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Advisor(s)
Abstract(s)
The importance of forecasting has become more evident with the appearance of the open electricity market and the restructuring of the national energy sector.
This paper presents a new approach to load forecasting in the medium voltage distribution network in Portugal. The forecast horizon is short term, from 24 hours up to a week. The forecast method is based on the combined use of a regression model and artificial neural networks (ANN).
The study was done with the time series of telemetry data of the DSO (EDP Distribution) and climatic records from IPMA (Portuguese Institute of Sea and Atmosphere), applied for the urban area of Évora - one of the first Smart Cities in Portugal.
The performance of the proposed methodology is illustrated by graphical results and evaluated with statistical indicators. The error (MAPE) was lower than 5%, meaning that chosen methodology clearly validate the feasibility of the test.
Description
Trabalho apresentado no 7th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS’16), 11-13 abril de 2016, Caparica, Portugal
Keywords
Electric power systems load forecasting smart-grids distribution systems electric substations artificial neural networks