Minimum Losses Reconfiguration of MV Distribution Networks through Local Control of Tie Switches

Augugliaro, A.; Dusonchet, L.; Ippolito, Mariano Giuseppe; Sanseverino, Eleonora Riva

doi:10.1109/mper.2002.4311849

Cited by 32 publications

(22 citation statements)

References 18 publications

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“…Lin and Chin [14] have presented an algorithm of network reconfiguration using voltage index, ohmic index, and decision index to determine the switching operation. Jeon et al [15] and Augugliaro et al [16] have proposed artificial-intelligence-based applications in a minimum loss reconfiguration. Nara et al [17] have proposed network reconfiguration techniques for minimum loss using a genetic algorithm (GA).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Multi-objective Approach for the Improvement of Distribution Network Efficiency by Considering DG

Syahputra¹

2012

IJCSIT

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This paper presents a fuzzy multi-objective approach for achieving the minimum active power loss and the maximum voltage magnitude in order to improve the efficiency of radial distribution networks with distributed generations. Multi-objective function are considered for load balancing among the feeders, minimization of the real power loss, deviation of nodes voltage, and branch current constraint violation, while subject to a radial network structure in which all loads must be energized. Originality of the research is that the fuzzy-based multi-objective optimization in reconfiguration of distribution network including the distributed generation in order to improve the efficiency of the networks. The implementation of the fuzzy multi-objective for distribution reconfiguration on a 70 nodes distribution network with distributed generation is described. The original efficiency of the network is 95.142%. The simulation results show that efficiency of the network is increased to 96.942% by using fuzzy multiobjective method.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Multi-objective Approach for the Improvement of Distribution Network Efficiency by Considering DG

Syahputra¹

2012

IJCSIT

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“…Other heuristics for network reconfiguration studies were developed, based on one of these classical methods, like the heuristics developed by Morelato and Monticelli [7], Peponis and Papadopoulos [8], Augugliaro et al [9], and Aoki et al [10]. The metaheuristics are also widely used in these studies.…”

Section: Introductionmentioning

confidence: 99%

Comparing performance of classical methods for service restoration in MV networks with a new method based on sensitivity parameters

Silva

Medeiros

Filho

2012

2012 10th IEEE/IAS International Conference on Industry Applications

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The objective of this paper is to demonstrate the validity of the use of sensibility parameters as a low computational cost tool to implement service restoration in medium voltage distribution networks. A linearization of the relationship between accumulated powers -active and reactive -in a node and the voltages of all nodes can be carried out by means of sensitivity parameters, in order to determine the influence in voltages, caused by variations in powers in the network nodes as intending supply restoration of loads. The validity of this analysis tool is made comparing it with the restoration/reconfiguration classical methods that uses either a constructive process or an opening process of mesh. It was observed that the service restoration by the use of sensitivity parameters normally presents a very small number of complete calculations of load flow when compared with the classical methods, in addition to a significant reduction in the switching operations, with obvious advantages in the time of restoration, and in the rates of network reliability.

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“…Distribution feeders have two types of switches: normally closed (sectionalizing) switches and normally opened (tie) switches (Augugliaro et al 2003;Kim & Ko 1993;Chiou & Wang 1999;Chiou & Chang 2005;Delbem et al 2005;Gomes & Carneiro 2005). Distribution feeders have two types of switches: normally closed (sectionalizing) switches and normally opened (tie) switches (Augugliaro et al 2003;Kim & Ko 1993;Chiou & Wang 1999;Chiou & Chang 2005;Delbem et al 2005;Gomes & Carneiro 2005).…”

Section: Introductionmentioning

confidence: 99%

A hybrid evolutionary algorithm for distribution feeder reconfiguration

Niknam

Khorshidi

Firouzi

2010

Sadhana

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Distribution feeder reconfiguration (DFR) is formulated as a multiobjective optimization problem which minimizes real power losses, deviation of the node voltages and the number of switching operations and also balances the loads on the feeders. In the proposed method, the distance (λ 2 norm) between the vectorvalued objective function and the worst-case vector-valued objective function in the feasible set is maximized. In the algorithm, the status of tie and sectionalizing switches are considered as the control variables. The proposed DFR problem is a non-differentiable optimization problem. Therefore, a new hybrid evolutionary algorithm based on combination of fuzzy adaptive particle swarm optimization (FAPSO) and ant colony optimization (ACO), called HFAPSO, is proposed to solve it. The performance of HFAPSO is evaluated and compared with other methods such as genetic algorithm (GA), ACO, the original PSO, Hybrid PSO and ACO (HPSO) considering different distribution test systems.

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Minimum Losses Reconfiguration of MV Distribution Networks through Local Control of Tie Switches

Cited by 32 publications

References 18 publications

Fuzzy Multi-objective Approach for the Improvement of Distribution Network Efficiency by Considering DG

Fuzzy Multi-objective Approach for the Improvement of Distribution Network Efficiency by Considering DG

Comparing performance of classical methods for service restoration in MV networks with a new method based on sensitivity parameters

A hybrid evolutionary algorithm for distribution feeder reconfiguration

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