Artificial Hummingbird Algorithm for Optimal Reactive Power Control for Radial Distribution Feeder Loadability Enhancement

Electrical distribution networks (EDNs) suffer from low-voltage profiles, high distribution losses, and reduced stability margins due to lack of adequate reactive power support. Thus, optimizing the allocation of switched capacitor banks (SCBs) and their control according to the loading pattern is one of the most challenging tasks for network operators. By aiming for reduction of real power loss and enhancement of voltage profile and network loadability, this paper proposes a new artificial hummingbird algorithm (AHA) for determining optimal sites and ratings of SCBs in EDNs. Later, periodic optimal control settings for SCBs were determined based on load profile, photovoltaic (PV) generation, and electric vehicles (EVs). In addition, the effectiveness of the AHA is compared with literature and other similar meta-heuristics in solving complex nonlinear multi-objective problems with various goals, variables, and constraints. The AHA outperformed the other approaches in terms of the target values and technical benefits of the proposed approach.