Application of Intelligent Optimization Algorithms on Short-Term Electric Load Forecasting: A Review

The optimization algorithms to determine the coefficients of predicting the short-term load original methods is one of the strategies to estimate complex issues with the electricity system's functioning and control. Although there are many essential subjects in power system operation, load pred...

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Bibliographic Details
Published in2023 3rd International Scientific Conference of Engineering Sciences (ISCES) pp. 140 - 144
Main Authors Sadiq, Taha Abbas, Hussein, Balasim Mohammed
Format Conference Proceeding
LanguageEnglish
Published IEEE 03.05.2023
Subjects
Basic
Classification algorithms
Hybrid
Load forecasting
Modified
Optimization algorithms
Planning
Power systems
Prediction algorithms
Predictive models
Short-term
Surveys
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Summary:The optimization algorithms to determine the coefficients of predicting the short-term load original methods is one of the strategies to estimate complex issues with the electricity system's functioning and control. Although there are many essential subjects in power system operation, load prediction has a crucial decision in the areas of planning, scheduling, load flow analysis, contingency analysis, and power system maintenance. The purpose of this work is to survey and categorize the electric load prediction methods that have been published in the last six years. Unlike those earlier review papers before, this work includes not only contemporary studies but also new classifications (basic, modified, and hybrid methods). Additionally, it contains a brief description of each approach, which this work provided, as benefits, and drawbacks of the optimization algorithms. At the end of this paper, a suggestion has been introduced according to the algorithm's properties.
DOI:10.1109/ISCES58193.2023.10311454