计及多类型需求响应的风电消纳随机优化调度模型  

Wind Power Accommodation Stochastic Optimization Model With Multi-type Demand Response

作　　者：鞠立伟[1] 秦超[1] 吴鸿亮 何璞玉 于超[3] 谭忠富[1] 

机构地区：[1]华北电力大学能源经济与环境研究所,北京市昌平区102206 [2]南方电网科学研究院,广东省广州市510080 [3]电力规划设计总院,北京市西城区100120

出　　处：《电网技术》2015年第7期1839-1846,共8页Power System Technology

基　　金：国家自然科学基金项目(71273090);教育部中央高校基本科研业务费专项资金(2015XS29)~~

摘　　要：考虑需求响应并基于鲁棒随机优化理论,构建了含风电的电力系统发电调度优化模型。首先,引入价格型需求响应模型和激励型需求响应模型,设定并建立电动汽车、商业用户、工业用户和居民用户参与需求响应的模式及收益函数。然后,为解决风电出力不确定性问题,利用鲁棒随机优化理论,建立需求响应参与下的风电消纳鲁棒随机优化模型。最后,以IEEE 36节点10机系统接入650 MW风电场为算例进行分析,结果显示:鲁棒随机优化理论能够克服风电不确定性对系统调度的影响;激励型需求响应能够转移用户负荷分布,但削减负荷的能力不如价格型明显,价格型需求响应能够削减负荷峰时需求,但不能转移用户用电需求,同时引入2者提升系统风电消纳的效果最强;同时,需求响应能够激励不同用户参与系统备用服务,获得直观的经济效益,有利于调动用户侧参与发电侧调度优化。In this paper demand response and robust stochastic optimization theory are presented, electric power system generating dispatching optimization model is constructed. Firstly, the price demand response model and encourage demand response model are presented, demand response model and profit function of electric vehicle, business users, industry users and residential users are set and constructed. Secondly, robust stochastic optimization theory constructing wind power consumption robust stochastic optimization model with demand response is presented. Finally, IEEE 36-node 10-unit system with 650 MW wind power farm is taken as simulation system. Simulation results show that robust stochastic optimization theory can overcome the uncertainty of wind power on system dispatching; incentive-based demand response（IBDR） can transfer users＇ load distribution, but cutting load ability is less obvious than price-based demand response（PBDR）. PBDR can cut load peak demand, but cannot transfer user＇ electricity demand; the results reach the optimum when IBDR and PBDR are introduced at the same time. Demand response can encourage different users participate system reserve service, getting intuitive economic profits, favor to dispatch user side to take part in generating dispatch optimization.

关 键 词：需求响应 风力发电 鲁棒理论 多类用户 

分 类 号：TM734[电气工程—电力系统及自动化]