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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D. G. Pylarinos
2016-10-01
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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.
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topic |
power consumption energy monitoring heuristic methods |
url |
https://etasr.com/index.php/ETASR/article/view/776 |
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