Abstract

We benchmark state-of-the-art methods for forecasting electricity demand on the household level. Our evaluation is based on two data sets containing the power usage on the individual appliance level. Our results indicate that without further refinement the considered advanced state-of-the-art forecasting methods rarely beat corresponding persistence forecasts. Therefore, we also provide an exploration of promising directions for future research.

Keywords:
Electricity demand Benchmark (surveying) Demand forecasting Electricity Computer science Power demand Electricity generation Econometrics Operations research Industrial engineering Environmental economics Power (physics) Power consumption Engineering Economics Electrical engineering

Metrics

64
Cited By
4.25
FWCI (Field Weighted Citation Impact)
27
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Load and Power Forecasting
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Efficiency and Management
Physical Sciences →  Energy →  Renewable Energy, Sustainability and the Environment

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