Modeling and Simulation of Renewable Energy Sources by Markov Chains

Abstract

The increased participation of renewable variable energy sources (RVS) in the Brazilian electricity matrix brings several challenges to the planning and operation of the Brazilian Electricity System (BES) due to the stochasticity present in RVS. Such challenges involve the modeling and simulation of intermittent generation processes. In this context, this work aims to simulate power generation scenarios of three Brazilian plants, each based on three distinct renewable sources: wind power, solar, and biomass. The methodology used is based on the modeling of historical time series by Markov Chains, and the generation of scenarios is performed by Monte Carlo simulation. The results obtained are promising: the simulated scenarios satisfactorily reproduced the characteristics of the historical generation data of the plants.