With the widespread use of distributed generation and electric vehicles, the uncertainty of distribution network operation is increased, challenging risk assessment. This paper proposes a generalized load modeling and risk assessment method based on GNG–Informer–WOA. GNG adaptively clusters load curves to identify typical patterns and noise; WOA optimizes Informer’s hyperparameters for high-precision prediction. An index system covering voltage out-of-limit, regulation capacity, and new energy consumption risks is established, with weights determined by fusing AHP and PCA via game theory. Case studies on the improved IEEE 33-bus system show the method effectively characterizes generalized load characteristics and accurately evaluates risks under different scenarios, supporting safe operation.
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Ying Wang
École Centrale de Nantes
Qikai Zhao
China Jiliang University
Mingshen Wang
Electric Power Research Institute
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Wang et al. (Sat,) studied this question.
synapsesocial.com/papers/69af95ee70916d39fea4e145 — DOI: https://doi.org/10.3390/en19051369