Monte Carlo Simulation approach for economic risk analysis of an emergency energy generation system

Abstract

Electric generators are largely employed as emergency power sources by preventing some facilities from sudden interruptions of electric energy supply. They may also be used to reduce the energy demand from the power grid by providing electricity over the peak periods. This paper aims to evaluate the owners' economic risk of purchasing an electric generator in order to provide energy during the peak time. The study considers different rated powers of diesel and natural gas-based generators as well as cases with and without an extra expense due to the carbon credit (CCr), which is a cost generated by the emission of greenhouse gases (GHG). Net Present Value (NPV) is used as a method for the economic feasibility analysis while Monte Carlo Simulation (MCS), a stochastic approach, is performed to evaluate the economic risk. To verify the applied methodology and accomplish the goals of this work, a Brazilian university project is taken as a case study and the campus is assumed to be an investor of an electric generator. The analysis is performed considering that the facilities are fed energetically during short periods of the day. All rules from Brazilian energy market are taken into consideration. Diesel and natural gas-based generators are able to guarantee a low risk of return on investment to investors and such risk is truly dependent on the generator rated power. Diesel generators present a narrow range of rated powers with a high probability of positive NPV whereas natural gas-based engines show a wide range of them with a null risk of an unprofitable purchase. In cases where carbon credits are considered as extra costs, the probability of a failed business is always higher than the cases they are not taken into account, although the carbon credits have no high sensitivity in the risk analysis.