Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora
Svetlana Roudolfovna Chemetova 1 * , Paulo Santos 1, Mário Ventim-Neves 2
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1 Instituto Politécnico de Setúbal, PORTUGAL
2 Universidade Nova de Lisboa, PORTUGAL
* Corresponding Author

Abstract

Currently, load forecasting is a fundamental task for planning, operation and exploration of the electric power systems. The importance of forecasting has become more evident with the restructuring of the national energy sector, thus, promoting projects linked to smart grids, namely in Portugal - InovGrid. This study proposes the computational forecast model of the load diagram based on the Levenberg-Marquardt algorithm of Artificial Neural Networks. The used data are the time series of active power, recorded by EDP Distribution Telemetry System, and the climatic time series of the Portuguese Institute of the Sea and Atmosphere, collected on the city of Évora. The forecast horizon is short term: from one hour to a week. The results showed that main statistical error parameter (mean absolute percentage error) was not exceed 5%.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.20897/jisem.201718

J INFORM SYSTEMS ENG, 2017 - Volume 2 Issue 3, Article No: 18

Publication date: 02 Aug 2017

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