Journal of Information Systems Engineering & Management

Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora

Svetlana Roudolfovna Chemetova E-MAIL CORRESPONDING AUTHOR
Instituto Politécnico de Setúbal, PORTUGAL
Instituto Politécnico de Setúbal, PORTUGAL
Universidade Nova de Lisboa, PORTUGAL
Journal : Journal of Information Systems Engineering & Management, Volume 2, Issue 3

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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