Optimal Power Flow Solution using Efficient Sine Cosine Optimization Algorithm

The problem encountered in most metaheuristic methods is the choice of the good control parameters of the algorithm. That is the objective of this work by using an efficient sine cosine algorithm (ESCA) in optimal power flow problem. The sine-cosine algorithm (SCA) is a modern method applied in nume...

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Veröffentlicht in:International journal of intelligent systems and applications Jg. 10; H. 2; S. 34
Hauptverfasser: Messaoudi, Abdelmoumene, Belkacemi, Mohamed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hong Kong Modern Education and Computer Science Press 08.04.2020
Schlagworte:
Algorithms
Convergence
Heuristic methods
Mathematical functions
Multiple objective analysis
Optimization
Parameters
Power flow
Trigonometric functions
ISSN:2074-904X, 2074-9058
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Zusammenfassung:The problem encountered in most metaheuristic methods is the choice of the good control parameters of the algorithm. That is the objective of this work by using an efficient sine cosine algorithm (ESCA) in optimal power flow problem. The sine-cosine algorithm (SCA) is a modern method applied in numerical optimization problems. It consists of search randomly the best vector of control variables from the initial group of elements and oscillates to converge to the global optimum or diverge from it, functioning with a simple formulation based on sine and cosine mathematical functions with few setting parameters. In the proposed efficient sine cosine Algorithm (ESCA) the best values of setting parameters are chosen to give the best optimum solution with fast convergence. This technique improves the quality of the solution by exploring more search domain than the SCA method. The modified algorithm has been applied to the classical IEEE 30-Bus network with various objective functions and constraints. To make the comparison of ESCA and different recent algorithms, present results show the importance of ESCA to give the best and effective solution to the multi-objective optimal power flow problem.
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ISSN:2074-904X
2074-9058
DOI:10.5815/ijisa.2020.02.04