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Impacts of Renewable Sources of Energy on Bid Modeling Strategy in an Emerging Electricity Market Using Oppositional Gravitational Search Algorithm

Author

Listed:
  • Satyendra Singh

    (School of Electrical Skills, Bhartiya Skill Development University Jaipur, Rajstahan 302037, India)

  • Manoj Fozdar

    (Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan 302017, India)

  • Hasmat Malik

    (Berkeley Education Alliance for Research in Singapore, University Town, NUS Campus, Singapore 138602, Singapore)

  • Irfan Ahmad Khan

    (Clean and Resilient Energy Systems (CARES) Lab, Texas A&M University, Galveston, TX 77553, USA)

  • Sattam Al Otaibi

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Fahad R. Albogamy

    (Turabah University College, Computer Sciences Program, Taif University, Taif 21944, Saudi Arabia)

Abstract

Power suppliers in a dynamic power market can achieve full benefit by introducing a bidding strategy mechanism. In the power sector, renewable resources have significant gradual usage and their effect on the production of detailed bidding approaches is becoming further complicated in the industry. Due to the irregular nature of these renewable resources and because they are subject to several fluctuations, there is an inherent issue with generating electricity. Taking these considerations into account, attempts have been made to create a model of bidding strategy to optimize the benefit of the electricity producers using the oppositional gravitational search algorithm. The Weibull and Beta distribution functions are utilized to describe the stochastic characteristics of the wind-speed profile and solar-irradiation, respectively. For the IEEE-30 and IEEE-57 frameworks, the suggested method is being checked and explained. In comparison to other optimization approaches, the results of this approach were taken into account, and it was discovered that it outperformed other techniques in addressing bid difficulties. In addition, it is worth noting that the impact of renewable energy on the bidding strategy lowered market clearing and thermal power generating costs, and encouraged renewable influenced producers to put forward the excess electricity into the real-time market.

Suggested Citation

  • Satyendra Singh & Manoj Fozdar & Hasmat Malik & Irfan Ahmad Khan & Sattam Al Otaibi & Fahad R. Albogamy, 2021. "Impacts of Renewable Sources of Energy on Bid Modeling Strategy in an Emerging Electricity Market Using Oppositional Gravitational Search Algorithm," Energies, MDPI, vol. 14(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5726-:d:633478
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    References listed on IDEAS

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    1. Li, Gong & Shi, Jing & Qu, Xiuli, 2011. "Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review," Energy, Elsevier, vol. 36(8), pages 4686-4700.
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    Cited by:

    1. del Río, Pablo & Kiefer, Christoph P., 2023. "Academic research on renewable electricity auctions: Taking stock and looking forward," Energy Policy, Elsevier, vol. 173(C).
    2. Shinji Kuno & Kenji Tanaka & Yuji Yamada, 2022. "Effectiveness and Feasibility of Market Makers for P2P Electricity Trading," Energies, MDPI, vol. 15(12), pages 1-24, June.

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