Optimization energy management in buildings with neural networks

Abstract

Neural networks algorithms are tested to replace an optimization module, for the energy management of a residential grid-connected PV system with storage. Multi-layer perceptrons are generic tools able to map non-linear relationships between inputs and outputs without knowing any information about the system model. This study shows multiple problems of the implementation of these techniques, despite their theoretical promising interests.