Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions

• Published in: Applied sciences Vol. 10; no. 13; p. 4575
• Main Authors: Singh Chawda, Gajendra, Prakash Mahela, Om, Gupta, Neeraj, Khosravy, Mahdi, Senjyu, Tomonobu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2020
• Subjects: Accuracy; Algorithms; Alternative energy sources; Conductance; Control; Control algorithms; Design; Efficiency; Electrical conductance; Genetic algorithms; global peak; Incremental conductance; Influence; Irradiation; Management; multiple power peaks; nonuniform irradiation; nonuniform operating conditions; nonuniform temperature; Optimization; Oscillations; Photovoltaic power generation; Radiation; Solar energy; Solar power; Swarm intelligence; Technology application; Temperature; Velocity; Weight reduction; Japan
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app10134575

In practical operating conditions, the Solar-Photo Voltaic (SPV) system experiences multifarious irradiation and temperature levels, which generate power with multiple peaks. This is considered as the nonuniform operating condition (NUOC). This requires accurate tracking of global power peaks to achieve maximum power from SPV, which is a challenging task. Hence, this paper presents an incremental Conductance based Particle Swarm Optimization (ICPSO) algorithm for accurate tracking of maximum global power from active power multiple peaks generated by the SPV. The proposed algorithm continuously adjusts the individual particle’s weight component, which depends on its distance from the global best position during the tracking process. The proposed algorithm has the merit of continuous adjustment of weight components which reduces active power oscillations at the optimal global position area. Proposed ICPSO algorithm has been successfully designed and implemented for Solar-photo voltaic (PV) under nonuniform operating condition. It is established that the proposed algorithm enhances the output power of the Solar-PV up to 7% with the maximum power tracking of 0.1 s compared to other maximum power point tracking algorithms.