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An Adaptive Renewable Energy Penetration Approach With Energy Storage Arbitrage for Profit Maximization in Deregulated Power Market.

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Title: An Adaptive Renewable Energy Penetration Approach With Energy Storage Arbitrage for Profit Maximization in Deregulated Power Market.
Authors: Sanyal, Arindam1 (AUTHOR), Goswami, Arup Kumar1 (AUTHOR), Tiwari, Prashant Kumar2 (AUTHOR), Sarathkumar, Tirunagaru V.3 (AUTHOR), Al-Ahmadi, Ahmad Aziz4 (AUTHOR), Almalki, Mishari Metab5 (AUTHOR), Flah, Aymen6,7,8 (AUTHOR) flahaymening@yahoo.fr, Ghaly, Ramy N. R.9,10 (AUTHOR), Biswas, Arnab (AUTHOR)
Source: International Transactions on Electrical Energy Systems. 10/5/2025, Vol. 2025, p1-18. 18p.
Subject Terms: *Renewable energy sources, *Energy storage, *Profit maximization, *Value at risk, *Risk managers, *Energy industries, *Markov processes
Abstract: The consequences of fossil fuel consumption are increasingly evident through various climate anomalies and severe environmental impacts. Renewable energy sources have emerged as popular alternatives due to their zero‐emission generation. However, the intermittent nature of renewables introduces uncertainty in the techno‐economic operation of power systems. This article presents a novel adaptive penetration approach designed to maximize profit while minimizing tail‐end risk for economic participation in the power market. The proposed adaptive strategy dynamically adjusts renewable energy penetration between 20% and 80%, based on real‐time renewable energy availability. A Discrete‐Time Markov Decision Process (DTMDP) is employed for decision‐making and profit estimation, incorporating probabilistic renewable generation models and energy storage arbitrage operations. Profit and risk are evaluated over a 24‐h horizon across twelve months, with tail‐end risk quantified using Conditional Value at Risk (CVaR). This study models wind and solar energy generation probabilistically and integrates a two‐stage energy storage arbitrage system. In the first stage, excess renewable generation is stored when supply exceeds demand, while in the second stage, stored energy is dispatched during power shortages. The IEEE 14‐bus system with hybrid generation is used as the case study. The adaptive approach is compared with static renewable penetration levels of 20% and 80%. Results show that while 20% penetration yields lower tail risk, it also produces lower profits. Conversely, 80% penetration results in higher profits but comes with increased tail‐end risk. Additionally, months with lower renewable energy probabilities, such as December, exhibited higher tail‐end risk compared to months like July with higher renewable availability. The adaptive penetration strategy achieved higher profits than the 20% scenario while maintaining lower tail‐end risk than the 80% scenario, demonstrating its effectiveness in balancing profitability and risk. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 188443074
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  Label: Title
  Group: Ti
  Data: An Adaptive Renewable Energy Penetration Approach With Energy Storage Arbitrage for Profit Maximization in Deregulated Power Market.
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  Data: <searchLink fieldCode="AR" term="%22Sanyal%2C+Arindam%22">Sanyal, Arindam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Goswami%2C+Arup+Kumar%22">Goswami, Arup Kumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tiwari%2C+Prashant+Kumar%22">Tiwari, Prashant Kumar</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sarathkumar%2C+Tirunagaru+V%2E%22">Sarathkumar, Tirunagaru V.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Al-Ahmadi%2C+Ahmad+Aziz%22">Al-Ahmadi, Ahmad Aziz</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Almalki%2C+Mishari+Metab%22">Almalki, Mishari Metab</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Flah%2C+Aymen%22">Flah, Aymen</searchLink><relatesTo>6,7,8</relatesTo> (AUTHOR)<i> flahaymening@yahoo.fr</i><br /><searchLink fieldCode="AR" term="%22Ghaly%2C+Ramy+N%2E+R%2E%22">Ghaly, Ramy N. R.</searchLink><relatesTo>9,10</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Biswas%2C+Arnab%22">Biswas, Arnab</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Transactions+on+Electrical+Energy+Systems%22">International Transactions on Electrical Energy Systems</searchLink>. 10/5/2025, Vol. 2025, p1-18. 18p.
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  Data: *<searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+storage%22">Energy storage</searchLink><br />*<searchLink fieldCode="DE" term="%22Profit+maximization%22">Profit maximization</searchLink><br />*<searchLink fieldCode="DE" term="%22Value+at+risk%22">Value at risk</searchLink><br />*<searchLink fieldCode="DE" term="%22Risk+managers%22">Risk managers</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+industries%22">Energy industries</searchLink><br />*<searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The consequences of fossil fuel consumption are increasingly evident through various climate anomalies and severe environmental impacts. Renewable energy sources have emerged as popular alternatives due to their zero‐emission generation. However, the intermittent nature of renewables introduces uncertainty in the techno‐economic operation of power systems. This article presents a novel adaptive penetration approach designed to maximize profit while minimizing tail‐end risk for economic participation in the power market. The proposed adaptive strategy dynamically adjusts renewable energy penetration between 20% and 80%, based on real‐time renewable energy availability. A Discrete‐Time Markov Decision Process (DTMDP) is employed for decision‐making and profit estimation, incorporating probabilistic renewable generation models and energy storage arbitrage operations. Profit and risk are evaluated over a 24‐h horizon across twelve months, with tail‐end risk quantified using Conditional Value at Risk (CVaR). This study models wind and solar energy generation probabilistically and integrates a two‐stage energy storage arbitrage system. In the first stage, excess renewable generation is stored when supply exceeds demand, while in the second stage, stored energy is dispatched during power shortages. The IEEE 14‐bus system with hybrid generation is used as the case study. The adaptive approach is compared with static renewable penetration levels of 20% and 80%. Results show that while 20% penetration yields lower tail risk, it also produces lower profits. Conversely, 80% penetration results in higher profits but comes with increased tail‐end risk. Additionally, months with lower renewable energy probabilities, such as December, exhibited higher tail‐end risk compared to months like July with higher renewable availability. The adaptive penetration strategy achieved higher profits than the 20% scenario while maintaining lower tail‐end risk than the 80% scenario, demonstrating its effectiveness in balancing profitability and risk. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=188443074
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      – Type: doi
        Value: 10.1155/etep/2506650
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 1
    Subjects:
      – SubjectFull: Renewable energy sources
        Type: general
      – SubjectFull: Energy storage
        Type: general
      – SubjectFull: Profit maximization
        Type: general
      – SubjectFull: Value at risk
        Type: general
      – SubjectFull: Risk managers
        Type: general
      – SubjectFull: Energy industries
        Type: general
      – SubjectFull: Markov processes
        Type: general
    Titles:
      – TitleFull: An Adaptive Renewable Energy Penetration Approach With Energy Storage Arbitrage for Profit Maximization in Deregulated Power Market.
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            – D: 05
              M: 10
              Text: 10/5/2025
              Type: published
              Y: 2025
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