The series–parallel configuration is one of the widely utilized schemes in the photovoltaic arrays. The existence of shaded or failed modules in the string of the array has a significant impact on the array-produced power. Therefore, this work introduce an innovative objective function and a novel approach of honey badger algorithm (HBA) as a first time to dynamically reconfigure the series–parallel interconnected photovoltaic array under the partial shading and random failure situations to boost the harvested array’s power. The reconfiguration process is performed via electrically reconnecting the modules among the strings via a set of switches. The performance of the proposed approach is examined with two series of analyses. The first one focuses on handling the impact of partial shading phenomena while the second concerns optimizing the array output in case of existing random failed modules inside the array besides partial shading conditions. Two arrays are considered, including a symmetric 9 × 9 array and an asymmetric 10 × 8 photovoltaic one. The proposed optimizer is compared with a set of recently proposed meta-heuristic approaches, including wild horse optimizer, artificial gorilla Troops optimizer, and particle swarm optimizer to clarify the reason for selecting the HBA optimizer. The harvested global maximum power, the mismatch power loss, and enhancement are quality measures performed to affirm the proposed approach’s ability to enhance the array output power. Moreover, energy-saving and income payback are investigated over a day and a year for two systems using symmetric 9 × 9 array and asymmetric 10 × 8 array. The comparisons and analyses showed that, the reconfigured arrays based on HBA provide higher values of maximum global power with smoother photovoltaic characteristics. Moreover, the 9 × 9 and 10 × 8 PV systems-based HBA save income by the percentage of 18.12%, 24.24% compared with series–parallel systems without reconfiguration per year, respectively.