Predictive Modeling of Photovoltaic Solar Power Generation

Abstract

Photovoltaic solar power referred to as solar power using photovoltaic cells, is a renewable energy source. The solar cells' electricity may be utilized to power buildings, neighborhoods, and even entire cities. A stable and low-maintenance technology, photovoltaic solar power is an appealing alternative for generating energy since it emits no greenhouse gases and has no moving components. This paper aimed to provide a photovoltaic solar power generation forecasting model developed with machine learning approaches and historical data. In conclusion, this type of predictive model enables the evaluation of additional non-traditional sources of renewable energy, in this case, photovoltaic solar power, which facilitates the planning process for the diversification of the energy matrix. Random Forests obtain the highest performance, with this knowledge power systems operators may forecast outcomes more precisely, this is the main contribution of this work.