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논문 기본 정보

자료유형
학술저널
저자정보
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.1 No.4
발행연도
2006.12
수록면
435 - 447 (13page)

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This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel ABA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After ABA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 ㎓ Pentium Ⅳ CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.
#Adaptive Evolutionary Algorithm(AEA) #Distribution System Service Restoration #Evolution Strategy(ES) #Genetic Algorithm(GA) #PC cluster system

목차

Abstract
1. Introduction
2. Service Restoration of the Distribution System
3. Parallel Adaptive Evolutionary Algorithm Using PC Clustering
4. Case Studies
5. Conclusion
Acknowledgements
References

참고문헌 (15)

참고문헌 신청
1. [학술지(정기간행물)] - / 1991 / A Heuristic Search Approach to Feeder Switching Operations for Overload, Faults, Unbalanced Flow and Maintenance 6 (4) : 1579 ~ 1585 google schola 2. [학술지(정기간행물)] - / 1998 / A New Aproach for Distribution Feeder Reconfiguration for Loss Reduction and Service Restoration 13 (3) google schola 3. [학술지(정기간행물)] - / 1988 / An Expert System Operational Aid for Restoration and Loss Reduction of Distribution Systems 3 (2) : 619 ~ 626 google schola 4. [학술지(정기간행물)] - / 1994. / Development of the Advanced Intelligent Restoration Guidance System for a Control Center : 731 ~ 738 google schola 5. [학술지(정기간행물)] - / 1995. / Distribution System Service Restoration using the Artificial Neural Network Approach and Pattern Recognition Method 142 (3) google schola

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