Statistical Sizing of a 100% Renewable Energy System with Battery Energy Storage System

This paper presents a statistical framework to size a 100% renewable energy system (RES) integrated with battery energy storage system. The framework introduces innovative statistical power generation models. The framework includes both raw hourly meteorological data of (wind speed, solar irradiance, and ambient temperature) that form typical meteorological year (TMY) and loading requirements. Sizing optimization was based on genetic algorithm (GA) as a minimum seeking algorithm. The results shows the effect of loading percentages on the different statistical parameters. The parameters can form, in separate or together, decision-making parameters to select the desirable size of the 100% RES and the associated battery energy storage system that needed to be installed.