Performance Improvements of Buck Converters in the Solar Panel System With a Modified Hill‐Climbing Algorithm

This study introduces the Step Size Optimization with Search Range Constraint (SSO‐SRC) algorithm. It is a novel modification of the Hill‐Climbing (HC) method that aims to enhance Maximum Power Point Tracking (MPPT) performance in photovoltaic (PV) systems. The proposed method employs a variable perturbation step size and a constrained search region. This approach balances rapid transient response with high steady‐state precision. The SSO‐SRC algorithm was implemented and tested using both DC‐DC synchronous and asynchronous buck converter topologies under dynamically changing environmental conditions. The results show response‐time improvements of 76% for the asynchronous converter and 72.32% for the synchronous converter. Furthermore, the algorithm maintained a tracking accuracy of up to 99%. It achieved peak efficiencies of 79.46% for the synchronous converter and 72.97% for the asynchronous converter. The results also demonstrate improved robustness and faster convergence compared with conventional PSO‐based control. The proposed algorithm also produces smoother output power. These findings demonstrate that the modified SSO‐SRC algorithm provides a reliable and low‐complexity MPPT solution for real‐time low‐power PV applications. It also offers practical applicability and computational efficiency without the computational overhead associated with AI‐based methods.