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Data-driven modeling and fast adjustment for digital coded metasurfaces database: Application in adaptive electromagnetic energy harvesting Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Cheng Liu, Wei Wang, Zhixia Wang, Bei Ding, Zhiqiang Wu, Jingjing Feng
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Uncertainties in the technological pathway towards low-carbon freight transport under carbon neutral target in China Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Biying Yu, Jin-Xiao Tan, Shitong Zhang
The freight transport sector is a critical sector for achieving carbon peak and carbon neutrality targets. However, there are many uncertainties regarding the e-commerce development, promotion speed of low-carbon measures, and freight transport technologies. Existing research lacks considering the multiple uncertainties on the low-carbon technological pathway for freight transport. Consequently, a
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Experimental study on thermoelectric characteristics of intermediate fluid thermoelectric generator Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Yulong Zhao, Guoyin Zhang, Lei Wen, Shixue Wang, Yulin Wang, Yanzhe Li, Minghui Ge
Thermoelectric technology plays a crucial role in harnessing waste heat from automobile exhaust, and developing low-resistance and high-efficiency thermoelectric generator is currently a focal point of research. The intermediate fluid thermoelectric generator (IFTEG) introduces a structural modification to conventional designs by utilizing boiling-condensation heat transfer of the intermediate fluid
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Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Hongjie Jia, Xiaoyu Wang, Xiaolong Jin, Lin Cheng, Yunfei Mu, Xiaodan Yu, Wei Wei
Buildings are typically integrated with multiple distributed energy resources (DERs), enabling them to act as building prosumers engaged in both energy production and consumption. Peer-to-peer (P2P) energy trading among building prosumers is crucial to improve their benefits. However, further exploration is required to balance the benefits between building prosumers and the system operator (e.g., the
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Stable Cuδ+ species - Catalyzed CO₂ hydrogenation to methanol in silanol nests on Cu/S-1 catalyst Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Zhengxing Cui, Yeqing Wang, Peipei Zhang, Song Lu, Yuxuan Chen, Xiaotao Yu, Min Guo, Tiancun Liu, Jiadi Ying, Qi Shen, Yinying Jin, Zhixin Yu
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Performance uniformity analysis in polymer electrolyte fuel cell using long-term dynamic simulation Appl. Energy (IF 11.2) Pub Date : 2024-04-24 S. Culubret, M.A. Rubio, D.G. Sanchez, A. Urquia
The temporal stability and spatial homogeneity of current density are key factors in Polymer Electrolyte Fuel Cell (PEFC) performance and durability. Temporal and spatial variations of relative humidity, fuel concentration, and water droplets in the channels are the principal causes of non-homogeneous current density. A dynamic pseudo-3D model was previously proposed by the authors and has been extended
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Frequency varying heating strategy for lithium-ion battery rapid preheating under subzero temperature considering the limitation of on-board current Appl. Energy (IF 11.2) Pub Date : 2024-04-24 Junqiu Li, Qiao Xue, Zhuo Gao, Zengcheng Liu, Yansheng Xiao
The electrical performance of lithium-ion battery gradually deteriorates with the temperature decrease. Alternating current (AC) heating is an efficient manner to improve the lithium-ion battery (LIB) discharge ability at low temperature. This paper proposes an effective method to quickly preheat battery under low temperature based on sinusoidal AC. An electrothermal coupled model is established to
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Recent advancements in the application of electrospun nanofibers for carbon dioxide capture and utilization Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Yifu Li, Zhien Zhang, Yunqiao Huang, Yi Zhang, Sivaraju Akula
The escalating CO emissions in recent years underlined the need for advanced Carbon Capture and Utilization (CCU) technologies. This context has spurred the exploration of novel materials for promoting CCU efficiency, among which electrospun nanofibers have emerged as a promising candidate. Electrospinning coupled with various post-treatment (such as heat-treating, in-situ growth, selective removal
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Behaviours of methane metabolism and community dynamics of methane anaerobic oxidation microbes on carbonate rocks with long-term cultivation in cold seep environment Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Cun Li, Jing-Chun Feng, Xiao Chen, Yingli Zhou, Jianzhen Liang, Si Zhang
The anaerobic oxidation of methane (AOM) and sulfate reduction processes in cold seep environments can control methane emission sources and thus mitigate the pressure of increasing global greenhouse gas concentrations. The surfaces of carbonate rocks in cold seep host an abundance of microorganisms that participate in AOM reactions. Investigating the metabolism and conversion of methane by these microbes
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Interfacial structuring of Mn[sbnd]N and Mn[sbnd]C bonds by defect engineering for high-performance Zn-Mn battery Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Shengen Gong, Jiaxin Zhao, Kaisheng Sun, Xiaoteng Jia, Danming Chao
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Research and development of innovative bidirectional control plate valve for reciprocating compressor Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Weilin Cui, Dexi Wang, Xiao Hong, Dajing Liu, Xinrui Fu, Shengdong Li
Currently, the reciprocating compressor valve operates on a single working principle, where the valve structure relies on the combined force of its own elasticity and gas thrust to drive the movement of the valve disc, and continues to open and close in the way of impact. Due to the defects of the conventional plate valve, such as delayed opening, premature closing, and insufficient full opening time
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An ecological input-output CGE model for unveiling CO2 emission metabolism under China's dual carbon goals Appl. Energy (IF 11.2) Pub Date : 2024-04-23 P.P. Wang, G.H. Huang, Y.P. Li, Y.Y. Liu, Y.F. Li
Carbon mitigation is essential for combating climate change and its impacts, safeguarding ecosystems, and protecting human health and livelihoods. This study develops an ecological input-output CGE (EIOC) model that integrates computable general equilibrium (CGE) model, input-output analysis (IOA), and ecological network analysis (ENA) to explore the evolution of the CO emission metabolism under long-term
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Multi-source domain transfer learning with small sample learning for thermal runaway diagnosis of lithium-ion battery Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Chenchen Dong, Dashuai Sun
Data-driven thermal runaway diagnosis based on small amounts of thermal runaway data often struggles to produce satisfactory accuracy. However, in actual application scenarios, obtaining real thermal runaway data has a high cost. To this end, we propose a diagnostic method for multi-source domain transfer learning with few-shot learning (MDTL-FSL), which combines the ideas of small sample learning
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Projecting the future fine-resolution carbon dioxide emissions under the shared socioeconomic pathways for carbon peak evaluation Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Dan Ding, Xiaoping Liu, Xiaocong Xu
Projecting future urban CO emissions is of paramount importance in comprehending and addressing climate change, as well as evaluating the impact of various policies on future greenhouse gas emissions. While previous studies on projecting CO emissions have primarily focused on large administrative scales, fine-resolution mapping of CO emissions is also vital for identifying CO emission hotspots and
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Green energy transition in OECD region through the lens of economic complexity and environmental technology: A method of moments quantile regression perspective Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Mohammad Razib Hossain, Devi Prasad Dash, Narasingha Das, Ehsan Ullah, Md. Emran Hossain
Despite having multidimensional positive externalities of renewable energy (RE) in theory, the literature on RE's economic and environmental determinants is still very nascent. We have addressed this research gap by considering a balanced panel of 38 OECD nations attempting a phase-by-phase energy transition. We have used data spanning from 2000 to 2020 and deployed the novel method of moments quantile
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Estimation of maximum photovoltaic cover ratios in greenhouses based on global irradiance data Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Natalie Hanrieder, Anna Kujawa, Ana Bendejacq Seychelles, Manuel Blanco, José Carballo, Stefan Wilbert
In this study, a method for estimating the maximum PV (photovoltaic) cover ratio for plastic greenhouses based on various years of global horizontal irradiance (GHI) data is presented and illustrated with an exemplary site in southeastern Spain. CAMS (Copernicus Atmosphere Monitoring Service) GHI data from 2005 to 2023 were analyzed to estimate the DLI (daily light integral) inside the greenhouses
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Hierarchical control strategy of wind-storage frequency support for SOC recovery optimization and arbitrage revenue Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Ming Pei, Qiheng Wang, Lin Ye, Yadi Luo, Licheng Sha, Zaichi Zhang, Xuri Song
With the continuous increase in the penetration rate of renewable energy, the frequency stability of the power system is gradually declining. Hence, this paper proposes a hierarchical coordinated control strategy of the wind farm (WF) and the battery energy storage system (BESS) to provide frequency support. The strategy includes the upper-layer frequency regulation (FR) optimization strategy and the
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Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave Appl. Energy (IF 11.2) Pub Date : 2024-04-23 Zhang Huanqiang, Gao Xiaoxia, Lu Hongkun, Zhao Qiansheng, Zhu Xiaoxun, Wang Yu, Zhao Fei
Accurate prediction of the wake is conducive to achieving the safe and efficient operation of large-scale offshore floating wind turbines. To further understand the wake characteristics of large-scale offshore floating wind turbine, a three-dimensional wake model with the consideration of wind and wave interaction is proposed and verified in this paper. The unique motion response characteristics of
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Quantifying the air pollution impacts on solar photovoltaic capacity factors and potential benefits of pollution control for the solar sector in China Appl. Energy (IF 11.2) Pub Date : 2024-04-22 Zhe Song, Sunliang Cao, Hongxing Yang
Solar photovoltaic (PV) plays a crucial role in China's energy transition. However, air pollution diminishes solar radiation resources, thereby reducing PV power generation efficiency. This study aims to quantify the impacts of air pollution on PV capacity factors in China while emphasizing the geographically specific potential benefits of improved air quality for the future PV sector. Using a PV power
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Re-dispatch simplification analysis: Confirmation holism and assessing the impact of simplifications on energy system model performance Appl. Energy (IF 11.2) Pub Date : 2024-04-22 Nicholas Gorman, Iain MacGill, Anna Bruce
Confirmation holism presents a serious but little-discussed challenge for testing energy system models using historical datasets. Confirmation holism is the thesis that no individual theory can be tested in isolation, but rather testing a theory relies on supporting axillary theories, and the primary and axillary theories can only be tested as a whole. The problem arises when using fit to historical
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Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities Appl. Energy (IF 11.2) Pub Date : 2024-04-22 Boqiang Lin, Chongchong Xu
Industrial intelligence optimizes resource allocation and enhances productivity, but discussions on its potential to empower green growth are inadequate. Utilizing panel data for 279 Chinese cities from 2008 to 2019, this study investigates the effect of industrial intelligence on urban energy-environmental performance. The findings reveal that industrial intelligence enhances urban energy-environmental
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Flexible industrial power-to-X production enabling large-scale wind power integration: A case study of future hydrogen direct reduction iron production in Finland Appl. Energy (IF 11.2) Pub Date : 2024-04-22 Robert Weiss, Jussi Ikäheimo
Hydrogen Direct Reduction of Iron (HDRI) combined with renewable electricity is an attractive option for low-carbon steel production. In this paper, we present a novel and computationally efficient techno-economic power-to-x-plant optimization model which is then applied to an HDRI plant located in Finland. Plant dimensioning was carried out in several current and future power market and regulatory
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Dynamic-stall-driven vertical axis wind turbine: An experimental parametric study Appl. Energy (IF 11.2) Pub Date : 2024-04-22 David Keisar, Idan Arava, David Greenblatt
Dynamic stall on the blades of low-solidity vertical axis wind turbines (VAWTs) is a major problem due to its adverse effects on performance, drive-train components, and generator sizing. However, when the turbine chord-to-radius ratios are relatively large, greater than approximately 0.5, counterintuitively, dynamic stall can be harnessed to produce useful torque. To examine this seeming contradiction
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A pendulum-based rotational energy harvester for self-powered monitoring of rotating systems in the era of industrial digitization Appl. Energy (IF 11.2) Pub Date : 2024-04-21 Sayed Nahiyan Masabi, Hailing Fu, James A. Flint, Stephanos Theodossiades
Wireless condition monitoring of rotating systems, including vehicle powertrains and wind turbines, is a key for continuously assessing the operational performance in the era of industrial digitization. However, one of their major challenges revolve around the dependence on power supply from batteries. Hence, this paper presents the concept, theoretical model, and experimental study of a pendulum-based
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Water transport in PEMFC with metal foam flow fields: Visualization based on AI image recognition Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Qifeng Li, Kai Sun, Mengshan Suo, Zhen Zeng, Chengshuo Guan, Huaiyu Liu, Zhizhao Che, Tianyou Wang
Water transport is an essential process in proton exchange membrane fuel cells (PEMFC). For the novel metal foam flow fields, water transport is difficult to be visualized and still remains inadequately understood. In this work, for the first time, the two-phase flows in the metal foam flow fields of a transparent PEMFC was visualized by using an artificial intelligence (AI) image recognition method
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Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Fatemeh Negar Irani, Mohammadjavad Soleimani, Meysam Yadegar, Nader Meskin
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Evaluating the efficiency and cost-effectiveness of RPB-based CO2 capture: A comprehensive approach to simultaneous design and operating condition optimization Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Howoun Jung, Nohjin Park, Jay H. Lee
Despite ongoing global initiatives to reduce CO emissions, implementing large-scale CO capture using amine solvents is fraught with economic uncertainties and technical hurdles. The Rotating Packed Bed (RPB) presents a promising alternative to traditional packed towers, offering compact design and adaptability. Nonetheless, scaling RPB processes to an industrial level is challenging due to the nascent
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A blockchain-based optimal peer-to-peer energy trading framework for decentralized energy management with in a virtual power plant: Lab scale studies and large scale proposal Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Khandoker Shahjahan Alam, A.M.A. Daiyan Kaif, Sajal K. Das
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Switched reluctance motor based water pumping system powered by solar using hybrid approach Appl. Energy (IF 11.2) Pub Date : 2024-04-20 G. Sundari, R. Muniraj, J. Shanmugapriyan
This paper proposes a hybrid approach for switched reluctance motor (SRM) based water pumping system. The proposed hybrid method is combination of both the Northern Goshawk Optimization (NGO) and Finite Basis Physics-Informed Neural Networks (FBPINNs). Hence, it is named as NGO-FBPINNs. The NGO method is employed to better control among the three level boost converter (TLBC) and FBPINNs is predict
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ApplianceFilter: Targeted electrical appliance disaggregation with prior knowledge fusion Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Dong Ding, Junhuai Li, Huaijun Wang, Kan Wang, Jie Feng, Ming Xiao
In smart home services, non-intrusive load monitoring (NILM) can reveal individual appliances’ power consumption from the aggregate power and requires only one measurement point at the entrance by a smart meter. Most of the existing load disaggregation methods are based on deep and complex neural networks, and excessively long input sequences could increase the model disaggregation time. Meanwhile
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System-cost-minimizing deployment of PV-wind hybrids in low-carbon U.S. power systems Appl. Energy (IF 11.2) Pub Date : 2024-04-20 Patrick R. Brown, Travis Williams, Maxwell L. Brown, Caitlin Murphy
Hybridization of solar photovoltaic (PV) and wind installations has the potential to reduce transmission costs through sharing of spur-line capacity and other interconnection cost components. Many studies have assessed hybridization opportunities on a site-by-site basis but have not captured the impact of PV-wind hybridization on overall power system evolution and system costs. Here, we use a high-resolution
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Day-ahead Numerical Weather Prediction solar irradiance correction using a clustering method based on weather conditions Appl. Energy (IF 11.2) Pub Date : 2024-04-19 Weijing Dou, Kai Wang, Shuo Shan, Chenxi Li, Yiye Wang, Kanjian Zhang, Haikun Wei, Victor Sreeram
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Data-driven Koopman model predictive control for hybrid energy storage system of electric vehicles under vehicle-following scenarios Appl. Energy (IF 11.2) Pub Date : 2024-04-19 Bin Chen, Miaoben Wang, Lin Hu, Guo He, Haoyang Yan, Xinji Wen, Ronghua Du
In the current studies on energy management strategy (EMS) for vehicle-following scenarios, the accuracy of vehicle state predictions based on mechanistic models is influenced by the time-varying conditions, affecting the optimization control performance. To address this issue, a data-driven Koopman model predictive control for hybrid energy storage system (HESS) of electric vehicles (EVs) in vehicle-following
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Energy management for scalable battery swapping stations: A deep reinforcement learning and mathematical optimization cascade approach Appl. Energy (IF 11.2) Pub Date : 2024-04-19 Yongxin Su, Shuaixian Yue, Lei Qiu, Jie Chen, Rui Wang, Mao Tan
The rapid growth of electric vehicles is driving the expansion of scalable Battery Swapping Stations (BSSs) to meet the demand for fast charging. However, existing BSS energy management struggles to adapt to the changes in battery counts online, the uncertainty of electricity prices and battery demand, as well as the complexity of demand response (DR). To address these issues, we propose a cascading
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Smart generation system: A decentralized multi-agent control architecture based on improved consensus algorithm for generation command dispatch of sustainable energy systems Appl. Energy (IF 11.2) Pub Date : 2024-04-19 Yue Quan, Lei Xi
The sustainable energies take increasing proportion in the power systems due to the “net-zero emission” goal, and the future trend is to make the new type power systems operate safely and stably while maintaining low carbon and economic efficiency. This paper proposes a novel smart generation system (SGS) architecture and a smart generation system consensus (SGSC) algorithm from the perspective of
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Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case Appl. Energy (IF 11.2) Pub Date : 2024-04-18 Jiarui Zhang, Yunfei Mu, Zhijun Wu, Hongjie Jia, Xiaolong Jin, Yan Qi
The increasing penetration of renewable energy generation brings about variability and randomness, which poses challenges to the power systems due to a potential shortage of flexibility resources. Inverter heat pumps (IHPs) can be utilized to address this issue by providing flexible ramping capacity (FRC). However, unlike conventional generation that offers a fixed FRC, the FRC of individual IHPs and
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Emergy analysis and comprehensive sustainability investigation of a solar-aided liquid air energy storage system based on life cycle assessment Appl. Energy (IF 11.2) Pub Date : 2024-04-18 Xingqi Ding, Yufei Zhou, Nan Zheng, Umberto Desideri, Liqiang Duan
Recently, the solar-aided liquid air energy storage (LAES) system is attracting growing attention due to its eco-friendliness and enormous energy storage capacity. Although researchers have proposed numerous innovative hybrid LAES systems and conducted analyses around thermodynamics, economics, and dynamic characteristics, very few studies have involved emergy analysis and sustainability assessment
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Optimal sizing of an off-grid and grid-connected hybrid photovoltaic-wind system with battery and fuel cell storage system: A techno-economic, environmental, and social assessment Appl. Energy (IF 11.2) Pub Date : 2024-04-18 Mahamat Adoum Abdoulaye, Sebastian Waita, Cyrus Wabuge Wekesa, Julius Mwakondo Mwabora
On the social index of access to clean energy, the country of CHAD is one of the least electrified in the world and the last in Sub-Saharan Africa (SSA), with only 11.3% of its population having electricity access. The access is considerably lower in rural areas of CHAD (1.3%), meaning that 98.7% of the Chadian rural population currently depends on the unsustainable and polluting fuels such as wood
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Persistence of disaggregate energy RD&D expenditures in top-five economies: Evidence from artificial neural network approach Appl. Energy (IF 11.2) Pub Date : 2024-04-18 Abdullah Emre Caglar, Muhammet Daştan, Salih Bortecine Avci
The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions
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Production capacity prediction based response conditions optimization of straw reforming using attention-enhanced convolutional LSTM integrating data expansion Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Yongming Han, Zhiyi Li, Tingting Wei, Xiaoyu Zuo, Min Liu, Bo Ma, Zhiqiang Geng
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Quantile-based heterogeneous effects of nuclear energy and political stability on the environment in highly nuclear energy-consuming and politically stable countries Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Mustafa Tevfik Kartal, Serpil Kılıç Depren, Fatih Ayhan, Talat Ulussever
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Multi-objective optimization of protonic ceramic electrolysis cells based on a deep neural network surrogate model Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Zheng Li, Jie Yu, Chen Wang, Idris Temitope Bello, Na Yu, Xi Chen, Keqing Zheng, Minfang Han, Meng Ni
Protonic ceramic electrolysis cell (PCEC) stands out as a promising device to realize large-scale green hydrogen production. This research is dedicated to advancing the optimization of PCEC, specifically targeting key performance indicators including voltage, current density, and Faradaic efficiency (FE). The central aim is the expeditious determination of optimal trade-off points that harmonize electrochemical
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Novel virtual sensors development based on machine learning combined with convolutional neural-network image processing-translation for feedback control systems of internal combustion engines Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Ratnak Sok, Arravind Jeyamoorthy, Jin Kusaka
Physical sensors are commonly used to record performance data of internal combustion engines (ICEs) for online feedback control and calibration, but they are prone to diagnostic and increased development costs. Lookup tables are commonly used in conventional calibration and feedback control; however, the table parameters increase with the advancement of ICE technologies under transient operations.
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An mechanical/thermal analytical model for prismatic lithium-ion cells with silicon‑carbon electrodes in charge/discharge cycles Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Zhiliang Huang, Huaixing Wang, Zhouwang Gan, Tongguang Yang, Cong Yuan, Bing Lei, Jie Chen, Shengben Wu
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Solar irradiance time series forecasting using auto-regressive and extreme learning methods: Influence of transfer learning and clustering Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Milan Despotovic, Cyril Voyant, Luis Garcia-Gutierrez, Javier Almorox, Gilles Notton
Solar resource forecasting is essential for an optimal energy management in smart grids using photovoltaic (PV) production. For many sites and for short time horizons (nowcasting), approaches based on the use of time series and statistical or Artificial Intelligence methods are often preferred. These methods require a long historical time series of solar radiation not always available. A practical
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Superhydrophobic multi-shell hollow microsphere confined phase change materials for solar photothermal conversion and energy storage Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Jiyan Li, Yong Long, Yanju Jing, Jiaqing Zhang, Silu Du, Rui Jiao, Hanxue Sun, Zhaoqi Zhu, Weidong Liang, An Li
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Physics-informed machine learning for noniterative optimization in geothermal energy recovery Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Bicheng Yan, Manojkumar Gudala, Hussein Hoteit, Shuyu Sun, Wendong Wang, Liangliang Jiang
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Battery electric vehicle charging in China: Energy demand and emissions trends in the 2020s Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Hong Yuan, Minda Ma, Nan Zhou, Hui Xie, Zhili Ma, Xiwang Xiang, Xin Ma
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Customer satisfaction at large charging parks: Expectation-disconfirmation theory for fast charging Appl. Energy (IF 11.2) Pub Date : 2024-04-17 Jessica Bollenbach, Stephanie Halbrügge, Lars Wederhake, Martin Weibelzahl, Linda Wolf
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Variational quantum circuit based demand response in buildings leveraging a hybrid quantum-classical strategy Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Akshay Ajagekar, Fengqi You
To counter the significant contribution of buildings to global energy consumption and greenhouse gas emissions, participation in demand response programs incentivizes grid-interactive buildings to curtail their load demand and promote energy efficiency with environmental sustainability. Quantum computing has the potential to impact problems at various scales, including demand response in buildings
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Energy technical resilience assessment based on complex network analysis – A case study of China Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Rui Su, Bin Chen, Saige Wang, Cuncun Duan
China's energy transformation has been accompanied by potential energy security issues. However, the influence degree and driving mechanism behind this phenomenon remain unclear. In this paper, we developed a complex network-based technical resilience assessment framework and quantified both the historical trajectory and the prospective pathway of energy technical resilience in China. We proposed to
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Mist cooling lithium–ion battery thermal management system for hybrid electric vehicles Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Aoto Teranishi, Takuma Kurogi, Izuru Senaha, Shoichi Matsuda, Keita Yasuda
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Advancing fault diagnosis in next-generation smart battery with multidimensional sensors Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Rui Xiong, Xinjie Sun, Xiangfeng Meng, Weixiang Shen, Fengchun Sun
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Optimal aggregation of a virtual power plant based on a distribution-level market with the participation of bounded rational agents Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Xin Liu, Tao Huang, Haifeng Qiu, Yang Li, Xueshan Lin, Jianxiong Shi
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Life cycle assessment of solar home system informal waste management practices in Malawi Appl. Energy (IF 11.2) Pub Date : 2024-04-16 Christopher Kinally, Fernando Antonanzas-Torres, Frank Podd, Alejandro Gallego-Schmid
This study performs the first life cycle assessment of solar home systems (SHSs) to use data quantifying lead pollution from informal lead-acid battery recycling. The typical life cycle of SHSs in off-grid communities surrounding Malawi's capital of Lilongwe is assessed, considering affordable components imported from China, lead-acid battery lifetimes of one year, the collection of materials through
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An interpretable framework for modeling global solar radiation using tree-based ensemble machine learning and Shapley additive explanations methods Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Zhe Song, Sunliang Cao, Hongxing Yang
Machine learning techniques provide an effective and cost-efficient solution for estimating solar radiation for solar energy utilization. However, the reported machine learning-based solar radiation models fail to offer comprehensive explanations for their outputs. Therefore, this study aims to tackle this issue by developing machine learning models that are both accurate and interpretable. To achieve
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Binary multi-frequency signal for accurate and rapid electrochemical impedance spectroscopy acquisition in lithium-ion batteries Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Xutao Liu, Shengyu Tao, Shiyi Fu, Ruifei Ma, Tingwei Cao, Hongtao Fan, Junxiong Zuo, Xuan Zhang, Yu Wang, Yaojie Sun
Electrochemical Impedance Spectroscopy (EIS) plays a crucial role in characterizing the internal electrochemical states of lithium-ion batteries and proves to be effective for estimating battery states. Traditional EIS measurement, however, requires expensive electrochemical workstations with time-consuming signal injection, especially in low-frequency regions, thus limiting its practical applications
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Upcycling waste graphite from spent LIBs for fabrication of novel mesoporous carbon and p-GN/BT based supercapacitor Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Roshan P. Rane, Shivam S. Shitole, Satyavan P. Varande, Bhavesh M. Patil, Paresh M. Patil, Vasant M. Patil, Atul C. Chaskar, Sunil N. Peshane, Vishwanath R. Patil
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Towards CSP technology modeling in power system expansion planning Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Valentina Norambuena-Guzmán, Rodrigo Palma-Behnke, Catalina Hernández-Moris, Maria Teresa Cerda, Ángela Flores-Quiroz
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Impact of wind on solar-induced natural ventilation through double-skin facade Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Yao Tao, Yihuan Yan, Jiyuan Tu, Long Shi
Although wind-buoyancy interactions have been widely explored, their mixing associated with semi-transparent facades are not yet clearly understood. This gap greatly restraints the implementation of naturally ventilated double-skin facades (NVDSFs). In this study, the impact of wind on the buoyancy flow in an NVDSF was investigated on a range of wind speeds, wind angles, and solar radiation intensities