摘要
计及了分散式空调负荷参与调控初始状态的不确定性及参数差异性,提出了适用于大量分散式空调负荷的聚类分组方法及直接负荷控制(DLC)分组轮控动态优化方法。在聚类分组过程中,以空调负荷可调控潜力为聚类目标,在保证DLC可操作空间的基础上充分发挥空调负荷的调控潜力。在DLC分组轮控动态优化过程中,通过合理选择优化周期,修正模型误差与温度预测带来的调控误差,使得空调负荷出力与调度计划更加吻合,同时保证了用户的舒适度需求。仿真算例验证了所提方法充分发挥分散式空调负荷调控潜力的良好效果。
Considering the uncertainty of the initial state and the diversity of parameters of decentralized air-conditioning loads participating in regulation,a new clustering method and a dynamic optimization method of direct load control（DLC）applied to massive decentralized air-conditioning loads are proposed.In the process of clustering,the regulation potential of airconditioning is set to be the clustering objective in order to fully utilize its regulation ability based on guaranteeing the operational space of DLC.During the DLC decision procedure,the scheduling error caused by model errors and temperature prediction errors can be corrected by rational selection of optimization cycle.Thus,the reducing power of air-conditioning load can perform more agreeably with the dispatching plan,while users＇comfort requirements are ensured.Finally,the effect of the proposed method on fully releasing the regulation potential of decentralized air-conditioning loads is verified through simulation cases.
出处
《电力系统自动化》
EI
CSCD
北大核心
2016年第14期33-42,共10页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(51577028)
中央高校基本科研业务费专项资金资助项目(2242016K41064)~~
关键词
需求响应
空调负荷
负荷代理商
聚类算法
动态优化
demand response
air-conditioning load
load agent
clustering algorithm
dynamic optimization
