A Novel Harris-Hawk-Optimization-Based Maximum-Power-Point-Tracking Control Strategy for a Grid-Connected PV Power-Generation System
Xiang Tao, Jianbo Xin, Shuai Zhang, Zaide Xu, Zhonghai Ye, Kai Wang, Bo Chen, Ning Zhou- Energy (miscellaneous)
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Control and Optimization
- Engineering (miscellaneous)
- Building and Construction
This paper aims to assess the efficacy of the Harris Hawk Optimization (HHO) algorithm within the domain of photovoltaic (PV) power-generation systems. The focus lies in elucidating how the HHO algorithm optimizes maximum-power-point tracking (MPPT) and augments the performance of grid-connected PV systems. Initially, in the MATLAB/Simulink environment, a comparison is made between the HHO algorithm and two other extensively utilized methods for maximum-power-point tracking (MPPT): Perturb and Observe (P&O) and Particle Swarm Optimization (PSO). Preliminary findings indicate the HHO algorithm’s notable advantages in efficiency and speed over the other algorithms. Furthermore, by establishing a practical experimental platform and synchronously verifying outcomes through simulation, we conducted a comprehensive assessment of the HHO algorithm on a single-phase full-bridge-inverter grid-connected system. Results show the HHO algorithm’s exceptional optimization capabilities, which displays superior adaptability and ability to adjust to varying external conditions.