Autonomy evaluation model for a photovoltaic residential microgrid with a battery storage system

The dependence on fossil resources remains high, accounting for 80% of the total primary energy production worldwide. In addition, the COVID-19 pandemic has devastated several industries and electric power is no exception. Therefore, renewable energy sources have become an important aspect of the energy sector, contributing to solutions to environmental problems and the development of a sustainable future. Therefore, this study proposes a model to evaluate the energy autonomy of a photovoltaic microgrid (EA_PV,MG) using a battery energy storage system (BESS). To carry out the analysis, the energy consumption history of a residence and the solar irradiation data of the location were used. Thus, this study includes the evaluation of the energy compensation of a photovoltaic microgrid that directly injects energy into the residence, and the surplus is stored in a BESS for later use. The results show the relevance of EA_PV,MG modeling for optimal system sizing. The model determines the autonomy of the microgrid without many power variations in the PV system for January, April, and October, corresponding to the summer, autumn, and spring seasons, respectively. However, in July (winter), the photovoltaic MG must increase the installation power considerably and the storage capacity of the BESS. Therefore, an optimal decision evaluating the EA_PV,MG will allow broadening an overview to opt for a PV microgrid that injects the highest amount of energy based on the actual residential load profile and the optimal capacity of the BESS. Consequently, the analysis of the EA of a microgrid based on solar irradiation and actual load data is essential for developing an optimal and stable operation of the residential energy system.