Energy Consumption Prediction in a Novel Automated Photovoltaic Design Platform

This paper describes a multi-step algorithm used to predict and typify the energy consumption profile of prosumer, allowing automation design self-consumption photovoltaic (PV) power systems in novel platform called PV SPREAD. The uses different methodologies address various possible scenarios data availability. In this paper, those are addressed using nonlinear autoregressive artificial neural networks (ANN) with external inputs (NARX) consumption. Results reveal that proposed successfully addresses gaps hotel load as case study. results also show limitations NARX when residential clients analyzed.