电力系统保护与控制Issue(10)：46-54,9.
基于SVM-MOPSO混合智能算法的配电网分布式电源规划
Distributed generation planning in distribution network based on hybrid intelligent algorithm by SVM-MOPSO
摘要
Abstract
Regarding stochastic disturbance in power system brought by grid-connected distributed generation (DG), generally considering operational effectiveness, along with timing characteristics of wind speed and sunlight intensity, taking economy, power quality and environmental efficiency as goals, the optimization model of stochastic chance-constrained programming is built. The hybrid intelligent algorithm is used, which simulates the uncertainty functions based on support vector machine (SVM) and solves the model by multi-objective particle swarm optimization (MOPSO), and then the Pareto non-inferior decision set is obtained. Simulation results show that the planning model can fully take into account randomness, timing characteristics and grid-connected probability distribution of DG, and improve the efficiency of the algorithm, then verify the rationality and validity of the proposed approach. Moreover, the introduction of Pareto front gives fully choices to policymakers and possesses more engineering value.关键词
分布式电源规划/时序特性/混合智能算法/支持向量机模拟/多目标粒子群算法Key words
distributed generation planning/timing characteristics/hybrid intelligent algorithm/support vector machine simulation/multi-objective particle swarm optimization分类
信息技术与安全科学引用本文复制引用
刘煌煌,雷金勇,蔡润庆,陈钢,杨振纲,刘前进..基于SVM-MOPSO混合智能算法的配电网分布式电源规划[J].电力系统保护与控制,2014,(10):46-54,9.基金项目
广东省战略性新兴产业核心技术攻关项目(2012A032300001) （2012A032300001）
