Emad M. Ahmed1,*, Mohamed A. Ahmed1, Ziad M. Ali2,3, Imran Khan4
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 231-254, 2022, DOI:10.32604/cmc.2022.022005
Abstract The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances. Then, a multi-label classification algorithm… More >