Optimal Control Based on Deep Learning Techniques for a Hybrid Solar-Biomass System for Residential Buildings
Abstract
The EU-funded H2020 project SolBio-Rev aims to develop an energy system based on the use of solar energy and biomass is being developed to provide heating, cooling, domestic hot water, and electricity to for different building typologies located in different climates. In this study, deep reinforcement learning techniques were applied for a SolBio-Rev system designed for a residential building located in a Mediterranean climate in order to define an optimal control policy able to minimize the operating cost during summer and winter.