Resiliency-informed optimal scheduling of smart distribution network with urban distributed photovoltaic: A stochastic P-robust optimization

Shuaijie Wang, Ye Hou, Xin Guan, Shu Liu and Zhaoyi Huo

Energy, 2024, vol. 313, issue C

Abstract: An increased worldwide emphasis on resilience has resulted in a greater concentration on the distribution networks' resiliency. Therefore, the conventional approach to advance scheduling for power distribution networks is no longer sufficient, thereby requiring the creation of resilient scheduling approaches. This paper examines a proactive day-ahead scheduling method for distribution networks that are linked with significant renewable energy sources. The suggested approach employs a probabilistic scenario-generating strategy to quantify the uncertainties related to wind speed, solar irradiation, catastrophe duration, and load fluctuations. This study utilizes a hybrid stochastic p-robust optimization technique to enhance the analysis and provide robust strategies against risks. The present methodology employs a regret-based metric to quantify the adverse impacts of uncertainty inside the proactive scheduling procedure. The suggested methodology is verified using an IEEE 33-bus test system that includes significant distributed photovoltaic sources. The findings indicate a significant decrease of 43 % in the highest level of regret, accompanied by a relatively limited rise of 1.22 % in the operational expenses of the distribution network. This framework efficiently manages natural occurrences in the day-ahead scheduling process, making it a very promising method for improving the robustness of power distribution networks.

Keywords: Resilient scheduling; Photovoltaic-reached distribution network; Natural disasters; Stochastic p-robust optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224032250

DOI: 10.1016/j.energy.2024.133449

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