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Maximum power point tracking in photovoltaic systems under different operational conditions by using ZA-INC algorithm
摘要： Today, environmental pollution has increased due to excess use of fossil resources. Amidst, renewable energy resources, solar energy is one of the infinite, clean and accessible options. Each solar cell has a unique operating point which is called maximum power point. Considering nonlinearity of I–V and P–V curves of Photovoltaic (PV) resources, their delivered power depends on operating point of the PV. That is, for changes in temperature or irradiation, some actions should be taken to obtain maximum operating point which is called maximum power point tracking (MPPT). This paper tries to configure power circuit using distributed maximum power point tracking (DMPPT) with a fly-back converter, optimize power and reduce fluctuations around maximum power point. MPPT is analyzed through simulation using P&O, INC and zero fluctuation, adaptive step, increasing (ZA-INC) guidance algorithms in two steps including variable irradiation with constant temperature and variable temperature with constant irradiation using DMPPT and centralized MPPT. In DMPPT scheme using ZA-INC algorithm, power is optimized, losses are reduced, fluctuations around maximum power point are reduced, gain and tracking speed are increased.
关键词： MPPT,Weather conditions,Photovoltaic,ZA-INC algorithm,Flyback converter
更新于2025-09-12 10:27:22
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Analysis of P-Band Repeat-Pass SAR Tomography Under Changing Weather Conditions
摘要： In this paper, the impact of changing weather conditions on repeat pass SAR tomography is addressed to support the up-coming spaceborne mission BIOMASS. In recent years it has been demonstrated that forest biomass retrieval can be improved by using P-band SAR tomography in tropical forest. Yet, these results were obtained by using campaign data acquired in a single day, while the revisit time of BIOMASS mission will be 3-4 days. To fill this gap, we simulate BIOMASS repeat pass tomography using ground-based TropiSCAT data with revisit time of 3 days and rainy days included. It is observed that the backscattered power within canopy layer, which is significantly correlated to the forest biomass, stays stable under changing weather conditions. The backscattered power variation of canopy layer are within 1.5 dB. For this forest site, this error is translated into an AGB error of about 50-80 t/ha, which is 20% or less of forest AGB.
关键词： P-band,BIOMASS mission,tomography,changing weather conditions,TropiSCAT
更新于2025-09-09 09:28:46