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The Optimization Algorithm of the Forced Current Cathodic Protection Base on Simulated Annealing

College of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
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This paper is an extended version of our conference paper: Song, C., Hou, Y., Du, J. The Optimization Algorithm for the Auxiliary Anode System of Grounding Grid Based on Simulated Annealing. In Proceedings of the 2018 International Symposium on Computer, Consumer and Control, Taichung, Taiwan, 6–8 December 2018; pp. 282–285.
Algorithms 2019, 12(4), 83; https://doi.org/10.3390/a12040083
Received: 31 January 2019 / Revised: 17 April 2019 / Accepted: 18 April 2019 / Published: 21 April 2019
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Abstract

The grounding grid of a substation is important for the safety of substation equipment. Especially to address the difficulty of parameter design in the auxiliary anode system of a grounding grid, an algorithm is proposed that is an optimization algorithm for the auxiliary anode system of a grounding grid based on improved simulated annealing. The mathematical model of the auxiliary anode system is inferred from the mathematical model of cathodic protection. On that basis, the parameters of the finite element model are optimized with the improved simulated annealing algorithm, thereby the auxiliary anode system of a grounding grid with optimized parameters is structured. Then the algorithm is proven as valid through experiments. The precision of the optimized parameters is improved by about 1.55% with respect to the Variable Metric Method and the Genetic Algorithm, so it can provide a basis for parameter design in the auxiliary anode system of a grounding grid. View Full-Text
Keywords: simulated annealing; auxiliary anode system; grounding grid; optimization algorithm; finite element model simulated annealing; auxiliary anode system; grounding grid; optimization algorithm; finite element model
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Song, C.; Wang, M.; Qin, X.; Wang, P.; Liu, B. The Optimization Algorithm of the Forced Current Cathodic Protection Base on Simulated Annealing. Algorithms 2019, 12, 83.

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