Artificial Intelligence-Based Protection for Smart Grids

Mostafa Bakkar, Santiago Bogarra, Felipe Córcoles, Ahmed Aboelhassan, Shuo Wang and Javier Iglesias
Additional contact information
Mostafa Bakkar: Department of Electrical Engineering, Universitat Politècnica de Catalunya (UPC), C. Colom 1, 08222 Terrassa, Spain
Santiago Bogarra: Department of Electrical Engineering, Universitat Politècnica de Catalunya (UPC), C. Colom 1, 08222 Terrassa, Spain
Felipe Córcoles: Department of Electrical Engineering, Universitat Politècnica de Catalunya (UPC), C. Colom 1, 08222 Terrassa, Spain
Ahmed Aboelhassan: Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China
Shuo Wang: Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China
Javier Iglesias: ABB Power Grids Spain S.A.U., San Romualdo 13, 28037 Madrid, Spain

Energies, 2022, vol. 15, issue 13, 1-18

Abstract: Lately, adequate protection strategies need to be developed when Microgrids (MGs) are connected to smart grids to prevent undesirable tripping. Conventional relay settings need to be adapted to changes in Distributed Generator (DG) penetrations or grid reconfigurations, which is a complicated task that can be solved efficiently using Artificial Intelligence (AI)-based protection. This paper compares and validates the difference between conventional protection (overcurrent and differential) strategies and a new strategy based on Artificial Neural Networks (ANNs), which have been shown as adequate protection, especially with reconfigurable smart grids. In addition, the limitations of the conventional protections are discussed. The AI protection is employed through the communication between all Protective Devices (PDs) in the grid, and a backup strategy that employs the communication among the PDs in the same line. This paper goes a step further to validate the protection strategies based on simulations using the MATLAB TM platform and experimental results using a scaled grid. The AI-based protection method gave the best solution as it can be adapted for different grids with high accuracy and faster response than conventional protection, and without the need to change the protection settings. The scaled grid was designed for the smart grid to advocate the behavior of the protection strategies experimentally for both conventional and AI-based protections.

Keywords: artificial neural network-based relay; protection strategies; smart grids; microgrids; distribution system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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