Accuracy of ANN based methodology for load composition forecasting at bulk supply buses

Yizheng Xu, J V Milanovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate prediction of load composition at bulk supply points can significantly improve power system planning, electricity market analysis and demand side management. This paper discusses an artificial neural network (ANN) based approach to forecasting load composition at the bulk supply bus based on RMS measurement of voltage, real and reactive power and local forecasted weather. Probabilistic distributions and confidence levels of the prediction under different prediction error intervals have been derived and analysed. It is demonstrated that the approach yields prediction of load composition with errors typically less than 10%.
Original languageEnglish
Title of host publicationhost publication
Number of pages6
DOIs
Publication statusPublished - 2014
EventInternational Conference on Probabilistic Methods Applied to Power Systems (PMAPS) -
Duration: 1 Jan 1824 → …

Conference

ConferenceInternational Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Period1/01/24 → …

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