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文章摘要
基于智能电能表的居民需求响应协同策略
Coordination strategy of residential demand response based on smart meter
Received:March 06, 2018  Revised:March 06, 2018
DOI:
中文关键词: 家庭能源管理  智能电表  负荷服务实体  需求响应  协同优化
英文关键词: home energy management system (HEMS)  smart meter  load serving entity (LSE)  demand response (DR)  coordinated optimization
基金项目:国家重点研发计划课题资助项目(2017YFB0902904); 国家自然科学基金资助项目(51477122)。
Author NameAffiliationE-mail
Jin Chengxu* School of Electrical Engineering, Wuhan University 2228917159@qq.com 
Xu Jian School of Electrical Engineering,Wuhan University kingjin163@hotmail.com 
Liao Siyang School of Electrical Engineering, Wuhan University liaosiyang@whu.edu.cn 
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中文摘要:
      随着新能源大量接入,传统由发电跟踪负荷变化的运行模式面临挑战。需求响应是重要的调度资源,信息技术的发展提高了居民负荷的响应能力。在此背景下,负荷服务实体(LSE)通过电价机制协调用户的响应实现供需互动。首先,对家用电器设备的分类和建模得到响应电价的优化模型,建立了基于智能电表的家庭能源管理系统(HEMS)。其次,根据负荷服务实体的供电成本函数得到电价制定模型。以电价和响应功率作为互动信息协调不同用户的响应,进行迭代计算直到收敛,实现整体优化。考虑到用户优化会导致总成本振荡无法收敛,在优化目标函数中添加连续两次迭代间负荷变化的惩罚项。最后,通过算例仿真,分析了上述协同优化策略对LSE和用户的影响,验证了所提策略在平滑功率曲线和降低用户成本的效果。
英文摘要:
      With the development of renewable sources, the traditional operation method of controlling generation to deal with load fluctuation is being challenged. Demand response (DR) is an important scheduling resource, and the advance in information technology improved the responsivity of residential load. In this context, the load service entity (LSE) realizes the supply-demand interaction of residential loads through price mechanism. Firstly, home energy management system (HEMS) based on smart meter is established by optimizing operation of household equipment to minimize energy cost. Secondly, the pricing mechanism of the LSE is derived according to the power supply cost function. Electricity prices and response power of HEMS are used as interactive information to coordinate the responses of users and optimize the overall load. Considering that distributed optimization of users may fail to converge, penalty for load changes between two consecutive iterations are added to the objective function. Through simulations, the influence of the above strategy on LSE and users is analyzed, and the effectiveness on smoothing the power curve and reducing household energy cost is verified.
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