A regression-based approach to short-term system load forecasting

A linear regression-based model for the calculation of short-term system load forecasts is described. The model's most significant aspects fall into the following areas: innovative model building, including accurate holiday modeling by using binary variables and temperature modeling by using he...

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Veröffentlicht in:IEEE transactions on power systems 1990-11, Vol.5 (4), p.1535-1547
Hauptverfasser: Papalexopoulos, A.D., Hesterberg, T.C.
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Hesterberg, T.C.
description A linear regression-based model for the calculation of short-term system load forecasts is described. The model's most significant aspects fall into the following areas: innovative model building, including accurate holiday modeling by using binary variables and temperature modeling by using heating and cooling degree functions; robust parameter estimation and parameter estimation under heteroskedasticity by using weighted least-squares linear regression techniques; use of 'reverse errors-in-variables' techniques to mitigate the effects on load forecasts of potential errors in the explanatory variables; and distinction between time-independent daily peak load forecasts and the maximum of the hourly load forecasts in order to prevent peak forecasts from being negatively biased. The model was tested under a wide variety of conditioning and is shown to produce excellent results.< >
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subjects 290100 - Energy Planning & Policy- Energy Analysis & Modeling
292000 - Energy Planning & Policy- Supply, Demand & Forecasting
296000 - Energy Planning & Policy- Electric Power
ACCURACY
Economic forecasting
ELECTRIC POWER INDUSTRY
ENERGY MODELS
ENERGY PLANNING, POLICY AND ECONOMY
FORECASTING
INDUSTRY
Load flow
Load forecasting
LOAD MANAGEMENT
Load modeling
MANAGEMENT
MATHEMATICS
Parameter estimation
Power system control
Power system modeling
Power system security
Power systems
Predictive models
REGRESSION ANALYSIS
STATISTICS
title A regression-based approach to short-term system load forecasting
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