Análise de risco da implantação de sistemas fotovoltaicos conectados à rede diante do sistema brasileiro de compensação de energia elétrica

Abstract

The increased demand for electricity, driven by population growth and technological and industrial development, added to the environmental issues and the possibility of depleting fossil fuels has encouraged renewable energy sources, such as photovoltaics. The energy generated by photovoltaic systems is a function of several random variables: solar irradiance, ambient temperature, wind speed, relative humidity, and wind direction. Given the increasing participation of solar generation in the national electrical system and encouraging this type of clean energy, it is essential to carry out economic analyses from a more precise perspective. In this context, this work presents a methodology for analyzing the risk of investments in electricity generation through grid-connected photovoltaic systems (GCPV), considering the Net Metering (NM) incentive policy established in ANEEL Normative Resolution No. 482/2012. The proposed risk analysis methodology is applied in two case studies of photovoltaic systems installed in the Itumbiara and Goiânia campuses of the Federal Institute of Goiás (IFG). The applied method makes use of Monte Carlo simulation to generate the synthetic series of random variables. Revenues are derived from the reduction of electricity consumption by the concessionaire and the compensation of credits obtained from electricity injected into the network in subsequent bills. The sensitivity analysis of the key parameters that influence the feasibility of the GCPV implementation is performed, namely: the zenith angle of the photovoltaic panels, the off-peak energy price, the price of energy credits, and the investment cost. The results indicate, through stochastic analyzes, the economic viability of the installation of SFCR before the NM system of ANEEL in all the simulations analyzed. However, the sensitivity analysis points out that some parameters are more sensitive, such as the price of compensated energy and the investment cost, which may make the project unfeasible depending on their values.