Huilian Liao

TL;DR: The proposed FBSA combines the foraging mechanism of E-coli bacterium introduced in bacterial foraging algorithm with the swarming pattern of birds in block introduced in particle swarm optimization to improve the convergence for high-dimensional function optimization.

TL;DR: A voltage sag estimation approach based on a deep convolutional neural network, which has been tested on the IEEE 68-bus test network and it has been demonstrated that the various sag categories can be identified accurately regardless of the operating condition under which the sags occur.

TL;DR: In this paper, a new stochastic approach to the comprehensive assessment of the impact of voltage sags on large-scale power networks is presented, which takes into account the stochastically nature of power system operation, including load variation, uncertainty of fault clearing time by protection relays, fault rates of network components, and the variation/uncertainty in equipment sensitivity to voltage sag.

TL;DR: In this paper, a new single-event characteristic, sag severity index (SSI), derived with respect to equipment sensitivity to voltage sags, is presented, which is more inclusive of associated uncertainties/variation in equipment response to voltage sag than existing single event characteristics.

TL;DR: In this paper, the impact of different flexible AC transmission system (FACTS) devices on critical power quality (PQ) phenomena including voltage sags, harmonics and unbalance from the perspective of both mitigation effect and potential negative impact is investigated.