计及调节弹性差异化的产消群价格型需求响应机制Price-based Demand Response Mechanism of Prosumer Groups Considering Adjusting Elasticity Differentiation
刘迪;孙毅;李彬;霍沫霖;奚巍民;
摘要(Abstract):
针对产消者调节弹性差异化的特点,在产消群的优化过程中,提出了考虑折扣因子的价格型需求响应机制。售电商根据负荷及分布式电源出力情况,以利益最大化为目标制定面向所有产消者的购售电价格及折扣因子,在保证公平性的前提下,使得积极参与响应的产消者能够享受到更低的结算电价。进而,提出了考虑折扣因子的边云协同迭代优化策略,通过价格的手段引导产消者在不同的场景下对负荷进行调增或调减。仿真实验表明,所提价格策略及优化方法能够有效提升售电商的收益以及用户的效益,且在不同的场景下均有着良好的表现,具有较强的鲁棒性。
关键词(KeyWords): 调节弹性;需求响应;产消群平衡;边云协同
基金项目(Foundation): 国家自然科学基金项目(51777068);; 中央高校基本科研业务费专项资金项目(2019QN108);; 国家电网有限公司科技项目“电力弹性负荷快速响应及柔性调节关键技术研究及应用”(SGJSDK00JLJS1800094)~~
作者(Author): 刘迪;孙毅;李彬;霍沫霖;奚巍民;
Email:
DOI: 10.13335/j.1000-3673.pst.2019.2047
参考文献(References):
- [1]施贵荣,孙荣富,徐海翔,等.大规模集群可再生能源有功分层协调控制策略[J].电网技术,2018,42(7):2160-2167.Shi Guirong,Sun Rongfu,Xu Haixiang,et al.Active power stratification coordination control strategy for large-scale cluster of renewable energy[J].Power System Technology,2018,42(7):2160-2167(in Chinese).
- [2]史连军,周琳,庞博,等.中国促进清洁能源消纳的市场机制设计思路[J].电力系统自动化,2017,41(24):83-89.Shi Lianjun,Zhou Lin,Pang Bo,et al.Design ideas of electricity market mechanism to improve accommodation of clean energy in China[J].Automation of Electric Power Systems,2017,41(24):83-89(in Chinese).
- [3]白杨,谢乐,夏清,等.中国推进售电侧市场化的制度设计与建议[J].电力系统自动化,2015,39(14):1-7.Bai Yang,Xie Le,Xia Qing,et al.Institutional design of Chinese retail electricity market reform and related suggestions[J].Automation of Electric Power Systems,2015,39(14):1-7(in Chinese).
- [4]刘敦楠,徐尔丰,许小峰.面向园区微网的“源-网-荷-储”一体化运营模式[J].电网技术,2018,42(3):681-689.Liu Dunnan,Xu Erfeng,Xu Xiaofeng.“Source-Network-LoadStorage” integrated operation model for microgrid in park[J].Power System Technology,2018,42(3):681-689(in Chinese).
- [5]曹昉,李欣宁,刘思佳,等.基于消费者参考价格决策及用户黏性的售电套餐优化[J].电力系统自动化,2018,42(14):67-74.Cao Fang,Li Xinjia,Liu Sijia,et al.Optimization of sales package for end-users based on user stickiness and reference pricing decision of consumers[J].Automation of Electric Power Systems,2018,42(14):67-74(in Chinese).
- [6]王克道,陈启鑫,郭鸿业,等.面向可交易能源的储能容量合约机制设计与交易策略[J].电力系统自动化,2018,42(14):54-60+90.Wang Kedao,Chen Qixin,Guo Hongye,et al Effect of heating network characteristics on ultra-short-term scheduling of integrated energy system[J].Automation of Electric Power Systems,2018,42(14):54-60+90(in Chinese).
- [7]代业明,高红伟,高岩,等.具有电力需求预测更新的智能电网实时定价机制[J].电力系统自动化,2018,42(12):58-63.Dai Yeming,Gao Hongwei,Gao Yan,et al.Real-time pricing mechanism in smart grid with forecasting update of power demand[J].Automation of Electric Power Systems,2018,42(12):58-63(in Chinese).
- [8] Nicholas G. Using behavioral economic theory in modeling of demand response[J].Applied Energy,2019,239:107-116.
- [9]李彬,陈京生,李德智,等.我国实施大规模需求响应的关键问题剖析与展望[J].电网技术,2019,43(2):694-704.Li Bin,Chen Jingsheng,Li Dezhi,et al.Analysis and prospect of key issues in China’s demand response for further large scale implementation[J].Power System Technology,2019,43(2):694-704(in Chinese).
- [10]张钦,王锡凡,王建学,等.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-106.Zhang Qin,Wang Xifan,Wang Jianxue,et al.Survey of demand response research in deregulated electricity markets[J].Automation of Electric Power Systems,2008,32(3):97-106(in Chinese).
- [11] Jordehi A R.Optimization of demand response in electric power systems,a review[J].Renewable and Sustainable Energy Reviews,2019,103:308-319.
- [12] Li P,Wang H,Zhang B.A distributed online pricing strategy for demand response programs[J].IEEE Transactions on Smart Grid,2019,10(1):350-360.
- [13] Wang S,Bi S,Zhang Y A.Demand response management for profit maximizing energy loads in real-time electricity market[J].IEEE Transactions on Power Systems,2018,33(6):6387-6396.
- [14]孙建军,张世泽,曾梦迪,等.考虑分时电价的主动配电网柔性负荷多目标优化控制[J].电工技术学报,2018,33(2):401-412.Sun Jianjun,Zhang Shize,Zeng Mengdi,et al.Multi-objective optimal control for flexible load in active distribution network considering time-of-use tariff[J]. Transactions of China Electrotechnical Society,2018,33(2):401-412(in Chinese).
- [15]吉斌,莫峻,谭建成.高比例光伏电能产消群电力需求响应机制设计[J].电网技术,2018,42(10):3315-3323.Ji bin,Mo Jun,Tan Jiancheng.Design of power demand response mechanism for high proportion of photovoltaic prosumer[J].Power System Technology,2018,42(10):3315-3323(in Chinese).
- [16] Muhammad A S H,Minyou C,Houfei L,et al.Optimization modeling for dynamic price based demand response in microgrids[J].Journal of Cleaner Production,2019,222:231-241.
- [17] Yang H,Zhang J,Qiu J,et al.A practical pricing approach to smart grid demand response based on load classification[J]. IEEE Transactions on Smart Grid,2018,9(1):179-190.
- [18] Ni Z, Das A. A new incentive-based optimization scheme for residential community with financial trade-offs[J].IEEE Access,2018,6:57802-57813.
- [19]任艺,周明,李庚银.考虑用户需求响应的售电公司购售电决策双层模型[J].电力系统自动化,2017,41(14):30-36.Ren Yi,Zhou Ming,Li Gengyin.Bi-level model of electricity procurement and sale strategies for electricity retailers considering user demand response[J].Automation of Electric Power Systems,2017,41(14):30-36(in Chinese).
- [20]窦迅,王俊,邵平,等.考虑用户贡献度的售电商购售电策略[J].电网技术,2019,43(8):2752-2760.Dou Xun,Wang Jun,Shaoping,et al.Purchase-sale strategy of power retailers considering user contribution degree[J]. Power System Technology,2019,43(8):2752-2760(in Chinese).
- [21]涂京,周明,宋旭帆,等.居民用户参与电网调峰激励机制及优化用电策略研究[J].电网技术,2019,43(2):443-453.Tu Jing,Zhou Ming,Song Xufan,et al.Research on incentive mechanism and optimal power consumption strategy for residential users’ participation in peak shaving of power grid[J].Power System Technology,2019,43(2):443-453(in Chinese).
- [22]李彪,万灿,赵健,等.基于实时电价的产消者综合响应模型[J].电力系统自动化,2019,43(7):81-90.Li Biao,Wan Can,Zhao Jian,et al.Real-time electricity price based integrated response model for prosumer[J].Automation of Electric Power Systems,2019,43(7):81-90(in Chinese).
- [23] Kim S,Giannakis G B.An online convex optimization approach to real-time energy pricing for demand response[J].IEEE Transactions on Smart Grid,2017,8(6):2784-2793.
- [24] Liu N,Yu X,Wang C,et al.Energy-sharing model with price-based demand response for microgrids of peer-to-peer prosumers[J].IEEE Transactions on Power Systems,2017,32(5):3569-3583.
- [25]窦春霞,罗维,岳东,等.基于多智能体的微网群内电力市场交易策略[J].电网技术,2019,43(5):1735-1744.Dou Chunxia,Luo Wei,Yue Dong,et al.Multi-agent-system-based electricity market trading strategy within microgrid groups[J].Power System Technology,2019,43(5):1735-1744(in Chinese).
- [26]刘念,赵璟,王杰,等.基于合作博弈论的光伏微电网群交易模型[J].电工技术学报,2018,33(8):1903-1910.Liu Nian,Zhao Jing,Wang Jie,et al.A trading model of PV microgrid cluster based on cooperative game theory[J].Transactions of China Electrotechnical Society,2018,33(8):1903-1910(in Chinese).
- [27]?zge O,Nina V,Petra H,et al.Aggregator-mediated demand response:minimizing imbalances caused by uncertainty of solar generation[J].Applied Energy,2019,247:426-437.
- [28]边缘计算产业联盟,工业互联网产业联盟.边缘计算与云计算协同白皮书(2018)[R].北京:边缘计算产业联盟,工业互联网产业联盟,2018:29-33.