CIRED - Open Access Proceedings Journal · 2017 · 27 citations · 10 references
ArchitectureBuilding ScienceDemand ForecastingForecastingTime Series AnalysisBuilding Energy ModelingBuilding Energy SystemsEnergy Demand ForecastingLoad CalculationLoad ForecastingTime Series ForecastingDemand Forecasting For BuildingsElectric Load ForecastingElectricity Consumption ForecastingK-nearest NeighborsLoad ProfilingPower Demand ModelingShort-term Load ForecastingSmart City Applications
Following the ongoing transformation of the European power system, in the future, it will be necessary to locally balance the increasing share of decentralised renewable energy supply. Therefore, a reliable short-term load forecast at the level of single buildings is required. In this study, we use a forecaster, which is based on K-nearest neighbours approach and was introduced in an earlier publication, on three buildings of Smart City Demo Aspern project. The authors demonstrate how this forecaster can be applied on different buildings without any manual setup or parametrisation, showing that it is viable to replace load-profiling solutions for predicting electricity consumption at the level of single buildings.
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