This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Distribution system analysis(DSA)currently faces several challenges due to inclusion of distributed energy resources(DERs),which have many characteristics,such as inherent variability,uncertainty,possibility of flexib...Distribution system analysis(DSA)currently faces several challenges due to inclusion of distributed energy resources(DERs),which have many characteristics,such as inherent variability,uncertainty,possibility of flexible four quadrant converter operations with distributed generation(DG),and the need for efficient operations to improve reliability of the supply system.This article argues for a high degree of case-specificity and discusses its implications in distribution networks with increasing DG penetration.The research is based on the exhaustive yearly simulation analyses of 132 candidate scenarios and investigates the effects of feeder-specific factors,such as geo-electric size and feeder spread,load density,and phase unbalancing.Nineteen(19)feeder variants—with phase-domain detailed modeling of all feeder components,including DGs,are subjected to increasing penetration of photovoltaic generation without altering the type and location of DGs.The objective is to analyze the role of feederspecific factors on feeder response characteristics in terms of annualized operational parameters,such as energy losses,feeder voltage profile,average power factor,and peak demand at a substation node,as well as tap-changer operations of voltage regulating equipment and their interaction with shunt compensation.Recorded annual load profiles—industrial,commercial,and residential—as well as location specific weather data are used to simulate the candidate scenarios based on three IEEE test feeders and one actual spot network in India.Results signify the consideration of feeder-specific factors in the planning exercise of grouping“similar”feeders for formulating the strategies that can improve daily operations of distribution feeders.The demonstrated case-specificity also implies that optimization algorithms for improved operations with DGs will need to be based on an integrated approach that accounts for feeder-specific factors as well as cyclic variability of DERs.展开更多
Low-voltage(LV) distribution networks are unbalanced and present loads with nonlinear behavior, which introduce harmonics in the networks. The predictable increase in photovoltaic microgeneration(PV μG) accentuates t...Low-voltage(LV) distribution networks are unbalanced and present loads with nonlinear behavior, which introduce harmonics in the networks. The predictable increase in photovoltaic microgeneration(PV μG) accentuates this unbalanced characteristic, as well as poses new technical problems,namely voltage rise and reverse power flow. To accurately account for the distributed PV and loads in the LV network, unbalanced three-phase power flow algorithms should be utilized,where different approaches may be used to represent lines with various degrees of accuracy. The more accurate algorithm considers the electromagnetic coupling between the line conductors,whereas the simpler algorithm represents each conductor of the line as a single-phase line with pure resistive behavior. This paper aims to analyze the influence of the line model on the load flow in a highly unbalanced LV network with a high penetration of PV production, and considers the impact of the harmonics produced by nonlinear loads. Based on the results obtained,it is possible to identify the most suitable model to be used, depending on the study to be performed. Different scenarios of PV generation and loads are addressed in this paper.展开更多
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金This work was supported in part by Indian Institute of Technology Gandhinagar in the form of“Additional Fellowship”to Kalpesh Joshi.
文摘Distribution system analysis(DSA)currently faces several challenges due to inclusion of distributed energy resources(DERs),which have many characteristics,such as inherent variability,uncertainty,possibility of flexible four quadrant converter operations with distributed generation(DG),and the need for efficient operations to improve reliability of the supply system.This article argues for a high degree of case-specificity and discusses its implications in distribution networks with increasing DG penetration.The research is based on the exhaustive yearly simulation analyses of 132 candidate scenarios and investigates the effects of feeder-specific factors,such as geo-electric size and feeder spread,load density,and phase unbalancing.Nineteen(19)feeder variants—with phase-domain detailed modeling of all feeder components,including DGs,are subjected to increasing penetration of photovoltaic generation without altering the type and location of DGs.The objective is to analyze the role of feederspecific factors on feeder response characteristics in terms of annualized operational parameters,such as energy losses,feeder voltage profile,average power factor,and peak demand at a substation node,as well as tap-changer operations of voltage regulating equipment and their interaction with shunt compensation.Recorded annual load profiles—industrial,commercial,and residential—as well as location specific weather data are used to simulate the candidate scenarios based on three IEEE test feeders and one actual spot network in India.Results signify the consideration of feeder-specific factors in the planning exercise of grouping“similar”feeders for formulating the strategies that can improve daily operations of distribution feeders.The demonstrated case-specificity also implies that optimization algorithms for improved operations with DGs will need to be based on an integrated approach that accounts for feeder-specific factors as well as cyclic variability of DERs.
基金supported by national funds through Funda??o para a Ciência e a Tecnologia (FCT)(No. UIDB/50021/2020)。
文摘Low-voltage(LV) distribution networks are unbalanced and present loads with nonlinear behavior, which introduce harmonics in the networks. The predictable increase in photovoltaic microgeneration(PV μG) accentuates this unbalanced characteristic, as well as poses new technical problems,namely voltage rise and reverse power flow. To accurately account for the distributed PV and loads in the LV network, unbalanced three-phase power flow algorithms should be utilized,where different approaches may be used to represent lines with various degrees of accuracy. The more accurate algorithm considers the electromagnetic coupling between the line conductors,whereas the simpler algorithm represents each conductor of the line as a single-phase line with pure resistive behavior. This paper aims to analyze the influence of the line model on the load flow in a highly unbalanced LV network with a high penetration of PV production, and considers the impact of the harmonics produced by nonlinear loads. Based on the results obtained,it is possible to identify the most suitable model to be used, depending on the study to be performed. Different scenarios of PV generation and loads are addressed in this paper.
