Study Of A Hybrid Photovoltaic-Wind Smart Microgrid Using Data Science Approach

Abstract

In this paper, a smart microgrid implemented in Paracas, Ica, Peru, composed of 6 kWp PV + 6 kW Wind and that provides electricity to a rural community of 40 families, was studied using a data science approach. Real data of solar irradiance, wind speed, energy demand, and voltage of the battery bank from 2 periods of operation were studied to find patterns, seasonality, and existing correlations between the analyzed data. Among the main results are the periodicity of renewable resources and demand, the weekly behavior of electricity demand and how it has progressively increased from an average of 0.7 kW in 2019 to 1.2 kW in 2021, and how power outages are repeated at certain hours in the morning when resources are low or there is a failure in the battery bank. These analyzed data will be used to improve sizing techniques and provide recommendations for energy management to optimize the performance of smart microgrids.