Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier

arXiv:2310.08601v2 Announce Type: replace-cross
Abstract: The system operators usually need to solve large-scale unit commitment problems within limited time frame for computation. This paper provides a pragmatic solution, showing how by learning and predicting the on/off commitment decisions of conventional units, there is a potential for system operators to warm start their solver and speed up their computation significantly. For the prediction, we train linear and kernelized support vector machine classifiers, providing an out-of-sample performance guarantee if properly regularized, converting …

abstract arxiv classifier commitment computation cs.lg decisions machine math.oc operators paper performance scale solution solve stat.ap support type units vector