Article
Environmental Sciences
Ilias Fountoulakis, Kyriakoula Papachristopoulou, Emmanouil Proestakis, Vassilis Amiridis, Charalampos Kontoes, Stelios Kazadzis
Summary: Default aerosol extinction coefficient profiles are commonly used instead of measured profiles in radiative transfer modeling, increasing the uncertainties in the simulations. The present study aimed to determine the magnitude of these uncertainties and contribute towards the understanding of the complex interactions between aerosols and solar radiation. Using measured instead of default profiles for the simulations led to more significant differences in the atmosphere, especially during dust episodes.
Article
Green & Sustainable Science & Technology
Zhuoyuan Lyu, Ying Shen, Yu Zhao, Tao Hu
Summary: Solar energy, as a clean energy source, has tremendous potential for utilization. This study developed a novel model for accurately predicting solar radiation intervals. Through empirical research and various prediction models, a more accurate and reliable prediction interval of solar radiation was obtained.
Article
Agronomy
Peyman Abbaszadeh, Keyhan Gavahi, Atieh Alipour, Proloy Deb, Hamid Moradkhani
Summary: Accurate yield prediction is crucial for agricultural planning. This study presents a framework that utilizes artificial intelligence techniques and Copula functions to integrate multiple deep neural networks' outputs, providing a probabilistic estimate of soybean crop yield. Results show that this approach outperforms individual neural networks in terms of accuracy and reliability while considering model uncertainties.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Qitao Shi, Ya-Lin Zhang, Lu Yu, Feng Zhu, Longfei Li, Jun Zhou, Yanming Fang
Summary: This paper proposes a distribution-free method for regression problems on real-value response and introduces an effective boosting-based method for training. It also presents an improved method for unbiased mean estimation of the target distribution.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Statistics & Probability
Torsten Hothorn, Achim Zeileis
Summary: This article discusses regression models for supervised learning problems with continuous response, suggesting a more general understanding of regression models as models for conditional distributions. Quantile regression forests are highlighted among algorithms estimating conditional distributions. A novel approach based on a parametric family of distributions characterized by their transformation function is proposed, along with a dedicated transformation tree algorithm for detecting distributional changes. Prediction intervals and inference procedures are provided by the resulting predictive distributions, making them fully parametric yet very general.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2021)
Article
Computer Science, Artificial Intelligence
Di Wang, Ping Wang, Pingping Wang, Cong Wang, Zhen He, Wei Zhang
Summary: This paper proposes a predictive system based on locally weighted jackknife prediction approach to build faster and more reliable probabilistic predictions. Experimental results comparing the proposed method with other predictive systems confirm its better performance in terms of continuous ranked probability scores and prediction interval.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Energy & Fuels
Benedikt Schulz, Mehrez El Ayari, Sebastian Lerch, Sandor Baran
Summary: Probabilistic energy forecasting is crucial for integrating volatile power sources like solar energy into the electrical grid. Hybrid models combining physical and statistical methods have shown to be effective, with post-processing models proving to significantly improve the forecast performance of ensemble predictions and correct systematic biases.
Review
Automation & Control Systems
Daniel Landgraf, Andreas Voelz, Felix Berkel, Kevin Schmidt, Thomas Specker, Knut Graichen
Summary: This article reviews methods for predicting probabilistic uncertainties for nonlinear systems, with a focus on approximating methods. The methods are classified based on approximation type and assumptions about input and output distribution, and their application in stochastic model predictive control is discussed. Finally, the most important probabilistic prediction methods are numerically evaluated.
ANNUAL REVIEWS IN CONTROL
(2023)
Article
Energy & Fuels
Aapo Poskela, Armi Tiihonen, Heikki Palonen, Peter D. Lund, Kati Miettunen
Summary: The degradation of dye solar cell performance can be predicted by monitoring early changes in electrolyte color, allowing for estimation of the cell's lifetime before efficiency declines. This early prediction can lead to reduced development time for solar cells. By linking color changes in the electrolyte with the concentration of charge carriers, the model accurately predicts the predominant degradation mechanism. Integrating architecture-specific knowledge on degradation mechanisms improves lifetime predictions.
Article
Energy & Fuels
Ju-Hye Kim, Pedro Jimenez Munoz, Manajit Sengupta, Jaemo Yang, Jimy Dudhia, Stefano Alessandrini, Yu Xie
Summary: This study introduced the WRF-solar ensemble prediction system and a calibration method, showing improvement in forecast quality and reduction of positive bias through ensemble forecasting and analog ensemble calibration, respectively.
IEEE JOURNAL OF PHOTOVOLTAICS
(2022)
Article
Energy & Fuels
Xianglong Li, Longfei Ma, Ping Chen, Hui Xu, Qijing Xing, Jiahui Yan, Siyue Lu, Haohao Fan, Lei Yang, Yongqiang Cheng
Summary: The paper presents a probabilistic prediction model of solar irradiance based on XGBoost, which utilizes historical data to train a point prediction model and generates probability prediction intervals under different confidence levels using kernel density estimation. Experimental results demonstrate that this method has better accuracy and is suitable for engineering practice.
Article
Energy & Fuels
Stefan Kolecansky, Jaroslav Hofierka, Jozef Boglarsky, Jozef Supinsky
Summary: The use of solar radiation in urban environments is crucial for sustainable development, with 3D models showing better accuracy than 2D models in assessing solar radiation on vertical surfaces. Improper representation of vertical surfaces in digital surface models can impact solar resource assessments in urban areas.
Article
Engineering, Mechanical
Xuefei Guan
Summary: This study develops a probabilistic model for the threshold stress intensity factor range in infinite fatigue life design. The model incorporates the concept of probability of propagation to derive the probability density function of the threshold intensity factor range, accounting for uncertainty in fatigue crack growth. By integrating the derived distribution into the Kitagawa-Takahashi diagram, a rational fatigue endurance reliability model is established. The analytical form of fatigue endurance reliability index is obtained through first-order asymptotic approximation. Realistic engineering application examples demonstrate the usefulness of the overall method.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Computer Science, Artificial Intelligence
Min-ge Xie, Zheshi Zheng
Summary: In this article, the authors study the homeostasis property of conformal prediction under a general regression setup. They introduce the concepts of upper and lower predictive distributions and predictive curve, and establish connections to hypothesis testing and confidence distributions. The homeostasis property ensures the validity of predictions even when the learning model is completely wrong.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Construction & Building Technology
Yingdong He, Edward Arens, Nianping Li, Zhe Wang, Hui Zhang, A. Yongga, Chenzhang Yuan
Summary: Solar radiation has a significant impact on occupant comfort and building energy consumption, but it has been relatively overlooked in environmental design and energy simulation. Recent developments have led to the adoption of simplified occupant-centered models, such as the SC Model, and comprehensive simulation procedures like the DC Model. The HNU Solar Model presented in this paper offers a quicker alternative for calculating annual increases in mean radiant temperature (MRT) compared to the DC Model, making it a useful tool for evaluating indoor environments and designing fenestration in HVAC systems.
BUILDING AND ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Dazhi Yang, Gokhan Mert Yagli, Dipti Srinivasan
Summary: The paper introduces a state-of-the-art probabilistic solar forecasting method that effectively addresses the challenges of reflecting high-frequency fluctuations and changing uncertainty in solar energy systems, benefiting real-time stochastic simulations on a large scale.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Dazhi Yang, Wenting Wang, Tao Hong
Summary: Weather is a crucial factor for power generation and energy consumption, and energy forecasting models often rely on numerical weather prediction. This article offers an NWP forecast dataset from ECMWF for the energy forecasting community, along with case studies on post-processing of solar forecasts.
Article
Energy & Fuels
Wenting Wang, Dazhi Yang, Tao Hong, Jan Kleissl
Summary: Ensemble numerical weather prediction serves as the backbone of solar forecasting by generating a set of equally likely trajectories of future weather. This study provides a dataset from ECMWF Ensemble Prediction System and demonstrates its usage in solar power forecasting through two case studies.
Article
Meteorology & Atmospheric Sciences
Disong Fu, Christian A. Gueymard, Dazhi Yang, Yu Zheng, Xiangao Xia, Jianchun Bian
Summary: The latest version of Level-3 AHI AOD product underestimates aerosol optical depth against ground measurements. An XGBoost model based on AHI AOD, meteorological quantities, and geographic information has been developed to correct these errors, resulting in a significant improvement in the corrected AOD values.
ATMOSPHERIC RESEARCH
(2023)
Article
Thermodynamics
Hao Zhang, Xiaomi Zhang, Dazhi Yang, Yong Shuai, Bachirou Guene Lougou, Qinghui Pan, Fuqiang Wang
Summary: This study compares the thermochemical reaction characteristics of six common ferrites and four metal dopants through thermogravimetric analysis. A modified oxygen carrier with low reaction temperature requirements and excellent reaction performance is found, achieving dual optimization in terms of thermal efficiency and chemical efficiency. A foam-structured material with SiC as support is prepared and experimentally tested, showing optimal reaction performance with the highest CO yield of 439 mu mol/g and a peak CO yield of 7.0 mL min-1 g-1 and CO2 conversion of 45.5% at a reduction temperature of only 1100 degrees C.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Engineering, Electrical & Electronic
Gang Zhang, Xiao Chen, Dazhi Yang, Alistair Duffy, Ming Li, Lixin Wang
Summary: This article investigates how crosstalk amplitudes of multiconductor polyvinyl chloride cables vary with heating temperatures and time, and proposes a method to estimate aging rates and accelerating ratios.
IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY
(2023)
Article
Automation & Control Systems
Xiaowei Ju, Yuan Cheng, Bochao Du, Mingliang Yang, Dazhi Yang, Shumei Cui
Summary: To address the issue of high-frequency ac loss in hairpin windings, a hybrid transposed hairpin winding (HTHW) scheme is proposed, combining flat wire and litz wire. The HTHW can significantly reduce ac loss while maintaining a high slot fill factor.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Materials Science, Characterization & Testing
Qi Li, Hai Zhang, Jue Hu, Stefano Sfarra, Miranda Mostacci, Dazhi Yang, Marc Georges, Vladimir P. Vavilov, Xavier P. V. Maldague
Summary: With increasing attention paid to the protection of cultural relics, non-destructive testing (NDT) technologies such as infrared thermography (IRT) and Terahertz time-domain spectroscopy (THz-TDS) are proving to be valuable in detecting defects in ancient buildings and artworks. The present study explores the integration of online/offline background segmentation algorithms, commonly used in video processing, as a feature extraction tool with NDT. Experimental results demonstrate the superior performance of the proposed novel algorithms in detecting defects in a replica painting.
JOURNAL OF NONDESTRUCTIVE EVALUATION
(2023)
Article
Green & Sustainable Science & Technology
Martin Janos Mayer, Dazhi Yang
Summary: This study investigates the uncertainty in photovoltaic (PV) power forecasting by using ensemble numerical weather prediction (NWP) and ensemble model chain methods. It is demonstrated that the best probabilistic PV power forecast needs to consider both ensemble NWP and ensemble model chain. Furthermore, the point forecast accuracy is significantly improved through this pairing strategy. The recommended strategy achieves a mean-normalized continuous ranked probability score of 18.4% and a root mean square error of 42.1%.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Computer Science, Information Systems
Gang Zhang, Xiao Chen, Dazhi Yang, Lixin Wang, Xin He, Zhehao Zhang
Summary: This paper investigates the phase stability of a phase stable cable using multi-physics coupling simulations. A three-dimensional electromagnetic-thermal-flow-mechanics multi-physics coupling model is established to simulate the cable's behavior in air. The results reveal differences in the electric field distribution and thermal deformation between the corrugated cable and a normal coaxial cable, highlighting the need for higher voltage endurance and design optimization.
Article
Thermodynamics
Dongxu Shen, Chao Lyu, Dazhi Yang, Gareth Hinds, Lixin Wang
Summary: This work proposes a novel connection fault diagnosis method based on mechanical vibration signals rather than voltage and current measurements. The simulation of the vibration environment and optimal sensor placement are achieved, and a broad belief network (BBN) is proposed for detecting and locating connection faults in lithium-ion battery packs based on the vibration signals. Incremental-learning algorithms are paired with the BBN to adapt to new data in real-time. The empirical evidence shows a diagnostic accuracy of 93.25%, demonstrating the effectiveness and feasibility of the proposed method.
Article
Thermodynamics
Guoming Yang, Hao Zhang, Wenting Wang, Bai Liu, Chao Lyu, Dazhi Yang
Summary: This study presents a capacity optimization model and economic analysis for PV-hydrogen hybrid systems, using physical modeling of PV to enhance profit. It also identifies government subsidy policy, prices and costs, and PV power utilization as influential factors for system optimization.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Bai Liu, Dazhi Yang, Martin Janos Mayer, Carlos F. M. Coimbra, Jan Kleissl, Merlinde Kay, Wenting Wang, Jamie M. Bright, Xiang'ao Xia, Xin Lv, Dipti Srinivasan, Yan Wu, Hans Georg Beyerj, Gokhan Mert Yagli, Yanbo Shenl
Summary: Current solar forecast verification processes mainly focus on performance comparison of competing methods. However, it is important to evaluate the best method relative to the best-possible performance under specific forecasting situations, and quantify predictability and forecast skill. Unfortunately, there is a lack of literature on the quantification of relative performance of solar irradiance, and few studies on the spatial distributions of predictability and forecast skill. This study quantifies and maps the predictability and forecast skill of solar irradiance in the United States, refutes misconceptions, and revives the formulation of skill score.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Electrochemistry
Miao Bai, Chao Lyu, Dazhi Yang, Gareth Hinds
Summary: Accurate evaluation of the health status of lithium-ion batteries is crucial for their utility and safety. Electrochemical impedance spectroscopy (EIS) has advantages in detecting lithium plating, but its ability to quantify the degree of lithium plating has not been fully explored. This study proposes an EIS-based method that uses impedance spectrum to estimate battery capacity loss and quantify the mass of lithium plating.
Article
Engineering, Electrical & Electronic
Gang Zhang, Xin He, Lixin Wang, Dazhi Yang, Kaixing Chang, Alistair Duffy
Summary: Soft faults in cables can cause short circuits and open circuits, which need to be detected and eliminated as early as possible for the safe and stable operation of the cables. The time-reversal multiple signal classification (TR-MUSIC) method has been proven effective for locating soft faults in cables due to its high resolution and noise robustness. However, traditional TR-MUSIC requires a vector network analyzer (VNA) for measuring the scattering matrix of cables, which adds complexity and cost. To address this, a new method is proposed using an arbitrary function generator and an oscilloscope to acquire the desired scattering parameters.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Green & Sustainable Science & Technology
M. Genovese, F. Piraino, P. Fragiacomo
Summary: This research proposes the concept of a hydrogen valley in southern Italy, where hydrogen is produced centrally and delivered via fuel cell hybrid trains to refueling stations, providing transportation services. The analysis from both technical and economic perspectives shows that the cost of hydrogen and energy efficiency reached competitive levels, and hydrogen rail transport offers significant benefits in terms of emissions reduction and economic gains compared to conventional diesel trains and fully electric trains.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Miaomiao Liu, Payam Nejat, Pinlu Cao, Carlos Jimenez-Bescos, John Kaiser Calautit
Summary: This article provides a critical review of the performance of windcatchers, pointing out the current research gaps and issues, and proposing directions for further investigation and market prospects.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Solomon Boadu, Ebenezer Otoo
Summary: Despite Africa's vast energy resources, including wind energy, the continent faces challenges in developing its wind energy industry. Northern African countries and South Africa currently dominate the wind energy sector in Africa. To uplift Africa's socio-economic status, strong political will, supportive policies, and institutional frameworks are needed to drive the development of wind energy and overcome existing challenges.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
E. K. Grubbs, S. M. Gruss, V. Z. Schull, M. J. Gosney, M. V. Mickelbart, S. Brouder, M. W. Gitau, P. Bermel, M. R. Tuinstra, R. Agrawal
Summary: As the global population grows, the demand for food, energy, and water will increase significantly. However, limited land availability and competition for solar resources pose challenges to resource generation technologies. In the United States, both agriculture and solar energy production have adopted densification schemes to improve yields and energy output per unit of land. This research proposes an Agrivoltaic food and energy coproduction architecture that optimizes power generation while maintaining crop productivity by implementing ideal anti-tracking during critical growth periods. This technology offers a viable pathway for widespread solar implementation throughout the contiguous United States.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Han Shao, Rui Henriques, Hugo Morais, Elisabetta Tedeschi
Summary: The integration of offshore wind energy into the electric grid provides opportunities in terms of environmental sustainability and cost efficiency, but poses challenges to power quality. This survey offers a deeper understanding of disturbance detection and classification tools, exploring root causes, disturbance locations, and algorithmic solutions. It highlights synchronized waveform measurement and discusses evaluation metrics for detection and classification algorithms. Additionally, a novel system-wide monitoring framework is proposed.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Eleni Davidson, Yair Schwartz, Joe Williams, Dejan Mumovic
Summary: A continued upward trend in global greenhouse gas emissions poses risks to global infrastructure and built assets. Maintaining high indoor environmental quality standards is a challenge for higher education institutions under future climates. Passive cooling mechanisms may be insufficient to tolerate predicted temperature increases. Different building typologies have varying energy demand projections.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
Kexin Pang, Jian Zhou, Stamatis Tsianikas, David W. Coit, Yizhong Ma
Summary: This study proposes a new framework for long-term microgrid expansion planning, using deep reinforcement learning method to consider various uncertainties and constraints. The framework aims to enhance the effectiveness of microgrid expansion planning from the perspectives of economy, resilience, and greenhouse gas emission reduction.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
Jun Zhao, Kangyin Dong, Xiucheng Dong
Summary: The continuous growth of global electricity penetration has provided modern energy for alleviating energy poverty, but its impact on carbon neutrality has been overlooked. The research reveals that clean electricity from traditional fossil energy and renewable energy has a positive influence on the greenhouse effect. Eradicating energy poverty can effectively alleviate the greenhouse effect, especially in non-Belt and Road Initiative (B&RI) nations.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Hossein Shahbeik, Hamed Kazemi Shariat Panahi, Mona Dehhaghi, Gilles J. Guillemin, Alireza Fallahi, Homa Hosseinzadeh-Bandbafha, Hamid Amiri, Mohammad Rehan, Deepak Raikwar, Hannes Latine, Bruno Pandalone, Benyamin Khoshnevisan, Christian Sonne, Luigi Vaccaro, Abdul-Sattar Nizami, Vijai Kumar Gupta, Su Shiung Lam, Junting Pan, Rafael Luque, Bert Sels, Wanxi Peng, Meisam Tabatabaei, Mortaza Aghbashlo
Summary: This review explores the production of biocrude oil from biomass feedstocks through the process of hydrothermal liquefaction (HTL). It discusses the impact of process parameters on the quality, quantity, cost, and environmental impacts of biofuels. The review also highlights the challenges and prospects for the future development of biocrude oil.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
Meysam Majidi Nezhad, Mehdi Neshat, Georgios Sylaios, Davide Astiaso Garcia
Summary: Digital twins promise innovation for the marine renewable energy sector by using modern technological advances and the existing maritime knowledge frameworks. This research presents critical aspects of digital twin implementation challenges in marine energy digitalization approaches that use and combine data systems.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
Yeganeh Sharifian, Hamdi Abdi
Summary: This paper discusses the background and objectives of the multi-area economic dispatch problem, as well as various techniques and methods applied in this field. It also covers comprehensive formulations of the problem and important issues in the field of probabilistic MAED, along with some related concepts and suggestions.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
J. G. B. Churchill, V. B. Borugadda, A. K. Dalai
Summary: The increasing global energy demand and the need to reduce fossil fuel reliance have created a demand for renewable and sustainable fuel sources. This review explores the potential of tall oil, a by-product of the pulping industry, as a feedstock for biofuels. The review provides an overview of tall oil production, purification, and treatment, and investigates recent trends and barriers towards tall oil-derived biofuels.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
David C. Broadstock, Xiangnan Wang
Summary: This study provides a general review of research on district cooling, identifying key topics and themes and highlighting potential research priorities for future studies.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
L. Scharnhorst, D. Sloot, N. Lehmann, A. Ardone, W. Fichtner
Summary: This study investigates and analyzes the barriers to demand response in industrial and commercial sectors, highlighting their significance. Concerns about diminished product quality, disruptions to production processes, human resource management, and revenue uncertainty are identified as the most frequently cited barriers. Overcoming these barriers requires bridging knowledge gaps, allocating sufficient resources, and adapting external incentives and policies.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Review
Green & Sustainable Science & Technology
Tong Feng, Yuechi Sun, Yating Shi, Jie Ma, Chunmei Feng, Zhenni Chen
Summary: Air pollution is a significant global challenge, and policymakers have implemented policies to reduce it. Evaluating the effectiveness of these policies is critical, and our study reveals trends and gaps in air pollution policy research. We found that research has shifted from focusing solely on air pollutants to including methodologies, policies, and health implications. China has emerged as a major contributor in this field of research.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)