A Method for Calculating the Optimal Size of Energy Storage for a GENCO

Market liberalization and the growth of renewable energy sources have enabled the rise of generation companies (GENCOs) managing diverse generation portfolios, creating a dynamic market environment that necessitates innovative energy management strategies to enhance operational efficiency and economic viability. Investing in the energy storage system (ESS), which, in addition to participating in the energy and ancillary services markets and in joint operations with other GENCO facilities, can mitigate the fluctuation level from renewables and increase profits. Besides the optimal operation and bidding strategy, determining the optimal size of the ESS aligned with the GENCO’s requirements is significant for its market success. The purpose of the ESS impacts both the sizing criteria and the sizing techniques. The proposed sizing method of ESS for a GENCO daily operation mode is based on the developed optimization operation model of GENCO with utility-scale energy storage and a cost-benefit analysis. A GENCO operates in a market-oriented power system with possible penalties for undelivered energy. The proposed method considers various stochastic phenomena; therefore, the optimization calculations analyze the GENCO operation over a long period to involve multiple potential combinations of uncertainties. Numerical results validate the competencies of the presented optimization model despite many unpredictable parameters. The results showed that both the battery storage system and the pumped storage hydropower plant yield a higher net income for a specific GENCO with a mixed portfolio, regardless of the penalty clause. Considering the investment costs, the optimal sizes for both types of ESS were obtained.

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Publication Details

Journal
Sustainability
Published
2025-03-05
DOI
https://doi.org/10.3390/su17052278
Primary Topic
Microgrid Control and Optimization
Type
article
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article

A Method for Calculating the Optimal Size of Energy Storage for a GENCO

Marin Mandić, Tonći Modrić, Elis Sutlović
Sustainability
Microgrid Control and Optimization
article

A Method for Calculating the Optimal Size of Energy Storage for a GENCO

Marin Mandić, Tonći Modrić, Elis Sutlović
article en

Abstract

Market liberalization and the growth of renewable energy sources have enabled the rise of generation companies (GENCOs) managing diverse generation portfolios, creating a dynamic market environment that necessitates innovative energy management strategies to enhance operational efficiency and economic viability. Investing in the energy storage system (ESS), which, in addition to participating in the energy and ancillary services markets and in joint operations with other GENCO facilities, can mitigate the fluctuation level from renewables and increase profits. Besides the optimal operation and bidding strategy, determining the optimal size of the ESS aligned with the GENCO’s requirements is significant for its market success. The purpose of the ESS impacts both the sizing criteria and the sizing techniques. The proposed sizing method of ESS for a GENCO daily operation mode is based on the developed optimization operation model of GENCO with utility-scale energy storage and a cost-benefit analysis. A GENCO operates in a market-oriented power system with possible penalties for undelivered energy. The proposed method considers various stochastic phenomena; therefore, the optimization calculations analyze the GENCO operation over a long period to involve multiple potential combinations of uncertainties. Numerical results validate the competencies of the presented optimization model despite many unpredictable parameters. The results showed that both the battery storage system and the pumped storage hydropower plant yield a higher net income for a specific GENCO with a mixed portfolio, regardless of the penalty clause. Considering the investment costs, the optimal sizes for both types of ESS were obtained.

SustainabilityVol. 17(5)
University of Split (HR)
Affordable and clean energy
Openalex Percentile: Top 96%
Microgrid Control and Optimization
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