Unit Commitment Scheduling Using a Hybrid ANN and Lagrangian Relaxation Method

Abstract

A hybrid artificial neural network (ANN) Lagrangian relaxation approach to combinatorial optimization problems in power systems, in particular to unit commitment is presented in this paper. Until now, the Lagrangian relaxation method has been studied as it appeared to be the most practical method for obtaining an approximate solution to unit commitment. Based on the use of supervised learning neural-net technology and the adaptive pattern recognition concept, which presume the relationship between power demand pattern and Lagrange multipliers (LMPs). The numerical results obtained are very encouraging.