Location and Capacity Planning of Electricity Hydrogen Hybrid Energy Storage System Considering Demand Response

被引：0
|
作者：
Li J. [1 ]
Yang B. [1 ]
Hu Y. [1 ]
Zhang R. [1 ]
Shu H. [1 ]
机构：
[1] Faculty of Electric Power Engineering, Kunming University of Science and Technology, Yunnan Province, Kunming
来源：
Dianwang Jishu/Power System Technology | 2023年 / 47卷 / 09期
基金：
中国国家自然科学基金;
关键词：
demand response; electric-hydrogen hybrid energy storage system; location and capacity; non-dominated sorting genetic algorithm; time-of-use price;
D O I：
10.13335/j.1000-3673.pst.2022.2285
中图分类号：
学科分类号：
摘要：
With the increasing proportion of distributed generation (DG) in the distribution network, the stability of the distribution network has been severely affected. The traditional distribution network management strategy is difficult to coordinate the multiple resources. Hence, the active distribution network mode has gradually become the mainstream of the grid operation. To reduce the impact of the DG access on the stability of the active distribution network, this paper establishes a bi-level model of the electric-hydrogen hybrid (EHH)-energy storage system (ESS) considering demand response. The upper model aims at minimizing the net load fluctuation considering demand response and maximizing the customer electricity satisfaction with the electric purchase cost and the customer electricity consumption comfort. Based on the electricity price elasticity matrix model, the optimal time-of-use price formulation strategy is obtained. The lower layer model takes the minimum life cycle cost (LCC) of the EHH-ESS, the voltage fluctuation of the active distribution network and the net load fluctuation considering the demand response and the EHH-ESS as the objective to obtain the optimal EHH-ESS planning scheme. The optimal trade-off between investment economy, load stability and voltage quality of active distribution network is realized by optimal planning of EHH-ESS. Finally, the validity of the proposed model and the superiority of the proposed method are verified through the extended IEEE-33 bus system. Meanwhile, the stability of the active distribution network and the economy of the EHH-ESS are analyzed under different operation scenarios. The simulation results based on the NSGA-III show that, compared with the method only configuring the EHH-ESS, although the LCC is increased by 5.16% after considering demand response and configuring the EHH-ESS, the net load fluctuation and the voltage fluctuation are reduced by 6.56% and 13.33% respectively. It is verified that the configuration of the EHH-ESS is able to maximize the stability of the active distribution network considering demand side response. © 2023 Power System Technology Press. All rights reserved.
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页码：3698 / 3709
页数：11
相关论文
共 38 条
  • [1] CHEN Yanbo, WU Chao, JIAO Yang, Coordinated optimal operation strategy of thermal power-energy storage considering demand response and life model of energy storage[J], Electric Power Automation Equipment, 42, 2, pp. 16-24, (2022)
  • [2] YANG Bo, YU Lei, CHEN Yixuan, Modelling，applications，and evaluations of optimal sizing and placement of distributed generations：a critical state-of-the-art survey[J], International Journal of Energy Research, 45, 3, pp. 3615-3642, (2021)
  • [3] LE Jian, QI Gan, ZHAO Liangang, Time-delay stability analysis of an active distribution network adopting a distributed economic dispatch strategy[J], Power System Protection and Control, 50, 21, pp. 75-87, (2022)
  • [4] Bo XU, WANG Jiexin, Mengyuan GUO, A hybrid demand response mechanism based on real-time incentive and real-time pricing[J], Energy, 231, (2021)
  • [5] DING Wei, YUAN Jiahai, HU Zhaoguang, Time-of-use price decision model considering users reaction and satisfaction index[J], Automation of Electric Power Systems, 29, 20, pp. 10-14, (2005)
  • [6] YANG Haizhu, LI Menglong, JIANG Zhaoyang, Optimal operation of regional integrated energy system considering demand side electricity heat and natural-gas loads response[J], Power System Protection and Control, 48, 10, pp. 30-37, (2020)
  • [7] AN Dong, YANG Deyu, WU Wenli, Optimal location and sizing of battery energy storage systems in a distribution network based on a modified multi-objective mayfly algorithm[J], Power System Protection and Control, 50, 10, pp. 31-39, (2022)
  • [8] XU Jizhi, ZHANG Xinyan, CHANG Xiqiang, Research on energy storage location and capacity determination based on PV curve and improved genetic algorithm[J], Acta Energiae Solaris Sinica, 43, 1, pp. 263-268, (2022)
  • [9] LI Xiulei, GENG Guangfei, JI Yuqi, Integrated optimal planning of energy storage and demand side response in active power distribution network[J], Power System Technology, 40, 12, pp. 3803-3810, (2016)
  • [10] XU Chuanbo, ZHAO Yunhao, WANG Xiaochen, Optimal configuration of hydrogen energy storage for wind and solar power stations considering electricity-hydrogen coupling under carbon neutrality vision[J], Electric Power Construction, 43, 1, pp. 10-18, (2022)
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