Multivariable Fault Analysis Algorithm for Protection of Power System with Renewable Energy Penetration

Abstract

Faulty events incident on the transmission line causes mechanical stress, excessive heating newlineof components and produce unbalance current in the utility network. Hence, it is desired newlineto trip the transmission line as soon as fault event is observed. This can be achieved using newlinefault detection, classification and estimation algorithm based protection relays. Efficient newlinefault detection, classification and estimation algorithm reduces restoration cost of newlinetransmission line, increase efficiency of protection scheme of power system and improves newlinereliability of power. newlineRecent concerns of environmental issues, fossil fuel problems, and risks of energy newlinesecurity have forced all the countries for focusing to increase the use of renewable energy. newlineThis has motivated the utilities to increase level of renewable energy in the grids. The newlinevariable and uncertain nature of these renewable energy sources has posed challenges to newlinethe utility network operators in terms of grid security, power system protection, power newlinequality, energy management and flexibility. The application of machine learning, signal newlineprocessing, deep learning, and intelligent techniques have solved protection problems. newlineThis research work has considered the protection challenges for the utility grid with and newlinewithout renewable energy. newlineThis research work designed an approach considering hybridization of Stockwell newlinetransform, Hilbert transform, and alienation coefficient for identifying, classify and newlinelocating the fault conditions incident on a line. The proposed algorithm uses multi- newlinevariables (three variables) derived from the current signals to create a fault index to newlineidentify the fault events. newline