GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions
The demand for clean and renewable energy is increasing due to environmental concerns. Photovoltaic (PV) system is very popular from the renewable sources and its usage is increasing. The PV system power transfer efficiency depends on several factors such electrical characteristics of loads, solar i...
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2025-01-01
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| author | Parveen Kumar Manish Kumar Ajay Kumar Bansal |
| author_facet | Parveen Kumar Manish Kumar Ajay Kumar Bansal |
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| collection | DOAJ |
| description | The demand for clean and renewable energy is increasing due to environmental concerns. Photovoltaic (PV) system is very popular from the renewable sources and its usage is increasing. The PV system power transfer efficiency depends on several factors such electrical characteristics of loads, solar irradiation, shading condition and panel temperature. The process of transferring maximum possible power to load from PV system by adjusting the system parameters is called maximum power point tracking (MPPT). Under the partially shaded conditions, multiple power peaks are created in the PV curves and makes the MPPT is a non-convex problem. It is a challenging problem to track the global maximum power point (GMPP) under partially shaded conditions. It is essential to recognize the GMPP and restart the string as early as possible to prevent the physical as well as economical damage. In this paper, a new hybrid algorithm for MPPT is proposed and called as QASHO, a combination of Spotted Hyena optimization (SHO) and Quadrature approximation (QA) technique. The QASHO is used to track the GMPP under different weather conditions such as partial shading. The simulation results are compared with Perturb and Observe (P&O) algorithm and Cuckoo Search optimization (CSO) algorithm and promised for better performance in tracking GMPP. The experimental results are provided to validate the proposed MPPT methodology. |
| format | Article |
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| institution | Matheson Library |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-8f2e5abff01d4d8f8b3bcc36e0b10f992025-07-17T23:01:25ZengIEEEIEEE Access2169-35362025-01-011312176212177110.1109/ACCESS.2023.327255410114385GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded ConditionsParveen Kumar0https://orcid.org/0000-0001-5986-7379Manish Kumar1https://orcid.org/0000-0002-4827-6642Ajay Kumar Bansal2https://orcid.org/0000-0002-5964-5992Department of Electrical Engineering, Central University Haryana, Mahendergarh, Haryana, IndiaDepartment of Electrical Engineering, Central University Haryana, Mahendergarh, Haryana, IndiaDepartment of Electrical Engineering, Central University Haryana, Mahendergarh, Haryana, IndiaThe demand for clean and renewable energy is increasing due to environmental concerns. Photovoltaic (PV) system is very popular from the renewable sources and its usage is increasing. The PV system power transfer efficiency depends on several factors such electrical characteristics of loads, solar irradiation, shading condition and panel temperature. The process of transferring maximum possible power to load from PV system by adjusting the system parameters is called maximum power point tracking (MPPT). Under the partially shaded conditions, multiple power peaks are created in the PV curves and makes the MPPT is a non-convex problem. It is a challenging problem to track the global maximum power point (GMPP) under partially shaded conditions. It is essential to recognize the GMPP and restart the string as early as possible to prevent the physical as well as economical damage. In this paper, a new hybrid algorithm for MPPT is proposed and called as QASHO, a combination of Spotted Hyena optimization (SHO) and Quadrature approximation (QA) technique. The QASHO is used to track the GMPP under different weather conditions such as partial shading. The simulation results are compared with Perturb and Observe (P&O) algorithm and Cuckoo Search optimization (CSO) algorithm and promised for better performance in tracking GMPP. The experimental results are provided to validate the proposed MPPT methodology.https://ieeexplore.ieee.org/document/10114385/Solar PV systempartial shadingglobal maximum power pointoptimizationspotted hyena optimizationquadrature approximation |
| spellingShingle | Parveen Kumar Manish Kumar Ajay Kumar Bansal GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions IEEE Access Solar PV system partial shading global maximum power point optimization spotted hyena optimization quadrature approximation |
| title | GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions |
| title_full | GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions |
| title_fullStr | GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions |
| title_full_unstemmed | GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions |
| title_short | GMPP Tracking of Solar PV System Using Spotted Hyena and Quadratic Approximation Based Hybrid Algorithm Under Partially Shaded Conditions |
| title_sort | gmpp tracking of solar pv system using spotted hyena and quadratic approximation based hybrid algorithm under partially shaded conditions |
| topic | Solar PV system partial shading global maximum power point optimization spotted hyena optimization quadrature approximation |
| url | https://ieeexplore.ieee.org/document/10114385/ |
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