A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system

Al-Wesabi Ibrahim; Jiazhu Xu; Imad Aboudrar; Khaled Alwesabi; Li Danhu; Hassan Z Al Garni; Elhachemi Mammeri; Hossam Kotb; Mohit Bajaj; Shir Ahmad Dost Mohammadi

doi:10.1038/s41598-025-85481-6

A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system

Sci Rep. 2025 Jan 25;15(1):3229. doi: 10.1038/s41598-025-85481-6.

Authors

Al-Wesabi Ibrahim¹, Jiazhu Xu², Imad Aboudrar³, Khaled Alwesabi⁴, Li Danhu⁵, Hassan Z Al Garni⁶, Elhachemi Mammeri⁷, Hossam Kotb⁸, Mohit Bajaj^{9

10

11}, Shir Ahmad Dost Mohammadi¹²

Affiliations

¹ College of Electrical and Information Engineering, Hunan University, Hunan, 410083, China. Ibrahim@hnu.edu.cn.
² College of Electrical and Information Engineering, Hunan University, Hunan, 410083, China. xjz@hnu.edu.cn.
³ Engineering and Sustainable Development Research Team, EST of Dakhla, Ibn Zohr University, Dakhla, Morocco.
⁴ College of Computer Science and Information Technology, Al-Razi University, Sana'a, 1152, Yemen.
⁵ College of Electrical and Information Engineering, Hunan University, Hunan, 410083, China.
⁶ Department of Electrical Engineering, Jubail Industrial College, Jubail, Saudi Arabia.
⁷ Laboratory of Applied Automatic, Department of automation and electrification of industrial process, Faculty of Hydrocarbons and Chemistry, M'hamed Bougara University of Boumerdes, Boumerdes, Algeria.
⁸ Department of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, 21544, Egypt.
⁹ Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India. mb.czechia@gmail.com.
¹⁰ Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan. mb.czechia@gmail.com.
¹¹ College of Engineering, University of Business and Technology, Jeddah, 21448, Saudi Arabia. mb.czechia@gmail.com.
¹² Department of Electrical and Electronics, Faculty of Engineering, Alberoni University, Kapisa, Afghanistan. sh_ahmad.dm@au.edu.af.

PMID: 39863668
DOI: 10.1038/s41598-025-85481-6

Abstract

This study first proposes an innovative method for optimizing the maximum power extraction from photovoltaic (PV) systems during dynamic and static environmental conditions (DSEC) by applying the horse herd optimization algorithm (HHOA). The HHOA is a bio-inspired technique that mimics the motion cycles of an entire herd of horses. Next, the linear active disturbance rejection control (LADRC) was applied to monitor the HHOA's reference voltage output. The LADRC, known for managing uncertainties and disturbances, improves the anti-interference capacity of the maximum power point tracking (MPPT) technique and speeds up the system's response rate. Then, in comparison to the traditional method (perturb & observe; P&O) and metaheuristic algorithms (conventional particle swarm optimization; CPSO, grasshopper optimization; GHO, and deterministic PSO; DPSO) through DSEC, the simulations results demonstrate that the combination HHOA-LADRC can successfully track the global maximum peak (GMP) with less fluctuations and a quicker convergence time. Finally, the experimental investigation of the proposed HHOA-LADRC was accomplished with the NI PXIE-1071 Hardware-In-Loop (HIL) prototype. The output findings show that the effectiveness of the provided HHOA-LADRC may approach a value higher than 99%, showed a quicker rate of converging and less oscillations in power through the detection mechanism.

Keywords: Dynamic and static environmental conditions; Dynamic control; MPPT; Optimization techniques; Photovoltaic battery chargers.