Skip to main content

BRIEF RESEARCH REPORT article

Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1459090
This article is part of the Research Topic Optimal Scheduling of Demand Response Resources In Energy Markets For High Trading Revenue and Low Carbon Emissions View all 15 articles

Optimal Revenue Sharing Model of Wind-Solar-Storage Hybrid Energy Plant under Green Power Trading Market

Provisionally accepted
Zhuo Zeng Zhuo Zeng 1Xiang Gao Xiang Gao 2*Baling Fang Baling Fang 3Tao Zhang Tao Zhang 1Ying Zhu Ying Zhu 1
  • 1 Hunan University, Changsha, China
  • 2 Shenzhen Polytechnic, Shenzhen, Guangdong, China
  • 3 Hunan University of Technology, Zhuzhou, China

The final, formatted version of the article will be published soon.

    This paper proposes an optimal revenue sharing model of wind-solar-storage hybrid energy plant under medium and long-term green power trading market to facilitate the coordinated operation and equitable revenue allocation. Firstly, a method for decomposing transaction volume of green power is introduced by considering the uncertainty of spot market prices and physical delivery characteristics of green power trading. Then, a coordinated scheduling strategy of hybrid renewable energy plant is proposed to maximize revenues generated from both the green power and spot markets. Consequently, a costbenefit contribution index system is developed to quantify the contribution of energy storage in the wind-solar-storage hybrid power plant. A cooperation revenue sharing model with contribution degree correction based on the minimum cost-remaining savings (MCRS) method is also proposed. The superiority of the proposed cooperation revenue sharing model for profitability enhancement of energy storage is validated through comparative case studies.

    Keywords: Renewable Energy, energy storage, electricity market, green power trading, Hybrid energy plant

    Received: 03 Jul 2024; Accepted: 30 Jul 2024.

    Copyright: © 2024 Zeng, Gao, Fang, Zhang and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xiang Gao, Shenzhen Polytechnic, Shenzhen, 518055, Guangdong, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.