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Stochastic-Robust Decision-Making Model for Flexible Load Aggregator Considering Uncertainties |
Jia Yulong1, Mi Zengqiang1, Yu Yang1, Shen Hao1, Fan Hui2 |
1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding 071003 China; 2. State Grid Hebei Electric Power Supply Co. Ltd Shijiazhuang 050000 China |
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Abstract With the increasing proportion of electric vehicles, distributed energy storages and thermostatically controlled loads connected to the new generation smart grid, flexible load aggregator, as a bidding entity, will be able to participate in day-ahead electricity market. In this paper, we propose that a stochastic robust model for bidding decision-making of flexible load aggregator in the day-ahead market considering uncertainty. The minimal operating costs of flexible load aggregator is the objective function. The uncertainty of day-ahead price is modeled using stochastic scenarios. The uncertainty of driving behaves of electric vehicles and ambient temperature of temperature-controlled loads are modeled using confidence bounds. Uncertainty of flexible load response are modeled using response willing coefficient simulation. By solving the mixed integer linear programming model, the effectiveness of the proposed model is verified by the example, and the bidding strategy for purchasing and selling energy in flexible load aggregator at different time period is obtained. The model will provide decision-making for flexible load aggregator to participate in the bidding of electricity market.
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Received: 11 April 2019
Published: 12 October 2019
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[1] Mao Tian, Lau W H, Shum C, et al.A regulation policy of EV discharging price for demand scheduling[J]. IEEE Transactions on Power Systems, 2018, 33(2): 1275-1288. [2] 齐先军, 程桥, 吴红斌, 等. 激励性需求响应对配电网运行可靠性的影响[J]. 电工技术学报, 2018, 33(22): 5319-5326. Qi Xianjun, Cheng Qiao, Wu Hongbin, et al.Impact of incentive-based demand response on operational reliability of distribution network[J]. Transactions of China Electrotechnical Society, 2018, 33(22): 5319-5326. [3] 易文飞, 张艺伟, 曾博, 等. 多形态激励性需求侧响应协同平衡可再生能源波动的鲁棒优化配置[J]. 电工技术学报, 2018, 33(23): 5541-5554. Yi Wenfei, Zhang Yiwei, Zeng Bo, et al.Robust optimization allocation for multi-type incentive-based demand response collaboration to balance renewable energy fluctuations[J]. Transactions of China Electrotechnical Society, 2018, 33(23): 5541-5554. [4] Yan Xing, Ozturk Y, Hu Zechun, et al.A review on price-driven residential demand response[J]. Renewable and Sustainable Energy Reviews, 2018, 96: 411-419. [5] Jia Yulong, Mi Zengqiang, Yu Yang, et al.A bilevel model for optimal bidding and offering of flexible load aggregator in day-ahead energy and reserve markets[J]. IEEE Access, 2018, 6: 67799-67808. [6] 杜鹏, 米增强, 贾雨龙, 等. 基于网损灵敏度方差的配电网分布式储能位置与容量优化配置方法[J]. 电力系统保护与控制, 2019, 47(6): 103-109. Du Peng, Mi Zengqiang, Jia Yulong, et al.Optimal placement and capacity of distributed energy storage in distribution system based on the sensitivity variance of network loss[J]. Power System Protection and Control, 2019, 47(6): 103-109. [7] 宁佳, 汤奕, 高丙团. 基于需求响应潜力时变性的风火荷协同控制方法[J]. 电工技术学报, 2019, 34(8): 1728-1738. Ning Jia, Tang Yi, Gao Bingtuan.Coordinated control method of wind farm-AGC unit-load based on time-varying characteristics of demand response potential[J]. Transactions of China Electrotechnical Society, 2019, 34(8): 1728-1738. [8] 舒隽, 关睿, 寒冰. 工业大用户分时电价优化方法[J]. 电工技术学报, 2018, 33(7): 1552-1559. Shu Jun, Guan Rui, Han Bing.Method of optimal time-of-use price for large industrial customers[J]. Transactions of China Electrotechnical Society, 2018, 33(7): 1552-1559. [9] Iria J, Soares F, Matos M.Optimal supply and demand bidding strategy for an aggregator of small prosumers[J]. Applied Energy, 2018, 213: 658-669. [10] 李博嵩, 王旭, 蒋传文, 等. 广泛负荷聚集商市场策略建模及风险效益分析[J]. 电力系统自动化, 2018, 42(16): 119-126. Li Bosong, Wang Xu, Jiang Chuanwen, et al.Market strategy modeling and risk profit analysis of demand-side resource aggregator[J]. Automation of Electric Power Systems, 2018, 42(16): 119-126. [11] 王晛, 王留晖, 张少华. 风电商与DR聚合商联营对电力市场竞争的影响[J]. 电网技术, 2018, 42(1): 110-116. Wang Xian, Wang Liuhui, Zhang Shaohua.Impacts of cooperation between wind power producer and DR aggregator on electricity market equilibrium[J]. Power System Technology, 2018, 42(1): 110-116. [12] 王晛, 张凯, 张少华. 风电参与投标的日前电力市场与需求响应交易市场联合均衡分析[J]. 中国电机工程学报. 2018, 38(19): 5738-5750. Wang Xian, Zhang Kai, Zhang Shaohua.Joint equilibrium analysis of day-ahead electricity market and drx market considering wind power bidding[J]. Proceedings of the CSEE, 2018, 38(19): 5738-5750. [13] Nguyen D T, Le Longbao.Risk-constrained profit maximization for microgrid aggregators with demand response[J]. IEEE Transactions on Smart Grid, 2015, 6(1): 135-146. [14] Di Somma M, Graditi G, Siano P.Optimal bidding strategy for a DER aggregator in the day-ahead market in the presence of demand flexibility[J]. IEEE Transactions on Industrial Electronics, 2019, 66(2): 1509-1519. [15] Panwar L K, Konda S R, Verma A A, et al.Demand response aggregator coordinated two-stage responsive load scheduling in distribution system considering customer behavior[J]. IET Generation, Transmission & Distribution, 2017, 11(4): 1023-1032. [16] 吴巍, 汪可友, 李国杰, 等. 提升风电消纳区间的鲁棒机组组合[J]. 电工技术学报, 2018, 33(3): 523-532. Wu Wei, Wang Keyou, Li Guojie, et al.Robust unit commitment to improve the admissible region of wind power[J]. Transactions of China Electrotechnical Society, 2018, 33(3): 523-532. [17] 孙国强, 周亦洲, 卫志农, 等. 能量和旋转备用市场下虚拟电厂热电联合调度鲁棒优化模型[J]. 中国电机工程学报, 2017, 37(11): 3118-3128. Sun Guoqiang, Zhou Yizhou, Wei Zhinong, et al.Thermal and electrical scheduling of a virtual power plant for participating in energy and spinning reserve markets based on robust optimization[J]. Proceedings of the CSEE, 2017, 37(11): 3118-3128. [18] Rashidizadeh-Kermani H, Vahedipour-Dahraie M, Catalao J P, et al.A bi-level risk-constrained offering strategy of a wind power producer considering demand side resources[J]. International Journal of Electrical Power & Energy Systems, 2019, 104: 562-574. [19] Hemmati M, Mohammadi-Ivatloo B, Ghasemzadeh S, et al.Risk-based optimal scheduling of reconfigurable smart renewable energy based microgrids[J]. International Journal of Electrical Power & Energy Systems, 2018, 101: 415-428. [20] 周亦洲, 孙国强, 黄文进, 等. 计及电动汽车和需求响应的多类电力市场下虚拟电厂竞标模型[J]. 电网技术, 2017, 41(6): 1759-1767. Zhou Yizhou, Sun Guoqiang, Huang Wenjin, et al.Strategic bidding model for virtual power plant in different electricity markets considering electric vehicles and demand response[J]. Power System Technology, 2017, 41(6): 1759-1767. [21] 余爽, 卫志农, 孙国强, 等. 考虑不确定性因素的虚拟电厂竞标模型[J]. 电力系统自动化, 2014, 38(22): 43-49. Yu Shuang, Wei Zhinong, Sun Guoqiang, et al.A bidding model for a virtual power plant considering uncertainties[J]. Automation of Electric Power Systems, 2014, 38(22): 43-49. [22] Nojavan S, Zare K, Mohammadi-Ivatloo B.Robust bidding and offering strategies of electricity retailer under multi-tariff pricing[J]. Energy Economics, 2017, 68: 359-372. [23] Nojavan S, Nourollahi R, Pashaei-Didani H, et al.Uncertainty-based electricity procurement by retailer using robust optimization approach in the presence of demand response exchange[J]. International Journal of Electrical Power & Energy Systems, 2019, 105: 237-248. [24] Hu Jianqiang, Cao Jinde, Chen M Z Q, et al. Load following of multiple heterogeneous TCL aggregators by centralized control[J]. IEEE Transactions on Power Systems, 2017, 32(4): 3157-3167. [25] Xu Zhiwei, Callaway D S, Hu Zechun, et al.Hierarchical coordination of heterogeneous flexible loads[J]. IEEE Transactions on Power Systems, 2016, 31(6): 4206-4216. [26] 李亚平, 姚建国, 雍太有, 等. 居民温控负荷聚合功率及响应潜力评估方法研究[J]. 中国电机工程学报, 2017, 37(19): 5519-5528. Li Yaping, Yao Jianguo, Yong Taiyou, et al.Estimation approach to aggregated power and response potential of residential thermostatically controlled loads[J]. Proceedings of the CSEE, 2017, 37(19): 5519-5528. |
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