2019
DOI: 10.1016/j.ijepes.2018.12.035
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Fuzzy adaptive setting for time-current-voltage based overcurrent relays in distribution systems

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Cited by 53 publications
(16 citation statements)
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“…Furthermore, the offline coordination of protection system can only consider a limited number of distribution system states. On the other hand, online protection coordination can be realized by adaptive protection setting, 26,37,38 group setting, 39‐41 telecommunication between protection devices, 26,42 and using multi‐agent‐based 13,28,43‐45 coordination methods. In some online methods, 46‐50 the optimal setting of protection devices can be determined for each change in the topology of the network or DG output.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, the offline coordination of protection system can only consider a limited number of distribution system states. On the other hand, online protection coordination can be realized by adaptive protection setting, 26,37,38 group setting, 39‐41 telecommunication between protection devices, 26,42 and using multi‐agent‐based 13,28,43‐45 coordination methods. In some online methods, 46‐50 the optimal setting of protection devices can be determined for each change in the topology of the network or DG output.…”
Section: Introductionmentioning
confidence: 99%
“…To that end, numerous MG protection schemes based on computational intelligence and machine learning approaches, such as fuzzy systems, multi-agent systems, artificial neural networks, and metaheuristics, have been proposed [9]. Fuzzy systems have been adopted in [10,11] to implement adaptive protection schemes, which alter the relay set-points in response to variations in the MG operation mode and the network topology. A multi-agent protection scheme has been proposed in [12], in which several agents including a measurement agent, breaker agent, optimal coordination agent, and protection agent cooperate to realize an adaptive protection scheme.…”
Section: Introductionmentioning
confidence: 99%
“…This dataset is commonly generated by running a large number of simulations with various fault scenarios. The existing machine learningbased protection schemes [9][10][11][12][13][14][15][16][17][18] are mostly focused on detection of faults with a small fault impedance. That is to say, they only consider scenarios in which the fault impedance is small during the training stage and validate their algorithms by the same small fault impedances.…”
Section: Introductionmentioning
confidence: 99%
“…Taking current and voltage as an input to the fuzzy inference system, an algorithm has been developed for fast intelligent relaying which has been presented earlier [9]. Momesso et al [10] have distinguished between a fuzzy based system and non fuzzy based system with respect to time and current graded protective relaying operating time. Many different approaches have been followed to develop a new kind of intelligent relaying [5] [6].…”
Section: Introductionmentioning
confidence: 99%