Abstract:In allusion to the problem that the supply-demand imbalance of synchronous phasor measurement units (abbr. PMUs) due to large number of nodes in the distribution network but low investment cost, a multi-objective optimization configuration model of PMU, in which the number of PMU configuration and the state estimation error were considered, was established to minimize both the number of required PMU and the state estimation error. An improved whale algorithm was utilized to solve the established model. Firstly, non-dominated ordering and congestion calculation were led in to select and order the Pareto non-dominated solutions to ensure the ability of the algorithm to solve the global optimum. Secondly, the Levy flight strategy was led in to perturb the spiral update position of the whale algorithm in a variational manner to make the algorithm not easy to fall into local optimal. Finally, the simulation calculation on IEEE 33 standard node system by the optimal allocation model was conducted. Simulation results show that comparing with genetic algorithm and particle swam optimization, there are higher feasibility and effectiveness when the PMU multi-objective optimal configuration model is solved by the improved whale algorithm.
标题：基于改进鲸鱼优化算法的同步相量测量单元多目标优化配置
英文标题：Multi-objective Optimization Configuration of Synchronized Phasor Measurement Units Based on Improved Whale Optimization Algorithm
