Multi-objective optimization of reactive power dispatch in power systems via SPMGSO algorithm

Mohammadi Mohsen, H. Siahkali
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引用次数: 1

Abstract

Nowadays, developments in computer science has made parallel processing feasible. One of the main control problems in power systems is the control of optimal reactive power dispatch. In this problem, we try to optimize specific objective functions using a series of control variables, while a set of constraints are met. This paper deals with multi-objective and simultaneous optimization of reactive power dispatch in power systems through parallel processing. Three objective functions are intended: reduction of active power losses, reduction of voltage deviation, and increasing voltage stability. To solve the optimization problem, Strength Pareto Multi-group Search Optimizer (SPMGSO) algorithm will be used. This algorithm employs parallel processing, and as a result, it saves the required time to solve the problem. This optimization technique also yields a set of non-dominated optimal solutions. The operator of the power system is able to utilize a multi-criteria decision technique based on M matrices to determine the best solution, and to apply the relevant control variables on the power system. A comparison of the simulation results on IEEE 30-bus system with results of NSGAII algorithm attests that SPMGSO algorithm is satisfactory.
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基于SPMGSO算法的电力系统无功调度多目标优化
如今,计算机科学的发展使并行处理成为可能。无功最优调度控制是电力系统的主要控制问题之一。在这个问题中,我们尝试使用一系列控制变量来优化特定的目标函数,同时满足一组约束。本文采用并行处理的方法研究了电力系统无功调度的多目标同步优化问题。有三个目标功能:减少有功功率损耗,减少电压偏差,提高电压稳定性。为了解决优化问题,将使用强度帕累托多群搜索优化算法(SPMGSO)。该算法采用并行处理,节省了求解问题所需的时间。这种优化技术也产生了一组非支配最优解。电力系统的操作员能够利用基于M矩阵的多准则决策技术来确定最优解,并将相关控制变量应用于电力系统。将SPMGSO算法与NSGAII算法在IEEE 30总线系统上的仿真结果进行了比较,证明了SPMGSO算法的有效性。
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