Journal ArticleDOI
An expert system based algorithm for short term load forecast
Saifur Rahman,R. Bhatnagar +1 more
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In this article, an expert-system-based 1-24-hour load forecasting algorithm is presented as an alternative to the traditional 1-6-hour and 24-hour forecasting algorithms.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%. >read more
Citations
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Electric load forecasting using an artificial neural network
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Analysis andEvaluation ofFiveShort-Term Load Forecasting Techniques
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References
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Journal ArticleDOI
Adaptive Short-Term Forecasting of Hourly Loads Using Weather Information
Pradeep C. Gupta,Keigo Yamada +1 more
TL;DR: In this paper, a comprehensive computer-oriented procedure for probabilistic forecasting of hourly power-system loads with lead times of 1 to 24 hours is described, based on both historical load data and information from the latest weather forecast.
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On-Line Load Forecasting for Energy Control Center Application
TL;DR: In this article, the authors present a real-time control center for power systems that provides a short-term internal system load forecast for on-line commitment, maintenance scheduling, security analysis, and on-online load flow solutions.
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On-Line Algorithms for Forecasting Hourly Loads of an Electric Utility
TL;DR: In this article, a method which lends itself to online forecasting of hourly electric loads is presented and the results of its use are compared to models developed using the Box-Jenkins method.
Journal ArticleDOI
Forecasting of Hourly Load By Pattern Recognition A Deterministic Approach
TL;DR: In this article, an algorithm using pattern recognition techniques and current weather parameters was proposed to forecast hourly electric load with a lead time of one to three hours, which can be increased to at most 24 hours with the use of forecasted weather parameters.