Reconfigured Photovoltaic Model to Facilitate Maximum Power Point Tracking for Micro and Nano-Grid Systems
<p dir="ltr">PV systems are a popular energy resource, prevalent worldwide; however, shade faults manifested in PV systems limit its power conversion efficiency. The occurrence of multiple power peaks and their location are highly uncertain in PV systems; this necessitates the use of...
محفوظ في:
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| مؤلفون آخرون: | , , |
| منشور في: |
2022
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| الملخص: | <p dir="ltr">PV systems are a popular energy resource, prevalent worldwide; however, shade faults manifested in PV systems limit its power conversion efficiency. The occurrence of multiple power peaks and their location are highly uncertain in PV systems; this necessitates the use of complex maximum power point tracking algorithms to introduce high voltage oscillations. To address this issue, a new reconfigurable PV array to produce a global maximum power point (GMPP) algorithm close to the Voc regions was introduced. This enables the use of a simple Perturb and Observe (P&O) algorithm to easily track GMPP. For reconfiguration, a simple 5 × 5 PV array is considered, and a new physical relocation procedure based on the position square method is proposed. Performance of the proposed reconfiguration model is tested for four various shade events and its row current evaluations are comprehensively analyzed. Furthermore, evaluations of fill factor, mismatch loss, and power loss are quantitatively compared against Dominance Square and TCT schemes. Since the power enhancement is ensured in a reconfigurable PV array, the fixed reconfiguration is tailored to suit residential PV and microgrid systems. For MPP evaluations, hardware demonstrations are performed with a lab scale prototype model developed with a PV simulator and a DC–DC power electronic interface. The I–V characteristics of conventional and reconfigured models are programmed into the simulator and the use of the hill climbing algorithm is validated. To analyze the voltage and power oscillations with MPP tracking, the PSO algorithm is also tested for two test patterns and its results are comprehensively studied.</p><h2>Other Information</h2><p dir="ltr">Published in: Energies<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/en15238860" target="_blank">https://dx.doi.org/10.3390/en15238860</a></p> |
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