The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market

Tang Xinfa (), Wang Jingjing, Wang Yonghua and Wan Youwei ()
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Tang Xinfa: School of Economic Management and Law, Jiangxi Science and Technology Normal University, Nanchang 330038, China
Wang Jingjing: School of Economic Management and Law, Jiangxi Science and Technology Normal University, Nanchang 330038, China
Wang Yonghua: State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330032, China
Wan Youwei: School of Economic Management and Law, Jiangxi Science and Technology Normal University, Nanchang 330038, China

Energies, 2024, vol. 17, issue 18, 1-18

Abstract: This paper presents an optimization method for scheduling a multi-energy VPP (Virtual Power Plant) supply–demand balance in the power market environment of Jiangxi Province. The primary objective of this method is to improve the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. The method takes into account the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. Furthermore, it integrates real-time market price feedback to achieve the accurate allocation of power supply and demand. Through a case study of a multi-energy VPP in Jiangxi Province, this paper examines the optimal combination model for various energy sources within VPP, and analyzes the impact of different market environments on supply–demand balance. The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.

Keywords: multi-energy VPP; balance between supply and demand; scheduling planning optimization; multi-objective optimization algorithm; energy efficiency of renewable energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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