Open AccessOptimized generated power of a solar PV system using an intelligent tracking technique
Author(s) -
Afshin Balal,
Mostafa Abedi,
Farzad Shahabi
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijpeds.v12.i4.pp2580-2592
Subject(s) - maximum power point tracking , maximum power principle , photovoltaic system , power (physics) , computer science , tracking (education) , control theory (sociology) , span (engineering) , electricity generation , solar micro inverter , physics , control (management) , electrical engineering , engineering , artificial intelligence , psychology , pedagogy , civil engineering , quantum mechanics , inverter
Partial shading condition (PSC) is common and complicated in all types of PV power plant. Therefore, the power production of solar system would be affected by the mismatch phenomena produced by PSC. Furthermore, when the array is partially shaded, the P–V characteristics become more complex which causes multiple peaks of the P-V curve. So, the simple maximum power point tracking (MPPT) methods such as perturb and observe (P&O) will fail. To address the above issue, this paper proposes a combination of two different approaches, implementing distributed MPPT (DMPPT) and optimized fuzzy/bee algorithm (OFBA). DMPPT can be utilized to maximize solar energy by allowing each module, or group of modules, be managed independently. Also, due to the output power oscillations around the operating point in the P&O method, an OFBA is employed which allowing for the decrease of output power oscillations without the usage of temperature and light sensors. The result shows that utilizing of DMPPT control approach in conjunction with the OFBA boosts the output generated power.