Novel gooseneck barnacle optimization a nature inspired technique for optimizing reactive power within systems of power with electric vehicles.

The significance of ORPD (Optimal Reactive Power Dispatch) cannot be emphasized within the operation of power systems, particularly according to the growing use of electric vehicles (EVs). Electric vehicles (EVs) have the potential to influence the power grid via their ability to augment power demand and function as distributed energy resources. The effective administration of Optimal Renewable Power Dispatch (ORPD) in conjunction with Electric Vehicle (EV) integration necessitates meticulous examination of charging schedules, battery capacity, and the desired state of charge. In the current paper, a novel optimizer known as the Novel Gooseneck Barnacle Optimization (NGBO) algorithm is introduced to address the ORPD problem within the presence of Electric Vehicles (EVs). The NGBO algorithm draws inspiration from the regular mating behavior of gooseneck barnacles involving self-fertilization and casting sperm. To evaluate its performance, the NGBO algorithm is applied to two standard exam systems, including the IEEE 118- and IEEE 57-system of bus, considering various scenarios of EV penetration. The experimental outcomes demonstrate the NGBO effectively mitigates active power loss and voltage variation in power systems, surpassing several existing metaheuristic optimization techniques by reducing power loss by up to 15% and voltage deviation by up to 10% compared to traditional methods, demonstrating the effectiveness of the method in handling EV-related uncertainties.