广东工业大学学报2017，Vol.34Issue(1)：50-54,64,6.DOI:10.12052/gdutxb.160087
计及风电场并网的机会约束规划的机组组合优化
Unit Commitment Optimization Based on Chance-constrained Programming in Wind Power Integrated System
摘要
Abstract
Because of the random nature of wind power output, a unit commitment optimization model with wind farm based on chance-constrained programming is proposed. The constraints of both power system and generator are considered. Chaos Discrete Particle Swarm Optimization algorithm (CDPSO) is used to arrange thermal unit commitment startup and shutdown and cultural chaos particle swarm optimization algorithm (CCPSO) is proposed to solve economic load dispatch. Based on it, Multi-objective optimization unit commitment optimization problem in wind power integrated system under the energy saving and lower emission is considered. The Monte Carlo stochastic simulation techniques verified opportunity constraints and the superiority of opportunities constraints coordination programs profit and risk under different confidence level are analyzed. It provides a new way of thinking to coordinating profit, risk and environment benefits. A system with one wind power farm and 10 coal-fired plants was taken as a study example and the results show that the model is correct.关键词
节能减排/机组组合优化/混沌文化粒子群优化算法/机会约束规划Key words
energy conservation/unit commitment optimization/chaos cultural particle swarm optimization/chance-constrained programming分类
信息技术与安全科学引用本文复制引用
陈璟华,梁丽丽,丁林军,周俊,刘国祥..计及风电场并网的机会约束规划的机组组合优化[J].广东工业大学学报,2017,34(1):50-54,64,6.基金项目
广东省自然科学基金资助项目(S2013040013776)；广东省教育厅育苗工程项目(2013LYM_0019) （S2013040013776）
