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Open AccessArticle

Optimized Surge Arrester Allocation Based on Genetic Algorithm and ATP Simulation in Electric Distribution Systems

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CEAMAZON—Amazon Energy Efficiency Center, Federal University of Pará (UFPA), Ave. Perimetral 2651, Guamá, 66077-830 Belém, PA, Brazil
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LINC—Laboratory of Computational Intelligence, Federal University of Pará (UFPA), St. Augusto Correa 01, Guamá, 66075-110 Belém, PA, Brazil
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CELPA—Electric Distribution Utility of Pará, Ave. Augusto Montenegro 5639-5671, Castanheira, 66645-001 Belém, PA, Brazil
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Authors to whom correspondence should be addressed.
Energies 2019, 12(21), 4110; https://doi.org/10.3390/en12214110
Received: 30 August 2019 / Revised: 18 October 2019 / Accepted: 22 October 2019 / Published: 28 October 2019
(This article belongs to the Special Issue Heuristic Optimization Techniques Applied to Power Systems)
The efficient protection of electric power distribution networks against lightning discharges is a crucial problem for distribution electric utilities. To solve this problem, the great challenge is to find a solution for the installation of surge arresters at specific points in the electrical grid and in a sufficient quantity that can ensure an adequate level of equipment protection and be within the utility’s budget. As a solution to this problem of using ATP (Alternative Transient Program), this paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), with a fitness function that maximizes the number of protected equipment according to the financial availability for investment in surge arresters. As ATP may demand too much processing time when running large distribution grids, an innovative procedure is implemented to obtain an overvoltage severity description of the grid and select only the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The results obtained for the IEEE-123 bus electric feeder indicate a great reduction of flashover occurrence, thus increasing the equipment protection level. View Full-Text
Keywords: transient analysis; surge arrester allocation; genetic algorithm; ATP transient analysis; surge arrester allocation; genetic algorithm; ATP
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Rocha, G.V.S.; Barradas, R.P.S.; Muniz, J.R.S.; Bezerra, U.H.; Araújo, I.M.; Costa, D.S.A.; Silva, A.C.; Nunes, M.V.A.; Silva, J.S. Optimized Surge Arrester Allocation Based on Genetic Algorithm and ATP Simulation in Electric Distribution Systems. Energies 2019, 12, 4110.

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