集成粒子群优化算法在电网规划中的应用

电网规划是一个大规模、复杂的、具有非线性离散变量和多约束的多目标数学优化问题。在优化过程中,考虑了投资费用、可靠性和对环境的影响等三个因素。提出将模拟退火优化方法嵌入粒子群优化算法中,以此构建集成粒子群优化算法。在搜索过程中还加入变异操作来增加种群多样性,以避免早熟收敛。局部搜索增加了算法的开发能力,而变异操作提高了算法的探测能力。探测与开发能力的平衡,通过两个阈值来实现。通过对一220kv电力传输系统的实例研究表明,集成粒子群优化算法局部搜索能力有显著提高。

Application of Integrated Particle Swarm Optimization to Transmission Network Optimal Planning

Power system transmission network planning is formulated as a multi-objective mathematical optimization problem. Three objectives: investment cost, reliability and environmental impact were considered in the optimization. An integrated particle swarm optimization (IPSO) was proposed, where the simulated annealing optimization algorithm was combined with PSO to speed up the local search, and mutation operation was embedded to avoid the common defect of premature convergence. Two thresholds were adopted to balance the exploration and exploitation abilities. The performance of new algorithm was demonstrated through a numerical example of the 220kv transmission network system and the obtained results show that the local search ability is improved.