Predictive Control for PV- Water Pumping System based of Interconnected High Gain Observer

This article presents a comprehensive evaluation of an integrated photovoltaic (PV) and water pumping system employing both Finite Set Model Predictive Control (FS-MPC) and Deat Beat Predictive Control (DB-MPC) under varying insolation levels (1000 W/m² to 700 W/m²). The system, initially tested at 1000 W/m², rapidly achieves Maximum Power Point Tracking (MPPT), stabilizing PV parameters at the MPP within 0.2 seconds. Notably, DB-MPC demonstrates superior dynamic response and faster settling times compared to conventional methods. The Interconnected High-Gain Observer accurately estimates motor speed, facilitating the attainment of the rated rotor speed in line with the desired reference speed. Transitioning from 1000 W/m² to 700 W/m² insolation, the system exhibits stability in Vpv and rapid Ipv adjustment at MPP. The InC algorithm extends PV array operation, showcasing a decrease in power output to 2204 W at 60% flow rate. These results affirm the efficacy and adaptability of the proposed control strategies in optimizing the performance of the PV-driven water pumping system, offering promising advancements in sustainable energy applications.

• solar water pumping
• finite control set model predictive control
• maximum power point tracking
• high-gain observer
• motor speed estimation
• insolation variation
• dynamic response

• 7 — Affordable and clean energy
• 9 — Industry, innovation and infrastructure

• Photovoltaic System Optimization Techniques
• Advanced Control Systems Optimization
• Multilevel Inverters and Converters
• solar water pumping
• finite control set model predictive control
• maximum power point tracking
• high-gain observer
• motor speed estimation
• insolation variation
• dynamic response
• Renewable Energy, Sustainability and the Environment
• Control and Systems Engineering
• Electrical and Electronic Engineering
• Energy
• Engineering