黄培东,詹红霞,彭光斌,张曦,张宁,龙飞.促进风电消纳的需求响应与储热CHP联合优化模型[J].电测与仪表,2017,54(14):. Huang Peidong,ZhanHongxia,PengGuangbin,ZhangXi,zhangning,longfei.An Optimization Model Combining Demand Response And CHP With Heat Storage To Promote Accommodation Of Wind Power[J].Electrical Measurement & Instrumentation,2017,54(14):.
促进风电消纳的需求响应与储热CHP联合优化模型
An Optimization Model Combining Demand Response And CHP With Heat Storage To Promote Accommodation Of Wind Power
传统调度方式下系统调峰能力不足,风电弃风严重。先借助需求侧管理调控负荷的能力进行削峰填谷、降低负荷谷时段风电弃风,再在需求响应的引导下,通过对热电联产机组(CHP,combined heat and power)处储热环节的控制,解耦以热定电刚性约束,增强系统调峰能力。以系统煤耗量最小为优化目标,构建了包含需求响应、储热的电热联合优化调度模型。算例采用粒子群算法进行优化求解,模拟结果表明：本方法既能有效减少风电弃风,又能降低系统煤耗。
英文摘要:
Under the traditional scheduling ,system load capacity is insufficient and abandoned wind seriously. Firstly, with the help of regulation load capacity, demand response can adjust user load shifting in load-peak period and reduce abandoned wind, then, under the guidance of demand response, control of the cogeneration unit heat storage link can decouple the electric heat of rigid constraints and improve the ability to load capacity. As the optimization goal of minimum system coal consumption quantity , construct include demand response, thermal storage optimization scheduling model of electro-thermal, and take the particle swarm algorithm to finish . The results of the example show the methods can effectively reduce wind wind, and can reduce the coal consumption of the system.
