This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system (FACTS) devices in a power system using a multi-objective optimization function. Thyristo...This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensators (TCSCs) and static var compensators (SVCs) are the utilized FACTS devices. Our objectives are active power loss reduction, newly introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, were considered in the optimum allocation. A goal attainment method based on the genetic algorithm (GA) was used to approach the global optimum. The estimated annual load profile was utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. Fars Regional Electric Network was selected as a practical system to validate the performance and effectiveness of the proposed method. The entire investment of the FACTS devices was paid off and an additional 2.4% savings was made. The cost reduction of peak point power generation implies that power plant expansion can be postponed.展开更多
针对提高电网静态电压稳定性、输电能力、暂态稳定性等多个目标,设计灵活交流输电系统(flexible AC transmission systems,FACTS)装置优化配置的数学模型。在分析几种典型FACTS装置、静止无功补偿器(static var compensator,SVC)、静止...针对提高电网静态电压稳定性、输电能力、暂态稳定性等多个目标,设计灵活交流输电系统(flexible AC transmission systems,FACTS)装置优化配置的数学模型。在分析几种典型FACTS装置、静止无功补偿器(static var compensator,SVC)、静止同步补偿器(static synchronous compensator,STATCOM)和可控串联补偿器(thyristor controlled series compensator,TCSC)功能特性的基础上,结合不同FACTS装置的投资费用,给出求解单目标最优解的计算方法。提出一种利用智能帕雷托(smartPareto,sPareto)解的方法获取多目标函数帕雷托(Pareto)前沿最精简的表示形式,直接反映各配置方案之间的折衷,实现方案的优化选择。在新英格兰39节点系统上对所提出的方法进行仿真验证,结果证实了上述方法的有效性和经济性。展开更多
This paper presents an efficient interactive differential evolution ODE） to solve the multi-objective security environmental/economic dispatch （SEED） pro- blem considering multi shunt flexible AC transmission syst...This paper presents an efficient interactive differential evolution ODE） to solve the multi-objective security environmental/economic dispatch （SEED） pro- blem considering multi shunt flexible AC transmission system （FACTS） devices. Two sub problems are proposed. The first one is related to the active power planning to minimize the combined total fuel cost and emissions, while the second is a reactive power planning （RPP） using multi shunt FACTS device based static VAR compensator （SVC） installed at specified buses to make fine corrections to the voltage deviation, voltage phase profiles and reactive power violation. The migration operation inspired from biogeography-based optimization （BBO） algorithm is newly introduced in the proposed approach, thereby effectively exploring and exploiting promising regions in a space search by creating dynamically new efficient partitions. This new mechanism based migration between individuals from different subsystems makes the initial partitions to react more by changing experiences. To validate the robustness of the proposed approach, the proposed algorithm is tested on the Algerian 59-bus electrical network and on a large system, 40 generating units considering valve-point loading effect. Comparison of the results with recent global optimization methods show the superiority of the proposed IDE approach and confirm its potential for solving practical optimal power flow in terms of solution quality and convergence characteristics.展开更多
This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated envi...This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.展开更多
文摘This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensators (TCSCs) and static var compensators (SVCs) are the utilized FACTS devices. Our objectives are active power loss reduction, newly introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, were considered in the optimum allocation. A goal attainment method based on the genetic algorithm (GA) was used to approach the global optimum. The estimated annual load profile was utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. Fars Regional Electric Network was selected as a practical system to validate the performance and effectiveness of the proposed method. The entire investment of the FACTS devices was paid off and an additional 2.4% savings was made. The cost reduction of peak point power generation implies that power plant expansion can be postponed.
文摘针对提高电网静态电压稳定性、输电能力、暂态稳定性等多个目标,设计灵活交流输电系统(flexible AC transmission systems,FACTS)装置优化配置的数学模型。在分析几种典型FACTS装置、静止无功补偿器(static var compensator,SVC)、静止同步补偿器(static synchronous compensator,STATCOM)和可控串联补偿器(thyristor controlled series compensator,TCSC)功能特性的基础上,结合不同FACTS装置的投资费用,给出求解单目标最优解的计算方法。提出一种利用智能帕雷托(smartPareto,sPareto)解的方法获取多目标函数帕雷托(Pareto)前沿最精简的表示形式,直接反映各配置方案之间的折衷,实现方案的优化选择。在新英格兰39节点系统上对所提出的方法进行仿真验证,结果证实了上述方法的有效性和经济性。
文摘This paper presents an efficient interactive differential evolution ODE） to solve the multi-objective security environmental/economic dispatch （SEED） pro- blem considering multi shunt flexible AC transmission system （FACTS） devices. Two sub problems are proposed. The first one is related to the active power planning to minimize the combined total fuel cost and emissions, while the second is a reactive power planning （RPP） using multi shunt FACTS device based static VAR compensator （SVC） installed at specified buses to make fine corrections to the voltage deviation, voltage phase profiles and reactive power violation. The migration operation inspired from biogeography-based optimization （BBO） algorithm is newly introduced in the proposed approach, thereby effectively exploring and exploiting promising regions in a space search by creating dynamically new efficient partitions. This new mechanism based migration between individuals from different subsystems makes the initial partitions to react more by changing experiences. To validate the robustness of the proposed approach, the proposed algorithm is tested on the Algerian 59-bus electrical network and on a large system, 40 generating units considering valve-point loading effect. Comparison of the results with recent global optimization methods show the superiority of the proposed IDE approach and confirm its potential for solving practical optimal power flow in terms of solution quality and convergence characteristics.
文摘This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.
