TL;DR本文探讨了利用已有的 ACOPF 数据来预测未来问题的解决方案的方法,使用数据驱动建模的 Random Forest 算法并采用多目标学习方法预测未来问题的解,从而实现了快速求解 ACOPF 问题的智能预热初始点。
Abstract
A large amount of data has been generated by grid operators solving AC
optimal power flow (ACOPF) throughout the years, and we explore how leveraging
this data can be used to help solve future ACOPF problems. We use this data to
train a random forest to predict solutions of future ACOP