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A novel power benefit prediction approach for two‐axis sun‐tracking type photovoltaic systems based on semiconductor theory
Author(s) -
Kuo KunChang,
Wang JenCheng,
Su YuLi,
Chou JuiJen,
Jiang JoeAir
Publication year - 2014
Publication title -
progress in photovoltaics: research and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.286
H-Index - 131
eISSN - 1099-159X
pISSN - 1062-7995
DOI - 10.1002/pip.2327
Subject(s) - photovoltaic system , maximum power point tracking , solar tracker , power (physics) , installation , computer science , tracking system , tracking (education) , solar energy , energy (signal processing) , grid connected photovoltaic power system , automotive engineering , reliability engineering , electronic engineering , engineering , electrical engineering , mathematics , statistics , artificial intelligence , physics , kalman filter , pedagogy , quantum mechanics , inverter , operating system , psychology
Photovoltaic (PV) systems incorporated with sun‐tracking technology have been proposed and verified to effectively increase the power harvest. However, the actual power generated from a PV module has not been investigated and compared with that analyzed from theoretical models of the PV material. This study proposes a novel method for estimating the power benefit harvested by a two‐axis sun‐tracking type (STT) PV system. The method is based on semiconductor theory and the dynamic characteristics, including maximum power point tracking of PV modules that can be integrated with the database of annual solar incidences to predict the power harvested by any STT PV system. The increment of annual energy provided by an STT PV system installed at any arbitrary latitude, compared with that by a fixed‐type system, can be accurately estimated using the proposed method. To verify the feasibility and precision performance of this method, a fixed‐type and a two‐axis STT PV system were installed at 24.92° north latitude in northern Taiwan and tested through long‐term experiments. The experimental results show that the energy increments estimated by the theoretical model and actual measurement are 19.39% and 16.74%, respectively. The results demonstrate that the proposed method is capable of predicting the power benefit harvested by an STT PV system with high accuracy. Using our method, a PV system installer can evaluate beforehand the economic benefits of different types of PV systems while taking different construction locations into consideration, thereby obtaining a better installation strategy for PV systems. Copyright © 2012 John Wiley & Sons, Ltd.