Advanced MPPT Control of Grid-Connected Photovoltaic Systems Using Hippopotamus Optimization Algorithm: Performance Evaluation Under Dynamic Irradiance and Partial Shading Conditions

Abstract

The increasing integration of photovoltaic (PV) systems into modern power networks has intensified the need for efficient Maximum Power Point Tracking (MPPT) techniques capable of maximizing energy extraction under variable environmental conditions. This paper presents a comprehensive comparative study of five MPPT approaches, namely Particle Swarm Optimization (PSO), Cuckoo Search (CS), Artificial Neural Network (ANN), Harris Hawks Optimization (HHO), and the recently developed Hippopotamus Optimization Algorithm (HOA), applied to a grid-connected photovoltaic system. The investigated system consists of a PV array, a DC–DC boost converter, a regulated DC-link, and a three-level voltage source converter connected to the utility grid. Extensive simulations are performed under rapidly changing irradiance levels and partial shading conditions to evaluate the tracking capability, dynamic response, stability, and power quality of the considered methods. The comparative analysis is conducted using several performance indicators, including tracking efficiency, settling time, Root Mean Square Error (RMSE), steady-state ripple, DC-link voltage regulation, duty-cycle stability, and grid current quality. The obtained results demonstrate that the proposed HOA-based MPPT strategy achieves the highest tracking efficiency of 99.87%, the shortest settling time of 8 ms, the lowest power oscillations, and the minimum tracking error among all investigated techniques. Furthermore, HOA ensures superior DC-link voltage stability, reduced harmonic distortion, smoother duty-cycle evolution, and improved active power injection into the utility grid. Compared with ANN, PSO, CS, and HHO, the HOA algorithm exhibits faster convergence toward the global maximum power point and enhanced robustness under dynamic operating conditions. The results confirm that HOA represents a promising optimization-based MPPT solution for high-performance grid-connected photovoltaic applications.