Honey badger optimization algorithm based maximum power point tracking for solar photovoltaic systems

Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters

“…Bio-inspired algorithms are optimization algorithms that draw on the principles and inspiration of nature's biological evolution to develop new search tools for optimization problems. Different bio-inspired algorithms have been proposed such as Particle Swarm Optimization [71], Coati Optimization Algorithm [72], Pelican Optimization Algorithm [73], Marine Predators Algorithm [74], Electric Eel Foraging Optimization [75], Hippopotamus Optimization Algorithm [76], Several applications of bio-inspired algorithms in power systems have been proposed over the years such as wide-area damping control design [77,78], electricity theft detection [79], integrated energy system optimization [80], optimization of HVAC systems [81], power system stabilizer design [82], load dispatch for microgrid [83], energy management [84], load profile generation [85], power system state estimation [86], short-term hydrothermal scheduling [87], distributed power generation planning [88], reactive power optimization [89], maximum power point tracking [90], wind turbine placement [91], coordination of directional overcurrent relays [92], placement of electric vehicle charging station [93], optimal DG unit placement [94], power quality disturbances identifi-cation [95], optimal power flow [96]. The use of bio-inspired algorithms to tune traditional ANN is possible and some authors have already pointed out this benefit to improve the generalization capacity of the ANN.…”