PMU最优配置问题的混合优化算法

为使得电力系统在完全可观测的条件下,PMU安装数目最少,提出了一种混合优化算法以解决相量测量单元PMU的最优配置问题.混合优化算法以粒子群优化算法为主体,引入交叉、变异操作,并结合模拟退火机制控制粒子的更新.在处理解的约束问题时,采用了一种基于概率的启发式修补策略,避免修复后的解特征单一.将混合算法与其他算法在多个IEEE标准系统上进行了比较分析,结果表明在较大规模系统上,混合优化算法收敛率比标准粒子群算法提高数倍,计算量比模拟退火算法减少了数十倍,表明了较好的可行性和较高的效率.

Hybrid Optimization Algorithm for Optimal Phasor Measurement Unit Placement

This paper presents a hybrid optimization algorithm to solve the problem of optimal phasor measurement unit placement. The optimal PMU placement problem is formulated to guarantee both full observability of the network and minimal number of PMUs. In the hybrid optimization algorithm, the mechanism of simulated annealing is involved into original particle swarm optimization; crossover and mutation operators are applied to increase the diversity of the swarm. To deal with the constraints, an improved heuristic reparation strategy is developed and it can avoid generating too many similar solutions. Simulation results on several IEEE systems show that for large systems the hybrid optimization algorithm convergence rate is several times than that of PSO but the calculation cost is several ten times less than that of SA and the algorithm is feasible and effective.