Queensland's institutional digital repository (The University of Queensland) · 2003 · 19 citations · 4 references
ComputingData ScienceElectrical EngineeringForecastingMachine LearningTime Series AnalysisElectricity MarketsForecast EvaluationForecasting MethodsSupport Vector MachinesTime Series ForecastingTime Series PredictionElectricity Market AnalysisElectricity Price ForecastingForecasting AccuracyForecasting Accuracy EvaluationMachine Learning-based Price ForecastingSpot Electricity MarketsSupport Vector ClassificationSupport Vector Machine Classification
In this paper we present an analysis of the results of a study into wholesale (spot) electricity price forecasting with Support Vector Machines (SVM) utilising past price and demand data and Projected Assessment of System Adequacy (PASA) data. The forecasting accuracy was evaluated using Australian National Electricity Market (NEM), New South Wales regional data over the year 2002. The inclusion of PASA data shows little improvement in forecasting accuracy.
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Corinna Cortes, Vladimir Vapnik · Machine Learning · 1995 · 33K citations · Full text
Damien C. Sansom, T. Downs, Tapan Kumar Saha · Queensland's institutional digital repository (The University of Queensland) · 2002 · 56 citations