电力系统自动化2011，Vol.35Issue(17)：14-19,6.
基于机会约束规划的风电预测功率分级处理
Classified Treatment of Wind Power Predictive Power Based on Chance Constrained Programming
摘要
Abstract
Improving the accuracy of current wind power prediction is very difficult and uneconomic,but power system dispatching and wind power control require accurate power curve.A novel method for classified treatment of wind farms active power using forecasting results is presented,which can reduce the influence of prediction error on the decision.The new method is based on predictive power.Considering the influence of predictive error distribution,a classified mode based on the reliability of predictive power is founded using chance constrained programming method,and predictive power is classified into three types： base load output,suboptimal output and high-frequency output.With the prerequisite of ensuring maximum use of wind power output,the classified treatment can distinguish different reliability components,supply decision basis for power dispatching and wind power control,and reduce the decision risk effectively.The policy iteration and particle swarm algorithm are used to solve the model,and the classified treatment is simulated by 24 h data of actual wind farms.The results verify the feasibility and effectiveness of the method.关键词
风力发电/预测功率/分级处理/机会约束规划/粒子群算法Key words
wind power/predictive power/classified treatment/chance constrained programming/particle swarm algorithm分类
动力与电气工程引用本文复制引用
王成福,梁军,张利,牛远方,贠志皓,韩学山..基于机会约束规划的风电预测功率分级处理[J].电力系统自动化,2011,35(17):14-19,6.基金项目
山东省自然科学基金资助项目（ZR2010EM055）~~ （）
