What is it about?
This study explores how artificial intelligence can help predict electricity consumption in university buildings within a smart city project in Mar del Plata, Argentina. Using neural networks and real energy data, the work aims to improve energy management and support more efficient and reliable power systems.
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Why is it important?
This work is timely because smart grids and smart cities increasingly depend on data-driven tools to improve energy efficiency and power quality. The study is unique in combining real measurements from university buildings with neural network forecasting models, showing how AI can support practical energy management in urban environments.
Perspectives
From my personal perspective, this work represents an important first step in developing machine learning research lines within our group. One aspect I find especially valuable is that the models were trained using real data from very specific local applications. Energy consumption patterns in Latin American public universities differ significantly from those in Europe or other regions, so developing forecasting tools adapted to our own context is both scientifically and practically relevant.
Dr Patricio G. Donato
Consejo Nacional de Investigaciones Cientificas y Tecnologicas
Read the Original
This page is a summary of: Pronóstico de variables eléctricas en el marco del proyecto de ciudades inteligentes en Mar del Plata, September 2022, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/argencon55245.2022.9939911.
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