A Simple Evaluation Method for Annual CO&lt;sub&gt;2&lt;/sub&gt; Emissions Reduced by Distribution Loss Minimization

Hayashi, Yasuhiro; Takano, Hirotaka; Matsuki, Junya; Yokoyama, Masao

doi:10.1541/ieejpes.127.1137

Cited by 8 publications

(4 citation statements)

References 15 publications

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“…4 shows another typical distribution network i.e., an underground-and-overhead-intermingled distribution network model [6] which consists of 3 distribution substations, 53 root feeders and 266 sectionalizing switches (total load of all sections is 31.97 MW). Table 2, Figs.…”

Section: Evaluation Using the Exact Determination Methods (1) Results mentioning

confidence: 99%

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

Takano¹,

Murata

Yasuda

et al. 2013

Journal of International Council on Electrical Engineering

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-In this paper, an improvement strategy is proposed for solving a determination problem of the optimal distribution network configuration (minimum distribution loss network configuration). To achieve the purpose, characteristics of the network configuration optimization problems are clarified by applying an exact determination method previously proposed to typical problems. Second, those characteristics are used to evaluate the performance of Tabu Search (TS), which is the most popular local search-based metaheuristics, when applied to the problems. Finally, TS algorithm is improved. Numerical simulations are carried out for a real scale complicated network model in order to verify the validity of improved TS.

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Section: Evaluation Using the Exact Determination Methods (1) Results mentioning

confidence: 99%

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

Takano¹,

Murata

Yasuda

et al. 2013

Journal of International Council on Electrical Engineering

Self Cite

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“…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%

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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“…Figure 5 illustrates an actual-scale distribution network model, which was made by referring to an actual operating underground and overhead intermingled distribution network in Japan [37,39]. This model can be divided into groups as described in Subsection 4.1, and thus the enumeration-based method was used to solve both of the problems in the traditional and proposed frameworks.…”

Section: Numerical Simulationsmentioning

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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A Simple Evaluation Method for Annual CO<sub>2</sub> Emissions Reduced by Distribution Loss Minimization

Cited by 8 publications

References 15 publications

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

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

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

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