Power Prediction of Bifacial Si PV Module with Different Reflection Conditions on Rooftop

被引:21
|
作者
Cha, Hae Lim [1 ]
Bhang, Byeong Gwan [1 ]
Park, So Young [1 ]
Choi, Jin Ho [1 ]
Ahn, Hyung Keun [1 ]
机构
[1] Konkuk Univ, Dept Elect Engn, 120 Neungdong, Seoul 05029, South Korea
来源
APPLIED SCIENCES-BASEL | 2018年 / 8卷 / 10期
关键词
bifacial PV module; prediction of back irradiance; rooftop photovoltaic system; PERFORMANCE;
D O I
10.3390/app8101752
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A bifacial solar module has a structure that allows the rear electrode to be added to the existing silicon photovoltaic module structure. Thus, it can capture energy from both the front and rear sides of the module. In this paper, modeling is suggested to estimate the amount of energy generated from the rear of the bifacial photovoltaic module. After calculating the amount of irradiance from the rear side, the estimated power generation is compared with the real power output from the rear side of the module. The experiments were performed using four different environments with different albedos. The theoretical prediction of the model shows a maximum of 5% and average of 1.86% error in the measurement data. Based on the nature of the bifacial solar module, which receives additional irradiance from the rear side, this study compared the output amounts with respect to different rear environments. Recently, installation of floating Photovoltaic has been increasing. As the reflection of irradiation from the water surface occurs, the positive influence of the installation with the bifacial photovoltaic can be expected. We are confident that this research will contribute to zero energy construction by designing systems based on bifacial PV module with high performance ratio when applying solar power in a microgrid environment, which is the future energy.
引用
收藏
页数:20
相关论文
共 50 条
  • [21] Comparison of Si and GaN Power Devices Used in PV Module Integrated Converters
    Acanski, M.
    Popovic-Gerber, J.
    Ferreira, J. A.
    2011 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), 2011, : 1217 - 1223
  • [22] Analysis of Power Output Impact on PV rooftop system under Different Installation Positions by PSCAD
    Thanomsat, N.
    Plangklang, B.
    COE ON SUSTAINABLE ENERGY SYSTEM (THAI-JAPAN), 2016, 89 : 149 - 159
  • [23] Implementation of a Switched PV Technique for Rooftop 2 kW Solar PV to Enhance Power during Unavoidable Partial Shading Conditions
    Kumar, B. Praveen
    Winston, D. Prince
    Christabel, S. Cynthia
    Venkatanarayanan, S.
    JOURNAL OF POWER ELECTRONICS, 2017, 17 (06) : 1600 - 1610
  • [24] Efficient prediction of maximum PV module output power through dynamic modeling
    Alam, Mohammad Saad
    Alouani, Ali T.
    Azeem, Mohammad F.
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2015, 11 : 27 - 35
  • [25] BiPV system performance and efficiency drops: overview on PV module temperature conditions of different module types
    Maturi, Laura
    Belluardo, Giorgio
    Moser, David
    Del Buono, Matteo
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON SOLAR HEATING AND COOLING FOR BUILDINGS AND INDUSTRY (SHC 2013), 2014, 48 : 1311 - 1319
  • [26] Real-Time Power Prediction for Bifacial PV Systems in Varied Shading Conditions: A Circuit-LSTM Approach Within a Digital Twin Framework
    Hong, Dou
    Ma, Jieming
    Wang, Kangshi
    Man, Ka Lok
    Wen, Huiqing
    Wong, Prudence
    IEEE JOURNAL OF PHOTOVOLTAICS, 2024, 14 (04): : 652 - 660
  • [27] Energy Production Analysis of Rooftop PV Systems Equipped with Module-Level Power Electronics under Partial Shading Conditions Based on Mixed-Effects Model
    Le, Ngoc Thien
    Truong, Thanh Le
    Asdornwised, Widhyakorn
    Chaitusaney, Surachai
    Benjapolakul, Watit
    ENERGIES, 2023, 16 (02)
  • [28] Power Enhancement of a PV Module Using Different Types of Phase Change Materials
    Shaito, Ali
    Hammoud, Mohammad
    Kawtharani, Fadel
    Kawtharani, Ali
    Reda, Hilal
    ENERGIES, 2021, 14 (16)
  • [29] Comparison of different physical models for PV power output prediction
    Dolara, Alberto
    Leva, Sonia
    Manzolini, Giampaolo
    SOLAR ENERGY, 2015, 119 : 83 - 99