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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
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Sensitivity of multiscale large Eddy simulations for wind power calculations in complex terrain Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Giorgia De Moliner, Paolo Giani, Giovanni Lonati, Paola Crippa
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GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Nanyang Zhu, Ying Wang, Kun Yuan, Jiahao Yan, Yaping Li, Kaifeng Zhang
Power forecast for each renewable power plant (RPP) in the renewable energy clusters is essential. Though existing graph neural networks (GNN)-based models achieve satisfactory prediction performance by capturing dependencies among distinct RPPs, the static graph structure employed in these models ignores crucial lead-lag correlations among RPPs, resulting from the time difference of the air flow at
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Effect of gas diffusion layer parameters on cold start of PEMFCs with metal foam flow field Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Xingxiao Tao, Kai Sun, Rui Chen, Qifeng Li, Huaiyu Liu, Wenzhe Zhang, Zhizhao Che, Tianyou Wang
Metal foam (MF) flow field has extensive potential in proton exchange membrane fuel cells (PEMFCs). Under its influences on the internal flow and heat/mass transfer in PEMFCs, the original electrode structure base on the “channel-rib” flow field could be no longer suitable. In this study, the effects of gas diffusion layer (GDL) parameters on the cold start of PEMFCs with MF flow fields are studied
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Knowledge-inspired data-driven prediction of overheating risks in flexible thermal-power plants Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Zhimin Wang, Qian Huang, Guanqing Liu, Kexuan Wang, Junfu Lyu, Shuiqing Li
Mechanism-data-integrated methods are promising technologies for safe and flexible operation of power stations, which play an important role in compensating for the renewable energy intermittency and fluctuation. As an attempt in this direction, this work is devoted to the tube overheating problem in the boiler with the aim of developing effective predictive methods. First, we obtain insights from
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Economic–environmental trade-offs based support policy towards optimal planning of wastewater heat recovery Appl. Energy (IF 11.2) Pub Date : 2024-04-15 Chuandang Zhao, Jiuping Xu, Fengjuan Wang, Guo Xie, Cheng Tan
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An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Adam Słowik, Krzysztof Cpałka, Yu Xue, Aneta Hapka
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Water management and mass transport of a fractal metal foam flow-field based polymer electrolyte fuel cell using operando neutron imaging Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Y. Wu, L. Xu, S. Zhou, J. Yang, W. Kockelmann, Y. Han, Q. Li, W. Chen, M.-O. Coppens, P.R. Shearing, D.J.L. Brett, R. Jervis
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Modelling and evaluating different multi-carrier energy system configurations for a Dutch house Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Joel Alpízar-Castillo, Laura M. Ramírez-Elizondo, Pavol Bauer
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Does oil future increase the network systemic risk of financial institutions in China? Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Chuanglian Chen, Lichao Zhou, Chuanwang Sun, Yuting Lin
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Application-oriented assessment of grid-connected PV-battery system with deep reinforcement learning in buildings considering electricity price dynamics Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Qi Chen, Zhonghong Kuang, Xiaohua Liu, Tao Zhang
Deep reinforcement learning (DRL) is decisive in addressing uncertainties in intelligent grid-building interactions. Using DRL algorithms, this research optimizes the operational strategy of the building's grid-connected photovoltaic-battery (PV-battery) system, and examines the economic impact of battery capacity, rooftop PV penetration, and electricity price volatility. Three algorithms are employed
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EV-observing distribution system management considering strategic VPPs and active & reactive power markets Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Mahoor Ebrahimi, Mahan Ebrahimi, Miadreza Shafie-khah, Hannu Laaksonen
The growing deployment of new flexible resources, renewable energy resources (RES), and Electric Vehicles (EV) in the distribution system necessitates new methods to manage the distribution system operation optimally. In this regard, our paper, by deploying the concept of Virtual Power Plants (VPPs) as the aggregation of multiple agents and local power markets that are known as important tools for
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Impact of delivery time, local renewable sources, and generation curtailment on the levelized cost of hydrogen Appl. Energy (IF 11.2) Pub Date : 2024-04-13 Elias Masihy C., Danilo Carvajal, Sebastian Oliva H.
Supply schemes, specifically delivery times, are essential factors in the resulting final cost of fuels. It is the particular case of hydrogen produced from variable renewable energies. However, the impact of different delivery times on the levelized cost of hydrogen (LCOH) remains unclear. This paper assesses the combined impact of different delivery times, local renewable sources, and onsite generation
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Synergistic treatment of sewage sludge and food waste digestate residues for efficient energy recovery and biochar preparation by hydrothermal pretreatment, anaerobic digestion, and pyrolysis Appl. Energy (IF 11.2) Pub Date : 2024-04-12 Chunxing Li, Yu Wang, Shengyu Xie, Ruming Wang, Hu Sheng, Hongmin Yang, Zengwei Yuan
The safe disposal of sewage sludge (SS) and food waste digestate residues (DR) is a tough issue considering the difficulty of dewatering and the environmental risks from heavy metals and pathogens. This study combined hydrothermal pretreatment (HP), anaerobic digestion (AD), and pyrolysis to synergistically dispose of SS and DR to enhance dewaterability, recover energy, and prepare biochar with heavy
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A novel informer-time-series generative adversarial networks for day-ahead scenario generation of wind power Appl. Energy (IF 11.2) Pub Date : 2024-04-12 Lin Ye, Yishu Peng, Yilin Li, Zhuo Li
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Exploring synergistic and individual causal effects of rare earth elements and renewable energy on multidimensional economic complexity for sustainable economic development Appl. Energy (IF 11.2) Pub Date : 2024-04-11 Khizar Abbas, Mengyao Han, Deyi Xu, Khalid Manzoor Butt, Khan Baz, Jinhua Cheng, Yongguang Zhu, Sanwal Hussain
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Optimal charging/discharging management strategy for electric vehicles Appl. Energy (IF 11.2) Pub Date : 2024-04-11 Mohammed Algafri, Uthman Baroudi
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Improving the robustness of distributed secondary control in autonomous microgrids to mitigate the effects of communication delays Appl. Energy (IF 11.2) Pub Date : 2024-04-11 Basil R. Hamad, Ahmed Al-Durra, Khaled Ali Al-Jaafari, Hatem Zeineldin, Yasser Abdel-Rady I. Mohamed, Ehab El-Saadany
Distributed control has been employed in autonomous microgrids (MGs) to attain secondary control goals. However, the reliance of MG’s distributed secondary control on communication makes it vulnerable to degraded performance and the risk of instability due to communication delays. This paper enhances the flexibility of the MG control framework, with each distributed generator incorporating supplementary
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Generation capacity expansion planning with spatially-resolved electricity demand and increasing variable renewable energy supply: Perspectives from power pooling in West Africa Appl. Energy (IF 11.2) Pub Date : 2024-04-11 Mounirah Bissiri, Pedro Moura, Ricardo Cunha Perez, Nuno Carvalho Figueiredo, Patrícia Pereira da Silva
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Frigg 2.0: Integrating price-based demand response into large-scale energy system analysis Appl. Energy (IF 11.2) Pub Date : 2024-04-11 Amos Schledorn, Sandrine Charousset-Brignol, Rune Grønborg Junker, Daniela Guericke, Henrik Madsen, Dominik Franjo Dominković
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Design and optimization of nanostructure antireflection film for thin GaAs solar cells based on the photoelectrical coupling model Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Yuan He, Yubing Tao, Zihan Liu, Qing Huang
Anti-reflection film (ARF) with nanostructure plays an important role in reducing surface reflectance and improving power generation performance of solar cells. However, the reduction of reflectance is over-concerned during the design process of ARF, while the actual electrical performance of solar cells caused by structure changes of ARF tends to be ignored. In present study, a two-dimension photo-electric
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Design and modeling of wave energy converter glider (WEC-Glider) with simulation validation in wave tank experiments Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Yongkuang Zhang, Qingshu Liu, Feng Gao, Songlin Zhou, Weidong Zhang, Weixing Chen
The Wave Glider, a marine mobile robot propelled by waves, has gained significant prominence in large-scale, long-term ocean research and monitoring due to its ability to almost unlimited endurance. However, its sole reliance on solar power struggles to support the growing demands for diverse detection tasks. The authors introduce an enhanced power supply system for the Wave Glider that generate electricity
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A hybrid electric load forecasting model based on decomposition considering fisher information Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Wenjing Xiao, Li Mo, Zhanxing Xu, Chang Liu, Yongchuan Zhang
Accurate and efficient short-term load forecasting plays an important role in the stable operation of power grids and the economic operation of society. Among those factors that effect the electric load, meteorology is one of the most important factors that changes electric load fluctuation. This research innovatively adds the influence factor of multi day continuous meteorological conditions to the
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“Selectivity and reaction kinetics of methane pyrolysis to produce hydrogen in catalytically active molten salts” Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Alister Sheil, Muxina Konarova, Mark McConnachie, Simon Smart
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Building plug load mode detection, forecasting and scheduling Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Lola Botman, Jesus Lago, Xiaohan Fu, Keaton Chia, Jesse Wolf, Jan Kleissl, Bart De Moor
In an era of increasing energy demands and environmental concerns, optimizing energy consumption within buildings is crucial. Despite the vast improvements in HVAC and lighting systems, plug loads remain an under-studied area for enhancing building energy efficiency. This paper studies smart plug active operating mode detection, plug-level load forecasting, and plug scheduling methodologies. This research
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Forecasting air transportation demand and its impacts on energy consumption and emission Appl. Energy (IF 11.2) Pub Date : 2024-04-10 Majid Emami Javanmard, Yili Tang, J. Adrián Martínez-Hernández
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Wind turbine airfoil noise prediction using dedicated airfoil database and deep learning technology Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Han Yang, Weimin Yuan, Weijun Zhu, Zhenye Sun, Yanru Zhang, Yingjie Zhou
Noise emission is a major issue in wind turbine airfoil design, particularly for large scale wind turbines in low wind speed sites adjacent to urban areas. Conventional methods for addressing aerodynamic noise involve computational aeroacoustics or measurements in anechoic wind tunnels, which are both time-consuming and costly. Some surrogate methods can help reducing the cost, but most of them still
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A flexible urban load density-dependent framework for low-carbon distribution expansion planning in the presence of hybrid hydrogen/battery/wind/solar energy systems Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Reza Artis, Mojtaba Shivaie, Philip D. Weinsier
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An analytical method for quantifying the flexibility potential of decentralised energy systems Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Nailya Maitanova, Sunke Schlüters, Benedikt Hanke, Karsten von Maydell
In this study, we developed a technology-independent method for quantifying the time-varying flexibility potential of different energy systems. As the flexibility of these systems was assumed to be an additional service, their primary application must not be undermined by flexibility provision; for example, providing flexibility from a heat pump must not threaten the space heating of a building. Therefore
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Coordinated optimization of logistics scheduling and electricity dispatch for electric logistics vehicles considering uncertain electricity prices and renewable generation Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Yuanyi Chen, Simon Hu, Yanchong Zheng, Shiwei Xie, Qiang Yang, Yubin Wang, Qinru Hu
Electric logistics vehicles (ELVs) have the potential to significantly reduce pollution and carbon emissions, which are considered highly promising for achieving green logistics. However, the challenges posed by time-consuming charging processes, indirect carbon emissions, and fluctuating electricity prices hinder the economic viability of ELVs. To enhance the competitiveness of ELVs compared to internal
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Thermal - electric cooperative control of solid oxide electrolytic cell stack considering system efficiency optimization Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Yu Chen, Xiaogang Wu, Kai Zhou, Haoran Hu
Solid oxide electrolysis cell holds great potential for large-scale hydrogen production. However, achieving high efficiency and fast and safe dynamic response is difficult due to the complex physical and chemical processes involved in the system, as well as the variable power input that the system may experience. To address these issues, this study aims to develop a thermo-electric coordinated control
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From irregular to continuous: The deep Koopman model for time series forecasting of energy equipment Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Jiaqi Ding, Pu Zhao, Changjun Liu, Xiaofang Wang, Rong Xie, Haitao Liu
The data driven time series forecasting is a key concern for the digital modeling and health management of energy equipment. However, due to various issues, e.g., sensor failures in the data collection of energy equipment, the missing of data or the outliers often exist, thus producing irregular time series data. This limits the modeling capabilities of conventional sequence models like recurrent neural
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A nuclear future? Small Modular Reactors in a carbon tax-driven transition to clean energy Appl. Energy (IF 11.2) Pub Date : 2024-04-09 Wanni Xie, John Atherton, Jiaru Bai, Feroz Farazi, Sebastian Mosbach, Jethro Akroyd, Markus Kraft
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Achieving a smart thermal management for lithium-ion batteries by electrically-controlled crystallization of supercooled calcium chloride hexahydrate solution Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Fenglian Lu, Weiye Chen, Shuzhi Hu, Lei Chen, Swellam W. Sharshir, Chuanshuai Dong, Lizhi Zhang
The discharge performance of lithium-ion batteries (LIBs) is severely degraded at low temperatures. The existing LIBs preheating systems face challenges including high costs and consumption of battery capacity. Therefore, this paper developed an innovative electrically-controlled crystallization electrode based on calcium chloride hexahydrate (CCH) (ECE-CCH) by melting-solidification method and devised
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Triple-layer optimization of distributed photovoltaic energy storage capacity for manufacturing enterprises considering carbon emissions and load management Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Ran Feng, Kai Wang, Xu Xu, Zi-Tao Yu, Qingyang Lin
Distributed photovoltaic energy storage systems (DPVES) offer a proactive means of harnessing green energy to drive the decarbonization efforts of China's manufacturing sector. Capacity planning for these systems in manufacturing enterprises requires additional consideration such as carbon price and load management. This paper proposed a triple-layer optimization model for DPVES capacity configuration
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Predicting evaporation heat transfer coefficient distribution in multi-path alternating-laminated-microchannel-tube (ALMT) heat exchanger based on infrared thermography Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Wenhua Guo, Feng Li, Rijing Zhao, Dong Huang, Yongfeng Zhao
The alternating-laminated-microchannel-tube (ALMT) heat exchanger has emerged in the refrigeration and air conditioning industry. However, existing studies on evaporation heat transfer coefficient are limited to a single microchannel tube, while research on multi-path ALMT heat exchanger is lacking. The evaporation heat transfer in actual multi-path heat exchangers is influenced by secondary fluid
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Deterioration mechanism of the wettability of a lithium-ion battery separator induced by low-temperature discharge Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Shenghui Wang, Zhichao Ma, Wenyang Zhao, Zixin Guo, Hongwei Zhao, Luquan Ren
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Experimental study on the feasibility of isobaric compressed air energy storage as wind power side energy storage Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Changchun Liu, Xu Su, Zhao Yin, Yong Sheng, Xuezhi Zhou, Yujie Xu, Xudong Wang, Haisheng Chen
The isobaric compressed air energy storage system is a critical technology supporting the extensive growth of offshore renewable energy. Experimental validation of the coupling control between isobaric compressed air energy storage and renewable energy sources, such as wind power, is essential. This study pioneers coupling experiments between isobaric compressed air energy storage and wind power. Unstable
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Effect of discontinuous biomimetic leading-edge protuberances on the performance of vertical axis wind turbines Appl. Energy (IF 11.2) Pub Date : 2024-04-08 Hong Chang, Deyou Li, Ruiyi Zhang, Hongjie Wang, Yurong He, Zhigang Zuo, Shuhong Liu
The clustering distribution of vertical axis wind turbines in limited sea areas is a hot direction in offshore wind power. This study attempts to use biomimetic protuberances to improve the low efficiency of individual vertical axis wind turbines. It provides, for the first time, insights into the influence of spacing between protuberances on the performance of biomimetic blades. The aerodynamic performance