@article{Rojas-Renteria_Espinoza-Huerta_Tovar-Pacheco_Gonzalez-Perez_Lozano-Dorantes_2016, place={Greece}, title={An Electrical Energy Consumption Monitoring and Forecasting System}, volume={6}, url={https://www.etasr.com/index.php/ETASR/article/view/776}, DOI={10.48084/etasr.776}, abstractNote={<p style="text-align: justify;">Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.</p>}, number={5}, journal={Engineering, Technology & Applied Science Research}, author={Rojas-Renteria, J. L. and Espinoza-Huerta, T. D. and Tovar-Pacheco, F. S. and Gonzalez-Perez, J. L. and Lozano-Dorantes, R.}, year={2016}, month={Oct.}, pages={1130–1132} }