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arXiv · 2411.02159

Distributed Stochastic ACOPF Based on Consensus ADMM and Scenario Reduction

Shan Yang·Yongli Zhu
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Abstract

This paper presents a Consensus ADMM-based modeling and solving approach for the stochastic ACOPF. The proposed optimization model considers the load forecasting uncertainty and its induced load-shedding cost via Monte Carlo sampling. The sampled scenarios are reduced using a clustering method combined with simultaneous backward reduction techniques to reduce the computational complexity. The proposed approach is tested on two IEEE systems, achieving about 2% cost reduction and more than 15 times lower reliability index in stochastic load settings compared to the baseline approach.

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Shan Yang, Yongli Zhu. 2024-11-04. Distributed Stochastic ACOPF Based on Consensus ADMM and Scenario Reduction. https://arxiv.org/abs/2411.02159

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