文献类型：期刊文献

英文题名：Capacity investment decisions of energy storage power stations supporting wind power projects

作者：Song, Mingzhen[1,2];Kong, Lingcheng[3];Xie, Jiaping[1,2]

机构：[1]Xinjiang Univ Finance & Econom, Sch Business Adm, Urumqi, Peoples R China;[2]Shanghai Univ Finance & Econom, Coll Business, Shanghai, Peoples R China;[3]East China Univ Sci & Technol, Business Sch, Shanghai, Peoples R China

年份：2023

卷号：123

期号：11

起止页码：2803

外文期刊名：INDUSTRIAL MANAGEMENT & DATA SYSTEMS

收录：;EI(收录号：20233714701019);WOS:【SCI-EXPANDED(收录号:WOS:001183696400001)】；

语种：英文

外文关键词：Electric power investment; Capacity decision; Time-of-use pricing; Energy storage; Wind power generation

摘要：Purpose Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help "peak shaving and valley filling" and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity. Design/methodology/approach Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand. Findings (1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels. Originality/value This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.