中国电机工程学报Issue(16)：4077-4085,9.DOI:10.13334/j.0258-8013.pcsee.2015.16.010
基于纵横交叉-拉丁超立方采样蒙特卡洛模拟法的分布式电源优化配置
Optimal Distributed Generator Allocation Method Based on Correlation Latin Hypercube Sampling Monte Carlo Simulation Embedded Crisscross Optimization Algorithm
摘要
Abstract
As large-scale of plug-in electric vehicles (PEV) and renewable energy sources (RES) such as wind and solar energy integrated into power grid, the smart distribution network planning inevitably needs to consider more uncertainties. Given this background, under the chance constrained programming framework, a multi-objective optimal distributed generation planning model was established considering the randomness and correlation of RES generation and PEV, in which the environmental cost, DG’s total cost and network loss were taken as the objectives. A correlation Latin hypercube sampling Monte Carlo simulation (CLMCS) embedded crisscross optimization algorithm (CSO)-based approach (CSO-CLMCS) was proposed to solve the optimization model. The method firstly used CLMCS to calculate the probabilistic load flow (PLF) according to the probability model of random variables. Then the constraint conditions were checked and the objective function value was obtained using the result of PLF. Finally, the optimal planning scheme was obtained by a new smart search algorithm, i.e. CSO. The simulation was conducted on an actual distribution network. The results validate the feasibility and effectiveness of the proposed model and method.关键词
分布式电源/电动汽车/多目标规划/蒙特卡洛模拟/纵横交叉算法Key words
distributed generation (DG)/plug-in electric vehicle (PEV)/multi-objective planning/Monte Carlo simulation/crisscross optimization algorithm分类
信息技术与安全科学引用本文复制引用
彭显刚,林利祥,刘艺,王星华,孟安波..基于纵横交叉-拉丁超立方采样蒙特卡洛模拟法的分布式电源优化配置[J].中国电机工程学报,2015,(16):4077-4085,9.基金项目
广东省自然科学基金项目(10151009001000045)。 Guangdong Nature Science Foundation (10151009001000045) （10151009001000045）
