Aimed at solving the problem of optimal planning for high voltage distribution substations,an efficient method is put forward.The method divides the problem into two sub-problems:source locating and combina tional opt...Aimed at solving the problem of optimal planning for high voltage distribution substations,an efficient method is put forward.The method divides the problem into two sub-problems:source locating and combina tional optimization.The algorithm of allocating and locating alternatively(ALA)is widely used to deal with the source lo cating problem,but it is dependent on the initial location to a large degree.Thus,some modifications were made to the ALA algorithm,which could greatly improve the quality of solutions.In addition,considering the non-convex and nonconcave nature of the sub-problem of combinational optimization,the branch-and-bound technique was adopted to obtain or approximate a global optimal solution.To improve the efficiency of the branch-and-bound technique,some heuristic principles were proposed to cut those branches that may generate a global optimization solution with low probability.Examples show that the proposed algorithm meets the requirement of engineering and it is an effective approach to rapidly solve the problem of optimal planning for high voltage distribution substations.展开更多
This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for...This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.展开更多
以高压静止无功补偿器(static var compensator,SVC)为研究对象,针对传统比例-积分-微分(proportional integral differential,PID)控制器难以对设定值进行有变化的跟踪和对扰动进行抑制的缺陷,提出在传统PID控制器的基础上加入一个2阶...以高压静止无功补偿器(static var compensator,SVC)为研究对象,针对传统比例-积分-微分(proportional integral differential,PID)控制器难以对设定值进行有变化的跟踪和对扰动进行抑制的缺陷,提出在传统PID控制器的基础上加入一个2阶微分控制环节以实现公共连接点的电压稳定控制,并采用改进的神经网络粒子群优化算法对控制器的参数进行优化,使得系统瞬态响应性能和控制性能达到最佳。仿真和实验结果验证了所提出的控制方法能够保证快速、无超调的跟踪电压设定值,具有较强的鲁棒性、适应性,提高了SVC系统的补偿精度。展开更多
基金supported by the National Natural Science Foundation of China (Grant No.59877017).
文摘Aimed at solving the problem of optimal planning for high voltage distribution substations,an efficient method is put forward.The method divides the problem into two sub-problems:source locating and combina tional optimization.The algorithm of allocating and locating alternatively(ALA)is widely used to deal with the source lo cating problem,but it is dependent on the initial location to a large degree.Thus,some modifications were made to the ALA algorithm,which could greatly improve the quality of solutions.In addition,considering the non-convex and nonconcave nature of the sub-problem of combinational optimization,the branch-and-bound technique was adopted to obtain or approximate a global optimal solution.To improve the efficiency of the branch-and-bound technique,some heuristic principles were proposed to cut those branches that may generate a global optimization solution with low probability.Examples show that the proposed algorithm meets the requirement of engineering and it is an effective approach to rapidly solve the problem of optimal planning for high voltage distribution substations.
文摘This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.
文摘以高压静止无功补偿器(static var compensator,SVC)为研究对象,针对传统比例-积分-微分(proportional integral differential,PID)控制器难以对设定值进行有变化的跟踪和对扰动进行抑制的缺陷,提出在传统PID控制器的基础上加入一个2阶微分控制环节以实现公共连接点的电压稳定控制,并采用改进的神经网络粒子群优化算法对控制器的参数进行优化,使得系统瞬态响应性能和控制性能达到最佳。仿真和实验结果验证了所提出的控制方法能够保证快速、无超调的跟踪电压设定值,具有较强的鲁棒性、适应性,提高了SVC系统的补偿精度。
