基于集成学习的含电气热商业楼宇群的分时电价求解
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摘要
当前,越来越多的含电气热商业楼宇配备有各类分布式发电设备,商业楼宇群的负荷构成越来越复杂。针对商业楼宇群分时电价的制定问题,该文在考虑了售电公司和商业楼宇群双方利益后,提出一种分时电价制定的双层优化模型。在该模型中,售电公司通过发布分时电价以及收集商业楼宇的用电信息,实现自身收益最大化;商业楼宇群根据售电公司发布的分时电价制定其考虑舒适度的日前用电计划,实现自身运营成本最低的目标。同时,结合强化学习,提出一种集成学习算法和单纯形法相结合的混合优化方法,实现模型的求解,通过算例结果验证其对降低商业楼宇运行成本和提高售电公司收益的有效性。
At present, the load of commercial buildings is becoming more and more complex. This paper proposed a bi-level optimization model for time-of-use prices, taking into account the interests of both electric retailer and commercial buildings. In this model, electric retailer maximizes his own revenue by publishing time-of-use prices and collecting electricity usage information for commercial buildings; commercial buildings make their own daily electricity usage plans based on the time-of-use prices and reduce their own operating costs. At the same time, a hybrid optimization algorithm based on ensemble learning(EL) was proposed in this paper to achieve the solution of the model. It was verified by example results that it can reduce the operating costs of commercial buildings and improve the interest of the electric retailer.
At present, the load of commercial buildings is becoming more and more complex. This paper proposed a bi-level optimization model for time-of-use prices, taking into account the interests of both electric retailer and commercial buildings. In this model, electric retailer maximizes his own revenue by publishing time-of-use prices and collecting electricity usage information for commercial buildings; commercial buildings make their own daily electricity usage plans based on the time-of-use prices and reduce their own operating costs. At the same time, a hybrid optimization algorithm based on ensemble learning(EL) was proposed in this paper to achieve the solution of the model. It was verified by example results that it can reduce the operating costs of commercial buildings and improve the interest of the electric retailer.
引文
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[29]吴雄,王秀丽,王建学,等.微网经济调度问题的混合整数规划方法[J].中国电机工程学报,2013,33(28):1-8.Wu Xiong,Wang Xiuli,Wang Jianxue,et al.Economic generation scheduling of a microgrid using mixed integer programming[J].Proceedings of the CSEE,2013,33(28):1-8(in Chinese).
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[34]Xu Zhiwei,Su Wencong,Hu Zechun,et al.A hierarchical framework for coordinated charging of plug-in electric vehicles in China[J].IEEE Transactions on Smart Grid,2016,7(1):428-438.
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[2]李扬,王治华,卢毅,等.峰谷分时电价的实施及大工业用户的响应[J].电力系统自动化,2001,25(8):45-48.Li Yang,Wang Zhihua,Lu Yi,et al.The implementation of peak and valley time price for electricity and the response of large industries[J].Automation of Electric Power System,2001,25(8):45-48(in Chinese).
[3]赵俊华,文福栓,杨爱民,等.电动汽车对电力系统的影响及其调度与控制问题[J].电力系统自动化,2011.35(14):2-10,29.Zhao Junhua,Wen Fushuan,Yang Aimin,et al.Impacts of electric vehicles on power systems as well as the associated dispatching and control problem[J].Automation of Electric Power Systems,2011,35(14):2-10,29(in Chinese).
[4]靳小龙,穆云飞,贾宏杰,等.融合需求侧虚拟储能系统的冷热电联供楼宇微网优化调度方法[J].中国电机工程学报,2017,37(2):581-591.Jin Xiaolong,Mu Yunfei,Jia Hongjie,et al.Optimal scheduling method for a combined cooling,heating and power building microgrid considering virtual storage system at demand side[J].Proceedings of the CSEE,2017,37(2):581-591(in Chinese).
[5]Wijayasekara D,Linda O,Manic M,et al.Mining building energy management system data using fuzzy anomaly detection and linguistic descriptions[J].IEEETransactions on Industrial Informatics,2014,10(3):1829-1840.
[6]Chai Bo,Costa A,Ahipasaoglu S D,et al.Optimal meeting scheduling in smart commercial building for energy cost reduction[J].IEEE Transactions on Smart Grid,2018,9(4):3060-3069.
[7]Wang Fei,Zhen Zhao,Mi Zengqiang,et al.Solar irradiance feature extraction and support vector machines based weather status pattern recognition model for short-term photovoltaic power forecasting[J].Energy and Buildings,2015,86:427-438.
[8]Lee S,Kwon B,Lee S.Joint energy management system of electric supply and demand in houses and buildings[J].IEEE Transactions on Power Systems,2014,29(6):2804-2812.
[9]Wang Fei,Zhou Lidong,Ren Hui,et al.Multi-objective optimization model of source-load-storage synergetic dispatch for a building energy management system based on TOU price demand response[J].IEEE Transactions on Industry Applications,2018,54(2):1017-1028.
[10]Zhou Yanglin,Gao Feng,Ci Song,et al.Time-of-use pricing in retail electricity market:Step tariff vs.usagebased schemes[C]//Proceedings of 2016 International Conference on Probabilistic Methods Applied to Power Systems.Beijing:IEEE,2016.
[11]郭联哲,谭忠富,李晓军.基于用户响应下的分时电价优化设计模型与方法[J].电网技术,2006,30(5):24-28.Guo Lianzhe,Tan Zhongfu,Li Xiaojun.Demand response based model and method for optimal design of time-of-use electricity price[J].Power System Technology,2006,30(5):24-28(in Chinese).
[12]谭忠富,陈广娟,赵建保,等.以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J].中国电机工程学报,2009,29(1):55-62.Tan Zhongfu,Chen Guangjuan,Zhao Jianbao,et al.Optimization model for designing peak-valley time-ofuse power price of generation side and sale side at the direction of energy conservation dispatch[J].Proceedings of the CSEE,2009,29(1):55-62(in Chinese).
[13]黄海涛,吴洁晶,顾丹珍,等.计及负荷率分档的峰谷分时电价定价模型[J].电力系统保护与控制,2016,44(14):122-129.Huang Haitao,Wu Jiejing,Gu Danzhen,et al.Pricing model of time-of-use electricity tariff considering customers classified by load factor[J].Power System Protection and Control,2016,44(14):122-129(in Chinese).
[14]艾欣,周树鹏,赵阅群.考虑风电不确定性的用户侧分时电价研究[J].电网技术,2016,40(5):1529-1535.Ai Xin,Zhou Shupeng,Zhao Yuequn.Study on time of use pricing of user side considering wind power uncertainty[J].Power System Technology,2016,40(5):1529-1535(in Chinese).
[15]李春燕,许中,马智远.计及用户需求响应的分时电价优化模型[J].电力系统及其自动化学报,2015,27(3):11-16.Li Chunyan,Xu Zhong,Ma Zhiyuan.Optimal time-of-use electricity price model considering customer demand response[J].Proceedings of the CSU-EPSA,2015,27(3):11-16(in Chinese).
[16]高亚静,吕孟扩,王球,等.基于离散吸引力模型的电动汽车充放电最优分时电价研究[J].中国电机工程学报,2014,34(22):3647-3653.Gao Yajing,LüMengkuo,Wang Qiu,et al.Research on optimal TOU price considering electric vehicles charging and discharging based on discrete attractive model[J].Proceedings of the CSEE,2014,34(22):3647-3653(in Chinese).
[17]Yang Peng,Tang Gongguo,Nehorai A.A game-theoretic approach for optimal time-of-use electricity pricing[J].IEEE Transactions on Power Systems,2013,28(2):884-892.
[18]de SáFerreira R,Barroso L A,Lino P R,et al.Time-ofuse tariff design under uncertainty in price-elasticities of electricity demand:a stochastic optimization approach[J].IEEE Transactions on Smart Grid,2013,4(4):2285-2295.
[19]Chen Sijie,Love H A,Liu C C.Optimal opt-in residential time-of-use contract based on principal-agent theory[J].IEEE Transactions on Power Systems,2016,31(6):4415-4426.
[20]Zhou Bin,Yang Rui,Li Canbing,et al.Multiobjective model of time-of-use and stepwise power tariff for residential consumers in regulated power markets[J].IEEE Systems Journal,2018,12(3):2676-2687.
[21]Yang Jiajia,Zhao Junhua,Wen Fushuan,et al.Aframework of customizing electricity retail prices[J].IEEETransactions on Power Systems,2018,33(3):2415-2428.
[22]Datchanamoorthy S,Kumar S,Ozturk Y,et al.Optimal time-of-use pricing for residential load control[C]//Proceedings of 2011 IEEE International Conference on Smart Grid Communications.Brussels:IEEE,2011.
[23]Hatami A,Seifi H,Sheikh-El-Eslami M K.Astochastic-based decision-making framework for an electricity retailer:time-of-use pricing and electricity portfolio optimization[J].IEEE Transactions on Power Systems,2011,26(4):1808-1816.
[24]Liao Yingchen,Chen Lu,Chen Xingying.An efficient time-of-use pricing model for a retail electricity market based on Pareto improvement[C]//Proceedings of 2011Asia-Pacific Power and Energy Engineering Conference.Wuhan:IEEE,2011.
[25]Yang Peng,Tang Gongguo,Nehorai A.A game-theoretic approach for optimal time-of-use electricity pricing[J].IEEE Transactions on Power Systems,2013,28(2):884-892.
[26]Qian Liping,Zhang Y J A,Huang Jianwei,et al.Demand response management via real-time electricity price control in smart grids[J].IEEE Journal on Selected Areas in Communications,2013,31(7):1268-1280.
[27]闫湖,黄碧斌,刘龙珠.人工智能在新一代电力系统中的应用前景分析[J].电力信息与通信技术,2018,16(11):7-11.Yan Hu,Huang Bibin,Liu Longzhu.Artificial intelligence application prospect in the new generation of electric power system[J].Electric Power Information and Communication Technology,2018,16(11):7-11(in Chinese).
[28]贺倩.人工智能技术的发展与应用[J].电力信息与通信技术,2017,15(9):32-37.He Qian.Development and application of artificial intelligence technology[J].Electric Power Information and Communication Technology,2017,15(9):32-37(in Chinese).
[29]吴雄,王秀丽,王建学,等.微网经济调度问题的混合整数规划方法[J].中国电机工程学报,2013,33(28):1-8.Wu Xiong,Wang Xiuli,Wang Jianxue,et al.Economic generation scheduling of a microgrid using mixed integer programming[J].Proceedings of the CSEE,2013,33(28):1-8(in Chinese).
[30]李正茂,张峰,梁军,等.含电热联合系统的微电网运行优化[J].中国电机工程学报,2015,35(14):3569-3576.Li Zhengmao,Zhang Feng,Liang Jun,et al.Optimization on microgrid with combined heat and power system[J].Proceedings of the CSEE,2015,35(14):3569-3576(in Chinese).
[31]Liu Nian,Chen Qifang,Liu Jie,et al.A heuristic operation strategy for commercial building microgrids containing EVs and PV system[J].IEEE Transactions on Industrial Electronics,2015,62(4):2560-2570.
[32]Lu Yuehong,Wang Shengwei,Sun Yongjun,et al.Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming[J].Applied Energy,2015,147:49-58.
[33]潘振宁,张孝顺,余涛,等.大规模电动汽车集群分层实时优化调度[J].电力系统自动化,2017,41(16):96-104.Pan Zhenning,Zhang Xiaoshun,Yu Tao,et al.Hierar chical real-time optimized dispatching for large-scale clusters of electric vehicles[J].Automation of Electric Power Systems,2017,41(16):96-104(in Chinese).
[34]Xu Zhiwei,Su Wencong,Hu Zechun,et al.A hierarchical framework for coordinated charging of plug-in electric vehicles in China[J].IEEE Transactions on Smart Grid,2016,7(1):428-438.
[35]Zhang Xiaoshun,Bao Tao,Yu Tao,et al.Deep transfer Q-learning with virtual leader-follower for supply-demand Stackelberg game of smart grid[J].Energy,2017,133:348-365.
[36]Clerc M,Kennedy J.The particle swarm-explosion,stability,and convergence in a multidimensional complex space[J].IEEE Transactions on Evolutionary Computation,2002,6(1):58-73.
[37]Iba K.Reactive power optimization by genetic algorithm[J].IEEE Transactions on Power Systems,1994,9(2):685-692.
[38]Bansal J C,Deep K.A modified binary particle swarm optimization for knapsack problems[J].Applied Mathematics and Computation,2012,218(22):11042-11061.
[39]Loukarakis E,Dent C J,Bialek J W.Decentralized multi-period economic dispatch for real-time flexible demand management[J].IEEE Transactions on Power Systems,2016,31(1):672-684.
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