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Capacity investment decisions of energy storage power stations supporting wind power projects

Mingzhen Song (School of Business Administration, Xinjiang University of Finance and Economics, Urumqi, China) (College of Business, Shanghai University of Finance and Economics, Shanghai, China)
Lingcheng Kong (Business School, East China University of Science and Technology, Shanghai, China)
Jiaping Xie (School of Business Administration, Xinjiang University of Finance and Economics, Urumqi, China) (College of Business, Shanghai University of Finance and Economics, Shanghai, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 12 September 2023

Issue publication date: 1 December 2023

112

Abstract

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.

Highlights

  1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

  2. Investment strategy of energy storage power stations on the supply side of wind power generators.

  3. Impact of pricing method on the investment decisions of energy storage power stations.

  4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

  5. A two-stage wind power supply chain including energy storage power stations.

Keywords

Acknowledgements

The work was supported by the National Natural Science Foundation of China (72073044), the Key Project of the National Social Science Foundation of China (20AJY008), the Fund of the Key Research Center of Humanities and Social Sciences in the general Colleges and Universities of Xinjiang Uygur Autonomous Region (XJEDU2023 P001), the University-local cooperation bidding project of Xinjiang University of Finance and Economics (2022SLC002).

Citation

Song, M., Kong, L. and Xie, J. (2023), "Capacity investment decisions of energy storage power stations supporting wind power projects", Industrial Management & Data Systems, Vol. 123 No. 11, pp. 2803-2835. https://doi.org/10.1108/IMDS-07-2022-0407

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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