Considering Different Network Topologies in Optimal Overcurrent Relay Coordination Using a Hybrid GA

Noghabi, Abbas Saberi; Sadeh, Javad; Mashhadi, Habib Rajabi

doi:10.1109/tpwrd.2009.2029057

Cited by 314 publications

(195 citation statements)

References 13 publications

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“…In [7], an evolutionary algorithm was applied for the first time to deal with the relay coordination problem. In various papers [8][9][10][11][12][13], different versions of a genetic algorithm have been applied to improve the convergence characteristics of genetic algorithms overall. A different version of the particle swarm optimization technique has also been suggested in order to achieve the optimum values for relay coordination [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Application of a Continuous Particle Swarm Optimization (CPSO) for the Optimal Coordination of Overcurrent Relays Considering a Penalty Method

et al. 2018

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Abstract:In an electrical power system, the coordination of the overcurrent relays plays an important role in protecting the electrical system by providing primary as well as backup protection. To reduce power outages, the coordination between these relays should be kept at the optimum value to minimize the total operating time and ensure that the least damage occurs under fault conditions. It is also imperative to ensure that the relay setting does not create an unintentional operation and consecutive sympathy trips. In a power system protection coordination problem, the objective function to be optimized is the sum of the total operating time of all main relays. In this paper, the coordination of overcurrent relays in a ring fed distribution system is formulated as an optimization problem. Coordination is performed using proposed continuous particle swarm optimization. In order to enhance and improve the quality of this solution a local search algorithm (LSA) is implanted into the original particle swarm algorithm (PSO) and, in addition to the constraints, these are amalgamated into the fitness function via the penalty method. The results achieved from the continuous particle swarm optimization algorithm (CPSO) are compared with other evolutionary optimization algorithms (EA) and this comparison showed that the proposed scheme is competent in dealing with the relevant problems. From further analyzing the obtained results, it was found that the continuous particle swarm approach provides the most globally optimum solution.

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Section: Introductionmentioning

confidence: 99%

Application of a Continuous Particle Swarm Optimization (CPSO) for the Optimal Coordination of Overcurrent Relays Considering a Penalty Method

et al. 2018

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“…Each relay in the power system must be coordinated with the other relays in the power system [1,2]. Several optimization techniques are proposed for optimum coordination of DOCRs [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. The optimum settings for TMS and PS are obtained using different algorithms proposed by the researchers.…”

Section: Introductionmentioning

confidence: 99%

Optimum Coordination of Directional Overcurrent Relays Using Modified Adaptive Teaching Learning Based Optimization Algorithm

Kalage¹,

Ghawghawe²

2016

Intell Ind Syst

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Relay coordination problem is highly constrained optimization problem. Heuristic techniques are often used to solve optimization problem. These techniques have a drawback of converging to a non-optimum solution due to the wide range of design variables. On the other hand, initial solution becomes difficult to find with shorter range of design variables. This paper presents modified adaptive teaching learning based optimization algorithm to overcome this drawback of conventional heuristic techniques. The coordination problem is formulated as a constrained non-linear optimization problem to determine the optimum solution for the time multiplier setting (TMS) and plug setting (PS) of DOCRs. Initial solution for TMS is heuristically obtained with the commonly chosen widest range for TMS values. The upper bound of TMS range then substituted by the maximum TMS value in the first initial solution. The new upper limit is obviously lower than the earlier one. Next phase of optimization is carried out with the new range of TMS for the pre-determined iterations of teacher phase. Consequent to the completion of the teacher phase, new upper bound is obtained from the available solution and optimization is carried out for the pre-determined iterations of learner phase. This process is repeated to get the optimum solution. Fixed range for PS is used to obtain the selectivity. Such a strategy of iteratively updating the upper bound of TMS range shows remarkable improvement over the techniques which employ fixed TMS range. This algorithm is tested on different networks and has been found more effective. Four case studies

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“…Different load shedding and switching cases are done to ensure the reliability of the protection system and power system stability, keep voltage within certain boundaries and reducing operating costs [7][8][9][10]. So that, alterations on the system topology raises the need of change the distance protection relay coordination settings [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

An Algorithm for Transmission Distance Relay Setting Calculation Under Network Topology Change

Arikan¹,

Gursanli²,

Aydin³

et al. 2016

International Journal of Innovative Research in Electrical, Ele

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Power systems are being expanded day by day with a more complex structure. The system topology always changes due to faults and/or operation requirements. Therefore; malfunctions might occur in the protection system which is one of the most important components for the system reliability, stability and economic operation. Distance protection relays fulfil the main protection function of the power transmission lines. In this study, an algorithm is created which recalculates the distance protection relay setting values depending on the topological changes of the network. The algorithm verified by testing on a selected area from the Turkish National Power Transmission System which comprises 154 kV 28 buses. Modelling of the power system carried out with Dig silent Power factory software. The algorithm is created in the DPL (Dig silent Programming Language) platform.

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Considering Different Network Topologies in Optimal Overcurrent Relay Coordination Using a Hybrid GA

Cited by 314 publications

References 13 publications

Application of a Continuous Particle Swarm Optimization (CPSO) for the Optimal Coordination of Overcurrent Relays Considering a Penalty Method

Application of a Continuous Particle Swarm Optimization (CPSO) for the Optimal Coordination of Overcurrent Relays Considering a Penalty Method

Optimum Coordination of Directional Overcurrent Relays Using Modified Adaptive Teaching Learning Based Optimization Algorithm

An Algorithm for Transmission Distance Relay Setting Calculation Under Network Topology Change

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