电网技术2012，Vol.36Issue(3)：134-139,6.
考虑地理因素的改进量子粒子群算法在多目标电网规划中的应用
Application of Improved Quantum Particle Swarm Optimization in Power Network Planning Considering Geography Factor
摘要
Abstract
In allusion to the balance optimization of multi-object power network planning and to built power network planning model taking reliability and economy as objects, an improved quantum particle swarm optimization （QPSO） is proposed; the Pareto domination is adopted to update the individual and local optimal of particle as well as to define the max-min distance of particle turbulence, and the non-dominated solution is clipped by turbulent distance; a convergence factor K is led in to speed up the convergence speed of particle that jumps out of local optimal. Meanwhile, the impacts of tmcertain factors of geographic environment where the power network being planned is located are taken into account, thus the penalty factor of geographic barrier is led into the objective function of the planning. Simulation results of an 18-bus power network planning show that the number of obtained Pareto optimal solutions, the quality of solutions and their distribution by the proposed improved （QPSO） algorithm are much better than the solutions solved by non-dominated sorting generic algorithm （NSGA） and multi-objective evolution algorithm （MOEA）.关键词
多目标优化/量子粒子群算法/电网规划Key words
KEY WORDS： multi-objective optimization/quantum particleswarm optimization （QPSO）/power network planning分类
信息技术与安全科学引用本文复制引用
曹承栋,常鲜戎,刘艳..考虑地理因素的改进量子粒子群算法在多目标电网规划中的应用[J].电网技术,2012,36(3):134-139,6.基金项目
国家自然科学基金项目f51077052/E0704）. （）
