voltage conditions and resulting voltage instability under summer peak load conditions, a fast-acting, localized, relay-based undervoltage load shedding (UVLS) scheme has been implemented for Entergy's Western Region. This paper describes the planning considerations and design criteria, followed by implementation details of the relay operation logic programmed using a standard microprocessor-based multi-functional relay. A number of dynamic simulations were performed using PSS/E program and the resulting voltage trajectories were used for testing the relay operation.
{"title":"Relay-based undervoltage load shedding scheme for Entergy's Western Region","authors":"S. Kolluri, J. Ramamurthy, S. Wong, M. Peterson, P. Yu, Mukund R. Chander","doi":"10.1109/PESGM.2015.7285651","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7285651","url":null,"abstract":"Fault-induced delayed voltage recovery (FIDVR) is a major concern in bulk electric systems, especially in high load growth areas of the system which may be limited in generation and transmission. As part of an overall emergency plan to manage exposure to low voltage conditions and resulting voltage instability under summer peak load conditions, a fast-acting, localized, relay-based undervoltage load shedding (UVLS) scheme has been implemented for Entergy's Western Region. This paper describes the planning considerations and design criteria, followed by implementation details of the relay operation logic programmed using a standard microprocessor-based multi-functional relay. A number of dynamic simulations were performed using PSS/E program and the resulting voltage trajectories were used for testing the relay operation.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115267649","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286493
Ezgi Uzuncan, M. Hesamzadeh
Electricity markets contain many uncertainties such as changes in generation and demand levels. Especially with increasing integration of wind power, uncertainties in generation availability have increased. This increases the network access risk for generators. Therefore, the need for a reliability mechanism for generators has emerged. Firm transmission access is a transmission reliability mechanism for generators. In order to find the optimal firm access for generators, network reliability studies under uncertainties need to be conducted by the network operator. In the literature, deterministic methods have been widely used. Deterministic approaches might lead to sub-optimal results, since they do not consider the likelihood of scenarios. Therefore, this paper proposes a probabilistic approach to estimate the optimal firm transmission access in the presence of wind power and demand uncertainties, through a chance-constrained optimisation model.
{"title":"Optimal firm transmission access using chance-constrained optimisation for renewable integration","authors":"Ezgi Uzuncan, M. Hesamzadeh","doi":"10.1109/PESGM.2015.7286493","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286493","url":null,"abstract":"Electricity markets contain many uncertainties such as changes in generation and demand levels. Especially with increasing integration of wind power, uncertainties in generation availability have increased. This increases the network access risk for generators. Therefore, the need for a reliability mechanism for generators has emerged. Firm transmission access is a transmission reliability mechanism for generators. In order to find the optimal firm access for generators, network reliability studies under uncertainties need to be conducted by the network operator. In the literature, deterministic methods have been widely used. Deterministic approaches might lead to sub-optimal results, since they do not consider the likelihood of scenarios. Therefore, this paper proposes a probabilistic approach to estimate the optimal firm transmission access in the presence of wind power and demand uncertainties, through a chance-constrained optimisation model.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115290777","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286648
K. Karoui, C. Rahmann, A. Arriagada
This paper presents a comprehensive study about low frequency oscillations and transient stability when considering the interconnection of an extreme longitudinal power system with a second system through a tie line. The evolution of critical low frequency oscillation modes is investigated as the power transfer through the tie line increases. Time domain simulations are also conducted in order to verify some of the obtained results in the linear analysis. The simulations are based on detailed models of the two main power systems in Chile. The tie line model is based on technical data of the AC interconnection project which is under construction in Chile today.
{"title":"AC interconnection between longitudinal power systems - The Chilean case","authors":"K. Karoui, C. Rahmann, A. Arriagada","doi":"10.1109/PESGM.2015.7286648","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286648","url":null,"abstract":"This paper presents a comprehensive study about low frequency oscillations and transient stability when considering the interconnection of an extreme longitudinal power system with a second system through a tie line. The evolution of critical low frequency oscillation modes is investigated as the power transfer through the tie line increases. Time domain simulations are also conducted in order to verify some of the obtained results in the linear analysis. The simulations are based on detailed models of the two main power systems in Chile. The tie line model is based on technical data of the AC interconnection project which is under construction in Chile today.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115655357","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7285762
Shaoyan Li, X. Gu, Kai Li, J. Dong
A reasonable unit restoration plan is pivotal for the restoration of a power system after blackout. In this paper, the units to be restored are divided into two types: network-layer units and plant-layer units. By analyzing their interactions between each other and the respective contributions to the system restoration, an optimization method of unit restoration based on NNIA for power system restoration is proposed. The continuous unit restoration process is divided into a series of sequential time steps, and three optimization goals of each time step are designed. Nondominated Neighbor Immune Algorithm and the energizing path optimization algorithm proposed in this paper are employed to solve the multi-objective optimization problem. Then, the grey relation projection algorithm is applied to determine the best scheme for each time step. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system.
{"title":"An optimization method of unit restoration based on NNIA for power system restoration","authors":"Shaoyan Li, X. Gu, Kai Li, J. Dong","doi":"10.1109/PESGM.2015.7285762","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7285762","url":null,"abstract":"A reasonable unit restoration plan is pivotal for the restoration of a power system after blackout. In this paper, the units to be restored are divided into two types: network-layer units and plant-layer units. By analyzing their interactions between each other and the respective contributions to the system restoration, an optimization method of unit restoration based on NNIA for power system restoration is proposed. The continuous unit restoration process is divided into a series of sequential time steps, and three optimization goals of each time step are designed. Nondominated Neighbor Immune Algorithm and the energizing path optimization algorithm proposed in this paper are employed to solve the multi-objective optimization problem. Then, the grey relation projection algorithm is applied to determine the best scheme for each time step. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115711700","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286088
S. Lakshminarayana, Wei Wei, H. Poor, Tony Q. S. Queky
In this work, the combined effects of cooperation (energy aggregation) and storage in mitigating the fluctuations of renewable energy are examined under the setting of distributed energy generation. While cooperation exploits the diversity of renewable energy generation across space, storage exploits the diversity present across time. The trade-off between these two techniques examined, and the regimes under which the two techniques are optimal is investigated. While cooperation between the distributed generating units is restricted by the network power flow (NPF) constraints and thermal limits of the transmission lines, energy storage is in turn restricted by device capacity and imperfections. The problem is formulated as a stochastic optimization problem with the objective of minimizing the time average cost of energy exchange, subject to satisfying the user demands, the NPF and storage constraints. A DC power flow model is used to formulate the NPF constraints. A low complexity online solution to solve this problem is proposed based on the Lyapunov optimization technique, and analytical bounds on the performance of the algorithm are derived. The algorithm results are validated by performing extensive simulations using the IEEE benchmark bus systems. First the importance of incorporating NPF constraints while modeling MG cooperation are illustrated, and it is shown that ignoring them can lead to erroneous power sharing strategies. Then, the benefits of MG cooperation are illustrated in the presence of limited capacity power transmission lines. Further, it is observed that when the battery is inefficient, its utilization is low (regardless of the battery capacity), and most of the residual load is satisfied by exchanging energy among other elements within the grid. However, when the battery is efficient and has a large storage capacity, it is observed that most of the excess renewable energy is stored in the battery, and utilized locally at a future time. Under this regime, cooperation does not yield significant benefits.
{"title":"Cooperation and storage tradeoffs in power-grids under DC power flow constraints and inefficient storage","authors":"S. Lakshminarayana, Wei Wei, H. Poor, Tony Q. S. Queky","doi":"10.1109/PESGM.2015.7286088","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286088","url":null,"abstract":"In this work, the combined effects of cooperation (energy aggregation) and storage in mitigating the fluctuations of renewable energy are examined under the setting of distributed energy generation. While cooperation exploits the diversity of renewable energy generation across space, storage exploits the diversity present across time. The trade-off between these two techniques examined, and the regimes under which the two techniques are optimal is investigated. While cooperation between the distributed generating units is restricted by the network power flow (NPF) constraints and thermal limits of the transmission lines, energy storage is in turn restricted by device capacity and imperfections. The problem is formulated as a stochastic optimization problem with the objective of minimizing the time average cost of energy exchange, subject to satisfying the user demands, the NPF and storage constraints. A DC power flow model is used to formulate the NPF constraints. A low complexity online solution to solve this problem is proposed based on the Lyapunov optimization technique, and analytical bounds on the performance of the algorithm are derived. The algorithm results are validated by performing extensive simulations using the IEEE benchmark bus systems. First the importance of incorporating NPF constraints while modeling MG cooperation are illustrated, and it is shown that ignoring them can lead to erroneous power sharing strategies. Then, the benefits of MG cooperation are illustrated in the presence of limited capacity power transmission lines. Further, it is observed that when the battery is inefficient, its utilization is low (regardless of the battery capacity), and most of the residual load is satisfied by exchanging energy among other elements within the grid. However, when the battery is efficient and has a large storage capacity, it is observed that most of the excess renewable energy is stored in the battery, and utilized locally at a future time. Under this regime, cooperation does not yield significant benefits.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121824559","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286118
Daisuke Sasaki, S. Tsukiyama, M. Matsunaga, Osamu Ishibashi, Shingo Takahashi
In order to support sustainability, a large variety of secondary batteries are necessary, each of which is a battery pack composed of many cells connected in series and parallel. Such battery packs must have connections suitable to its application; however, optimality cannot be claimed deterministically in the design stage, since battery behavior heavily depends on the environment of usage and the variability of production. To cope with this situation, we propose a statistical method for analyzing the lifetime distribution of a battery pack composed of plural cells, given aging curve and its distribution of a single cell. Then, we show a few experimental results to evaluate the performance of the proposed method.
{"title":"A statistical method for analyzing lifetime of a battery pack","authors":"Daisuke Sasaki, S. Tsukiyama, M. Matsunaga, Osamu Ishibashi, Shingo Takahashi","doi":"10.1109/PESGM.2015.7286118","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286118","url":null,"abstract":"In order to support sustainability, a large variety of secondary batteries are necessary, each of which is a battery pack composed of many cells connected in series and parallel. Such battery packs must have connections suitable to its application; however, optimality cannot be claimed deterministically in the design stage, since battery behavior heavily depends on the environment of usage and the variability of production. To cope with this situation, we propose a statistical method for analyzing the lifetime distribution of a battery pack composed of plural cells, given aging curve and its distribution of a single cell. Then, we show a few experimental results to evaluate the performance of the proposed method.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116714261","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286572
Jose L. Morillo, Juan F. Pérez, N. Quijano, A. Cadena
Planning the expansion of distribution systems (DS) is a nonlinear and combinatorial problem that combines technical and regulatory constraints. Commonly, the planning of DS is intended to achieve a radial topology to reduce its complexity. However, in a smart-grid context, distribution feeders are subject to reconfigurations to transfer load between feeders in failure events, or to compensate for voltage profile and power quality issues caused by distributed generation (DG). In this paper we propose a novel methodology for the planning of primary feeders, which considers the DS performance in both open and closedloop arrangements. To this end we introduce the concept of reach current, which we use to define and solve a minimum power-loss flow problem. We solve this problem for each type of conductor considered to find a set of primary-feeder candidates. Additionally, an efficiency evaluation is performed to select the best among the candidate primary feeders. Simulation results on a test system show how this method is able to capture open and closed-loop operations, explicitly considering DG in the DS expansion planning within a smart-grid scheme.
{"title":"Planning distribution primary feeders for smart-grid operation via network flow analysis","authors":"Jose L. Morillo, Juan F. Pérez, N. Quijano, A. Cadena","doi":"10.1109/PESGM.2015.7286572","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286572","url":null,"abstract":"Planning the expansion of distribution systems (DS) is a nonlinear and combinatorial problem that combines technical and regulatory constraints. Commonly, the planning of DS is intended to achieve a radial topology to reduce its complexity. However, in a smart-grid context, distribution feeders are subject to reconfigurations to transfer load between feeders in failure events, or to compensate for voltage profile and power quality issues caused by distributed generation (DG). In this paper we propose a novel methodology for the planning of primary feeders, which considers the DS performance in both open and closedloop arrangements. To this end we introduce the concept of reach current, which we use to define and solve a minimum power-loss flow problem. We solve this problem for each type of conductor considered to find a set of primary-feeder candidates. Additionally, an efficiency evaluation is performed to select the best among the candidate primary feeders. Simulation results on a test system show how this method is able to capture open and closed-loop operations, explicitly considering DG in the DS expansion planning within a smart-grid scheme.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"452 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116763757","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7285633
Xiaping Zhang, Liang Che, M. Shahidehpour
In this paper, the impact of natural gas system on the short-term scheduling with high penetration of renewable energy is illustrated and analyzed. The natural gas infrastructure constraints are integrated into the security-constrained unit commitment model, which minimizes the expected operation cost while considering the variable wind power generation. Benders decomposition is applied to solve the problem with non-linear natural gas network constraints. Illustrative examples demonstrate the effectiveness of the proposed approach for analyzing the impact natural gas system on system scheduling with volatile renewable energy.
{"title":"Impact of natural gas system on short-term scheduling with volatile renewable energy","authors":"Xiaping Zhang, Liang Che, M. Shahidehpour","doi":"10.1109/PESGM.2015.7285633","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7285633","url":null,"abstract":"In this paper, the impact of natural gas system on the short-term scheduling with high penetration of renewable energy is illustrated and analyzed. The natural gas infrastructure constraints are integrated into the security-constrained unit commitment model, which minimizes the expected operation cost while considering the variable wind power generation. Benders decomposition is applied to solve the problem with non-linear natural gas network constraints. Illustrative examples demonstrate the effectiveness of the proposed approach for analyzing the impact natural gas system on system scheduling with volatile renewable energy.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117154031","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286193
S. Rahimi, K. Zhu, S. Massucco, F. Silvestro
Volt/Var Optimization (VVO) function is a key element in operation of distribution networks and major part of advanced Distribution Management Systems (DMS). From planning prospective, VVO function can be used to optimize reactive power flow in distribution network to recommend the best operating condition for the control equipment in a predefined period of time in future (i.e. 24 hour). In fact VVO minimizes the total system loss for a forecasted set of load and computes the optimized setting for transformer on-load tap changers (OLTC), Voltage Regulators (VR), and Capacitor Banks (CB), while system voltage profile is maintained within its limits. In this paper we use a full mixed integer linear programming (MILP) model for solving VVO problem for a planning application. The objective of this paper is to develop a planning VVO engine which can calculate the most probable expected loss of the network for the next 24 hours, and can recommend the best expected operating condition for the control equipment. To model the uncertainty of load, an ARMA model is applied to create several forecasted load scenarios to feed them into the VVO engine (which is implemented in a commercial solver GAMS (General Algebraic Modeling System). The implemented models have been tested on a real distribution network in southern Sweden and results are presented.
{"title":"Stochastic Volt-Var optimization function for planning of MV distribution networks","authors":"S. Rahimi, K. Zhu, S. Massucco, F. Silvestro","doi":"10.1109/PESGM.2015.7286193","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286193","url":null,"abstract":"Volt/Var Optimization (VVO) function is a key element in operation of distribution networks and major part of advanced Distribution Management Systems (DMS). From planning prospective, VVO function can be used to optimize reactive power flow in distribution network to recommend the best operating condition for the control equipment in a predefined period of time in future (i.e. 24 hour). In fact VVO minimizes the total system loss for a forecasted set of load and computes the optimized setting for transformer on-load tap changers (OLTC), Voltage Regulators (VR), and Capacitor Banks (CB), while system voltage profile is maintained within its limits. In this paper we use a full mixed integer linear programming (MILP) model for solving VVO problem for a planning application. The objective of this paper is to develop a planning VVO engine which can calculate the most probable expected loss of the network for the next 24 hours, and can recommend the best expected operating condition for the control equipment. To model the uncertainty of load, an ARMA model is applied to create several forecasted load scenarios to feed them into the VVO engine (which is implemented in a commercial solver GAMS (General Algebraic Modeling System). The implemented models have been tested on a real distribution network in southern Sweden and results are presented.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244341","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 : 2015-07-26DOI: 10.1109/PESGM.2015.7286229
Neha Agarwal, K. Verma, K. R. Niazi, A. Swarnkar, N. Gupta
In recent years the integration of renewable energy sources to distribution system is gaining attention worldwide. However, the intermittent nature of renewable sources creates challenges in integration of Distributed Generation (DG) units. In this paper, a Genetic Algorithm (GA) based methodology has been proposed for optimal penetration of different types of renewable DG units in the distribution system for minimizing annual energy loss and improving the voltage profile considering the intermittent nature of renewable DG units and load. The simulation results verify the suitability of the proposed methodology for all operating scenarios.
{"title":"Optimal penetration of renewable sources for distribution system performance improvement","authors":"Neha Agarwal, K. Verma, K. R. Niazi, A. Swarnkar, N. Gupta","doi":"10.1109/PESGM.2015.7286229","DOIUrl":"https://doi.org/10.1109/PESGM.2015.7286229","url":null,"abstract":"In recent years the integration of renewable energy sources to distribution system is gaining attention worldwide. However, the intermittent nature of renewable sources creates challenges in integration of Distributed Generation (DG) units. In this paper, a Genetic Algorithm (GA) based methodology has been proposed for optimal penetration of different types of renewable DG units in the distribution system for minimizing annual energy loss and improving the voltage profile considering the intermittent nature of renewable DG units and load. The simulation results verify the suitability of the proposed methodology for all operating scenarios.","PeriodicalId":423639,"journal":{"name":"2015 IEEE Power & Energy Society General Meeting","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127275364","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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