Article
Remote Sensing
Weipeng Xing, Guangyuan Zhang, Stefan Poslad
Summary: The study proposes using a deep belief network to estimate Global Horizontal Irradiance with high accuracy and efficiency. This method fills the gap of GHI estimations in China at minutely or hourly intervals in all sky conditions.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Green & Sustainable Science & Technology
Liwei Yang, Xiaoqing Gao, Jiajia Hua, Liping Wang
Summary: Accurate forecasting of Global Horizontal Irradiance (GHI) is crucial for power system expansion, power generation production scheduling, maintenance scheduling, and ensuring continuous power supply. A method called FY-4A-Heliosat, based on FY-4A satellite images, has been proposed for GHI forecasting. The method outperforms the climatology and persistence model (CP) in most cases and seasons, but underestimates GHI in all seasons. Annual studies show that FY-4A-Heliosat performs better than CP for all forecast horizons, with nRMSE ranging from 17% to 25%.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Green & Sustainable Science & Technology
Jen-Yu Han, Petr Vohnicky
Summary: The increased interest in renewable electricity sources has led to a focus on the rapidly developing solar energy sector. This study utilizes machine learning algorithms to estimate global horizontal irradiance (GHI) and diffuse horizontal irradiance (DHI) using satellite imagery. The results indicate that the machine learning models perform with similar accuracy as traditional models, and outperform them when estimating DHI.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Environmental Studies
Zia Ul Rehman Tahir, Ghulam Murtaza Amjad, Muhammad Hamza, Muhammad Rizwan Shad, Adnan Qamar, Philippe Blanc, Sabtain Abbas, Muhammad Azhar, Muhammad Safyan, Muhammad Abdullah, Muhammad Atif, Syed Tauqeer Haider
Summary: The availability of accurate solar radiation data is crucial for assessing the solar energy potential of commercial power plants. This study validates the McClear model's global horizontal irradiance (GHI) against measured data for Pakistan's complex topography. The results show good agreement between McClear GHI and measured GHI under clear-sky conditions, with high correlation coefficients.
ENERGY & ENVIRONMENT
(2022)
Article
Green & Sustainable Science & Technology
Yunhui Tan, Quan Wang, Zhaoyang Zhang
Summary: This study proposes a method to estimate near-real-time global horizontal irradiance (GHI) solely using Himawari-8 satellite data without supplementary meteorological parameters. Four machine learning algorithms and their ensemble are employed, achieving similar good performance with R2 around 0.81 and nRMSE within the range of 25.22%-26.34%. The results outperform the official Himawari-8 shortwave radiance product in ground validation tests. However, different machine learning models show different behavior under different weather conditions, and all models perform poorly under overcast conditions, suggesting the need for further investigation to improve model performance. Nevertheless, this efficient method relying on Himawari-8 satellite data is expected to be widely applicable for near-real-time GHI estimation in the future.
Article
Chemistry, Multidisciplinary
Caston Sigauke, Edina Chandiwana, Alphonce Bere
Summary: Accurate forecasting of global horizontal irradiance (GHI) is crucial for power grid stability. This research proposes the use of spatial regression coupled with Gaussian Process Regression (GP Spatial) and the GP Autoregressive Spatial model (GP-AR Spatial) for GHI prediction. The results show that the GP model outperforms the benchmark model in terms of accuracy.
APPLIED SCIENCES-BASEL
(2023)
Article
Energy & Fuels
Raihan Kamil, Pranda M. P. Garniwa, Hyunjin Lee
Summary: Solar irradiance models play a key role in compensating for the lack of measurement data at ground stations, with machine learning emerging as a popular method due to its accuracy. This study compared three representative models and found that the long short-term memory (LSTM) model outperformed others in accuracy.
Article
Green & Sustainable Science & Technology
Muhammed A. Hassan, Loiy Al-Ghussain, Adnan Darwish Ahmad, Ahmad M. Abubaker, Adel Khalil
Summary: In this study, different models for forecasting half-hourly global horizontal irradiance were evaluated, with the dynamic model proving to be the most accurate for single forecasting. When aggregate forecasting with annual optimal weights, the dynamic, average, and amplified models contributed the most, with the dynamic model holding the largest weight due to its superior prediction during overcast and partially cloudy days. The aggregated model showed the highest precision with relative mean square errors below 15.0% and coefficients of determination above 98.8%.
Article
Green & Sustainable Science & Technology
Hui-Min Zuo, Jun Qiu, Fang-Fang Li
Summary: Accurate solar forecasts are crucial for optimal power grid dispatch, but changes in cloud distribution pose a challenge. This study proposes a CNN-LSTM model using ASI and GHI sequences as input to predict the future 10-min GHI values. The model improves accuracy by 18% compared to other models.
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY
(2023)
Article
Energy & Fuels
Pranda M. P. Garniwa, Rial A. Rajagukguk, Raihan Kamil, HyunJin Lee
Summary: Short-term global horizontal irradiance (GHI) forecast methodologies are utilized to mitigate photovoltaic power instability and secure early participation in the energy auction market. This study combines optical flow (OF) method and long short-term memory model (LSTM) to enhance temporal horizon and accuracy. The combination of OF and LSTM models outperforms the combination of OF and conventional models, providing better accuracy for GHI forecasts. The findings encourage the inclusion of satellite data in GHI forecast and optimization of energy management systems integrating photovoltaic systems.
Article
Green & Sustainable Science & Technology
Pranda M. P. Garniwa, Hyunjin Lee
Summary: This study assessed the ability of nine parameterized methods to estimate Linke turbidity (TL) in the five Ko center dot ppen-Geiger climate zones. By simulating all TL values into a global horizontal irradiance (GHI) model, called the Hammer model, the evaluation was strengthened. The results showed that atmospheric turbidity on the Korean Peninsula varies across seasons, with higher turbidity in spring and summer and lower turbidity in fall and winter. Among the nine TL methods, TLValko1, TLValko2, and TLCapdrou consistently performed poorly in terms of relative root mean square error (rRMSE) and relative mean bias error (rMBE). TLRemund, TLDogniaux1, TLDogniaux2, TLIneichen, TLMolineaux, and TLGreiner were recommended for evaluating atmospheric turbidity in different climate types. Minor differences in rRMSE and rMBE values make it difficult to identify the most superior method.
Article
Environmental Sciences
Chenguang Tian, Xu Yue, Jun Zhu, Hong Liao, Yang Yang, Yadong Lei, Xinyi Zhou, Hao Zhou, Yimian Ma, Yang Cao
Summary: Fire emissions have a significant impact on radiation, climate, and ecosystems through aerosol radiative effects. The magnitude of the feedback between these factors and fire emissions remains uncertain on a global scale.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2022)
Article
Environmental Sciences
Dongyu Jia, Jiajia Hua, Liping Wang, Yitao Guo, Hong Guo, Pingping Wu, Min Liu, Liwei Yang
Summary: Accurate solar radiation estimation is crucial for solar energy systems, with high-precision remote sensing data being used to fill the gap in surface radiation observations. This study tested a global solar irradiance estimation method using data from the FengYun-4A satellite, showing that the estimated global horizontal irradiance (GHI) was slightly affected by seasons, while direct normal irradiance (DNI) estimation was less accurate. A new DNI radiation algorithm during autumn and winter is proposed for northern China to improve accuracy.
Article
Energy & Fuels
Adnan Ayaz, Faraz Ahmad, Mohammad Abdul Aziz Irfan, Zabdur Rehman, Krzysztof Rajski, Jan Danielewicz
Summary: With the depletion of fossil reserves, the demand for renewable energy, especially solar power plants, has reached its peak globally. In order to properly estimate the solar energy potential, a feasibility study is necessary before installing solar power plants. This study compared ground-based measurements with satellite-based data and found significant differences. Real-time measurements are essential for accurately assessing solar energy resources.
Article
Environmental Sciences
Kostas Eleftheratos, John Kapsomenakis, Ilias Fountoulakis, Christos S. Zerefos, Patrick Jockel, Martin Dameris, Alkiviadis F. Bais, Germar Bernhard, Dimitra Kouklaki, Kleareti Tourpali, Scott Stierle, J. Ben Liley, Colette Brogniez, Frederique Auriol, Henri Diemoz, Stana Simic, Irina Petropavlovskikh, Kaisa Lakkala, Kostas Douvis
Summary: This study analyzes the changes and trends of DNA-damaging ultraviolet-B (UV-B) radiation, showing that it will decrease before 2050 and increase afterwards due to enhanced greenhouse gas concentrations. The decrease is associated with reduced total cloud cover and negative trends in total ozone, while the increase is linked to upward ozone trends. The findings highlight the importance of understanding the effects of climate change on UV radiation.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2022)
Article
Green & Sustainable Science & Technology
Xixi Sun, Jamie M. Bright, Christian A. Gueymard, Brendan Acord, Peng Wang, Nicholas A. Engerer
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2019)
Article
Green & Sustainable Science & Technology
Dazhi Yang, Christian A. Gueymard
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2019)
Article
Environmental Sciences
Christian A. Gueymard, Dazhi Yang
ATMOSPHERIC ENVIRONMENT
(2020)
Article
Green & Sustainable Science & Technology
German Salazar, Christian Gueymard, Janis Bezerra Galdino, Olga de Castro Vilela, Naum Fraidenraich
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2020)
Article
Green & Sustainable Science & Technology
Jamie M. Bright, Xixi Sun, Christian A. Gueymard, Brendan Acord, Peng Wang, Nicholas A. Engerer
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2020)
Article
Energy & Fuels
Dazhi Yang, Stefano Alessandrini, Javier Antonanzas, Fernando Antonanzas-Torres, Viorel Badescu, Hans Georg Beyer, Robert Blaga, John Boland, Jamie M. Bright, Carlos F. M. Coimbra, Mathieu David, Azeddine Frimane, Christian A. Gueymard, Tao Hong, Merlinde J. Kay, Sven Killinger, Jan Kleissl, Philippe Lauret, Elke Lorenz, Dennis van der Meer, Marius Paulescu, Richard Perez, Oscar Perpinan-Lamigueiro, Ian Marius Peters, Gordon Reikard, David Renne, Yves-Marie Saint-Drenan, Yong Shuai, Ruben Urraca, Hadrien Verbois, Frank Vignola, Cyril Voyant, Jie Zhang
Article
Energy & Fuels
N. R. Kamphuis, C. A. Gueymard, M. T. Holtzapple, A. T. Duggleby, K. Annamalai
Letter
Thermodynamics
Christian A. Gueymard
ENERGY CONVERSION AND MANAGEMENT
(2020)
Article
Green & Sustainable Science & Technology
Wenmin Qin, Lunche Wang, Christian A. Gueymard, Muhammad Bilal, Aiwen Lin, Jing Wei, Ming Zhang, Xuefang Yang
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2020)
Article
Chemistry, Multidisciplinary
Gustavo Nofuentes, Christian A. Gueymard, Jose A. Caballero, Guilherme Marques-Neves, Jorge Aguilera
Summary: This study evaluates the relationship between Average Photon Energy (APE) and spectral Direct Normal Irradiance (DNI) by analyzing a dataset collected in Jaen, Spain. The findings suggest that APE may uniquely characterize the DNI spectrum distribution only within the 450-900nm waveband, with the coefficient of variation (CV) staying below 3.5% in this range.
APPLIED SCIENCES-BASEL
(2021)
Article
Geochemistry & Geophysics
Jun Li, Wenjun Tang, Kun Yang, Yu Xie, Christian A. Gueymard, Jun Qin, Manajit Sengupta
Summary: Cloud parameters have a critical impact on surface shortwave radiation computation, and introducing a parameterization of cloud transmittance and reflectance based on radiative transfer simulations improves the accuracy of existing models. The revised model shows higher accuracy and no underestimation under high cloud optical thickness, outperforming the MODIS official SSR product. The improved model can be used globally to map surface shortwave radiation with reliable performance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Energy & Fuels
Sophie Pelland, Christian A. A. Gueymard
Summary: This research tests the performance of CM-SAF SRI and NSRDB-S satellite-based spectral irradiance products at seven ground stations, against benchmark data and models. The results show that CM-SAF SRI generally outperforms First Solar and no spectral effects benchmarks, while NSRDB-S has lower accuracy in predicting long-term spectral derate factors compared to instantaneous SMMs. Spectra comparisons reveal systematic differences between NSRDB-S and benchmark spectra, likely due to differences in aerosol treatment.
IEEE JOURNAL OF PHOTOVOLTAICS
(2022)
Article
Environmental Sciences
Gabriel Lopez, Christian A. Gueymard, Jesus Polo, Joaquin Alonso-Montesinos, Aitor Marzo, Nuria Martin-Chivelet, Pablo Ferrada, Martha Isabel Escalona-Llaguno, Francisco Javier Batlles
Summary: The spectral distribution of solar irradiance is crucial for the power production of PV modules. However, current spectroradiometers have limitations in accurately measuring the full spectrum of some PV technologies. This study proposes a new methodology using the SMARTS spectral code to extend the spectral range and resolution of measured irradiance spectra, providing satisfactory results in both clear and hazy sky conditions. This approach serves as a foundation for obtaining the instantaneous spectral irradiance incident on PV module arrays and evaluating the impact of atmospheric constituents on surface irradiance.
Article
Green & Sustainable Science & Technology
Dazhi Yang, Yizhan Gu, Martin Janos Mayer, Christian A. Gueymard, Wenting Wang, Jan Kleissl, Mengying Li, Yinghao Chu, Jamie M. Bright
Summary: This study improves the YANG4 model by fitting separate sets of model coefficients for each climatological regime, resulting in the superior YANG5 model. In the tested 126 stations, YANG5 shows lower normalized root mean square errors for beam normal irradiance and diffuse horizontal irradiance compared to YANG4.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Proceedings Paper
Energy & Fuels
Manajit Sengupta, Aron Habte, Yu Xie, Anthony Lopez, Christian A. Gueymard
SOLARPACES 2018: INTERNATIONAL CONFERENCE ON CONCENTRATING SOLAR POWER AND CHEMICAL ENERGY SYSTEMS
(2019)
Article
Energy & Fuels
Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy
Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.
Article
Energy & Fuels
Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao
Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.
Article
Energy & Fuels
Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal
Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.
Article
Energy & Fuels
Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan
Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.
Article
Energy & Fuels
Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian
Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.
