Unit Commitment optimization using improved Genetic Algorithm

This paper shows an investigation for solving the Thermal Unit Commitment (UC) problem by utilizing of Genetic Algorithm advantages. A Parallel Structure was developed to handle the infeasibility problem in a structured and improved Genetic Algorithm (GA) which provides an effective search and there...

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Veröffentlicht in:2009 IEEE Bucharest Power Tech S. 1 - 6
Hauptverfasser: Abookazemi, K., Mustafa, M.W.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2009
Schlagworte:
Costs
Fuels
Genetic Algorithm
Genetic algorithms
Iterative methods
Job shop scheduling
Measurement units
Parallel Structure
Performance evaluation
Power generation
Power systems
System testing
Unit Commitment
ISBN:9781424422340, 1424422345
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Beschreibung
Zusammenfassung:This paper shows an investigation for solving the Thermal Unit Commitment (UC) problem by utilizing of Genetic Algorithm advantages. A Parallel Structure was developed to handle the infeasibility problem in a structured and improved Genetic Algorithm (GA) which provides an effective search and therefore greater economy. In addition, this proposed method could help us to obtain better performance by using both computational methods and classification of unit characteristics. Typical constraints such as; unit maximum/minimum MW limit, system power balance, minimum up and down times, start up and shut-down ramps, have been considered. A number of important UC control parameters have been identified accordingly. This method was developed and tested by using C# program. Tests have been performed on 10 and 20 units systems over a scheduling period of 24 hours. The final results were compared with those obtained genetic schemes in other same research.
ISBN:9781424422340
1424422345
DOI:10.1109/PTC.2009.5282117