A Study on Improvement of Tabu Search-based Determination Method for Distribution Network Configuration

Takano, Hirotaka; Murata, Junichi; Yasuda, Makoto; Maki, Yukino

doi:10.5370/jicee.2013.3.1.061

Cited by 3 publications

(6 citation statements)

References 5 publications

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“…1. Three-sectionalized and three-connected model Figure 5 illustrates an actual-scale three-sectionalized and three-connected distribution network model [10,25,27,28,37]. This model consists of four distribution substations (omitted from the figure), 72 feeding points, and 252 switches.…”

Section: Example Of Actual-scale Distribution Network Modelsmentioning

confidence: 99%

“…Figure 6 shows an underground-overhead-intermingled distribution network model composed of three distribution substations (omitted from the figure), 53 feeding points, and 266 switches. This model is made by referring to actually operating underground and overhead distribution networks in Japan [10,38]. In Japan, underground distribution networks normally have simple structures such as two-sectionalized and two-connected structure, while structures of overhead networks are complicated.…”

Section: Underground-overhead-intermingled Modelmentioning

confidence: 99%

“…Finding appropriate switch states is traditionally formulated as a combinatorial optimization problem and familiar in the electrical power field. Distribution loss minimization in normal operation conditions is one of the most famous reconfiguration problems [3][4][5][6][7][8][9][10][11], while minimization of outage loads in restorative phases is well known as the service restoration problem [12][13][14][15][16][17][18][19][20][21][22][23]. Similarly, traditional and/or intelligent optimization algorithms have been applied to solve the formulated problems.…”

mentioning

confidence: 99%

“…Branch exchange methods and simplex methods are typical examples of the former [3][4][5][6][7]13]. The latter includes applications of expert systems [12,20,23] and metaheuristics [8,10,15,16,22]. Although various optimization algorithms have been proposed for the problems of distribution network reconfiguration, there is no established solution method.…”

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confidence: 99%

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Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field

Takano

Murata

Asano

et al. 2021

Springer Tracts in Nature-Inspired Computing

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An electric power distribution network consists of distribution substations, distribution feeders, circuit breakers, and interconnecting and sectionalizing switches, and have an extremely important role in delivering electrical power to the customers. Historically, the distribution feeders, e.g. 6.6 kV feeders in Japan, have been expanded radially from the distribution substations to supply power to spreading power consuming area. With the aim of enhancing reliability of the power supply, the distribution feeders are divided into several load sections by the sectionalizing switches, and then each of the load sections is connected to different feeders through the interconnecting switches. By the states of the circuit breakers and the switches, power flow in the distribution networks is controlled. This is called the multi-sectionalized and multi-connected distribution network. In this network structure, each load section can receive power from one or more distribution feeders even if one feeder has a

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Section: Example Of Actual-scale Distribution Network Modelsmentioning

confidence: 99%

Section: Underground-overhead-intermingled Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field

Takano

Murata

Asano

et al. 2021

Springer Tracts in Nature-Inspired Computing

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“…Otherwise, some intelligent optimization algorithms with an appropriate penalty term added to the objective function will be useful. The difficulty in the distribution network reconfiguration is to identify feasible candidates among a huge number of possibilities and find the optimal one [37,38]. If the distribution network can be partitioned into groups as described in Section 4.1, the iden-tification of radial configuration candidates is not difficult.…”

Section: Compare Values Of the Objective Function Among Created Confi...mentioning

confidence: 99%

Service Restoring Reconfiguration for Distribution Networks Considering Uncertainty in Available Information

et al. 2021

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The recent growth in the penetration of photovoltaic generation systems (PVs) has brought new difficulties in the operating and planning of electric power distribution networks. This is because operators of the distribution networks normally cannot monitor or control the output of the PVs, which introduces additional uncertainty into the available information that operations must rely on. This paper focuses on the service restoration of the distribution networks, and the authors propose a problem framework and its solution method that finds the optimal restoration configuration under extensive PV installation. The service restoration problems have been formulated as combinatorial optimization problems. They do, however, require accurate information on load sections, which is impractical in distribution networks with extensively installed PVs. A combined framework of robust optimization and two-stage stochastic programming adopted in the proposed problem formulation enables us to deal with the PV-originated uncertainty using readily available information only. In addition, this problem framework can be treated by a traditional solution method with slight extensions. The validity of the authors’ proposal is verified through numerical simulations on a real-scale distribution network model and a discussion of their results.

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Improving the Search Ability of Tabu Search in the Distribution Network Reconfiguration Problem

Takano

Murata²,

Maki

et al. 2013

J. Adv. Comput. Intell. Intell. Inform.

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The distribution network reconfiguration problem is to decide whether each sectionalizing switch is to be open or closed in order to maintain or improve electrical power supply reliability, power quality and network operation efficiency. Obtaining the optimal network configuration is, however, extremely difficult because the network reconfiguration problem is actually a large-size combinatorial optimization problem. Many optimization algorithms have thus been applied to the reconfiguration problem to support power utility’s decision-making. This paper proposes a local search-based solution for the reconfiguration problem in which tabu search – one of the most widely used local search-based metaheuristics – is employed to solve the problem. Tabu search is improved by introducing an effective search strategy that utilizes the properties of this kind of problems. Numerical simulations are performed on a complex actual-scale distribution network model in order to verify the validity of the proposed solution.

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A Study on Improvement of Tabu Search-based Determination Method for Distribution Network Configuration

Cited by 3 publications

References 5 publications

Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field

Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field

Service Restoring Reconfiguration for Distribution Networks Considering Uncertainty in Available Information

Improving the Search Ability of Tabu Search in the Distribution Network Reconfiguration Problem

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