Multi-objective resilient recovery strategy for urban wind-solar-MPS-EV electric system after disastrous events

Yihao Xu, Yankai Xing, Guangdou Zhang, Jian Li, Haopeng An, Olusola Bamisile and Qi Huang

Applied Energy, 2024, vol. 369, issue C, No S0306261924009346

Abstract: The situation in an urban distribution network becomes intricate under high-impact, low-probability events. Furthermore, the growing quantity of components within the urban distribution network renders their analysis more challenging. Thus, the desired recovery strategy should not only meet the requirements of restoration rates but also guarantee a stable power supply. To address this issue, this paper proposes a multi-objective decision analysis framework, which consists of EV user requirements, MPS routing, and emergency repair crew schedule, to generate a more precise recovery strategy. These objectives' dynamic behaviors in the transportation network are transformed into spatiotemporal characteristic variables and introduced into inequality constraints. Also, the Wasserstein generative adversarial network with gradient penalty is employed in this framework to characterize solar and wind realistic output. By minimizing the weighted sum composed of MPS operational costs, EV user expenses, load loss, and voltage fluctuation, an optimized recovery strategy is provided to the grid operator. Case studies investigate the effectiveness of recovery strategy in IEEE 33-bus and 123-bus benchmark systems. The results indicate the proposed approach can effectively handle complex scenarios achieving rapid and reliable restoration, while also preserving regular charging behavior and maintaining a stable power voltage supply.

Keywords: Power system resilience; Electric vehicles; Distribution system restoration; Power quality; High-impact and low-probability (HILP) events (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123551

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