Enhancing Renewable Energy Integration via Robust Multi-Energy Dispatch: A Wind–PV–Hydrogen Storage Case Study with Spatiotemporal Uncertainty Quantification

Qilong Zhang, Guangming Li (), Xiangping Chen, Anqian Yang and Kun Zhu
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Qilong Zhang: School of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui 553004, China
Guangming Li: School of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui 553004, China
Xiangping Chen: School of Electrical Engineering, Guizhou University, Guiyang 550025, China
Anqian Yang: Electric Power Research Institute of Guizhou Power Grid Co., LTD., Guiyang 550025, China
Kun Zhu: School of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui 553004, China

Energies, 2025, vol. 18, issue 17, 1-18

Abstract: This paper addresses the challenge of renewable energy curtailment, which stems from the inherent uncertainty and volatility of wind and photovoltaic (PV) generation, by developing a robust model predictive control (RMPC)-based scheduling strategy for an integrated wind–PV–hydrogen storage multi-energy flow system. By building a “wind–PV–hydrogen storage–fuel cell” collaborative system, the time and space complementarity of wind and PV is used to stabilize fluctuations, and the electrolyzer–hydrogen production–gas storage tank–fuel cell chain is used to absorb surplus power. A multi-time scale state-space model (SSM) including power balance equation, equipment constraints, and opportunity constraints is established. The RMPC scheduling framework is designed, taking the wind–PV joint probability scene generated by Copula and improved K-means and SSM state variables as inputs, and the improved genetic algorithm is used to solve the min–max robust optimization problem to achieve closed-loop control. Validation using real-world data from Xinjiang demonstrates a 57.83% reduction in grid power fluctuations under extreme conditions and a 58.41% decrease in renewable curtailment rates, markedly enhancing the local system’s capacity to utilize wind and solar energy.

Keywords: renewable integration; spatiotemporal uncertainty; RMPC; hydrogen storage (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: 2025
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