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Dynamic optimal reactive power dispatch based on parallel particle swarm optimization algorithm

机译:基于并行粒子群算法的动态最优无功调度

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In this paper, Message Passing Interface (MPI) based parallel computation and particle swarm optimization (PSO) algorithm are combined to form the parallel particle swarm optimization (PPSO) method for solving the dynamic optimal reactive power dispatch (DORPD) problem in power systems. In the proposed algorithm, the DORPD problem is divided into smaller ones, which can be carried out concurrently by multi-processors. This method is evaluated on a group of IEEE power systems test cases with time-varying loads in which the control of the generator terminal voltages, tap position of transformers and reactive power sources are involved to minimize the transmission power loss and the costs of adjusting the control devices. The simulation results demonstrate the accuracy of the PPSO algorithm and its capability of greatly reducing the runtimes of the DORPD programs.
机译:本文将基于消息传递接口(MPI)的并行计算与粒子群优化(PSO)算法相结合,形成了并行粒子群优化(PPSO)方法,用于解决电力系统动态最优无功调度问题。在提出的算法中,DORPD问题被分为较小的问题,可以由多处理器同时执行。该方法在一组带有时变负载的IEEE电力系统测试用例中进行了评估,其中涉及对发电机端电压,变压器抽头位置和无功电源的控制,以最大程度地减少传输功率损耗和调整电源的成本。控制设备。仿真结果证明了PPSO算法的准确性及其大大减少DORPD程序运行时间的能力。

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