引用本文:王,顾伟,张成龙,等.智能社区综合能源优化管理研究[J].电力系统保护与控制,2017,45(1):89-97.
WANG Jun,GU Wei,ZHANG Chenglong,et al.Research on integrated energy management for smart community[J].Power System Protection and Control,2017,45(1):89-97
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智能社区综合能源优化管理研究
王 珺1,顾 伟1,张成龙2,王志贺3,唐沂媛1
(1.东南大学电气工程学院，江苏 南京 210096;2.国网能源研究院，北京 100000;
3..徐州供电公司，江苏 徐州 221000)
摘要:
居民负荷由于用电时间集中，已成为电力峰荷的主要组成部分，同时随着智能电网技术的发展，需求侧响应作为缓解电力供需矛盾的有效途径备受关注。以智能社区为背景，结合冷热电联供(Combined Cooling Heating and Power，CCHP)系统能效高、经济效益好等优势，与居民需求侧响应的潜力，提出两阶段优化模式。第一阶段，社区物业根据负荷预测及光伏出力预测，优化CCHP系统各部分出力，最大化物业净收益。第二阶段，家庭能量管理系统(Home Energy Management System，HEMS)根据CCHP系统启停及出力情况与分时电价，优化家庭负荷工作时间，最小化用户费用。最后通过对比不同案例仿真结果，证明了该两阶段优化模式能够实现供能侧与用能侧的双赢。
关键词:  两阶段优化  智能社区  CCHP  DR  HEMS
DOI：10.7667/PSPC160001
分类号:
基金项目:国家科技支撑项目(2015BAA01B01);国家自然科学基金资助项目(51277027);国家电网公司科技项目支持(“两个替代”潜力评估)
Research on integrated energy management for smart community
WANG Jun1,GU Wei1,ZHANG Chenglong2,WANG Zhihe3,TANG Yiyuan1
(1. School of Electrical Engineering, Southeast University, Nanjing 210096, China;2. State Grid Energy Research
Institute, Beijing 100000, China;3. Xuzhou Electric Power Company, Xuzhou 221000, China)
Abstract:
Residential electricity load due to the concentration of its use time has become a main component of electric power peak, meanwhile, with the development of smart grid technology, demand side response as an effective way to ease the imbalance between supply and demand has attracted much attention. Set in smart community, and combined the superiority of CCHP in energy efficiency and economic with the potential of household load in demand response, a two-stage optimization model is proposed. At first stage, property company optimizes the output of each part of CCHP system according to the forecast of load and photovoltaic output, in order to maximize the profits of property company. At second stage, HEMS optimizes the residential load schedule based on the condition of CCHP and time-of-use electricity price, minimum users’ cost. Finally, comparison between the simulation results of different cases proves that the two-stage optimization can realize a win-win situation both in users and property company. This work is supported by National Key Technology Support Program (No. 2015BAA01B01), National Natural Science Foundation of China (No. 51277027), and State Grid Science and Technology Project ( “Two Alternatives”) Potential Assessment.
Key words:  two-stage optimization  smart community  CCHP  DR  HEMS
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