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논문 기본 정보

자료유형
학술저널
저자정보
Jong-Yul Kim (Korea Electrotechnology Research Institute) Hwa-Seok Lee (Koje College) June-Ho Park (Pusan National University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.2 No.4
발행연도
2007.12
수록면
413 - 419 (7page)

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초록· 키워드

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The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 30-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.

목차

Abstract
1. Introduction
2. Particle Swarm Optimization
3. Optimal Power Flow Problem Formulation
4. Application Results
5. Conclusion
Acknowledgements
References

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