Regret-aware optimization of hydrogen-assisted congestion control in a renewable-dominated reconfigurable distribution network

Xin He, BaoLai Zhang, HaoYang Jia, Kaixuan Xin, Youpeng Wang, Cheng Yu and BenXi Zhang

Renewable Energy, 2025, vol. 250, issue C

Abstract: The implementation of active power distribution network architectures, combined with significant renewable energy integration, enables better congestion management in power distribution systems. Hydrogen-based energy systems, electric vehicles, and diverse storage technologies are emerging as key solutions for managing contingent distribution networks under renewable energy variability. This study introduces an integrated virtual energy storage system (VESS) that combines renewable energy, hydrogen technology, electric vehicles, and various storage solutions to optimize congestion management. The main focus is network topology optimization through reconfiguration, which dynamically adjusts the grid's configuration to improve load balancing, reduce congestion, and minimize network losses. Additionally, a demand response program is incorporated, allowing dynamic adjustments to power and thermal consumption in response to price signals and grid congestion. To manage the uncertainties inherent in this approach, a stochastic P-robust optimization method is proposed, evaluating system performance under risk-aware operational strategies. Results demonstrate substantial improvements, with the risk-averse mode reducing regret levels by 70 % at the cost of a 10 % increase in operational costs, while storage utilization increased from 13 % to 46 %. The reconfiguration process improved system reliability and flexibility through a strategic switching mechanism, emphasizing the potential of the proposed VESS to advance the capabilities of smart grid technology.

Keywords: Renewable distribution network; Virtual energy storage system; Reconfiguration; Hydrogen energy; Demand adjustment; p-Robust optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:250:y:2025:i:c:s0960148125007463

DOI: 10.1016/j.renene.2025.123084

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