Work

A Highly Accurate and Efficient Statistical Framework for Short-Term Load Forecasting: A Case Study for Mexico

Year: 2026

Type: article

Abstract: Short-term load forecasting is fundamental for the effective and reliable operation of power systems. Very accurate forecasting methods often involve complex hybrid approaches that combine statistical, physical, and/or intelligent techniques. In this work, we present an innovative, clear, and effective methodology for short-term hourly peak load forecasting that is both simple and highly accurate. The methodology is based on the load forecast used for electricity market purposes, together with fine-tuning dynamic estimation. As a case study, the methodology was applied and tested in Mexico’s interconnected power system. It was implemented across various regions and at both regional and load-\ zone levels of this interconnected power system and, even under a variety of standard and extreme load conditions, achieved outstanding results.

Source: Forecasting

DOI: 10.3390/forecast8010003

Authors: Luis Conde-López, Monica Borunda, Gerardo Ruiz-Chavarría, Tomás Aparicio-Cárdenas

Institutions: Tecnológico Nacional de México, Centro Nacional de Investigación y Desarrollo Tecnológico, Universidad Nacional Autónoma de México

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,172