Modified Particle Swarm Optimizer as Optimization of Time Dial Settings for Coordination of Directional Overcurrent Relay

Khurshaid, Tahir; Wadood, Abdul; Farkoush, Saeid Gholami; Kim, Chang-Hwan; Cho, Namhun; Rhee, Sang-Bong

doi:10.1007/s42835-018-00039-z

Cited by 42 publications

(32 citation statements)

References 22 publications

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“…In [30,31], several bio-inspired algorithms were developed to solve the DOCR coordination issue by designing a linear formulation. In [32][33][34][35][36], a different version of particle swarm optimization (PSO) was used to determine the optimum values for DOCRs. A different version of the differential algorithm was reported in [37] to solve the DOCR coordination problem to point out the superiority of modified differential evolution algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

et al. 2019

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In power systems protection, the optimal coordination of directional overcurrent relays (DOCRs) is of paramount importance. The coordination of DOCRs in a multi-loop power system is formulated as an optimization problem. The main objective of this paper is to develop the whale optimization algorithm (WOA) for the optimal coordination of DOCRs and minimize the sum of the operating times of all primary relays. The WOA is inspired by the bubble-net hunting strategy of humpback whales which leads toward global minima. The proposed algorithm has been applied to six IEEE test systems including the IEEE three-bus, eight-bus, nine-bus, 14-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed WOA are compared with those obtained by other up-to-date algorithms. The obtained results show the effectiveness of the proposed WOA to minimize the relay operating time for the optimal coordination of DOCRs.

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Section: Literature Reviewmentioning

confidence: 99%

Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

et al. 2019

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“…Heretofore, different mathematical techniques and evolutionary algorithms are proposed in the literature to solve the coordination problem of the overcurrent relays. Among them are referred the genetic algorithm, 3,4 hybrid genetic algorithm, 5 particle swarm optimization, 6 modified particle swarm optimization, 7,8 differential evolution algorithm, 9 artificial bees colony algorithm, 10 water cycle algorithm, 11 seeker algorithm, 2 modified seeker algorithm, 12 improved firefly algorithm, 13 improved harmony search algorithm, 14 electromagnetic field optimization, modified electromagnetic field optimization, 15 hybrid biogeography‐based optimization with linear programming (LP), 16 modified adaptive teaching learning‐based optimization algorithm, 17 modified particle swarm optimization‐interval LP approach, 18 non‐dominated sorting genetic algorithm‐II, 19 and combination of cuckoo search and LP algorithms 20 . However, evolutionary algorithms suffer from the drawback in procuring an optimistic convergence of solutions due to highly variables and constraints 17 .…”

Section: Introductionmentioning

confidence: 99%

An info‐gap risk‐averse optimization model for coordination of overcurrent protective relays considering power system uncertainty

Salahi

Rezaei

Moshtagh

2020

Int Trans Electr Energ Syst

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Summary The power system protection scheme must detect faults as soon as possible and isolate the faulty section from the rest of the network in the shortest possible time. Protection in medium voltage distribution networks is usually performed through applying coordinated protective overcurrent relays. Changes in the network topology and operational parameters may cause some uncertainties, which can have deteriorative impacts on the fault current measuring by overcurrent relays, hence lead to in‐coordinated operation of the overcurrent relays. In this paper, it is aimed to optimally solve the problem of the overcurrent relays coordination considering the fault current uncertainty. To this end, a new risk‐averse robust optimization portfolio is proposed based on information gap decision theory to derive the optimistic coordination scheme under severe uncertainties. The presented model is mathematically formulated and implemented effectively to some medium voltage test power systems. The illustrative numerical results demonstrate the effectiveness of the conducted optimization model in both risk‐neutral and risk‐averse strategies in procuring the robust coordination solution of the overcurrent relays.

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“…In [16], grey wolf optimization was used to interrogate the relay problem. In [17][18][19][20][21][22], various styles of particle swarm optimization were interrogated to deal with the relay coordination issue. In [23][24][25][26], a di erent version of a genetic algorithm to enhance the convergence characteristics of the genetic algorithm was applied.…”

Section: Introductionmentioning

confidence: 99%

Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single‐ and Multi‐Loop Distribution Systems

et al. 2019

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To ensure a safe and trustworthy pattern in contradiction to the possible faults, a precise, reliable, and fast relaying strategy is of high importance in an electrical power system. These challenges give the impression of being more refined in multi-loop distribution systems. More recently, overcurrent relays (OCRs) have evolved as proficient counteragents for such cases. In this way, inaugurating an optimal protection coordination strategy is accepted as the primary precondition in guaranteeing the safe protection of the coordination strategy. This study is aimed at lessening the overall operational time of the main relays in order to reduce the power outages. The coordination problem is conducted by adjusting only one parameter, namely the time multiplier setting (TMS). In electrical power relaying coordination, the objective function to be minimized is the sum of the overall operational time of the main relays. In the prescribed work, the coordination of the OCRs in the single- and multi-loop distribution network is realized as an optimization issue. The optimization is accomplished by means of JAYA algorithm. The suggested technique depends on the idea that the result acquired for a certain issue ought to pass near the finest result and avert the worst result. This technique involves only the common control factors and does not involve specific control factors. JAYA is adopted to OCR problem and run 20 times with the same initial condition for each case study, and it has been realized that for every run, the JAYA algorithm converges to the global optimum values requiring less number of iterations and computational time. The results obtained from JAYA algorithm are compared with other evolutionary and up-to-date algorithms, and it was determined that JAYA outperforms the other techniques.

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Modified Particle Swarm Optimizer as Optimization of Time Dial Settings for Coordination of Directional Overcurrent Relay

Cited by 42 publications

References 22 publications

Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

An info‐gap risk‐averse optimization model for coordination of overcurrent protective relays considering power system uncertainty

Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single‐ and Multi‐Loop Distribution Systems

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