Stochastic Analysis of the Flow of the Vilcanota River in the Machupicchu Hydroelectric Power Plant using ARIMA models 2023

Moscoso M.C.; Rey J.E.A.; Segura J.B.; Serna-Landivar J. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/laccei2024.1.1.1126

Resumen

The constant demand for energy consumption suggests that its supply be duly attended to for the economic and social development of the country.Since fossil fuels generate a large amount of carbon emissions and are also being depleted; The change towards renewable energies is essential.However, the creation and commissioning of clean energy plants is a crucial challenge because it is difficult to obtain natural resources for continuous energy generation.Consequently, a forecast model is an important tool to anticipate energy generation, consumption and reserve.This document presents a flow forecasting model for hydroelectric energy production, using the autoregressive integrated moving average (ARIMA) model.The data involved was obtained from the Machupicchu Hydroelectric Power Plant.Although the energy capacity of the hydroelectric plant is greatly affected by environmental variability, having a forecast model and a long-term plan that will greatly benefit the production of renewable energy to meet the continuous increase in the demand.

Instituciones: Universidad Nacional Agraria La Molina; Universidad Tecnológica del Perú; Universidad Privada del Norte