An Electrical Energy Consumption Monitoring and Forecasting System

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 con...

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Main Authors: J. L. Rojas-Renteria, T. D. Espinoza-Huerta, F. S. Tovar-Pacheco, J. L. Gonzalez-Perez, R. Lozano-Dorantes
Format: Article
Language:English
Published: D. G. Pylarinos 2016-10-01
Series:Engineering, Technology & Applied Science Research
Subjects:
Online Access:https://etasr.com/index.php/ETASR/article/view/776
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spelling doaj-39ba74196dbb4ffba7e0f460e15140d72020-12-02T15:46:17ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362016-10-0165An Electrical Energy Consumption Monitoring and Forecasting SystemJ. L. Rojas-Renteria0T. D. Espinoza-Huerta1F. S. Tovar-Pacheco2J. L. Gonzalez-Perez3R. Lozano-Dorantes4Engineering Dpt, Autonomous Universityof Queretaro, MexicoFaculty of Accounting and Administration, Autonomous University of Queretaro, MexicoIndustrial Maintenance and Construction Dpt, Technological University of San Juan del Rio, MexicoLinking Dpt, Polytechnic University of Santa Rosa Jauregui, MexicoEngineering Dpt, Anahuac University, MexicoElectricity 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. https://etasr.com/index.php/ETASR/article/view/776power consumptionenergy monitoringheuristic methods
collection DOAJ
language English
format Article
sources DOAJ
author J. L. Rojas-Renteria
T. D. Espinoza-Huerta
F. S. Tovar-Pacheco
J. L. Gonzalez-Perez
R. Lozano-Dorantes
spellingShingle J. L. Rojas-Renteria
T. D. Espinoza-Huerta
F. S. Tovar-Pacheco
J. L. Gonzalez-Perez
R. Lozano-Dorantes
An Electrical Energy Consumption Monitoring and Forecasting System
Engineering, Technology & Applied Science Research
power consumption
energy monitoring
heuristic methods
author_facet J. L. Rojas-Renteria
T. D. Espinoza-Huerta
F. S. Tovar-Pacheco
J. L. Gonzalez-Perez
R. Lozano-Dorantes
author_sort J. L. Rojas-Renteria
title An Electrical Energy Consumption Monitoring and Forecasting System
title_short An Electrical Energy Consumption Monitoring and Forecasting System
title_full An Electrical Energy Consumption Monitoring and Forecasting System
title_fullStr An Electrical Energy Consumption Monitoring and Forecasting System
title_full_unstemmed An Electrical Energy Consumption Monitoring and Forecasting System
title_sort electrical energy consumption monitoring and forecasting system
publisher D. G. Pylarinos
series Engineering, Technology & Applied Science Research
issn 2241-4487
1792-8036
publishDate 2016-10-01
description 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.
topic power consumption
energy monitoring
heuristic methods
url https://etasr.com/index.php/ETASR/article/view/776
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