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Wind Effect Modeling and Analysis for Estimation of Photovoltaic module temperature

JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME 2018年第1期140卷 011008页

作者： Magare, Dhiraj Sastry, Oruganti Gupta, Rajesh Bora, Birinchi Singh, Yogesh Mohammed, Humaid Indian Inst Technol Dept Energy Sci & Engn Mumbai 400076 Maharashtra India Minist New & Renewable Energy Natl Inst Solar Energy New Delhi 122003 India

The performance of photovoltaic (PV) modules in outdoor field conditions is adversely affected by the rise in module operating temperature. Wind flow around the module affects its temperature significantly, which ultimately influences the module output power. In this paper, a new approach has been presented, for module temperature estimation of different technology PV modules (amorphous Si, hetero-junction with intrinsic thin-layer (HIT) and multicrystalline Si) installed at the site of National Institute of Solar Energy (NISE), India. The model based on presented approach incorporates the effect of wind speed along with wind direction, while considering in-plane irradiance, ambient temperature, and the module efficiency parameters. For all the technology modules, results have been analyzed qualitatively and quantitatively under different wind situations. Qualitative analysis based on the trend of module temperature variation under different wind speed and wind direction along with irradiance and ambient temperature has been presented in detail from experimental data. Quantitative results obtained from presented model showed good agreement with the experimentally measured data for different technology modules. The model based on presented approach showed marked improvement in results with high consistency, in comparison with other models analyzed for different technology modules installed at the site. The improvement was very significant in case of multicrystalline Si technology modules, which is most commonly used and highly temperature sensitive technology. Presented work can be used for estimating the effect of wind on different technology PV modules and for prediction of module temperature, which affects the performance and reliability of PV modules.

关键词： photovoltaic module module temperature wind speed wind direction

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Predicting module temperature and photovoltaic electricity generation using meteorological data

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2024年第9期38卷 5123-5133页

作者： Kim, Yong-min Lee, Hee-Lak Park, Jiyoung Moon, Seung Jae Hanyang Univ Dept Power Engn Seoul 04763 South Korea Korea East West Power Power Plant 3 Operat Dept Dangjin Power Complex Dangjin 31700 South Korea Hanyang Univ Dept Mech Convergence Engn Seoul 04763 South Korea Korea Automot Technol Inst Cheonan 31214 South Korea

The instability of the increasingly important photovoltaic (PV) electricity generation in Korea due to a dependence on meteorological conditions is an emerging problem. In this study, we examined the influence of various meteorological conditions on the prediction accuracy of PV generation and module temperature. The predictions were based on weather data acquired from the Korea Meteorological Administration and compared with actual PV generation data from the Dangjin coal yard PV power facility. The results were analyzed on the basis of meteorological conditions, insolation, ambient temperature, and wind velocity.

关键词： Insolation Meteorological condition module temperature Photovoltaic generation Power generation prediction

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Floating photovoltaic module temperature estimation: Modeling and comparison

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RENEWABLE ENERGY 2023年 208卷 162-180页

作者： Rahaman, Md Atiqur Chambers, Terrence L. Fekih, Afef Wiecheteck, Giovana Carranza, Gabriel Possetti, Gustavo Rafael Collere Univ Louisiana Dept Elect Engn Lafayette LA 70503 USA Univ Louisiana Dept Mech Engn Lafayette LA USA Univ Estadual Ponta Grossa Dept Civil Engn Ponta Grossa Brazil Univ Louisiana Affiliated Res Fac Energy Efficiency & Sustainable Lafayette LA USA Companhia Saneamento Parana Sanepa Curitiba Brazil

As the power demand increases, photovoltaic (PV) energy evolves with time, and besides the traditional ground-mounted and roof-based PV systems, floating photovoltaic (FPV) systems have gained popularity due to higher efficiency from lower module temperatures and water evaporation reductions. This paper estimates and com-pares the temperature of the floating PV module using thermal, empirical, and computational fluid dynamics (CFD) models. The dynamic thermal model considers a three-level energy-balance equation for the FPV module. From that, a simplified thermal model has been developed, which requires fewer parameters and is easier to estimate the module temperature. Secondly, the least squares regression was used to generate the empirical model, resulting in the smallest possible root mean square error when comparing the observed and predicted values. Finally, the FPV system has been developed in the COMSOL environment for CFD analysis using the same heat transfer method. The estimated results from the models were compared with the actual data collected from a Brazilian site and the existing FPV and ground-mounted temperature models. The RMSE performance of the FPV models was comparable to that of the data obtained from an installed FPV system and performed much better than other similar FPV models and their ground-based counterparts.

关键词： Floating photovoltaic (FPV) system Thermal model Dynamic modeling Computational fluid dynamics model Empirical model module temperature

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Field-test analysis of PV system output characteristics focusing on module temperature

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SOLAR ENERGY MATERIALS AND SOLAR CELLS 2003年第3-4期75卷 665-671页

作者： Nishioka, K Hatayama, T Uraoka, Y Fuyuki, T Hagihara, R Watanabe, M Nara Inst Sci & Technol Grad Sch Mat Sci Nara 6300101 Japan Sanyo Elect Corp New Mat Res Ctr New Elect Mat Dept Moriguchi Osaka 5708502 Japan Sharp Co Ltd Engn Dept 2 Photovola Div Shinjo Nara 6392198 Japan

Field-test data from a 50 kW photovoltaic (PV) system installed at The Nara Institute of Science and Technology (NAIST) were analyzed in detail. We found that the PV system operated in a wide temperature range and was strongly affected by the temperature coefficient of conversion efficiency when the module temperature became high. The temperature coefficient dependence of the system performance was analyzed in order to estimate the annual output of the system in an actual operating environment. As a result, it was found that the annual output energy of the PV system increased about 1% by an improvement of 0.1%/degreesC in the temperature coefficient. This result indicates that it is very important to consider the temperature characteristics in solar cell development. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： photovoltaic solar cell module temperature irradiation temperature coefficient conversion efficiency annual output cumulative output operation time

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The Method for Photovoltaic module temperature Short-term Forecasting Based on Numerical Weather Prediction 3

The Method for Photovoltaic Module Temperature Short-term Fo...

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3rd Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Cheng, Xu Wu, Ji Li, Deng-xuan Zhu, Xiang China Elect Power Res Inst Renewable Energy Res Ctr CEPRI Nanjing Peoples R China

ISBN: (纸本)9781665425513

As module temperature plays an important role in the PV power forecasting, an accurate short-term prediction will be very helpful in improving PV power short-term forecasting. In this article, a method of short-term forecasting for PV module temperature based on numerical weather prediction(NWP) is proposed, which has a time resolution of prediction point was 15-minute,prediction aging of the next 24 hour. In the case study, this approach continuously provides reasonable temperature short-term forecasting of the PV module. The practice indicates that this method is simple and effective.

关键词： module temperature photovoltaic numerical weather prediction short-term forecasting

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Photovoltaic module temperature Estimation: A Comparison Between Artificial Neural Networks and Adaptive Neuro Fuzzy Inference Systems Models 1

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1st International Symposium on Intelligent Computing Systems (ISICS)

作者： Tziu Dzib, J. Alejos Moo, E. J. Bassam, A. Flota-Banuelos, Manuel Escalante Soberanis, M. A. Ricalde, Luis J. Lopez-Sanchez, Manuel J. Univ Autonoma Yucatan Fac Ingn Av Ind Contaminantes Merida Yucatan Mexico Univ British Columbia Clean Energy Res Ctr 2360 East Mall Vancouver BC V6T 1Z3 Canada

ISBN: (数字)9783319304472

ISBN: (纸本)9783319304472;9783319304465

The main objective of this paper is to present a comparison between two models for estimation of a photovoltaic system's module temperature (T-mod) using Artificial Neural Networks and Adaptive Neuro Fuzzy Inference Systems. Both estimations use measurements of common operation variables: current, voltage and duty cycle (d) from a power converter of the photovoltaic system as input variables and T-mod as a desired output. The models used the same database for the training process, different training strategies were evaluated with the objective to find which model has the best estimation with respect to the T-mod. Subsequently, the output results from these architectures are validated via the Root Mean Squared Error, Mean Absolute Percentage Error and correlation coefficient. Results show that the Artificial Neural Network model in comparison with Adaptive Neuro Fuzzy Inference System model provides a better estimation of T-mod with R = 0.8167. Developed models may have an application with smart sensors on cooling systems for photovoltaic modules with the objective of improving their operation efficiency.

关键词： Renewable energy Artificial intelligence Photovoltaic system module temperature Levenberg-Marquardt algorithm Statistical comparison

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Thermal Modeling and Verification of PV module temperature and Energy Yield Using Outdoor Measurements for Ankara, Turkey

Thermal Modeling and Verification of PV Module Temperature a...

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International Conference on Photovoltaic Technologies (PVCon)

作者： Tuncel, Bilge Ozden, Talat Akinoglu, Bulent G. Balog, Robert S. Middle East Tech Univ Dept Phys Ankara Turkey Middle East Tech Univ GUNAM Ctr Solar Energy Res & Applicat Ankara Turkey Gumushane Univ Dept Energy Syst Engn Gumushane Turkey Middle East Tech Univ GUNAM Ctr Solar Energy Res & Applicat Gumushane Turkey Middle East Tech Univ Earth Syst Sci Program Ankara Turkey Texas A&M Univ Renewable Energy & Adv Power Elect Res Lab College Stn TX USA

ISBN: (纸本)9781538675380

Ankara is in the Central Anatolia region of Turkey where the climate is dry-continental with an annual solar insolation of around 1750 kWh/m(2). In the transition to renewable energy, detailed analyses are required to ensure effective and economic utilization of the available solar resource. An essential part of these analyses is to calculate expected energy yield. For photovoltaic (PV) systems, this includes the effect of temperature on the PV efficiency, which determines the power yield of the PV modules. In this study, a first-principles thermal modeling approach is improved by adding the speed and direction of wind across the PV module into a forced convection term as well as including the temperature dependency of the module conversion efficiency. The analytical model is based on the principle of conservation of energy and uses meteorological data that are readily available from most state meteorological services. The mathematical analysis is suitable to predict the performance of a proposed PV installation without the time and expense of installing and monitoring a pilot system. The mathematical model is compared against measured data from the METU-GUNAM Outdoor Test Facility in Ankara to validate the methodology. Preliminary analyses showed that the model performs well especially during sunrise and sunsets shoulders of the diurnal cycle with a deviation of only a few W/m(2) for the electrical power yield and about 2 degrees C for the module temperature. However, these deviations could become as large as 12 W/m(2)and 8 degrees C at solar noon which suggests that the model still requires further improvement. In general, this error was found to be less that obtained by using basic explicit correlation methods and offers the advantage that it can be used for other geographical environments for which insolation and meteorological data is available without needing to construct a test-site.

关键词： Solar energy photovoltaic modules module efficiency module temperature thermal modeling

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The Method for Photovoltaic module temperature Ultra-short-term Forecasting Based on RBF Neural Network

The Method for Photovoltaic Module Temperature Ultra-short-t...

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China International Conference on Electricity Distribution (CICED)

作者： Cheng, Xu Chen, Furong Yu, Bingxia Zhang, Xuesong China Elect Power Res Inst Beijing Peoples R China State Grid Nanjing Power Supply Co Nanjing Jiangsu Peoples R China State Grid Zhejiang Elect Power Res Inst Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781467390682

As module temperature plays an important role in the conversion efficiency of photovoltaic(PV) module, an accurate prediction will be very helpful in improving PV power forecasting. In this article, a method of ultra-short-term forecasting for PV module temperature based on RBF neural network was proposed, which had a prediction aging of the next 4 hour, time resolution of prediction point was 15-minute, and prediction rolling cycle of 15-minutes. In the case study, this approach continuously provides reasonable temperature forecasting of the PV module. It is indicated that this approach is of significance in practical application.

关键词： module temperature photovoltaic RBF neural network ultra-short-term forecasting

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Research on Short-term module temperature Prediction Model Based on BP Neural Network for Photovoltaic Power Forecasting

Research on Short-term Module Temperature Prediction Model B...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Sun, Yujing Wang, Fei Zhen, Zhao Mi, Zengqiang Liu, Chun Wang, Ba Lu, Jing North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Baoding Hebei Province Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China China Elect Power Res Inst Beijing Peoples R China

ISBN: (纸本)9781467380409

As one of the most related parameters of photovoltaic (PV) power generation, the temperature of PV modules and its prediction play very important role in PV power forecasting. A short-term step-wise temperature prediction model for PV module based on back propagation (BP) neural network is proposed in this paper. Firstly, the impact factors of PV module temperature are determined according to the PV module physical characteristics and the correlation coefficient. Secondly, two different prediction methods, direct and step-wise modeling methods based on BP neural network are applied to build the prediction models respectively. Thirdly, the mapping models between the module temperature and the impact factors for step-wise prediction are established under each weathers types. Finally, the deviations of two different kinds of prediction models are analyzed and discussed using actual operation data. The results indicate that, other things equal, the step-wise prediction model has better accuracy than the direct prediction model.

关键词： impact factor module temperature neural network photovoltaic power forecasting step-wise prediction

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NOVEL METHOD AND SYSTEM FOR MONITORING CPV CELL AND module temperature

NOVEL METHOD AND SYSTEM FOR MONITORING CPV CELL AND MODULE T...

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35th IEEE Photovoltaic Specialists Conference

作者： Adkins, D. A. Univ Nottingham Inst Sustainable Energy Technol Nottingham NG7 2RD England

ISBN: (纸本)9781424458912

This paper presents a novel system for accurate monitoring of photovoltaic cell temperature, allowing the introduction of thermal management strategies critical to maintaining high efficiencies and cell lifetimes. The sensor device outlined consists of a junction diode formed on the surface of a cell;a metallic contact is deposited onto the cell during manufacture forming a Schottky barrier diode. The additional metalsemiconductor junction is formed by the evaporation of a metal contact with suitable work function. A wire is then bonded to the contact for connection to an external monitoring/control circuit. Furthermore, the reverse leakage current of the Schottky diode is temperature dependent, and can be used as part of a feedback system to monitor and control the device temperature, either by controlling the movement of the module tracking so that the device is no longer in direct light or by switching in an active cooling device such as a fan if required.

关键词： CPV cell monitoring cell lifetime module temperature photovoltaic cell temperature solar cells solar energy concentrators thermal management

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