Allocation of fault indicators in distribution feeders containing distributed generation

Sau, Rodrigo F.G.; Dardengo, Victor P.; Almeida, Madson C. de

doi:10.1016/j.epsr.2019.106060

Cited by 8 publications

(17 citation statements)

References 14 publications

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“…The following computational intelligence based optimisation methods (also called metaheuristic optimisation methods) have been used for the solution of the OAPCD problem: � Alliance algorithm [62]; � Ant colony system (ACS) [33,[46][47][48]; � Artificial bee colony (ABC) [76,81,93]; � Differential evolution (DE) [84]; � Differential search [80]; � Genetic algorithm (GA) [24,25,35,36,39,43,53,56,57,61,78,86,88,89,91,95,99,100,108,110,116,117,119]; � Greedy randomized adaptive search procedure [82]; � Immune algorithm [42,51]; � Memetic algorithm [71,74]; [26]; � Shuffled frog leaping algorithm [60]; � Tabu search [45,50]. These optimisation algorithms are generally nature-inspired methods.…”

Section: Computational Intelligence Based Optimisation Methodsmentioning

confidence: 99%

“…When a fault takes place downstream the fault indicator, it sends a signal to the control centre. The allocation of fault indicator is considered in the following reviewed works [51,53,54,61,70,[87][88][89][90][91]97,101,105,106,[108][109][110][118][119][120].…”

Section: Fault Indicatormentioning

confidence: 99%

“…Published Contribution [119] Feb 2020 NSGA-II optimally allocates conventional and directional fault indicators, considering the real distance among the suspect fault locations.…”

Section: Referencementioning

confidence: 99%

“…3. Multiple objectives [29,34,48,52,54,55,59,60,67,70,73,74,77,78,80,84,86,93,95,100,108,109], and [119]. In this case, there are multiple objectives for the OAPCD problem, and the proposed multi-objective optimisation method first calculates the set of Pareto optimal solutions, and, then, it calculates the best compromise solution among the set of Pareto optimal solutions.…”

Section: Objectivesmentioning

confidence: 99%

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Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

et al. 2021

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The fundamental goal of the distribution system operator (DSO) is to serve its customers with reliable and low-cost electricity. Failures in power distribution systems are responsible for 80% of customer service interruptions. The emergence of smart distribution system (SDS) with advanced distribution automation (DA) and communication infrastructure offers a great opportunity to improve reliability, through the automation of fault location, isolation, and service restoration (FLISR) process. DA includes the installation of protection and control devices (PCD). The use of PCD makes fault management more efficient, reduces average outage duration per customer in case of faults, reduces costs due to unsupplied energy, and improves distribution system reliability. Although the use of PCD remarkably enhances distribution system reliability, it is neither economical nor affordable to install them in all potential locations. To obtain the optimal allocation of PCD (OAPCD), an optimisation problem has to be formulated and solved. Several models and methods have been suggested for the OAPCD in SDSs. Herein, an overview of the state-of-the-art models and methods applied to the OAPCD in SDSs are introduced, identifying the contributions of reviewed works, identifying advantages and disadvantages, classifying and analysing current and future research directions in this area.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Section: Computational Intelligence Based Optimisation Methodsmentioning

confidence: 99%

Section: Fault Indicatormentioning

confidence: 99%

“…Published Contribution [119] Feb 2020 NSGA-II optimally allocates conventional and directional fault indicators, considering the real distance among the suspect fault locations.…”

Section: Referencementioning

confidence: 99%

Section: Objectivesmentioning

confidence: 99%

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Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

et al. 2021

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“…In this situation, it is essential to reduce possible fault points so that maintenance personnel does not have to check every possible location. However, this paper will not address multiple location reductions, e.g., by allocating fault indicators (Farajollahi et al, 2019;Sau et al, 2020).…”

Section: Global Search Of Fault Locationmentioning

confidence: 99%

Impedance-based Fault Location Error Analysis in Distribution Network with Distributed Generation

Kume

Momesso

Monteiro

et al. 2020

Anais Do Simpósio Brasileiro De Sistemas Elétricos 2020

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Reliability and continuity in the electrical system are one of the issues where distribution companies are continually seeking improvements. The penetration of Distributed Generators (DGs) contributes to modify the amplitude of the fault signals, which significantly affects the accuracy of the fault location algorithms. In this context, this paper proposes an impedance-based method to fault location in distribution systems with DGs. A new process analyzing the linear behavior of input and output information of the algorithm to search the short-circuits location is used. The smart meters were allocated at the substation and DGs nodes, and a real 135-bus distribution electrical system was used to perform the robustness tests. The results showed that the fault location method has high accuracy, and no significant influences on the location results regarding the penetration level have been observed. Because of its simplicity and high accuracy, we emphasize its applicability to realistic problems.

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Evaluation of DG impacts on distribution networks

Kumar¹,

Prem²,

Ali

2021

Uncertainties in Modern Power Systems

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Allocation of fault indicators in distribution feeders containing distributed generation

Cited by 8 publications

References 14 publications

Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

Impedance-based Fault Location Error Analysis in Distribution Network with Distributed Generation

Evaluation of DG impacts on distribution networks

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