An expert system based algorithm for short term load forecast

Abstract
Existing studies on 1-24 hr load forecasting algorithms are reviewed, and an expert-system-based algorithm is presented as an alternative. The logical and syntactical relationships between weather and load as well as the prevailing daily load shapes have been examined to develop the rules for this approach. Two separate, but similar, algorithms have been developed to provide 1-6 hr and 24 hr forecasts. These forecasts have been compared with observed hourly load data for a Virginia electric utility for all seasons of the year. The 1 hr and 6 hr forecast errors (absolute average) ranged from 0.869% to 1.218% and from 2.437% to 3.48% respectively. The 24 hour forecast errors (absolute average) ranged from 2.429% to 3.300%.

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