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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| Vydané v: | 2023 3rd International Scientific Conference of Engineering Sciences (ISCES) s. 140 - 144 |
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| Hlavní autori: | , |
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| Jazyk: | English |
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03.05.2023
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Sadiq, Taha Abbas Hussein, Balasim Mohammed |
| Author_xml | – sequence: 1 givenname: Taha Abbas surname: Sadiq fullname: Sadiq, Taha Abbas email: alluhaiby518@gmail.com organization: University of Technology,Department of Electrical Engineering,Baghdad,Iraq – sequence: 2 givenname: Balasim Mohammed surname: Hussein fullname: Hussein, Balasim Mohammed email: balasim@inbox.ru organization: College of Engineering, University of Diyala,Department of Electrical Power and Machine Engineering,Diyala,Iraq |
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| Snippet | The optimization algorithms to determine the coefficients of predicting the short-term load original methods is one of the strategies to estimate complex... |
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| StartPage | 140 |
| SubjectTerms | Basic Classification algorithms Hybrid Load forecasting Modified Optimization algorithms Planning Power systems Prediction algorithms Predictive models Short-term Surveys |
| Title | Application of Intelligent Optimization Algorithms on Short-Term Electric Load Forecasting: A Review |
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