Multiobjective optimal placement of switches and protective devices in electric power distribution systems using ant colony optimization

Tippachon, Wiwat; Rerkpreedapong, D.

doi:10.1016/j.epsr.2009.02.006

Cited by 113 publications

(105 citation statements)

References 12 publications

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“…The optimization procedure provides multiple trade-off solutions of efficient configurations with different amounts and placements of NCRs in the distribution network. Since the optimal placement of protective devices is a complex combinatorial problem with nonlinearity, discontinuity, and non-differentiability characteristics [4], [9], [10], solving the problem with traditional methods (e.g., linear and nonlinear programming) is difficult. Then, the use of metaheuristic methods such as the Non-dominated Sorting Genetic Algorithm (NSGA-II) [11] is an appropriate alternative to attain efficient solutions.…”

Section: Introductionmentioning

confidence: 99%

“…The authors use the non-dominated sorting genetic algorithm (NSGA-II) in the search of the best solutions, in the same way as in [8], where the problem address with the minimization of the installation cost of sectionalizers while improving SAIDI and ECOST indices. With a different metaheuristic, the multi-objective ant colony system (MACS) is used in [9] for optimal placement of switching and protective devices in distribution systems by means of minimizing SAIFI, SAIDI, and total cost.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Recloser Placement in DG-Enhanced Distribution Networks Using a Multi-objective Optimization Approach

López¹,

Pantoja²

2024

RE&PQJ

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Abstract. Efficient placement of protective devices in electric power distribution networks is necessary in order to achieve a reliable system and provide continuous power supply to customers as long as possible. The islanded operation with distributed generation (DG) provides a way to reduce the energy not supplied (ENS) but the placement of protections, such as reclosers, is necessary in order to allow the system to achieve this mode of operation. This paper presents a multi-objective optimization method to place efficiently normally closed reclosers by using a constrained non-dominated sorting genetic algorithm (C-NSGA-II) to reduce SAIDI, ENS and investment costs. A co-simulation approach is used in such a way that the power system is modelled in PowerFactory, while MATLAB is used to implement the C-NSGA-II. Then, a distribution test network is probed in simulation cases with different DG penetration levels, showing the efficiency of the proposed optimization method. Results show the importance of protective devices and DG in enhancing system reliability and reducing the energy not supplied to customers.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Recloser Placement in DG-Enhanced Distribution Networks Using a Multi-objective Optimization Approach

López¹,

Pantoja²

2024

RE&PQJ

View full text Add to dashboard Cite

show abstract

“…Reference [6] Engages with the decreasing of the system cost to determine the optimal device position. The main difference between methods proposed in [11] and [6,9] is using single or multi objective. Reference [11] has determined device placements in distribution system to improve SAIFI, SAIDI and total cost.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, there is an increasing interest in optimization of allocation of protective and switching devices in distribution systems and there have been many studies in this regard [2][3][4][5][6][7][8][9][10]. References [6,7,11] propose different mathematical models and optimization methodologies for optimal placement of protective and switching devices. The objectives of the references are to increase the reliability and to decrease the costs.…”

Section: Introductionmentioning

confidence: 99%

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Optimized Switch Allocation to Improve the Restoration Energy in Distribution Systems

Hashemi‐Dezaki¹,

Abyaneh²,

Agheli³

et al. 2012

Journal of Electrical Engineering

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In distribution networks switching devices play critical role in energy restoration and improving reliability indices. This paper presents a novel objective function to optimally allocate switches in electric power distribution systems. Identifying the optimized location of the switches is a nonlinear programming problem (NLP). In the proposed objective function a new auxiliary function is used to simplify the calculation of the objective function. The output of the auxiliary function is binary. The genetic algorithm (GA) optimization method is used to solve this optimization problem. The proposed method is applied to a real distribution network and the results reveal that the method is successful.K e y w o r d s: Power distribution systems, switches, restoration energy, genetic algorithm (GA)

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Using mobile emergency generators as reliability enhancers in distribution systems

Rodrigues

Araujo

Penido

2020

Int Trans Electr Energ Syst

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Summary In this paper, the use of mobile emergency generators (MEGs) is analyzed as a way to improve reliability indices of distribution networks, which is a practice already used by many system operators, but very little studied in the literature. MEGs can be used in the case of faults in distribution systems as devices capable of restoring the power supply to groups of customers that would otherwise be interrupted during the entire duration of the fault. Unlike fixed distributed generation (DG), an MEG can be easily transported between different points on a feeder, and its starting position greatly influences its impacts on reliability, so this work proposes a way to find the MEG's best starting position, considering all the events in which it will have to travel to different nodes. A fault simulation algorithm is also proposed, so that faults are analyzed about their impact on the reliability indices, taking into account that an MEG can be used by the system operator in each fault situation. Simulations are conducted on a real feeder, and reliability indices are compared in different scenarios on this feeder.

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Multiobjective optimal placement of switches and protective devices in electric power distribution systems using ant colony optimization

Cited by 113 publications

References 12 publications

Optimization of Recloser Placement in DG-Enhanced Distribution Networks Using a Multi-objective Optimization Approach

Optimization of Recloser Placement in DG-Enhanced Distribution Networks Using a Multi-objective Optimization Approach

Optimized Switch Allocation to Improve the Restoration Energy in Distribution Systems

Using mobile emergency generators as reliability enhancers in distribution systems

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