Determination of models of simple regression and multivariate analysis for the forecast of the electricity price in Colombia at 2030

The electricity price in Colombia responds to demographic, economic, climatic changes, among others, that generate uncertainty and therefore risks in the electric production. Considering that the decision-making process has a great importance in the electricity market and that the participation of g...

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Autores:
Hernández Bueno, Nelson Javier
Pinto Calderón, María De Los ángeles
Muñoz Maldonado, Yecid Alfonso
Ospino Castro, Adalberto Jose
Ospino C., Adalberto
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/1212
Acceso en línea:
https://hdl.handle.net/11323/1212
https://repositorio.cuc.edu.co/
Palabra clave:
Econometric Modeling
Methods of Statistical Simulation
Forecasting
Electricity Price
Rights
openAccess
License
Atribución – No comercial – Compartir igual
Description
Summary:The electricity price in Colombia responds to demographic, economic, climatic changes, among others, that generate uncertainty and therefore risks in the electric production. Considering that the decision-making process has a great importance in the electricity market and that the participation of generators in energy auctions is usually based on intuition and previous experience, the need to study the possible alternatives and methods that minimize the risks before deciding some important matter can be appreciate. In this article, the estimation of the behavior of electrical energy prices in Colombia at the year 2030 for different scenarios and there are propose the following scientific models: (1) Simple regression; (2) econometric model. As result are obtained forecasts for each model, identifying that the econometric model has the lowest margin of error compared to the historical data that considers the behavior of different variables for the forecast