Monte Carlo simulation, network equivalents, probabilistic power flow, renewable generation, seasonality
Abstract
The seasonality of energy generation sources impacts the operational and planning stages of the electric sector, causing variations in the generation profile throughout the year, among other factors. This work conducts a study on the impact of hydrological seasonality on the accuracy of network equivalents through probabilistic power flow via Monte Carlo simulation. The accuracy of the equivalents is quantified, considering uncertainties in demand, variations in the generation profile, and the occurrence of transmission element contingencies. Three network reduction methods are evaluated in two simulation environments: chronological and non-chronological. The first aims to analyze the impact of using an equivalent obtained from the typical configuration of a specific month on the other months of the year. The second aims to compare different network reduction methodologies in the face of variations in the reduction point, such as transmission contingencies. The studies are conducted using the IEEE 24-bus and IEEE 118-bus systems. The simulation results are discussed, highlighting the importance of using the appropriate reduced network to ensure coherent results.
