Planejamento probabilístico de sistemas híbridos de energia elétrica com análise de risco

Abstract

This work presents a methodology for planning hybrid electrical energy systems (HEES) with risk analysis, considering the regulatory policy applied to distribution systems in Brazil (ANEEL Normative Resolution 482/2012). For this purpose, the problem is modeled as stochastic programming considering uncertainties associated with random variables of the problem: clearness index for the photovoltaic system, load demand, fuel price for thermoelectric generation and energy tariff. In the proposed model, scenarios are defined to consider the random variables mentioned in a combined way, that is, a given combination of these variables results in a scenario. Additionally, the methodology includes a tool to analyze the economic risk propensity of each consumer. The methodology determines the number and type of the photovoltaic panels, diesel generation capacity and battery storage system capacity, in which the objective is to minimize investment and operation costs over the planning horizon. Case studies involving two large commercial consumers are introduced to evaluate the proposed methodology. To model and solve the resulting optimization problem, the Pyomo, a Python-based, open-source optimization modeling language and Gurobi solver was used, respectively. An important conclusion is that the methodology can assist consumers in the decision-making of investing in HEES