Cuckoo Search Combined with PID Controller for Maximum Power Extraction of Partially Shaded Photovoltaic System

• Main Authors: Al-Shaalan, A.M (Author), Al-Shamma’a, A.A (Author), Al-Wesabi, I. (Author), Ding, M. (Author), Fang, Z. (Author), Hussein Farh, H.M (Author), Kandil, T. (Author)
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: Condition; Cuckoo search algorithms; Electric control equipment; Global optimization; Hardware in loop; hardware-in-loop; Heuristics algorithm; heuristics algorithms; Hybrid CSA-PID; Hybrid cuckoo search algorithm-PID; Maximum power point trackers; MPPT; Partial shading; Partial shading condition; partial shading conditions; Particle swarm optimization (PSO); Photovoltaic arrays; Photovoltaic effects; photovoltaic system; Photovoltaic systems; PID controllers; Proportional control systems; Real time control; Solar cells; Three term control systems
• Online Access: View Fulltext in Publisher

 In the case of partial shading conditions (PSCs), normal equations cannot be completely implemented. The mathematical model of the Photovoltaic (PV) array needs to be modified and re-established with the existence of bypass diodes connected to the PV module, which can alleviate the negative effects of the PSCs and generate several peaks on the PV output characteristics curve. The first aim of this study is to modify and re-establish the mathematical model of the PV array under PSCs. Second, it aims to improve and validate the reliable Cuckoo Search Algorithm (CSA) by integrating it with PID (hybrid CSA-PID) to diminish the impact of PSCs problems. The hybrid CSA-PID was proposed to both track the global maximum power point (GMPP) of PV systems and reduce the tracking time to eliminate the fluctuations around the GMPP. Further, the PID controller was used to eliminate the error percentage obtained by CSA under PSCs to generate the required duty cycle, which provides the required and desired maximum voltage accordingly. The proposed CSA-PID technique has been implemented using both Matlab/Simulink and Hardware-In-Loop experiments on the MT real-time control platform NI PXIE-1071. For validation, the Hybrid CSA-PID method is evaluated and compared with CSA, modified particle swarm optimization (MPSO), PSO, and modified perturb and observe (MP&O) methods under similar conditions. Finally, the obtained findings demonstrated the efficacy and superiority of the proposed hybrid CSA-PID technique, demonstrating its resilience, fast reaction, and good performance in terms of tracking time and GMPP tracking. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.