Parallel genetic algorithm for service restoration in electric power distribution systems

Fukuyama, Yoshikazu; Chiang, Hsiao Dong; Miu, Karen

doi:10.1016/0142-0615(95)00016-x

Cited by 58 publications

(10 citation statements)

References 9 publications

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“…According to the function shown as (9), the chaotic variable is transformed into intervals of corresponding optimized variable. 1 ) 1 ( (9) Where i c and i d is gain factor, which is applied to transfer chaotic variables to value range of corresponding optimized variables; x is the optimal value point.…”

Section: A Chaotic Optimization Algorithmmentioning

confidence: 99%

“…So it is difficult to solve in a very short period by traditional optimization method. At present, artificial intelligence techniques are widely used, and have demonstrated many successful applications in the area of power systems, for example tabu search method [2,3], fuzzy theory [4,5], expert system [6,7], genetic algorithm [8,9] and so on. Among them, if only expert system it is difficult to make a complete 2010-10-12, Doctoral Fund of Chongqing University of technology (076026) Authors are with the school of Electronic Information and Automation in Chongqing University of technology.Chongqing,400054,China (E_mail:cn_lsl@tom.com.…”

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confidence: 99%

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Distribution service restoration using chaotic optimization and immune algorithm

Lei

Yang

et al. 2011

International Conference on Information Science and Technology

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Abstract─A method of chaotic optimization and immune algorithm is presented for service restoration after faults in distribution system in this paper, which might improve the probability for optimal solution, and have the characteristic of chaotic optimization and artificial immunity algorithm. In the proposed algorithm, chaotic optimization is used to initialize the antibody of immune algorithm firstly in order to improve convergence speed by the excellent global search ability, which is regarded as thick search. Then artificial immune algorithm is applied by local search to complete thin search in the chaotic optimization, in order to make the population diversity and avoid getting to stuck in local minima to a certain degree. The effectiveness of the proposed method is demonstrated with actual system taken from a certain district distribution grid in Chongqing. The result shows that chaos immune optimization algorithm in the paper might improve convergence speed and precision of restoration and avoid premature convergence.

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Section: A Chaotic Optimization Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

Distribution service restoration using chaotic optimization and immune algorithm

Lei

Yang

et al. 2011

International Conference on Information Science and Technology

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“…Several studies based on the experience of electric utilities suggest that customer satisfaction is more closely correlated with service interruption frequency and interruption duration [1]. The impact of an interruption of supply to any given customer will depend on the duration of actions to locate and isolate the problem and to transfer load to neighbor feeders, cutting down service restoration duration [2].…”

Section: Introductionmentioning

confidence: 99%

“…Distribution operators in control centers detect out-of-service areas first, and then select switches to be opened and closed, in order to restore the out-of-service areas. [1].…”

Section: Introductionmentioning

confidence: 99%

Distribution systems restoration using the Interior Point Method and sensibility analysis

Borges

Carneiro

Garcia

et al. 2011

2011 IEEE Power and Energy Society General Meeting

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This Panel Discussion proposes the development of methodologies to solve the Distribution System restoration problem, according to multiple objectives, such as to restore as much consumers as possible with minimal switching operations. This methodology uses graph theory to identify out-of-service areas and loops in the system. After that, the system switches are opened and closed based on a sensibility index, obtained from an Optimum Power Flow (OPF) algorithm using the Interior Point Method (IPM). This methodology solves the problem step-bystep, providing a feasible switching operation sequence. The results are compared with some systems presented in the literature.

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“…In order to deal with these problems, several evolution-based algorithms have been developed [1]- [6], [10]- [14], [19]- [21], [24]- [29], [31], [34]- [36]. The results so far obtained are encouraging, especially in comparison with those obtained by mathematical programming and traditional Artificial Intelligence approaches.…”

Section: Introductionmentioning

confidence: 99%

Main Chain Representation for Evolutionary Algorithms Applied to Distribution System Reconfiguration

Delbem

Carvalho

Bretas

2005

IEEE Trans. Power Syst.

148

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Distribution system problems, such as planning, loss minimization, and energy restoration, usually involve network reconfiguration procedures. The determination of an optimal network configuration is, in general, a combinatorial optimization problem. Several Evolutionary Algorithms (EAs) have been proposed to deal with this complex problem. Encouraging results have been achieved by using such approaches. However, the running time may be very high or even prohibitive in applications of EAs to large-scale networks. This limitation may be critical for problems requiring online solutions.The performance obtained by EAs for network reconfiguration is drastically affected by the adopted computational tree representation. Inadequate representations may drastically reduce the algorithm performance. Thus, the employed representation for chromosome encoding and the corresponding operators are very important for the performance achieved. An efficient data structure for tree representation may significantly increase the performance of evolutionary-based approaches for network reconfiguration problems.The present paper proposes a tree encoding and two genetic operators to improve the EA performance for network reconfiguration problems. The corresponding EA approach was applied to reconfigure large-scale systems. The performance achieved suggests that the proposed methodology can provide an efficient alternative for reconfiguration problems.

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Parallel genetic algorithm for service restoration in electric power distribution systems

Cited by 58 publications

References 9 publications

Distribution service restoration using chaotic optimization and immune algorithm

Distribution service restoration using chaotic optimization and immune algorithm

Distribution systems restoration using the Interior Point Method and sensibility analysis

Main Chain Representation for Evolutionary Algorithms Applied to Distribution System Reconfiguration

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