Parallel Multipopulation Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control
Parallel Multipopulation Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control
复制标题
电压和无功功率控制的并行多群差分进化粒子群优化
DOI：
10.1002/eej.23100
复制
发表时间：
2018
影响因子：
0.4
通讯作者：
吉田武尊，福山良和
中科院分区：
文献类型：
--
作者：
吉田武尊・福山良和;吉田武尊，福山良和
提出了一种用于电压无功控制(VQC)的并行多种群差分进化粒子群算法。该问题可归结为一个混合整数非线性优化问题，各种进化计算技术已被应用于该问题，包括粒子群算法、微分进化算法和DEEPSO算法。由于VQC是在线控制的一种，因此需要加快计算速度。此外，解决方案的质量仍有改进的空间。为了加快计算速度，提高解的质量，本文采用并行多种群DEEPSO算法。将该方法应用于IEEE 30、57和118节点系统。结果表明，与传统的进化计算方法相比，该方法具有计算速度快、有功网损小等优点。
This paper presents parallel multipopulation differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control (VQC). The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Since VQC is one of the online controls, speed‐up of computation is required. Moreover, there is still room for improvement in solution quality. This paper applies parallel multipopulation DEEPSO in order to speed up the calculation and improve solution quality. The proposed method is applied to IEEE 30, 57, and 118 bus systems. The results indicate that the proposed method can realize fast computation and minimize more active power losses than the conventional evolutionary computation techniques.