Multi-criteria Reconfiguration of Distribution Electrical Networks for Minimization of Power Losses and Damage Cost due to Power Supply Interruption

Triştiu, Ion; Eremia, Mircea; Bulac, Constantin; Toma, Lucian

doi:10.1109/pct.2007.4538348

Cited by 8 publications

(6 citation statements)

References 10 publications

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“…While solving multiobjective optimization problems, it is necessary to pay attention to convergence to optimal set of solutions (Pareto set) and maintain diversity of solutions within the set of current solutions [14]. Evolution algorithms, among which are genetic algorithms, have provided very good results in reconfiguration of distribution networks [1][2][3][4].…”

Section: Methods To Solve Multiobjective Network Reconfiguration Problemmentioning

confidence: 99%

“…Recently, special attention has been paid to the issue of reliability of power supply, in order to increase economic efficiency of the distribution companies. Therefore, network reconfiguration process can be used as method to improve network reliability indicators [1].…”

Section: Introductionmentioning

confidence: 99%

“…Over the recent years, reconfiguration has been addressed through stochastic, that is, metaheuristic methods, such are the methods based on simulated annealing algorithms [7], fuzzy logics [5], tabu search [12], ant colony [11], and genetic algorithms [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distribution Network Reconfiguration Considering Power Losses and Outages Costs Using Genetic Algorithm

Nuhanovic¹,

Hivziefendić²,

Hadžimehmedović³

2013

Journal of Electrical Engineering

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This paper discusses the problem of finding the optimal network topological configuration by changing the feeder status. The reconfiguration problem is considered as a multiobjective problem aiming to minimize power losses and total interruptions costs subject to the system constraints: the network radiality voltage limits and feeder capability limits. Due to its complexity, the metaheuristic methods can be applied to solve the problem and often the choice is genetic algorithm. NSGA II is used to solve the multiobjective optimization problem in order to get Pareto optimal set with possible solutions. The proposed method has been tested on real 35 kV distribution network. The numerical results are presented to illustrate the feasibility of the proposed genetic algorithm.

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Section: Methods To Solve Multiobjective Network Reconfiguration Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distribution Network Reconfiguration Considering Power Losses and Outages Costs Using Genetic Algorithm

Nuhanovic¹,

Hivziefendić²,

Hadžimehmedović³

2013

Journal of Electrical Engineering

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“…The power losses can be identified by several components, of which the most important is given by the technical losses and two of the components can be identified in this category: power losses and energy losses [17]. The active power losses for a three-phase electrical line i, flowing on the line is:…”

Section: A Evaluation Of Losses Costmentioning

confidence: 99%

Radial distribution systems reconfiguration considering power losses cost and damage cost due to power supply interruption of consumers

Ghasemi¹,

Moshtagh²

2013

ijeei

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Distribution system reconfiguration problem is a complex optimization process to find a structure with minimum losses in which the satisfaction of both sides, that is consumers and distribution system companies, need to be met. One of the most significant parameters in this regard is to increase the reliability of system. This parameter, on one hand, increases the satisfaction of power consumption and on the other hand, improves the economic benefits of distribution companies. Distribution system reconfiguration, considering the reliability parameters, seems to make the attempts to solve the problem of optimization difficult. In this paper, a new heuristic approach for distribution system reconfiguration in order to decrease the power losses cost and damage cost due to power supply interruption of consumers has been presented. Radial network construction and all energized nodes constraints are the most important ones that should be considered in distribution system reconfiguration problem. Hence, in this paper a new codification is proposed which is computationally efficient and guarantees to generate only feasible radial topologies all times. In order to illustrate the performance of proposed heuristic method, modified 33-bus and 119-bus distribution networks have been employed which have led to the desired results.

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“…Reference [6] provides a heuristic approach using load flow analysis in order to find the best network reconfiguration for real power loss minimization in terrestrial distribution electrical network. Minimizing the damage cost due to an electrical power supply interruption in a terrestrial distribution electrical network is treated in paper [7]. Reference [8] uses a genetic algorithm (GA) for finding the best shipboard electrical network configuration in order to maximize the power delivered to electric loads after a fault event.…”

Section: State Of the Art Of Electrical Network Reconfigurationmentioning

confidence: 99%

Knowledge-based system for aircraft electrical power system reconfiguration

Giraud¹,

Piquet²,

Budinger³

et al. 2012

2012 Electrical Systems for Aircraft, Railway and Ship Propulsion

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Aircraft electrical power system (EPS), in charge of supplying power to aircraft electric systems, needs a reconfiguration capability in order to overcome cases of EPS component failures. During the design phase, EPS reconfiguration elicitation is a complex task due to the high number of failure combinations and to the aeronautical operational constraints, which are to be taken into account. Therefore a knowledge-based system is developed in order to help designers for such a task. It is based on the implementation of two different types of rules: mandatory and know-how rules. EPS connectivity is managed by graph-theory algorithms. The knowledge-based system is capable of producing several reconfiguration solutions. The knowledge-based system functioning is illustrated in detail on a simplified EPS. Results on an actual and modern EPS are also presented.I.

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Multi-criteria Reconfiguration of Distribution Electrical Networks for Minimization of Power Losses and Damage Cost due to Power Supply Interruption

Cited by 8 publications

References 10 publications

Distribution Network Reconfiguration Considering Power Losses and Outages Costs Using Genetic Algorithm

Distribution Network Reconfiguration Considering Power Losses and Outages Costs Using Genetic Algorithm

Radial distribution systems reconfiguration considering power losses cost and damage cost due to power supply interruption of consumers

Knowledge-based system for aircraft electrical power system reconfiguration

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