Hydrological uncertainty analysis using Monte Carlo simulations to determine power purchasing agreements for small hydroelectric powerplants

Abstract

The energy generated by Small Hydroelectric Plants (SHPs) is sold in Brazil using a Physical Energy Guarantee, also known as a Power Purchase Agreement (PPA), the maximum amount of energy that a generator can sell. The PPA is calculated based on monthly average flow series data, however, studies have shown that this can overestimate the PPA and that daily average flow series data are more accurate in reflecting the amount of generated electric energy. Unlike other hydrological evaluations, the uncertainty levels associated with the data used to calculate the PPA at SHPs are neither considered nor quantified. This study investigates the impact of hydrological uncertainties on SHP PPAs. The Monte Carlo method was used to analyze the uncertainty levels for an SHP case study. It has been elaborated 2 models, where the results show that the models have on average an upper deviation of 1.30 MW from current PPA and a lower deviation of 1.19 MW from the current PPA. Dispersion analysis revealed that SHPs with smaller installed capacities and lower PPAs faced more business risks than SHPs with higher PPAs, which are generally more thoroughly evaluated by investors.