引用本文: | 刘煌煌,雷金勇,蔡润庆,等.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,2014,42(10):46-54.[点击复制] |
LIU Huang-huang,LEI Jin-yong,CAI Run-qing,et al.Distributed generation planning in distribution network based on hybrid intelligent algorithm by SVM-MOPSO[J].Power System Protection and Control,2014,42(10):46-54[点击复制] |
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摘要: |
针对分布式电源(Distributed Generation,DG)并网给电力系统带来的随机扰动,综合考虑配电网运行效益,计及风光时序特性,以经济性、电能质量及环保性为目标,搭建了机会约束规划模型。采用混合智能算法求解,即基于支持向量机(Support Vector Machine,SVM)算法模拟优化变量到目标函数以及约束条件映射的不确定性函数,运用多目标粒子群算法(Multi-Objective Particle Swarm Optimization,MOPSO)求解模型,得出Pareto非劣决策集并 |
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 |
DOI:10.7667/j.issn.1674-3415.2014.10.008 |
投稿时间:2013-07-25 |
基金项目:广东省战略性新兴产业核心技术攻关项目(2012A032300001) |
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Distributed generation planning in distribution network based on hybrid intelligent algorithm by SVM-MOPSO |
LIU Huang-huang,LEI Jin-yong,CAI Run-qing,CHEN Gang,YANG Zhen-gang,LIU Qian-jin |
(College of Electric Power, South China University of Technology, Guangzhou 510640, China;Electric Power Research Institute of China Southern Power Grid, Guangzhou 510080, China;China Southern Power Grid Synthetic Energy Co., Ltd, Guangzhou 510075, China;China Southern Power Grid Co., Ltd, Guangzhou 510623, China) |
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 |
Key words: distributed generation planning timing characteristics hybrid intelligent algorithm support vector machine simulation multi-objective particle swarm optimization |