A GA-based Multi-Objective Optimization for Service Restoration in Power Distribution Systems

Inagaki, Jiro; Nakajima, Jun; Haseyama, Miki; Kitajima, Hideo

doi:10.1541/ieejpes.124.404

Cited by 17 publications

(27 citation statements)

References 14 publications

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“…In order to verify the method proposed in this study, we first consider the same model as in the previous papers [1,5,6, 10]; we call it the small-scale system. Then, to confirm the effectiveness of the proposed method for larger systems, we extend the small-scale system to a larger one (we call it the large-scale system).…”

Section: Simulation Models and Resultsmentioning

confidence: 99%

“…We use the same model system as in the previous papers [1,5,6,10]. The model includes 4 banks (Tr1: 700 A; Tr2, Tr3: 400 A; Tr4: 900 A), 53 sectionalizing switches, and 78 load sections; the delivery voltage is 6600 V. The loads are distributed uniformly in every section, and the load power factor is 1.0.…”

Section: The Small-scale System and Its Operating Conditionsmentioning

confidence: 99%

“…On the other hand, the problem of unrestored load minimization in the latter case is a huge optimization problem with 2 N candidate solution combinations, where N is the number of sectionalizing switches in the system in question. Even metaheuristic methods [5,6,10], which are now attracting much attention, leave many loads unrestored.…”

Section: Introductionmentioning

confidence: 99%

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Application of improved genetic algorithm to service restoration problem for distribution systems

Michibata

Aoki

2011

Electrical Engineering Japan

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SUMMARYThe problem of recovery from power-system failures is the problem of handling operations that make it possible to supply power from other lines in response to power-system failures or construction by switching between the opened and closed states of sectionalizing switches. Considerable research has already been conducted with regard to this issue. This paper addresses the issue of determining target systems for final recovery in cases when some sections remain subject to power failure (i.e., sound bank capacity < load capacity). For this purpose, intersection is conducted only for parameters within such power-failure sections. In such research, calculations are implemented by setting a value of 2 to the sectionalizing switches of a single parameter. In addition, when the state of a sound section changes due to mutation improvements, the method of simultaneously changing the selected points and neighboring sectionalizing switches is applied. It is clear that the proposed method, consisting of conventional GA only, is superior in terms of average fitness values.

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Section: Simulation Models and Resultsmentioning

confidence: 99%

Section: The Small-scale System and Its Operating Conditionsmentioning

confidence: 99%

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Application of improved genetic algorithm to service restoration problem for distribution systems

Michibata

Aoki

2011

Electrical Engineering Japan

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“…14. As is evident from the diagrams, by operating four switches (5,6,7,8) in the short-term restoration configuration, a load of 179 A supplied from feeder 15 is shifted to feeder 16 of bank 3, and a load of 117 A supplied from feeder 9 is shifted to substation DS4. As a result, the long-term overload capacity of bank 1 is satisfied.…”

Section: Results For Restoration Configurationmentioning

confidence: 99%

“…Various methods have been proposed so far to solve the problem of the restoration configuration in case of distribution lines without DGs [4][5][6][7][8] but no well-estab-lished solution has been obtained even in this case. The reason is that determination of the target configuration and the restoration sequence are combinatorial optimization problems of recovering supply to the whole outage area.…”

Section: Introductionmentioning

confidence: 99%

Service restoration method considering simultaneous disconnection of distributed generators by one‐bank fault of distribution system

Takano

Hayashi

Matsuki

et al. 2008

Elect Comm in Japan

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SUMMARYDistributed generators (DGs) such as fuel cells and solar cells are going to be installed in the demand side of distribution systems. The DGs can reduce distribution loss by appropriate allocation. However, there are several problems installing DGs such as service restoration of distribution system with DGs and so on. When one bank fault of distribution substation occurs in distribution system, since DGs are simultaneously disconnected from the system, it is not easy to restore isolated load by one bank switching in distribution substation. Therefore, a service restoration method to determine restoration configuration and restoration procedures (switching procedure from normal configuration to restoration configuration) taking into account simultaneous disconnection of DGs is needed. In this paper, the authors propose a computation method to determine the optimal restoration configuration and the restoration procedure considering simultaneous disconnection of DGs by one bank fault of distribution system. In the proposed algorithm, after all of the restoration configuration candidates are effectively enumerated under the operational constraints, the optimal configuration to restore the isolated load is selected among enumerated configuration candidates. After determining the optimal restoration configuration, the optimal restoration procedures are obtained by greedy algorithm. Numerical simulations are carried out for a real scale system model with 237 sectionalizing switches (configuration candidates are 2 237 ) and 21 DGs (total output is 5250 kW which is 3% of total load) in order to examine the validity of the proposed algorithm.

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Service restoration problem in distribution power system using improved GA

Iwasaki

Aoki

2008

Electrical Engineering Japan

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SUMMARYThe service restoration problem in distribution power systems has already been addressed with regard to this issue, for purposes such as the minimization of unrecovered load and power supply loss, considerations of priority sections, and preparation of switching procedures. However, since this involves the application of a number of methods, the related algorithms are complex. In this paper, in order to resolve this issue we first apply GA as an optimization method for investigation purposes, to simplify the algorithms used. Next, to confirm this proposed method's effects in reducing computing time, we consider the efficacy of the proposed method by using smaller numbers of generations and individual sizes than have been used in the past. The effectiveness of the proposed method is shown by the system when failure occurs. It is clear that the proposed method, consisting of GA only, is superior in terms of average fitness values and the ability to reduce computation times.

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A GA-based Multi-Objective Optimization for Service Restoration in Power Distribution Systems

Cited by 17 publications

References 14 publications

Application of improved genetic algorithm to service restoration problem for distribution systems

Application of improved genetic algorithm to service restoration problem for distribution systems

Service restoration method considering simultaneous disconnection of distributed generators by one‐bank fault of distribution system

Service restoration problem in distribution power system using improved GA

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