Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.