Risk-Averse Stochastic Programming for Planning Hybrid Electrical Energy Systems: A Brazilian Case

This work presents a risk-averse stochastic programming model for the optimal planning of hybrid electrical energy systems (HEES), considering regulatory policy applied to distribution in Brazil. Uncertainties associated with variables related photovoltaic (PV) generation, load demand, fuel price diesel generation and electricity tariff are considered, through definition scenarios. The conditional value-at-risk (CVaR) metric is used optimization problem consider consumer’s risk propensity. determines number type PV panels, battery storage capacities, which objective minimize investment operating costs over horizon. Case studies involving large commercial consumer carried out evaluate proposed model. Results showed that under normal conditions only system viable. PV/diesel tends be viable adverse hydrological consumers. Under this condition, PV/battery reduction 87% cost. An important conclusion analysis tool essential assist consumers decision-making process investing HEES.