Residential end-use load-shape estimation. Volume 1. Methodology and results of statistical disaggregation from whole-house metered loads. Final report
End-use load shapes are important for the development of improved load forecasting techniques, analysis of load management and costing/rate making. A methodology for estimating end-use load shapes using hourly whole-house metered load data, household demographic survey data, and weather data (temperature) is presented. Although the focus of the project was on the residential sector, the techniques developed can also be applied to the industrial and commercial sectors. In the present approach, the coupling of lifestyle and weather in load demand is clearly modeled. Weather-independent load is modeled with Fourier-like terms (sine and cosine functions) and dummy variables, and weather-dependent load is represented by a thermodynamics-based nonlinear dynamic model exhibiting heat build-up effect, thermostat set-point variation, and appliance saturation. Automatic data pre-processing is incorporated to eliminate anomalous data using pattern recognition techniques. The overall methodology provides an effective means for end-use load shape modeling. In particular, the effect of weather on electricity demand, which concerns power system forecasters and planners, is accurately represented.
- Research Organization:
- Scientific Systems, Inc., Cambridge, MA (USA)
- OSTI ID:
- 5746649
- Report Number(s):
- EPRI-EM-4525-Vol.1; ON: TI86920280
- Country of Publication:
- United States
- Language:
- English
Similar Records
A multi-level load shape clustering and disaggregation approach to characterize patterns of energy consumption behavior
Regional load curve models: specification and estimation of the DRI Model. Final report. [Forecasts of electric loads in 32 US regions]