电网技术Issue(4)：1019-1024,6.
基于混沌群粒子优化−情景约简算法的混合电力系统机组组合模型及其求解
Unit Commitment Model and Solution in the Hybrid Power System Based on Chaos Embedded Particle Swarm Optimization-Scenario Reduction Algorithms
摘要
Abstract
Large-scale grid-integration of new energy sources such as wind power generation and so on leads to new problems in secure and stable operation of traditional power grids. For a hybrid power grid containing thermal power plants, wind farms and energy storage equipments, by means of constructing a unit commitment model and the stochastic property of wind power output uncertainty is simulated by scenario tree. Leading chaos embedded particle swarm optimization (CEPSO) into scenario reduction algorithms (SRA) the results of stochastic simulation and the ability to search the optimal solution are improved. Taking a hybrid power system composed of a wind farm and a 10-machine system as simulation example, simulation results show that the obtained unit commitment scheme can dispatch as many wind power units as possible and the operational cost of thermal generation units can be reduced to suit to the demand of energy conservation and emission reduction.关键词
机组组合/情景树方法/混沌粒子群/情景约简算法/不确定性Key words
unit commitment (UC)/scenario tree/chaos embedded particle swarm optimization (CEPSO)/scenario reduction algorithms (SRA)/uncertainty分类
信息技术与安全科学引用本文复制引用
田廓..基于混沌群粒子优化−情景约简算法的混合电力系统机组组合模型及其求解[J].电网技术,2013,(4):1019-1024,6.基金项目
国家自然科学基金项目(71271082) （71271082）
美国能源基金会项目(G-1006-12658) （G-1006-12658）
