Article
Energy & Fuels
Noah D. Athens, Jef K. Caers
Summary: This study investigates the impact of data and model uncertainty on gravity interpretation in geothermal exploration, using a stochastic approach to analyze gravity data from Dixie Valley geothermal field. Sparse data sampling is shown to affect inversion results, with high data density areas showing more consistent results compared to low data density areas. Data uncertainty has a marked impact on depth-to-basement estimates and modeled fault locations, highlighting the importance of considering uncertainty in geothermal exploration modeling.
Article
Acoustics
William F. Jenkins, Peter Gerstoft, Yongsung Park
Summary: This paper proposes a sample-efficient sequential Bayesian optimization strategy for source localization with a geoacoustic model. By modeling the objective function as a Gaussian process surrogate model and using a heuristic acquisition function, the proposed method can converge on optimal solutions rapidly.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2023)
Article
Computer Science, Artificial Intelligence
Myeonginn Kang, Seokho Kang
Summary: Quantifying prediction uncertainty in neural networks is crucial and can be achieved by building specialized models or using surrogate measures. This study proposes a surrogate approach that quantifies prediction uncertainty without using training data. The proposed surrogate measures capture sensitivity and are effective in estimating prediction uncertainty in regression networks. The study demonstrates their effectiveness on nine regression datasets. © 2023 Elsevier B.V. All rights reserved.
APPLIED SOFT COMPUTING
(2023)
Article
Environmental Sciences
A. Trucchia, L. Frunzo
Summary: In this study, Global Sensitivity Analysis (GSA) and Uncertainty Quantification (UQ) were conducted on an ADM1-based Anaerobic Digestion Model focused on municipal solid waste digestion. The model introduced a surface-based kinetic approach to better model the disintegration step of complex organic matter. GSA and UQ were essential for further improvements and a deeper understanding of the main processes and input factors.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Chunwei Zhou, Gang Liu, Shengming Liao
Summary: Successful enhanced geothermal systems depend on fluid flow in fractured reservoir with good fissure connectivity. The study proposes a fuzzy inversion model to explore the location of the predominant flow area. The model achieves good inversion results, reduces dependence on initial guess area and property, and has good anti-interference ability.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Construction & Building Technology
Gangqiang Kong, Shuaijun Hu, Qing Yang
Summary: An accurate calculation of energy consumption is crucial for the design of underground metro stations. This study presents a simplified deterministic method that considers weather and heat gain uncertainty to evaluate the energy performance of metro stations. Monte Carlo technique was employed to confirm the probability distributions of load and energy demand and improve design robustness. Sensitivity analysis of input variables was conducted, and the simplified deterministic method proved to be more accurate in describing energy performance fluctuations compared to existing methods.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Computer Science, Interdisciplinary Applications
J. O. Campos, R. M. Guedes, Y. B. Werneck, L. P. S. Barra, R. W. dos Santos, B. M. Rocha
Summary: Cardiovascular diseases can affect the heart's biomechanical response, and personalized simulations provide new information about heart function. It is important to study the uncertainties and influential inputs in computational models for cardiac analysis, as well as find cost-effective alternatives for conducting these analyses.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Engineering, Multidisciplinary
Georgios Balokas, Benedikt Kriegesmann, Steffen Czichon, Raimund Rolfes
Summary: This study proposes an alternative method to efficiently simulate the nonlinear multiscale process for predicting the ultimate strength of textile composite materials. Results show strong interaction effects between uncertain parameters, and the method can be easily extended to other types of textiles and load cases.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Environmental Sciences
Francesca Pace, Anna Marti, Pilar Queralt, Alessandro Santilano, Adele Manzella, Juanjo Ledo, Alberto Godio
Summary: This study investigates the geoelectrical features of the Travale geothermal field in Italy using three-dimensional magnetotelluric data inversion. It presents the first resistivity model of the field and reveals the presence of deep elongated resistive bodies correlated with strike-slip tectonics. The findings provide new insights into the complex geothermal system of Travale.
Article
Physics, Multidisciplinary
Haozhi Li, Juan Zhao, Xiaokun Guo, Yu Cheng, Yanmin Xu, Xiaohui Yuan
Summary: In this paper, a sensitivity analysis method based on a Polynomial Chaos Expansion (PCE) surrogate model is proposed for flexoelectric materials. The mathematical expressions of the surrogate model for the flexoelectric materials are established by considering uncertain parameters, and the sensitivity expression is obtained through derivation. The validity and correctness of the proposed algorithm are demonstrated using numerical examples with the finite difference method (FDM).
FRONTIERS IN PHYSICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Shaoyi Cheng, Bisheng Wu, Ming Zhang, Xi Zhang, Yanhui Han, Robert G. Jeffrey
Summary: Hydraulic fracturing is widely used for enhancing conductivity of rock formations and increasing the rate of unconventional resource extraction. Uncertainties in completion operations and geomechanical parameter measurement may lead to large errors in fracture pattern prediction and parameter optimization. This paper presents a non-intrusive stochastic model that combines a hydraulic fracturing model with a surrogate model, allowing for uncertainty quantification. The model is validated against semi-analytical solutions and is used to investigate the impact of randomness in geomechanical and geometric parameters on fracture growth.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Energy & Fuels
Keiichi Ishizu, Yasuo Ogawa, Toru Mogi, Yusuke Yamaya, Toshihiro Uchida
Summary: The study examined the MT imaging of a deep conductor of supercritical fluids in the Kakkonda area of northeast Japan using numerical tests based on a conceptual resistivity model. The results showed that while the MT method was able to image the deep conductor of supercritical fluids, there were discrepancies in the shape and resistivity value of the imaged conductor compared to the true conductor. Specifically, it is important to note that the actual bottom part of a deep vertically elongated conductor may be wider in the horizontal direction than what is imaged by MT inversion.
Article
Engineering, Multidisciplinary
Linjun Zhong, Yang Yang, Leshi Shu, Ping Jiang, Hua Wei
Summary: The paper proposes a novel tolerance design method using a 'reverse model' and Kriging model to analyze robustness and reduce computational cost. It utilizes sensitivity region and interval uncertainty to describe tolerance range and employs a nested double-loop structure for the search process. The effectiveness of the method is demonstrated through numerical examples and an engineering case study.
JOURNAL OF ENGINEERING DESIGN
(2022)
Article
Green & Sustainable Science & Technology
Rahim Zahedi, Sareh Daneshgar, Mohammad Ali Nasle Seraji, Hamidreza Asemi
Summary: The study reveals the existence of a large geothermal system in the northwest of Delijan, Iran. Magnetometry methods were used to determine the magnetic anomalies caused by the geothermal structures in the area, and the depth and structural characteristics were estimated using the Euler method. Modeling and inversion results indicate a significant magnetic anomaly at a depth of 2500-5000 beneath the surface, interpreted as the source of the geothermal system.
Article
Computer Science, Interdisciplinary Applications
Hamid Taghavi Ganji, Elnaz Seylabi
Summary: This paper presents a variant of LSTM recurrent neural network for modeling and predicting the seismic response of buried structures to uncertain shear waves in heterogeneous soil profiles. The proposed model can accept uncertain input features and uses synthetic time histories for training to improve efficiency. The results demonstrate that this approach can effectively predict tunnel response at different locations and show high accuracy in forward uncertainty quantification and sensitivity analysis.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Geochemistry & Geophysics
Arben Pitarka, Robert Mellors
Summary: In order to improve 3D seismic-wave propagation modeling for frequencies up to 10 Hz, researchers estimated the statistical properties of small-scale velocity heterogeneities in the Yucca Flat basin by comparing observed and synthetic waveform cross correlations.
BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA
(2021)
Article
Geochemistry & Geophysics
Gene A. Ichinose, Sean R. Ford, Robert J. Mellors
Summary: Combining rotational motions with translational displacements improves the inference of radiation patterns in MT inversions.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2021)
Article
Multidisciplinary Sciences
Ziyan Li, Derek Elsworth, Chaoyi Wang, L. Boyd, Z. Frone, E. Metcalfe, A. Nieto, S. Porse, W. Vandermeer, R. Podgorney, H. Huang, T. McLing, G. Neupane, A. Chakravarty, P. J. Cook, P. F. Dobson, C. A. Doughty, Y. Guglielmi, C. Hopp, M. Hu, R. S. Jayne, S. E. Johnson, K. Kim, T. Kneafsey, S. Nakagawa, G. Newman, P. Petrov, J. C. Primo, M. Robertson, V. Rodriguez-Tribaldos, J. Rutqvist, M. Schoenball, E. L. Sonnenthal, F. A. Soom, S. Sprinkle, C. Ulrich, C. A. Valladao, T. Wood, Y. Q. Zhang, Q. Zhou, L. Huang, Y. Chen, T. Chen, B. Chi, Z. Feng, L. P. Frash, K. Gao, E. Jafarov, S. Karra, N. Makedonska, D. J. Li Li, R. Pawar, N. Welch, P. Fu, R. J. Mellors, C. E. Morency, J. P. Morris, C. S. Sherman, M. M. Smith, D. Templeton, J. L. Wagoner, J. White, H. Wu, J. Moore, S. Brown, D. Crandall, P. Mackey, T. Paronish, S. Workman, B. Johnston, K. Beckers, J. Weers, Y. Polsky, M. Maceira, C. P. Chai, A. Bonneville, J. A. Burghardt, J. Horner, T. C. Johnson, H. Knox, J. Knox, B. Q. Roberts, P. Sprinkle, C. E. Strickland, J. N. Thomle, V. R. Vermeul, M. D. White, D. Blankenship, M. Ingraham, T. Myers, J. Pope, P. Schwering, A. Foris, D. K. King, J. Feldman, M. Lee, J. Su, T. Baumgartner, J. Heise, M. Horn, B. Pietzyk, D. Rynders, G. Vandine, D. Vardiman, T. Doe, J. McLennan, Y. S. Wu, J. Miskimins, P. Winterfeld, K. Kutun, M. D. Zoback, A. Singh, R. N. Horne, K. Li, A. Hawkins, Y. Zhang, E. Mattson, D. Elsworth, K. J. Im, Z. Li, C. J. Marone, E. C. Yildirim, J. Ajo-Franklin, A. Ghassemi, D. Kumar, V. Sesetty, A. Vachaparampil, H. F. Wang, H. Sone, K. Condon, B. Haimson, W. Roggenthen, C. Medler, N. Uzunlar, C. Reimers, M. W. McClure
Summary: This study emphasizes the importance of understanding the mechanisms controlling fluid injection-triggered seismicity in order to mitigate the impact of earthquakes. By conducting experiments and observations, researchers proposed a new framework to define maximum event magnitudes as a function of pre-existing critical stresses and fluid injection volume.
NATURE COMMUNICATIONS
(2021)
Article
Engineering, Civil
Mingjie Chen, Ali Al-Maktoumi, Mohammad Mahdi Rajabi, Azizallah Izady, Hilal Al-Mamari, Jianchao Cai
Summary: In the past decade, feasibility of using CO2 as a working fluid for harvesting geothermal energy has been studied and demonstrated in North Oman. Depleting petroleum reservoirs in the area serve as excellent candidates for CO2 geological storage and geothermal reservoirs. The study provides quantitative guidance on site selection and geothermal field development in the region.
JOURNAL OF HYDROLOGY
(2021)
Article
Energy & Fuels
Mohammad Mahdi Rajabi, Mingjie Chen, Ali Bozorgpour, Ali Al-Maktoumi, Azizallah Izady
Summary: This study aims to analyze the techno-economic feasibility of CO2-circulated geothermal production in a closed reservoir system, specifically focusing on the unique geothermal reservoir conditions found in the foreland basin of North Oman. The findings suggest that the proposed triplet horizontal well placement is technically feasible and economically viable for harvesting low-enthalpy geothermal energy from depleted reservoirs in the North Oman region.
Article
Geosciences, Multidisciplinary
Ate Visser, Edward Kwicklis, Irene Farnham, Andrew F. B. Tompson, Ronald L. Hershey
Summary: This study analyzed groundwater samples from Pahute Mesa in Nevada, USA, using noble gases to infer groundwater recharge temperatures and provide evidence of groundwater flow patterns. The findings suggest that most recharge in the area occurred under cooler conditions than present, except near major drainages where ephemeral runoff still recharges shallow groundwater.
HYDROGEOLOGY JOURNAL
(2022)
Article
Optics
Gregory Krueper, Charles Yu, Stephen B. Libby, Robert Mellors, Lior Cohen, Juliet T. Gopinath
Summary: This study presents a model of a fiber-based Mach-Zehnder interferometer using Holland-Burnett entangled states to enhance sensitivity. The predicted result shows that a phase sensitivity 28% beyond the shot noise limit is achievable with current technology, and the TMSV source can provide about 25 times more photon flux than other entangled sources. This system will make fiber-based quantum-enhanced sensing accessible and practical for remote sensing and probing photosensitive materials.
Review
Environmental Sciences
Patrick Amoatey, Azizallah Izady, Ali Al-Maktoumi, Mingjie Chen, Issa Al-Harthy, Khalifa Al-Jabri, Titus A. M. Msagati, Thabo T. I. Nkambule, Mahad Said Baawain
Summary: Evaporation ponds are a cost-effective and simple wastewater treatment technology, but their operational limitations can have negative impacts on the environment. Studies have shown that contaminants released from evaporation ponds include heavy metals, pesticides, impacting human health and fauna, but limited data is available on health risks associated with occupational and environmental exposure.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Multidisciplinary Sciences
Robin S. Matoza, David Fee, Jelle D. Assink, Alexandra M. Iezzi, David N. Green, Keehoon Kim, Liam Toney, Thomas Lecocq, Siddharth Krishnamoorthy, Jean-Marie Lalande, Kiwamu Nishida, Kent L. Gee, Matthew M. Haney, Hugo D. Ortiz, Quentin Brissaud, Leo Martire, Lucie Rolland, Panagiotis Vergados, Alexandra Nippress, Junghyun Park, Shahar Shani-Kadmiel, Alex Witsil, Stephen Arrowsmith, Corentin Caudron, Shingo Watada, Anna B. Perttu, Benoit Taisne, Pierrick Mialle, Alexis Le Pichon, Julien Vergoz, Patrick Hupe, Philip S. Blom, Roger Waxler, Silvio De Angelis, Jonathan B. Snively, Adam T. Ringler, Robert E. Anthony, Arthur D. Jolly, Geoff Kilgour, Gil Averbuch, Maurizio Ripepe, Mie Ichihara, Alejandra Arciniega-Ceballos, Elvira Astafyeva, Lars Ceranna, Sandrine Cevuard, Il-Young Che, Rodrigo De Negri, Carl W. Ebeling, Laslo G. Evers, Luis E. Franco-Marin, Thomas B. Gabrielson, Katrin Hafner, R. Giles Harrison, Attila Komjathy, Giorgio Lacanna, John Lyons, Kenneth A. Macpherson, Emanuele Marchetti, Kathleen F. McKee, Robert J. Mellors, Gerardo Mendo-Perez, T. Dylan Mikesell, Edhah Munaibari, Mayra Oyola-Merced, Iseul Park, Christoph Pilger, Cristina Ramos, Mario C. Ruiz, Roberto Sabatini, Hans F. Schwaiger, Dorianne Tailpied, Carrick Talmadge, Jerome Vidot, Jeremy Webster, David C. Wilson
Summary: The eruption of the Hunga volcano in Tonga on 15 January 2022 caused an explosion in the atmosphere, generating a range of atmospheric waves that were observed globally. The eruption produced significant infrasound, audible sound, and ionospheric perturbations, and contributed to the occurrence of tsunamis. The exceptional observations of the atmospheric waves are highlighted in this study.
Article
Geochemistry & Geophysics
Jonathan Ajo-Franklin, Veronica Rodriguez Tribaldos, Avinash Nayak, Feng Cheng, Robert Mellors, Benxin Chi, Todd Wood, Michelle Robertson, Cody Rotermund, Eric Matzel, Dennise C. Templeton, Christina Morency, Kesheng Wu, Bin Dong, Patrick Dobson
Summary: This report describes a large-scale distributed acoustic sensing (DAS) recording study in the Imperial Valley, aiming to evaluate DAS as a tool for geothermal exploration and monitoring. The study utilizes a 27 km array to acquire high-density seismic data and record local seismic events and ambient noise. The report provides installation information, noise characteristics, and metadata for future research.
SEISMOLOGICAL RESEARCH LETTERS
(2022)
Article
Engineering, Environmental
Ruqaya Al-Syabi, Azizallah Izady, Mahad Said Baawain, Abdullah Al-Mamun, Mingjie Chen
Summary: Management of municipal solid waste leachate has become a pressing environmental issue in many countries due to population growth and consumption trends. This study explores the simultaneous application of advanced oxidation processes (AOPs) for the treatment of municipal solid waste leachate, demonstrating their effectiveness in reducing organic compounds. Results show that combining different AOPs methods leads to significantly higher removal efficiencies compared to individual applications.
JOURNAL OF ENVIRONMENTAL ENGINEERING AND SCIENCE
(2022)
Article
Engineering, Civil
Mohammad Mahdi Rajabi, Mingjie Chen, Mohammad Reza Hajizadeh Javaran, Ali Al-Maktoumi, Azizallah Izady, Yanhui Dong
Summary: This study develops a simulation-optimization algorithm that considers both the sequestration and circulation stages of a CO2 plume geothermal system in choosing optimal well location and operations. By minimizing the probability of negative net present value and considering economic factors, the study provides insights into the profitability and risk of non-profitability of the proposed system.
JOURNAL OF HYDROLOGY
(2022)
Article
Geochemistry & Geophysics
Gene A. Ichinose, Robert J. Mellors, Justin G. Barno, Rengin Gok
Summary: From a direct comparison between array derived dynamic strain rate (ADDS) and distributed acoustic sensing (DAS) strain rate, it was found that they are coherent for frequencies less than or equal to 1 Hz, but this correlation decays quickly for higher frequencies.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2022)
Article
Computer Science, Interdisciplinary Applications
Chih-Chieh Chien, William F. Jenkins II, Peter Gerstoft, Mark Zumberge, Robert Mellors
Summary: This study investigates the relationship between fluid injection in enhanced geothermal systems and induced seismicity from hydraulic fracturing using unsupervised machine learning. Spectrograms of the detected signals are dimensionally reduced to a lower-dimensional latent feature space with a deep neural network called autoencoder. Gaussian mixture model clustering is then performed on this feature space to assign each signal to one of 7 classes. The results show bimodal spatiotemporal distributions, with a shallow mode occurring between 250 and 500 m and a deep mode centered around 750 m. The correlation between the clustered signal classes and injection-related activities is weak or non-existent. This study demonstrates the capability to analyze not only when and where signals are detected, but also their types, facilitating rapid and targeted data exploration and providing insights into source mechanisms.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Geochemistry & Geophysics
Feng Cheng, Jonathan B. Ajo-Franklin, Avinash Nayak, Veronica Rodriguez Tribaldos, Robert Mellors, Patrick Dobson
Summary: We utilize distributed acoustic sensing (DAS) and ambient noise interferometry to image the geothermal reservoirs in Imperial Valley, California, using unlit fiber-optic telecommunication infrastructure (dark fiber). By applying ambient noise interferometry to DAS records, we obtain a high-resolution two-dimensional (2D) S wave velocity (V-s) structure to a depth of 3 km. We discover a high V-s and low V-p/V-s ratio feature beneath the Brawley geothermal system, indicating hydrothermal mineralization and lower porosity.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2023)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
