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159 results on '"Qie Sun"'

1. The potential of radiative cooling enhanced photovoltaic systems in China

Author

Maoquan Huang, Hewen Zhou, G.H. Tang, Mu Du, and Qie Sun

Subjects
Radiative cooling, Structural optimization, PV systems, Potential, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract

Soaring solar cell temperature hindered photovoltaic (PV) efficiency, but a novel radiative cooling (RC) cover developed in this study offered a cost-effective solution. Using a randomly particle-doping structure, the radiative cooling cover achieved a high “sky window” emissivity of 95.3% while maintaining a high solar transmittance of 94.8%. The RC-PV system reached a peak power output of 147.6 W/m2. A field study to explore its potential in various provinces in China revealed significant efficiency improvements, with yearly electricity outputs surpassing those of ordinary PV systems by a relative improvement of 2.78%–3.72%. The largest increases were observed under clear skies and in dry, cool climates, highlighting the potential of RC-PV systems under real weather and environmental conditions. This work provided the theoretical foundation for designing scalable radiative cooling films for PV systems, unlocking the full potential of solar energy.

Published
2024
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2. Optimal Energy Management of Data Center Micro-Grid Considering Computing Workloads Shift

Author

Luyao Liu, Xinwei Shen, Zhigang Chen, Qie Sun, and Ronald Wennersten

Subjects
Data center micro-grid, renewable energy, delay-tolerant workloads, time shift, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Data centers have been experiencing increasingly significant challenges in electricity consumption and carbon emissions with the fast-development of artificial intelligence (AI). In the context of carbon neutrality, the integration of data centers with renewable green energy has become a prevailing trend. To effectively integrate renewable energy, it is imperative to thoroughly explore the data center’s operation flexibility. Delay-tolerant computational workloads have been considered as one of the most promising flexible resources for power regulation within data center micro-grids (DCMs). This paper first analyzes the working characteristics of three kinds of typical delay-tolerant computing workloads, i.e. short-running deferrable workloads, long-running continuous workload, long-running interruptible workload, and then clarifies the time-shifting mechanisms for each. Next, the corresponding time-shifting models of the delay-tolerant workloads are established. Finally, considering the time attributes of workloads and system settings, the day-ahead optimization scheduling framework of DCM incorporating the time-shifting models of multiple workloads are formulated, with the aim of minimizing the operation cost of DCM and renewable power curtailment. Application of the power management scheme in a data center case study confirms its effectiveness in improving the operational economy of data center and increasing green energy utilization.

Published
2024
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3. Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties

Author

Biao Feng, Yu Fu, Qingxi Huang, Cuiping Ma, Qie Sun, and Ronald Wennersten

Subjects
Integrated energy system, Uncertainty, High proportion of renewable energy, IGDT method, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

With the development of integrated energy systems, the system energy demands become more complicated and the renewable energy proportion becomes higher. Under this background, integrated energy systems gradually present a state of high randomness and strong uncertainty, which affects the system collaborative optimization. In order to handle the multiple uncertainties’ effects effectively, multi-objective optimization considering uncertainties of energy demand and renewable energy using information gap decision theory (IGDT) method was carried out. By analyzing the optimization results and comparing the results of different weight coefficient of multiple uncertainties, the renewable energy uncertainty has a strong effect, while the energy demand uncertainty’s effect is more complex.

Published
2023
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4. Day-Ahead Forecast of Photovoltaic Power Based on a Novel Stacking Ensemble Method

Author

Luyao Liu, Qie Sun, Ronald Wennersten, and Zhigang Chen

Subjects
PV power forecast, day-ahead forecast, ensemble forecast, stacking forecast, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Accurate prediction of photovoltaic (PV) power is the prerequisite for the safe and stable operation of the power grid with high penetration of PV. Despite various machine learning models for forecasting PV power have been developed, their accuracies are generally unstable. Toward this end, this study proposes a novel Stacking ensemble forecast model to improve the precision of day-ahead PV power forecasts. Different from the traditional Stacking model that uses the original training dataset to train the base learners, the proposed model creates multiple sub-training sets from the original training dataset to train the base learners, so as to enhance the diversity of base models and further improve the prediction accuracy. Specifically, in the proposed Stacking ensemble model, four machine learning learners, i.e., generalized regression neural network (GRNN), extreme learning machine (ELM), Elman neural network (ElmanNN), and Long shot-term memory (LSTM) neural network are incorporated, which are trained with the diverse sub-training datasets, and a variety of candidate base models are generated. For those candidate base models, the ones with the best performance are selected and integrated through a meta-model, namely the back-propagation network work (BPNN), to produce the final PV power prediction. The proposed model is evaluated using measured data from a 15kW PV power station in Ashland, Oregon, USA. Results indicate that across three weather scenarios, the performance of the novel Stacking ensemble model consistently outperforms single models and the traditional Stacking ensemble model in terms of the errors for out-of-sample forecasting, which proves the effectiveness of the developed procedure in improving PV power forecasting accuracy.

Published
2023
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5. Integrating Compressed CO2 Energy Storage in an Integrated Energy System

Author

Qingxi Huang, Yongxin Song, Qie Sun, Xiaohan Ren, and Wei Wang

Subjects
compressed CO2 energy storage system, integrated energy system, battery energy storage system, optimization, Technology
Abstract

The integration of an energy storage system into an integrated energy system (IES) enhances renewable energy penetration while catering to diverse energy loads. In previous studies, the adoption of a battery energy storage (BES) system posed challenges related to installation capacity and capacity loss, impacting the technical and economic performance of the IES. To overcome these challenges, this study introduces a novel design incorporating a compressed CO2 energy storage (CCES) system into an IES. This integration mitigates the capacity loss issues associated with BES systems and offers advantages for configuring large-scale IESs. A mixed integer linear programming problem was formulated to optimize the configuration and operation of the IES. With an energy storage capacity of 267 MWh, the IES integrated with a CCES (IES–CCES) system incurred an investment cost of MUSD 161.9, slightly higher by MUSD 0.5 compared to the IES integrated with a BES (IES–BES) system. When not considering the capacity loss of the BES system, the annual operation cost of the IES–BES system was 0.5 MUSD lower than that of the IES–CCES system, amounting to MUSD 766.6. However, considering the capacity loss of the BES system, this study reveals that the operation cost of the IES–BES system surpassed that of the IES–CCES system beyond the sixth year. Over the 30-year lifespan of the IES, the total cost of the IES–CCES system was MUSD 4.4 lower than the minimum total cost of the IES–BES system.

Published
2024
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6. Simulation of the VOC Adsorption Mechanism on Activated Carbon Surface by Nitrogen-Containing Functional Groups

Author

Yan Zhang, Shuhui Zhang, Shaofeng Xu, Fan Cao, Xiaohan Ren, Qie Sun, Li Yang, Ronald Wennersten, and Ning Mei

Subjects
activated carbon, functional group, VOC, DFT, adsorption, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

In this paper, the physical adsorption of volatile organic compounds (VOCs) such as methyl chloride (CH3Cl), carbon disulfide (CS2), dimethyl sulfide (C2H6S), and benzene (C6H6) by three models of activated carbon (without a functional group, with a pyridine-containing functional group, and with a pyrrole-containing functional group) was simulated. The surface electrostatic potential (ESP), physical adsorption energy, and non-covalent interaction between activated carbon and VOC molecules were analyzed based on the density functional theory (DFT). The effect mechanism of nitrogen-containing functional groups on VOC adsorption by activated carbon was determined. Our simulations showed that nitrogen-containing functional groups can change the surface ESP and polarity of activated carbon. The pyrrole functional group is conducive to CH3Cl and CS2 adsorption on the activated carbon plane, while the pyridine functional group is relatively small or even unfavorable for CH3Cl and CS2 adsorption on the activated carbon plane. The promotional effect of the pyrrole functional group on the adsorption of C2H6S is more significant than that of the pyridine functional group. The adsorption of C6H6 on activated carbon occurs through parallel-displaced π–π stacking interactions, in which functional groups have little influence on it. The adsorption energy of VOCs on the activated carbon plane is higher than that at the edge, so VOCs are more likely to be adsorbed on the activated carbon plane.

Published
2024
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7. Uncertainty modeling of household appliance loads for smart energy management

Author

Yu Wang, Yu Fu, Haiyang Lin, Qie Sun, Jean-Louis Scartezzini, and Ronald Wennersten

Subjects
Uncertainty, Occupant behaviors, Smart energy management, Agent-based modeling, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Households represent a large share of flexibility on the demand side for assisting the smooth operation of the highly renewable grid. The stochastic nature of activities and various appliance usage patterns of household occupants affects the flexibility potential greatly, but is usually oversimplified in the existing research. This paper aims to propose a novel method for simulating the dynamics of household energy-related activities and appliance usage, which provides realistic synthetic load profiles for smart energy management. To this aim, a highly resolved multi-agent system model is proposed, which comprises an Agent-Based Activity Chain Model (ABACM) and 34 types of common household appliance models. Firstly, the patterns of various occupant behaviors are obtained through mining of real-world residential time-of-use data. Then, the stochastic activity profiles of occupants are generated using the ABACM, with a root mean square error of 0.95%. Finally, the electricity consumption profiles of household appliances are simulated based on specific energy-related activities. The proposed method is validated and proved to be able to capture stochastic occupant behaviors and represent the dynamics of residential energy consumption. The future work will focus on using the proposed model for exploring the potential of residential demand response.

Published
2022
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8. Techno-Economic Evaluation of a Compressed CO2 Energy Storage System for Load Shifting Based on Dynamic Modelling

Author

Bin Zhang, Junbo Yang, Sule Tian, Qingxi Huang, Wei Wang, Qie Sun, and Xiaohan Ren

Subjects
compressed CO2 energy storage system, load shifting, mixed integer non-liner programming, flexibility, Technology
Abstract

To reduce the electricity grid’s valley—peak difference, thereby resulting in a smoother electricity load, this study employs a compressed CO2 energy storage system to facilitate load shifting. Load shifting by the CCES system not only enhances the energy flexibility of the electricity load but also creates energy arbitrage from variations in the electricity prices. An optimization model is developed to optimize the operation of the CCES system to minimize the standard deviation of the electricity load. Thereby, load shifting by the CCES system can be achieved. Based on the real electricity loads and prices, results indicate that, with an energy storage capacity of 267 MWh, the CCES system can provide 3845 MWh, 4052 MWh, and 3816 MWh of upward flexible energy and 3846 MWh, 3180 MWh, and 3735 MWh of downward flexible energy during a week in summer, winter, and the transition season, respectively. With a lifespan of 35 years, the CCES system can attain a net present value (NPV) of MUSD 239.9 and a payback time of 2 years. The sensitivity analysis shows that increasing the energy storage capacity of the CCES system augments both the upward and downward flexible energy of the electricity load but reduces the NPV of the CCES system.

Published
2023
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9. The Effect of Nitrogen- and Oxygen-Containing Functional Groups on C2H6/SO2/NO Adsorption: A Density Functional Theory Study

Author

Lei Zhang, Shuhui Zhang, Shaofeng Xu, Xiaohan Ren, Yan Zhang, Fan Cao, Qie Sun, Ronald Wennersten, and Li Yang

Subjects
adsorption, functional group, density functional theory, C2H6, SO2, NO, Technology
Abstract

This paper investigates the mechanism of nitrogen- and oxygen-containing functional groups in the collaborative adsorption of harmful gases by activated carbon through numerical simulation. The aim is to provide theoretical guidance for the industrial production of high-performance and universally applicable activated carbon. By employing density functional theory, we explore the impact of pyridine, pyrrole, carboxyl, and carbonyl groups on the co-adsorption of C2H6/SO2/NO by activated carbon through analyzing surface electrostatic potential (ESP), physical adsorption energy, and non-covalent interaction. The findings demonstrate that the presence of nitrogen- and oxygen-containing functional groups within activated carbon surfaces enhances their polarity, while simultaneously forming strong non-covalent interactions with C2H6 and SO2. The N-atom of NO can form a strong C-N ionic bond with the C-atom of the benzene ring. The adsorption site of NO is influenced by the nitrogen- and oxygen-containing functional groups. On an activated carbon model containing a pyrrole functional group, NO exhibits meta-adsorption behavior, while on activated carbon with pyridine, carboxyl, and carbonyl groups, it shows ortho-adsorption characteristics. The interaction between C2H6 and SO2, as well as NO, primarily involves the H-bond, whereas the interaction between SO2 and NO is predominantly driven by dipole–dipole interactions. These intermolecular forces significantly contribute to the mutual adsorption of these molecules.

Published
2023
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10. The effect of correlation of uncertainties on collaborative optimization of integrated energy system

Author

Yu Fu, Qie Sun, and Ronald Wennersten

Subjects
Integrated energy system, Uncertainty, Correlation, Copula theory, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Integrated energy system is an effective alternative to provide low-carbon sustainable energy to meet growing and complex energy demands. Uncertainty has a great impact on system configuration and operation schedule and the correlation between uncertain parameters increases the difficulty of high-precision optimization and control under this background. Thus, this paper focus on the correlation of uncertainties using copula theory and analyze the effect of correlation on optimization results. The case study shows that considering the correlation between uncertain parameters can affect the optimization results of the system not only in configuration but also the operation characteristics and reduce the total cost of the system.

Published
2021
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11. Effectiveness of the CVaR method in risk management in an integrated energy system

Author

Yu Fu, Qie Sun, and Ronald Wennersten

Subjects
Integrated energy system, Uncertainty, CVaR method, Risk management, Stochastic programming, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Integrated energy systems can effectively improve the efficiency of energy utilization and promote sustainable development of energy, while meeting the diversified energy demands. In order to deal with the operation risk caused by system uncertainties, the CVaR method was introduced into the system optimization model for risk management. The CVaR model was adopted to solve a multi-objective optimization problem using a two-stage stochastic programming method, where the uncertainty about solar energy and energy demand are considered at the same time. By comparing the optimization results obtained from the CVaR method and from the conventional scenario-based stochastic programming method, the effectiveness of the CVaR method in risk management of integrated energy systems is verified.

Published
2020
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12. Structure Design of Polymer-Based Films for Passive Daytime Radiative Cooling

Author

Mu Du, Maoquan Huang, Xiyu Yu, Xingjie Ren, and Qie Sun

Subjects
radiative cooling, porous structure, RDSP, passive cooling, Mechanical engineering and machinery, TJ1-1570
Abstract

Passive daytime radiative cooling (PDRC), a cooling method that needs no additional energy, has become increasingly popular in recent years. The combination of disordered media and polymeric photonics will hopefully lead to the large-scale fabrication of high-performance PDRC devices. This work aims to study two typical PDRC structures, the randomly distributed silica particle (RDSP) structure and the porous structure, and systematically investigates the effects of structural parameters (diameter D, volume fraction fv, and thickness t) on the radiative properties of the common plastic materials. Through the assistance of the metal-reflective layer, the daytime cooling power Pnet of the RDSP structures is slightly higher than that of the porous structures. Without the metal-reflective layer, the porous PC films can still achieve good PDRC performance with Pnet of 86 W/m2. Furthermore, the effective thermal conductivity of different structures was evaluated. The single-layer porous structure with optimally designed architecture can achieve both good optical and insulating performance, and it is the structure with the most potential in PDRC applications. The results can provide guidelines for designing high-performance radiative cooling films.

Published
2022
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13. Heat Transfer Performance of Gel Foam Layer with Nanoparticles Doping under a Radiative Heat Flux

Author

Rifeng Zhou, Pengyu Cui, Qingli Cheng, Xuqing Lang, Yong Zhang, Qie Sun, and Mu Du

Subjects
multi-phase, gel foam, insulation, nanoparticle, Mechanical engineering and machinery, TJ1-1570
Abstract

The risk of fire in the chemical industry’s production process is fatal. Gel foam has been widely employed in petroleum storage tanks, oil pools, and other petrochemical equipment for fire extinguishing and thermal protection. Recently, nanoparticles have been doped into gel foam to enhance thermal stability and insulation. However, heat transfer behaviors of the gel foam layer containing nanoparticles are still missing. In this study, a numerical heat transfer model of a gel foam layer containing silica nanoparticles under a radiative heat flux was established. Through simulation, the changes in foam thickness and temperature distribution were analyzed. The effects of the maximum heating temperature, initial gas content, nanoparticle size, and concentration on the thermal insulation behavior of the gel foam layer were systematically studied. The results showed that the thermal stability and insulation performance of the three-phase gel foam layer decreased with the increase in the initial gas content and particle size. Increasing the nanoparticle concentration could enhance the foam’s thermal stability and insulation performance. The results provide guidance for a designing gel foam with high thermal protection performance.

Published
2022
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24. Circ-sh3rf3/GATA-4/miR-29a regulatory axis in fibroblast–myofibroblast differentiation and myocardial fibrosis

Author

Cai-Xia Ma, Zhi-Ru Wei, Tong Sun, Ming-Hui Yang, Yu-Qie Sun, Kun-Lun Kai, Jia-Chen Shi, Meng-Jiao Zhou, Zi-Wei Wang, Jing Chen, Wei Li, Tian-Qi Wang, Shan-Feng Zhang, Lixiang Xue, Min Zhang, Qianqian Yin, and Ming-Xi Zang

Subjects
Pharmacology, Cellular and Molecular Neuroscience, Molecular Medicine, Cell Biology, Molecular Biology
Published
2023
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26. Line-of-shower trigger method to lower energy threshold for GRB detection using LHAASO-WCDA

Author

C. F. Feng, Bin Zhou, X. L. Ji, R. Lu, H. B. Xiao, J. R. Shi, W. Zeng, Z. H. Wang, Shengxue Zhang, Pak-Hin Thomas Tam, H. C. Li, Jun Liu, H. Y. Jia, B. D'Ettorre Piazzoli, W. X. Wu, Junjie Mao, Y. Q. Guo, Dong Liu, F. Ji, H. R. Wu, Y. J. Wei, Alejandro Sáiz, Oleg Shchegolev, L. Feng, V. Rulev, L. Xue, Xuliang Chen, Xing-Yuan Hou, D. M. Wei, S. Hu, M. L. Chen, Jianeng Zhou, J. Y. Liu, Warit Mitthumsiri, Y. Zhang, Q. An, Y. He, Q. Gao, Ruizhi Yang, X. N. Sun, H. B. Hu, H. Liu, L. Chen, X. G. Wang, S. Q. Xi, J. Fang, X. H. You, Ping Zhou, Z. C. Huang, Y. Z. Li, P. F. Zhang, C. Y. Wu, Hong-Guang Wang, G. M. Xiang, W. Liu, Yu-Lei Chen, Zihuang Cao, X. C. Chang, Z. K. Zeng, Y. J. Bi, H. D. Liu, Y. D. Cheng, Bo Zhang, Y. Zheng, L. Q. Yin, Duo Yan, F. Zheng, Hao Zhou, X. X. Zhou, Q. Yuan, Hefan Li, J. F. Chang, Z. X. Liu, Felix Aharonian, H. N. He, C. D. Gao, Lei Zhao, Q. H. Chen, Youping Li, Y. M. Ye, B. B. Li, Yongchun Wang, Y. D. Cui, Bai Yibing, L. P. Wang, J. B. Zhao, Y. J. Wang, J. Y. Yang, S. Z. Chen, Yunchao Liu, B. Z. Dai, Rong Xu, Z. X. Fan, Z. Y. You, Z. G. Dai, X. F. Wu, He Zhang, S. H. Feng, S. B. Yang, J. J. Xia, W. Gao, S. L. He, Y. P. Wang, B. M. Chen, Fan Yang, A. Masood, Kun Fang, S.H. Chen, Yugang Zhang, H. Cai, Lang Shao, H. Wang, J.W. Xia, L. Z. Zhao, G. C. Xiao, X. X. Zhai, Y. C. Nan, Shi-Qi Hu, X. J. Bi, Z. Li, R. Liu, E. W. Liang, X. Zuo, M. J. Yang, Y. H. Yao, W. L. Li, L. X. Zhang, H. K. Lv, Xufang Li, B. Y. Pang, Zebo Tang, M. H. Gu, Z. Y. Pei, Xuejiao Li, F. R. Zhu, T. L. Chen, Qie Sun, K. J. Zhu, Ying Zhang, H. M. Zhang, J. Chen, H. L. Dai, Y. L. Xin, T. Wen, S. W. Cui, M. Zha, J. C. He, W. H. Huang, L. X. Bai, Binyu Zhao, Yun-Feng Liang, Jixia Li, X. H. Cui, Xinbo He, K. Jiang, X. J. Hu, J. W. Zhang, Li-Sheng Geng, Wenwu Tian, Z. X. Wang, Xiaofei Zhang, David Ruffolo, Yu. V. Stenkin, C. Hou, Z. B. Sun, Shuibin Lin, Lu Zhang, K. Levochkin, Cheng Guang Zhu, X. D. Sheng, Minghao Qi, Houdun Zeng, Jun-Jie Wei, Jia Zhang, Y. A. Han, H. B. Li, Danzengluobu, Rui Zhang, H. C. Song, Linbin Yang, Y. Z. Fan, J. T. Cai, H. H. He, Y. M. Xing, F. Y. Li, D. H. Huang, H. Zhu, Xiang Zhang, M. M. Ge, J. G. Guo, S. R. Zhang, N. Cheng, L. L. Ma, G. H. Gong, J. S. Wang, Cunguo Wang, Shujuan Liu, N. Yin, Y. H. Yu, W. J. Long, Axikegu, Xuelong Wang, P. P. Zhang, Chunlong Li, Minghui Liu, D. Bastieri, Jinyao Liu, Z. G. Yao, X. H. Ma, M. Heller, K. Li, Z. J. Jiang, J. Liu, R. N. Wang, V. I. Stepanov, Jian Wang, Chiming Jin, D.A. Kuleshov, G. G. Xin, M. J. Chen, S. P. Zhao, Y. Y. Guo, Donglian Xu, X. L. Guo, X. J. Dong, Y. K. Hor, T. Montaruli, Y. L. Feng, W. Wang, P. Pattarakijwanich, S. Wu, B. D. Wang, C. X. Liu, Y. W. Bao, X. T. Huang, R. Zhou, L. Y. Wang, D. della Volpe, C. W. Yang, Jun-Hui Fan, Zujian Wang, Q. B. Gou, Qizhi Huang, B. Liu, Bingshui Gao, Xiang-Yu Wang, Tao Zeng, and Bin Ma

Subjects
Physics, Nuclear and High Energy Physics, Cherenkov detector, Astrophysics::High Energy Astrophysical Phenomena, Detector, Astrophysics, law.invention, Air shower, Nuclear Energy and Engineering, Duty cycle, law, Observatory, Gamma-ray burst, Energy (signal processing), Line (formation)
Abstract

Observation of high energy and very high emission from Gamma Ray Bursts (GRBs) is crucial to study the gigantic explosion and the underline processes. With a large field-of-view and almost full duty cycle, the Water Cherenkov Detector Array (WCDA), a sub-array of the Large High Altitude Air Shower Observatory (LHAASO), is appropriate to monitor the very high energy emission from unpredictable transients such as GRBs. Nevertheless, the main issue for an extensive air shower array is the high energy threshold which limits the horizon of the detector. To address this issue a new trigger method is developed in this article to lower the energy threshold of WCDA for GRB observation. The proposed method significantly improves the detection efficiency of WCDA for gamma-rays around the GRB direction at 10-300 GeV. The sensitivity of the WCDA for GRB detection with the new trigger method is estimated. The achieved sensitivity of the quarter WCDA array above 10 GeV is comparable with that of Fermi-LAT. The data analysis process and corresponding fluence upper limit for GRB 190719C is presented as an example.

Published
2021
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29. Ultrahigh-energy photons up to 1.4 petaelectronvolts from 12 γ-ray Galactic sources

Author

Alejandro Sáiz, Y. H. Yao, W. X. Wu, P. P. Zhang, Zhuo Li, R. Liu, Pak-Hin Thomas Tam, H. C. Li, Liang Chen, J. C. Wang, Y. L. Xin, L. Chen, M. J. Chen, Hong-Guang Wang, Y. J. Wei, S. Hu, Junjie Mao, Y. Q. Guo, J. Y. Liu, V. Rulev, P. F. Zhang, L. Xue, H. B. Hu, H. Liu, Rui Zhang, Linbin Yang, C. F. Feng, F. Ji, Xiaofei Zhang, F. Zheng, V. I. Stepanov, Ping Zhou, Q. H. Chen, H. R. Wu, Warit Mitthumsiri, X. C. Chang, Z. K. Zeng, C. D. Gao, Bin Zhou, W. L. Li, S. Z. Chen, M. M. Ge, Lei Zhao, Y. Z. Li, Y. Y. Guo, Y. J. Bi, Zhe Cao, Y. K. Hor, Xuejiao Li, H. D. Liu, S. H. Feng, B. Liu, Y. D. Cheng, Bo Zhang, H. K. Lv, H. M. Zhang, K. Levochkin, Y. J. Wang, L. X. Bai, Jixia Li, T. Montaruli, Duo Yan, Hefan Li, Ying Zhang, Bingshui Gao, Q. An, H. B. Xiao, J. R. Shi, X. D. Sheng, Z. X. Liu, W. H. Huang, M. L. Chen, Jianeng Zhou, Q. Gao, Minghao Qi, W. Zeng, Li-Sheng Geng, J. Chen, B. M. Chen, T. Wen, S. W. Cui, Z. X. Wang, Chiming Jin, S. B. Yang, L. Z. Zhao, C. W. Yang, J. B. Zhao, D.A. Kuleshov, Y. M. Xing, L. P. Wang, E. W. Liang, X. F. Wu, Zhe Li, B. Y. Pang, B. B. Li, X. Zuo, Cong Li, S. Q. Xi, Kun Fang, W. Gao, B. Z. Dai, Z. H. Wang, H. Cai, Jun Liu, Zhen Wang, J. C. He, Houdun Zeng, J. Fang, G. C. Xiao, Y. C. Nan, Z. G. Yao, Z. Y. Pei, Jun-Hui Fan, X. X. Zhou, Q. Yuan, H. B. Li, Shi-Qi Hu, G. G. Xin, J. F. Chang, Xufang Li, Oleg Shchegolev, G. M. Xiang, S. P. Zhao, W. Liu, X. L. Ji, M. J. Yang, H. H. He, R. Lu, Zhengguo Cao, Felix Aharonian, J. W. Zhang, H. C. Song, Yongchun Wang, Yugang Zhang, Wenwu Tian, He Zhang, Bai Yibing, S. L. He, Donglian Xu, Y. L. Feng, Zebo Tang, X. L. Guo, Y. D. Cui, X. J. Dong, Zheng Wang, Jun-Jie Wei, Q. B. Gou, Qizhi Huang, H. N. He, K. J. Zhu, M. Zha, B. D. Wang, Ruizhi Yang, X. N. Sun, Y. P. Wang, Z. C. Huang, H. L. Dai, H. Wang, Xiang Zhang, Xing-Yuan Hou, Yunchao Liu, H. Y. Jia, D. M. Wei, Z. G. Dai, Rong Xu, Fan Yang, A. Masood, F. Y. Li, Xinbo He, Youping Li, X. T. Huang, L. Y. Wang, X. R. Li, J. J. Xia, K. Jiang, Binyu Zhao, X. J. Hu, Yun-Feng Liang, W. Wang, Y. A. Han, J. G. Guo, Yu. V. Stenkin, Lang Shao, J.W. Xia, P. Pattarakijwanich, X. H. You, S.H. Chen, S. R. Zhang, C. Hou, Shuibin Lin, Lu Zhang, L. Feng, Xuelong Wang, S. Wu, X. X. Zhai, Xuliang Chen, C. X. Liu, L. L. Ma, Y. He, Z. X. Fan, Z. Y. You, F. R. Zhu, Y. W. Bao, Qie Sun, Yi Chen, X. G. Wang, Yi Zhang, Xiang-Yu Wang, D. H. Huang, R. Zhou, Hao Zhou, H. Zhu, X. J. Bi, D. della Volpe, Tao Zeng, T. L. Chen, Bin Ma, J. S. Wang, Cunguo Wang, L. X. Zhang, Shujuan Liu, N. Yin, N. Cheng, D. Bastieri, X. H. Cui, Cheng Li, W. J. Long, Shengxue Zhang, Axikegu, Li Zhang, G. H. Gong, Danzengluobu, M. H. Gu, Y. H. Yu, Jie Zhang, Y. Z. Fan, Dong Liu, C. Y. Wu, J. T. Cai, Long Chen, Y. Zheng, L. Q. Yin, Y. M. Ye, J. Y. Yang, B D Ettorre Piazzoli, David Ruffolo, Z. B. Sun, Cheng Guang Zhu, X. H. Ma, M. Heller, K. Li, Z. J. Jiang, J. Liu, Yong Zhang, Minghui Liu, R. N. Wang, and Jinyao Liu

Subjects
Physics, Multidisciplinary, Photon, COSMIC cancer database, Proton, Astrophysics::High Energy Astrophysical Phenomena, Astrophysics::Instrumentation and Methods for Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Electron, Astrophysics, 01 natural sciences, Galaxy, Supernova, Crab Nebula, Pulsar, 0103 physical sciences, 010306 general physics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics
Abstract

The extension of the cosmic-ray spectrum beyond 1 petaelectronvolt (PeV; 1015 electronvolts) indicates the existence of the so-called PeVatrons—cosmic-ray factories that accelerate particles to PeV energies. We need to locate and identify such objects to find the origin of Galactic cosmic rays1. The principal signature of both electron and proton PeVatrons is ultrahigh-energy (exceeding 100 TeV) γ radiation. Evidence of the presence of a proton PeVatron has been found in the Galactic Centre, according to the detection of a hard-spectrum radiation extending to 0.04 PeV (ref. 2). Although γ-rays with energies slightly higher than 0.1 PeV have been reported from a few objects in the Galactic plane3–6, unbiased identification and in-depth exploration of PeVatrons requires detection of γ-rays with energies well above 0.1 PeV. Here we report the detection of more than 530 photons at energies above 100 teraelectronvolts and up to 1.4 PeV from 12 ultrahigh-energy γ-ray sources with a statistical significance greater than seven standard deviations. Despite having several potential counterparts in their proximity, including pulsar wind nebulae, supernova remnants and star-forming regions, the PeVatrons responsible for the ultrahigh-energy γ-rays have not yet been firmly localized and identified (except for the Crab Nebula), leaving open the origin of these extreme accelerators. Observations of γ-rays with energies up to 1.4 PeV find that 12 sources in the Galaxy are PeVatrons, one of which is the Crab Nebula.

Published
2021
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31. Deep Neural Network-Based Impacts Analysis of Multimodal Factors on Heat Demand Prediction

Author

Jun Guo, Zhanyu Ma, Fredrik Wallin, Zhongwei Si, Jiyang Xie, Qie Sun, and Hailong Li

Subjects
0209 industrial biotechnology, Information Systems and Management, Artificial neural network, Meteorology, Computer science, 020209 energy, 02 engineering and technology, Solar irradiance, Energy engineering, Wind speed, Absolute deviation, 020901 industrial engineering & automation, Mean absolute percentage error, Physics::Space Physics, Outlier, 0202 electrical engineering, electronic engineering, information engineering, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Information Systems
Abstract

Prediction of heat demand using artificial neural networks has attracted enormous research attention. Weather conditions, such as direct solar irradiance and wind speed, have been identified as key parameters affecting heat demand. This paper employs an Elman neural network to investigate the impacts of direct solar irradiance and wind speed on the heat demand from the perspective of the entire district heating network. Results of the overall mean absolute percentage error (MAPE) show that direct solar irradiance and wind speed have quite similar impacts. However, the involvement of direct solar irradiance can clearly reduce the maximum absolute deviation when only involving direct solar irradiance and wind speed, respectively. In addition, the simultaneous involvement of both wind speed and direct solar irradiance does not show an obvious improvement of MAPE. Moreover, the prediction accuracy can also be affected by other factors like data discontinuity and outliers.

Published
2020
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37. Erratum: Properties of a New Group of Cosmic Nuclei: Results from the Alpha Magnetic Spectrometer on Sodium, Aluminum, and Nitrogen [Phys. Rev. Lett. 127 , 021101 (2021)]

Author

Massimo Gervasi, I. Lazzizzera, C. Mañá, Veronica Bindi, Corrado Gargiulo, M. Molero, M. Capell, J. Marquardt, Alexandre Lebedev, E. Fiandrini, T. Kirn, Yi-Cong Yu, Y. Yang, F. Machate, Fajun Zhang, S. C. Lee, J. J. Torsti, S. Pensotti, Antonino Zichichi, H. Y. Chou, H. T. Lee, M. Pohl, Ilya Usoskin, Z. Cui, C. H. Chung, V. Formato, Zheng Wang, M. Bourquin, L. Wang, G. N. Kim, Zhihua Zhang, Rami Vainio, Paolo Zuccon, M. Graziani, H. L. Zhuang, C. Consolandi, Valerio Vagelli, M Valencia-Otero, W. J. Burger, Pier-Giorgio Rancoita, P. Mott, M. Incagli, F. Cervelli, Arturo Alejandro Menchaca-Rocha, J. W. Song, M. Duranti, R. Q. Xiong, F. Barao, K. C. Han, M. Behlmann, E. Valente, H. D. Phan, F. Zhao, K. Dadzie, R. Sonnabend, N. Nikonov, J Liang, S. Li, Chuanguo Zhang, B. Khiali, Mayda Velasco, J. H. Zhang, S. Chouridou, Q. L. Wang, J. Casaus, C. Delgado, Lin Cheng, Elisa Laudi, Zhen Sun, L Mussolin, S. Di Falco, M. Paniccia, E. F. Bueno, Jun Liu, Jianfeng Feng, Maxim Konyushikhin, Valery Zhukov, D. M. Gómez-Coral, Timothy H. Hsieh, N. Attig, L Strigari, G. La Vacca, F. Giovacchini, V. Choutko, G. Ambrosi, M. Li, S. Wang, David Maurin, Mario Zannoni, C. Gámez, D. Krasnopevtsev, A. Kuhlman, J Tian, Thomas Lippert, Z. H. He, F. Nozzoli, J. D. Burger, T. Siedenburg, Samuel C.C. Ting, B Beranek, Zhixiang Tang, N. Masi, Bernd Heber, L. Barrin, Z. Y. Qu, P. H. Fisher, R. J. García-López, W. Xu, V. Di Felice, S. M. Ting, P. von Doetinchem, Xi Luo, X. D. Cai, J Negrete, Claudio Corti, A. Schulz von Dratzig, Z. Q. Yu, G. Castellini, K. Bollweg, G. Laurenti, C X Wang, Z Liu, Z. L. Weng, D. Rapin, Laurent Derome, V. Plyaskin, F. Dong, R. K. Hashmani, Xubo Qin, K. Luebelsmeyer, Qie Sun, C. Solano, S. Q. Lu, F. Donnini, C. Freeman, Stefan Schael, Yu Wang, F. Palmonari, A. Egorov, M. Pauluzzi, Z Shakfa, Carlos Díaz, Mauro Tacconi, B. S. Shan, Bruna Bertucci, H. S. Chen, M. B. Demirköz, G R Chen, Andrei Kounine, Q. Yan, S. Başeğmez-du Pree, Naihua Wang, A. Pashnin, Jun Hu, J Wei, M. Palermo, T. Urban, O. Kounina, H. Wu, Luísa Arruda, M. Aguilar, G. Coignet, Roald Z. Sagdeev, Julio C. Marín, Y. Chen, Yi Jia, Eun-Suk Seo, X. Q. Wang, Andrea Contin, Ying Lu, H. Jinchi, S. Della Torre, A.I. Oliva, Y. H. Chang, S. Rosier-Lees, T Su, V. Koutsenko, Eino Valtonen, A. Kulemzin, G. Schwering, V. V. Mikhailov, Stepan Poluianov, L. Ali Cavasonza, S. Burmeister, D. Rozza, F. Dimiccoli, X J Song, J. Z. Luo, A. Bartoloni, Z. H. Li, Qiang Li, Liqiu Wang, Lucio Quadrani, J. Berdugo, D. Grandi, J H Li, E Robyn, Fan Zhang, M. Vazquez Acosta, I. I. Yashin, A. Eline, M. Orcinha, Manuela Vecchi, C Zheng, G. Martinez, C. Clark, W. Y. Jang, Guo-Ming Chen, Chia-Hui Lin, J. Gong, C. Goy, H. Yi, Roberto Battiston, B. Borgia, Q. Meng, Henning Gast, Tim Martin, Sadakazu Haino, C. Tüysüz, A. Rozhkov, Varlen Grabski, A. Reina Conde, X. W. Tang, Jinglai Li, J. P. Vialle, M. J. Boschini, Z. M. Zheng, C. Light, Nicola Tomassetti, Tatiana Medvedeva, and Behcet Alpat

Subjects
Physics, COSMIC cancer database, Cosmic ray composition & spectra, Sodium, Analytical chemistry, General Physics and Astronomy, chemistry.chemical_element, Cosmic ray sources, Nitrogen, Cosmic ray acceleration, Cosmic ray composition & spectra, Cosmic ray propagation, Cosmic ray sources, Gravitation, Cosmology & Astrophysics [Physics Subject Headings (PhySH)], Cosmology & Astrophysics, chemistry, Group (periodic table), Aluminium, Cosmic ray acceleration [Physics Subject Headings (PhySH)], Cosmic ray propagation, Alpha Magnetic Spectrometer, ddc:530, Gravitation
Published
2021
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39. Properties of a New Group of Cosmic Nuclei: Results from the Alpha Magnetic Spectrometer on Sodium, Aluminum, and Nitrogen

Author

Roberto Battiston, N. Nikonov, T. Martin, J. W. Song, M. Vecchi, M. Duranti, G. N. Kim, Zhihua Zhang, J. Casaus, H. L. Zhuang, B. Borgia, M. Pauluzzi, Corrado Gargiulo, H. Jinchi, D. Grandi, M. Paniccia, S. C. Lee, M. Bourquin, J Tian, Bernd Heber, G. Schwering, E Robyn, B. Bertucci, L Mussolin, M. Vazquez Acosta, C X Wang, Yichao Yu, D M Gómez-Coral, Ignazio Lazzizzera, C. Gámez, R. Q. Xiong, G. Martinez, C. Freeman, L. Ali Cavasonza, Fan Zhang, O. Kounina, H. Wu, Samuel C.C. Ting, B Beranek, K. Bollweg, Qie Sun, Mayda Velasco, S. Başeğmez-du Pree, Corinne Goy, Yung Huang Chang, K. Luebelsmeyer, G. Laurenti, J. Z. Luo, Lucio Quadrani, Liqiu Wang, C. Solano, E F Bueno, I. I. Yashin, Jun Liu, H. S. Chen, Z. H. He, Roald Z. Sagdeev, S. Della Torre, P. von Doetinchem, Andrea Contin, X. D. Cai, F. Nozzoli, G R Chen, A. Kulemzin, M. Palermo, G. Coignet, Z Liu, J Wei, Z. L. Weng, S. Rosier-Lees, R. J. García-López, Valery Zhukov, D. Rapin, V. Plyaskin, Matteo Boschini, M. Pohl, C. Consolandi, V. Formato, Mauro Tacconi, V. Di Felice, A. Egorov, J. D. Burger, T. Siedenburg, B. S. Shan, M. Konyushikhin, M. B. Demirköz, Youhua Yang, Z Shakfa, Rami Vainio, V Vagelli, F. Donnini, H. D. Phan, F. Zhao, C Zheng, Massimo Gervasi, H. T. Lee, Carlos Díaz, J. Berdugo, J Negrete, Claudio Corti, F. Dimiccoli, Yi Jia, Elisa Laudi, Lin Cheng, Mario Zannoni, Stefan Schael, J Liang, Z. Y. Qu, L. Wang, Andrei Kounine, Q. Yan, M. Graziani, B. Khiali, Timothy H. Hsieh, T. Urban, M. Li, J H Li, J. H. Zhang, D. Rozza, C. Light, N. Attig, Pier-Giorgio Rancoita, A. Pashnin, M. Capell, V. Choutko, C. Mañá, G. Ambrosi, C. H. Chung, J. Marquardt, Xi Luo, Naihua Wang, T Medvedeva, J. J. Torsti, S. Pensotti, Veronica Bindi, G. Castellini, M Valencia-Otero, S. Li, W. J. Burger, K. C. Han, M. Molero, F. Cervelli, E. Fiandrini, X. Qin, S. Di Falco, Q. L. Wang, W Xu, S Wang, C. Delgado, T. Kirn, Nicola Tomassetti, F. Giovacchini, D. Krasnopevtsev, P. Mott, M. Behlmann, Luísa Arruda, Behcet Alpat, Julio C. Marín, A. Lebedev, Zhixiang Tang, A. Menchaca-Rocha, Ilya Usoskin, S. Chouridou, J. Q. Li, A. Kuhlman, A.I. Oliva, M. Orcinha, F. Barao, L Strigari, X. W. Tang, Thomas Lippert, M. Incagli, R. K. Hashmani, P. H. Fisher, S. M. Ting, Xiaoqun Wang, K. Dadzie, F. Palmonari, J. P. Vialle, Zhenzi Wang, Z. M. Zheng, F. Machate, H. Y. Chou, Z. Cui, Q. Meng, Yu Wang, Sadakazu Haino, C. Tüysüz, M. Aguilar, R. Sonnabend, W. Y. Jang, Guo-Ming Chen, Chia-Hui Lin, J. Gong, S. Q. Lu, H. Yi, Henning Gast, S. Burmeister, X J Song, A. Bartoloni, A. Rozhkov, Varlen Grabski, Jun Hu, A. Reina Conde, Eun-Suk Seo, Ying Lu, P. Zuccon, V. Koutsenko, Eino Valtonen, Z. H. Li, Qiang Li, C. Clark, A. Eline, E. Valente, Chuanguo Zhang, N. Masi, L. Barrin, A. Schulz von Dratzig, Z. Q. Yu, F. Dong, Y. Chen, A. Zichichi, T Su, V. V. Mikhailov, Stepan Poluianov, Fajun Zhang, Jonathan L. Feng, Zhen Sun, G. La Vacca, David Maurin, Laurent Derome, Bourquin, Maurice, Chen, Yao, Liu, Zhen, Paniccia, Mercedes, Pohl, Martin, Rapin, Divic Jean, Robyn, Erwan, Wei, Jiahui, Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), AMS, Aguilar, M, Cavasonza, L, Alpat, B, Ambrosi, G, Arruda, L, Attig, N, Barao, F, Barrin, L, Bartoloni, A, Başeğmez-du Pree, S, Battiston, R, Behlmann, M, Beranek, B, Berdugo, J, Bertucci, B, Bindi, V, Bollweg, K, Borgia, B, Boschini, M, Bourquin, M, Bueno, E, Burger, J, Burger, W, Burmeister, S, Cai, X, Capell, M, Casaus, J, Castellini, G, Cervelli, F, Chang, Y, Chen, G, Chen, H, Chen, Y, Cheng, L, Chou, H, Chouridou, S, Choutko, V, Chung, C, Clark, C, Coignet, G, Consolandi, C, Contin, A, Corti, C, Cui, Z, Dadzie, K, Delgado, C, Della Torre, S, Demirköz, M, Derome, L, Di Falco, S, Di Felice, V, Díaz, C, Dimiccoli, F, von Doetinchem, P, Dong, F, Donnini, F, Duranti, M, Egorov, A, Eline, A, Feng, J, Fiandrini, E, Fisher, P, Formato, V, Freeman, C, Gámez, C, García-López, R, Gargiulo, C, Gast, H, Gervasi, M, Giovacchini, F, Gómez-Coral, D, Gong, J, Goy, C, Grabski, V, Grandi, D, Graziani, M, Haino, S, Han, K, Hashmani, R, He, Z, Heber, B, Hsieh, T, Hu, J, Incagli, M, Jang, W, Jia, Y, Jinchi, H, Khiali, B, Kim, G, Kirn, T, Konyushikhin, M, Kounina, O, Kounine, A, Koutsenko, V, Krasnopevtsev, D, Kuhlman, A, Kulemzin, A, La Vacca, G, Laudi, E, Laurenti, G, Lazzizzera, I, Lebedev, A, Lee, H, Lee, S, Li, J, Li, M, Li, Q, Li, S, Li, Z, Liang, J, Light, C, Lin, C, Lippert, T, Liu, J, Liu, Z, Lu, S, Lu, Y, Luebelsmeyer, K, Luo, J, Luo, X, Machate, F, Mañá, C, Marín, J, Marquardt, J, Martin, T, Martínez, G, Masi, N, Maurin, D, Medvedeva, T, Menchaca-Rocha, A, Meng, Q, Mikhailov, V, Molero, M, Mott, P, Mussolin, L, Negrete, J, Nikonov, N, Nozzoli, F, Oliva, A, Orcinha, M, Palermo, M, Palmonari, F, Paniccia, M, Pashnin, A, Pauluzzi, M, Pensotti, S, Phan, H, Plyaskin, V, Pohl, M, Poluianov, S, Qin, X, Qu, Z, Quadrani, L, Rancoita, P, Rapin, D, Conde, A, Robyn, E, Rosier-Lees, S, Rozhkov, A, Rozza, D, Sagdeev, R, Schael, S, von Dratzig, A, Schwering, G, Seo, E, Shakfa, Z, Shan, B, Siedenburg, T, Solano, C, Song, J, Song, X, Sonnabend, R, Strigari, L, Su, T, Sun, Q, Sun, Z, Tacconi, M, Tang, X, Tang, Z, Tian, J, Ting, S, Tomassetti, N, Torsti, J, Tüysüz, C, Urban, T, Usoskin, I, Vagelli, V, Vainio, R, Valencia-Otero, M, Valente, E, Valtonen, E, Vázquez Acosta, M, Vecchi, M, Velasco, M, Vialle, J, Wang, C, Wang, L, Wang, N, Wang, Q, Wang, S, Wang, X, Wang, Y, Wang, Z, Wei, J, Weng, Z, Wu, H, Xiong, R, Xu, W, Yan, Q, Yang, Y, Yashin, I, Yi, H, Yu, Y, Yu, Z, Zannoni, M, Zhang, C, Zhang, F, Zhang, J, Zhang, Z, Zhao, F, Zheng, C, Zheng, Z, Zhuang, H, Zhukov, V, Zichichi, A, Zuccon, P, Aguilar M., Cavasonza L.A., Alpat B., Ambrosi G., Arruda L., Attig N., Barao F., Barrin L., Bartoloni A., Basegmez-Du Pree S., Battiston R., Behlmann M., Beranek B., Berdugo J., Bertucci B., Bindi V., Bollweg K., Borgia B., Boschini M.J., Bourquin M., Bueno E.F., Burger J., Burger W.J., Burmeister S., Cai X.D., Capell M., Casaus J., Castellini G., Cervelli F., Chang Y.H., Chen G.M., Chen G.R., Chen H.S., Chen Y., Cheng L., Chou H.Y., Chouridou S., Choutko V., Chung C.H., Clark C., Coignet G., Consolandi C., Contin A., Corti C., Cui Z., Dadzie K., Delgado C., Della Torre S., Demirkoz M.B., Derome L., Di Falco S., Di Felice V., Diaz C., Dimiccoli F., Von Doetinchem P., Dong F., Donnini F., Duranti M., Egorov A., Eline A., Feng J., Fiandrini E., Fisher P., Formato V., Freeman C., Gamez C., Garcia-Lopez R.J., Gargiulo C., Gast H., Gervasi M., Giovacchini F., Gomez-Coral D.M., Gong J., Goy C., Grabski V., Grandi D., Graziani M., Haino S., Han K.C., Hashmani R.K., He Z.H., Heber B., Hsieh T.H., Hu J.Y., Incagli M., Jang W.Y., Jia Y., Jinchi H., Khiali B., Kim G.N., Kirn T., Konyushikhin M., Kounina O., Kounine A., Koutsenko V., Krasnopevtsev D., Kuhlman A., Kulemzin A., La Vacca G., Laudi E., Laurenti G., Lazzizzera I., Lebedev A., Lee H.T., Lee S.C., Li J.Q., Li M., Li Q., Li S., Li J.H., Li Z.H., Liang J., Light C., Lin C.H., Lippert T., Liu J.H., Liu Z., Lu S.Q., Lu Y.S., Luebelsmeyer K., Luo J.Z., Luo X., Machate F., Mana C., Marin J., Marquardt J., Martin T., Martinez G., Masi N., Maurin D., Medvedeva T., Menchaca-Rocha A., Meng Q., Mikhailov V.V., Molero M., Mott P., Mussolin L., Negrete J., Nikonov N., Nozzoli F., Oliva A., Orcinha M., Palermo M., Palmonari F., Paniccia M., Pashnin A., Pauluzzi M., Pensotti S., Phan H.D., Plyaskin V., Pohl M., Poluianov S., Qin X., Qu Z.Y., Quadrani L., Rancoita P.G., Rapin D., Conde A.R., Robyn E., Rosier-Lees S., Rozhkov A., Rozza D., Sagdeev R., Schael S., Von Dratzig A.S., Schwering G., Seo E.S., Shakfa Z., Shan B.S., Siedenburg T., Solano C., Song J.W., Song X.J., Sonnabend R., Strigari L., Su T., Sun Q., Sun Z.T., Tacconi M., Tang X.W., Tang Z.C., Tian J., Ting S.C.C., Ting S.M., Tomassetti N., Torsti J., Tuysuz C., Urban T., Usoskin I., Vagelli V., Vainio R., Valencia-Otero M., Valente E., Valtonen E., Vazquez Acosta M., Vecchi M., Velasco M., Vialle J.P., Wang C.X., Wang L., Wang L.Q., Wang N.H., Wang Q.L., Wang S., Wang X., Wang Y., Wang Z.M., Wei J., Weng Z.L., Wu H., Xiong R.Q., Xu W., Yan Q., Yang Y., Yashin I.I., Yi H., Yu Y.M., Yu Z.Q., Zannoni M., Zhang C., Zhang F., Zhang F.Z., Zhang J.H., Zhang Z., Zhao F., Zheng C., Zheng Z.M., Zhuang H.L., Zhukov V., Zichichi A., Zuccon P., and Astronomy

Subjects
Cosmic ray composition & spectra, Analytical chemistry, General Physics and Astronomy, Cosmic Ray nuclei, Galactic cosmic rays, International Space Station, 01 natural sciences, Cosmology & Astrophysics, Alpha Magnetic Spectrometer, Cosmic-rays, AMS, 010303 astronomy & astrophysics, Range (particle radiation), COSMIC cancer database, Nitrogen, Aluminum nuclei, FIS/01 - FISICA SPERIMENTALE, Cosmic ray propagation, Gravitation, Primary cosmic rays, Materials science, Silicon, Cosmic-ray source abundance, Astrophysics::High Energy Astrophysical Phenomena, Sodium, chemistry.chemical_element, Cosmic ray, ddc:500.2, Astrophysics::Cosmology and Extragalactic Astrophysics, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], Cosmic ray acceleration, FIS/05 - ASTRONOMIA E ASTROFISICA, Flux (metallurgy), cosmic rays, Cosmic Nuclei, AMS-02, 0103 physical sciences, ddc:530, Nuclear Physics - Experiment, 010306 general physics, Cosmic ray acceleration, Cosmic ray composition & spectra, Cosmic ray propagation, Cosmic ray sources, Gravitation, Cosmology & Astrophysics, Cosmic ray sources, Sodium nuclei, magnetic spectrometer, Secondary cosmic rays, chemistry, Astroparticle physics, Cosmic-ray nuclei, Aluminum
Abstract

Physical review letters : PRL 127(15), 021101 (2021). doi:10.1103/PhysRevLett.127.021101, Published by American Physical Society, College Park, Md.

Published
2021
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40. Discovery of a new $\gamma$-ray source LHAASO J0341+5258 with emission up to 200TeV

Author

Zhengguo Cao, L. Feng, Xufang Li, Zebo Tang, Jun-Jie Wei, C. Y. Wu, Jia Zhang, L. X. Bai, Yi Zhang, H. K. Lv, Jixia Li, L. L. Yang, Z. X. Wang, M. Zha, Y. M. Ye, X. H. Ma, L. P. Wang, X. G. Wang, Donglian Xu, X. L. Guo, Y. A. Han, Binyu Zhao, Yun-Feng Liang, Houdun Zeng, Zhe Li, Y. Su, B. Z. Dai, Z. G. Dai, Jinmei Liu, B. D'Ettorre Piazzoli, Z. G. Yao, Y. Zheng, W. X. Wu, M. L. Chen, Jianeng Zhou, Hefan Li, W. Wang, P. Pattarakijwanich, Rong Xu, J. J. Xia, X. X. Zhai, J. Fang, F. R. Zhu, Qie Sun, Yi Chen, H. B. Li, G. M. Xiang, W. Liu, B. Y. Pang, S. Wu, X. L. Ji, R. Lu, K. Li, Y. J. Bi, H. D. Liu, Y. D. Cheng, Bo Zhang, L. Q. Yin, Hanzhong Zhang, C. X. Liu, D. della Volpe, Y. D. Cui, Kun Fang, Yugang Zhang, E. W. Liang, Ping Zhou, Z. J. Jiang, Y. J. Wei, J. Liu, Yong Zhang, Duo Yan, Yu. V. Stenkin, S. L. He, Y. P. Wang, Z. X. Liu, D. H. Huang, R. N. Wang, S. M. Liu, F. Ji, V. Rulev, Y. Z. Li, H. H. He, H. Zhu, C. Hou, Zheng Wang, B. Q. Ma, Y. C. Nan, L. Xue, Jun Liu, Lu Zhang, H. Y. Jia, D. M. Wei, V. I. Stepanov, E. S. Chen, Sina Chen, K. J. Zhu, Y. Q. Qi, Fulai Guo, J. Y. Shi, Minghui Liu, Yi Liu, J. B. Zhao, H. Wang, X. F. Wu, Zhen Wang, Z. X. Fan, Z. Y. You, Shi-Qi Hu, J. Y. Yang, N. Cheng, Z. K. Zeng, C. D. Gao, X. H. You, Long Gao, H. C. Song, Lei Zhao, D.A. Kuleshov, X. X. Zhou, Q. Yuan, B. M. Chen, Ruizhi Yang, X. N. Sun, Shengxue Zhang, Danzengluobu, J. F. Chang, S. P. Zhao, H. Liu, J.W. Xia, W. Gao, G. C. Xiao, Felix Aharonian, Xinbo He, K. Jiang, Pak-Hin Thomas Tam, H. C. Li, Y. Wang, Y. Z. Fan, Dong Liu, Y. W. Bao, P. F. Zhang, X. J. Bi, H. N. He, T. L. Chen, L. Z. Zhao, X. J. Hu, R. Zhou, Ying Zhang, Oleg Shchegolev, Junjie Mao, Y. Q. Guo, F. Y. Li, K. Levochkin, J. T. Cai, X. D. Sheng, Cong Li, X. Zuo, B. B. Li, Long Chen, Yunchao Liu, H. L. Dai, T. Wen, S. W. Cui, S. Z. Chen, David Ruffolo, Y. M. Xing, H. R. Wu, Liang Chen, Xiang-Kun Dong, S. Hu, J. Y. Liu, X. Y. Huang, P. P. Zhang, X. H. Cui, Minghao Qi, Z. B. Sun, Y. Bai, Z. Y. Pei, Cheng Guang Zhu, Yuan-Hao Wang, Zhuo Li, Warit Mitthumsiri, H. M. Zhang, Q. An, Y. H. Yao, W. H. Huang, H. Zhou, W. J. Long, Binbin Zhou, Li-Sheng Geng, R. Liu, Xiang Zhang, J. G. Guo, J. W. Zhang, S. R. Zhang, Wenwu Tian, L. L. Ma, Q. Gao, C. F. Feng, Jiangang He, J. S. Wang, Cunguo Wang, Y. L. Xin, Z. C. Huang, H. B. Hu, N. Yin, B. Q. Qiao, Xin Li, Cheng Li, Jiajun Qin, M. H. Gu, Boyang Wang, Rui Zhang, H. B. Xiao, W. Zeng, L. X. Zhang, S. H. Feng, M. M. Ge, Axikegu, Yonggang Wang, M. J. Chen, Zhao-Qi Wang, Y. Y. Guo, Li Zhang, G. H. Gong, Zhe Cao, Y. K. Hor, Y. H. Yu, T. Montaruli, Jian Wang, Chiming Jin, Z. Min, Xuelong Wang, G. G. Xin, Kai-Kai Duan, D. Bastieri, Y. L. Feng, T. Ke, S. J. Lin, X. T. Huang, L. Y. Wang, B. Liu, Jingzhi Yan, Bingshui Gao, Xiang-Yu Wang, Yulong Li, Tao Zeng, Xuliang Chen, Y. He, C. W. Yang, Jun-Hui Fan, Q. B. Gou, W. L. Li, D. X. Xiao, Qizhi Huang, J. Chen, Xiao-Hu Zhang, H. Cai, M. J. Yang, S. Q. Xi, Hong-Guang Wang, Alejandro Sáiz, Q. H. Chen, S. B. Yang, Fan Yang, A. Masood, F. Zheng, Lang Shao, and M. Heller

Subjects
Physics, Astrophysics::High Energy Astrophysical Phenomena, Hadron, Gamma ray, Flux, Astronomy and Astrophysics, Astrophysics, Galactic plane, Crab Nebula, Pulsar, Space and Planetary Science, Angular diameter, High Energy Physics::Experiment, Supernova remnant, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics::Galaxy Astrophysics
Abstract

We report the discovery of a new unidentified extended $\gamma$-ray source in the Galactic plane named LHAASO J0341+5258 with a pre-trial significance of 8.2 standard deviations above 25 TeV. The best fit position is R.A.$=55.34^{\circ}\pm0.11^{\circ}$ and Dec$=52.97^{\circ}\pm0.07^{\circ}$. The angular size of LHAASO J0341+5258 is $0.29^\circ \pm 0.06^\circ_{stat} \pm0.02^\circ_{sys}$. The flux above 25 TeV is about $20\%$ of the flux of Crab Nebula. Although a power-law fit of the spectrum from 10 TeV to 200 TeV with the photon index $\alpha=2.98 \pm 0.19_{stat} \pm 0.02_{sys}$ is not excluded, the LHAASO data together with the flux upper limit at 10 GeV set by the Fermi LAT observation, indicate a noticeable steepening of an initially hard power-law spectrum %($\alpha \leq 1.75$) spectrum with a cutoff at $\approx 50$ TeV. We briefly discuss the origin of UHE gamma-rays. The lack of an energetic pulsar and a young SNR inside or in the vicinity of LHAASO J0341+5258 challenge, but do not exclude both the leptonic and hadronic scenarios of gamma-ray production., Comment: Accepted by APJL

Published
2021

41. Pathways for sustainable energy transition

Author

Bin Chen, Rui Xiong, Jin Yang, Hailong Li, and Qie Sun

Subjects
Consumption (economics), Renewable Energy, Sustainability and the Environment, business.industry, 020209 energy, Strategy and Management, Corporate governance, Energy (esotericism), 05 social sciences, Fossil fuel, 02 engineering and technology, Environmental economics, Energy engineering, Industrial and Manufacturing Engineering, Energy storage, Renewable energy, 050501 criminology, 0202 electrical engineering, electronic engineering, information engineering, Cleaner production, business, 0505 law, General Environmental Science
Abstract

Energy transitions are ongoing processes all over the world. While sustainable solutions are envisioned for the future, many societies are still under high-carbon and high-pollution energy regime borne by fossil fuels. How to design pathways towards sustainable energy transition has attracted worldwide concerns. Understanding the possible transition pathways of the energy system requires the integration of new energy technologies, environmental sciences, economics and management. This Special Issue of Journal of Cleaner Production targets to collect the latest research results on sustainable energy systems, discover innovative avenues and inspiring models and share knowledge on energy system modelling and management. In this paper, we identify 4 themes on sustainable energy transition pathways including: (1) Sustainable energy economics and management; (2) Renewable energy generation and consumption; (3) Environmental impacts of energy systems; and (4) Electric vehicle and energy storage. Theories, technologies, innovative models, and successful experiences are discussed accordingly. It is suggested that creative, robust and audacious strategies in governance, management and education are needed to boost sustainable energy transition across various scales and sectors.

Published
2019
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42. Evaluating the benefits of Integrating Floating Photovoltaic and Pumped Storage Power System

Author

Qie Sun, Luyao Liu, Ronald Wennersten, Hailong Li, Xiaohan Ren, and Hongyi Yin

Subjects
Renewable Energy, Sustainability and the Environment, business.industry, Computer science, 020209 energy, Photovoltaic system, Energy Engineering and Power Technology, 02 engineering and technology, Grid, Energy engineering, Energy storage, Automotive engineering, Renewable energy, Electric power system, Fuel Technology, Electricity generation, 020401 chemical engineering, Nuclear Energy and Engineering, 0202 electrical engineering, electronic engineering, information engineering, ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS, Electricity, 0204 chemical engineering, business
Abstract

Floating Photovoltaic systems have developed very fast in recent years. Compared to individual Floating Photovoltaic systems, further advantages, such as grid connectivity and energy storage, can be obtained when Floating Photovoltaic operates collaboratively with Pumped Storage Power Systems. This paper proposed an Integrated Floating Photovoltaic-Pumped Storage Power System and quantitatively assessed the potential of the integrated system in electricity generation and conservation of water and land resource. The study developed a coordinated operation model for the Integrated Floating Photovoltaic-Pumped Storage Power System, which employed a dual-objective optimization, namely to maximize the benefits of electricity generation and to minimize the energy imbalance at the same time. The dual-objective optimization was solved using the genetic algorithm method. Other benefits of the Integrated Floating Photovoltaic-Pumped Storage Power System, namely conservation of water and land resource, were also assessed. The proposed methodology was applied to a 2 GW Floating Photovoltaic farm and a 1 GW Pumped Storage Power System. Results indicated that the Integrated Floating Photovoltaic-Pumped Storage Power System has a great potential for gaining the benefits of electricity generation (9112.74 MWh in a typical sunny day averagely) and reducing energy imbalance (23.06 MW aggregately in one day). The coordinated operation provides the possibility to achieve a higher generation benefits without affecting the reliability of the grid, while the optimization method plays a key role of efficient coordination. In addition, the system would help to save 20.16 km2 land and 19.06 million m3 water a year due to the reduction in evaporation loss. The synthetic benefits greatly improve the economic and environmental feasibility of photovoltaic systems in reality.

Published
2019
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43. Temperature response characteristics of the thermal control system of alpha magnetic spectrometer under the operations of international space station

Author

Qie Sun, Jiwei Song, Chen Zheng, and Lin Cheng

Subjects
Physics, Nuclear and High Energy Physics, business.industry, 020209 energy, Photovoltaic system, 02 engineering and technology, 021001 nanoscience & nanotechnology, Heat flux, Thermal, International Space Station, 0202 electrical engineering, electronic engineering, information engineering, Radiator (engine cooling), Orbit (dynamics), Alpha Magnetic Spectrometer, Aerospace engineering, 0210 nano-technology, business, Beta angle, Instrumentation
Abstract

The alpha magnetic spectrometer (AMS) in orbit is thermally affected by operations of the international space station (ISS). According to long-term monitoring data in orbit, three kinds of the most frequent ISS operations were determined, they were locking the ISS solar arrays by themselves, changing the ISS flying attitude with locking solar arrays and rotating the ISS starboard radiator with locking solar arrays. The β interval of ( − 75 ° , − 21 ° ) in which these three kinds of ISS operations have the most significant effect on the AMS thermal environment was calculated in reference to the ISS geometric model, and the calculation result was proved to agree well with the temperature records in orbit. The AMS radiator heat balance model was found under the different ISS operations. The numerical simulations were performed to provide quantitative analysis on external heat flux on AMS radiators. Based on those, the general temperature responses of the AMS radiators following the ISS β angle under the most frequent ISS operations were analyzed accordingly. We found that the ISS operations have varying degrees of the thermal influence on the AMS radiators under the same β angle. The suggestions of controlling the possible temperature anomalies caused by the ISS operations were given according to the temperature response characteristics of the AMS components under the most frequent ISS operations.

Published
2019
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44. Simulation analysis of household solar assistant radiant floor heating system in cold area

Author

Fei Yang, Lin Cheng, Ronald Wennersten, Qie Sun, and Jian Liu

Subjects
Primary energy, Radiation model, Matlab simulink, 020209 energy, Radiation heating, Mechanical engineering, 02 engineering and technology, Heating system, 020401 chemical engineering, Electromagnetic coil, Thermal, Cold area, 0202 electrical engineering, electronic engineering, information engineering, Environmental science, Astrophysics::Earth and Planetary Astrophysics, 0204 chemical engineering
Abstract

This study analyzed the performance of household solar assistant radiant floor heating system in cold area (taking Jinan as an example). Solar assistant radiant floor heating system models, including solar radiation model, collector model, thermal tank model and underground coil radiation heating model, were established in MATLAB Simulink. Based on the theoretical and simulation calculation, the optimal installation angle of solar collectors in different seasons and operating performance of the system under different parameters were obtained. The simulation results provide reference and guidance for the design and operation parameters of solar assistant radiant floor heating system in cold area in the future, and plays a certain role in promoting the application of this kind of primary energy saving system.

Published
2019
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45. Peak shaving and valley filling potential of energy management system in high-rise residential building

Author

Qie Sun, Ronald Wennersten, Yu Wang, and Luyao Liu

Subjects
business.industry, 020209 energy, 02 engineering and technology, Environmental economics, Grid, Energy management system, 020401 chemical engineering, Peaking power plant, Computer data storage, 0202 electrical engineering, electronic engineering, information engineering, Environmental science, Demand profile, Electricity, 0204 chemical engineering, business, High rise, Renewable resource
Abstract

In recent years, China has recognized rapidly increasing High-rise Residential Building (HRB) constructions due to the high rate of urbanization. The intensive and variable electricity demand in HRBs exerts large pressure on grid. Pairing Energy Management System (EMS) with PV storage system provides a clean and efficient way to utilize local renewable resources. By dispatching shiftable loads and storage resources, EMS could effectively reshape the electricity net demand profiles and match customer demand and PV generation. In this paper, a Multi-Agent System (MAS) framework is employed to investigate the peak shaving and valley filling potential of EMS in a HRB which is equipped with PV storage system. The effects of EMS on shiftable loads and PV storage resources are analyzed. The simulation results reveal the feasibility of the proposed approach to effectively flatten the HRB electricity demand and net demand profiles. With the help of EMS, the peak-to-valley ratio of demand profiles and net demand profile are reduced significantly.

Published
2019
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46. A dynamic price model based on levelized cost for district heating

Author

Hailong Li, Fredrik Wallin, Jingjing Song, Qie Sun, and Qi Zhang

Subjects
Ecology, Economics, Price model, Environmental Science (miscellaneous), Environmental economics, Cost of electricity by source, Energy engineering, Energy (miscellaneous)
Abstract

District Heating (DH) is facing a tough competition in the market. In order to improve its competence, an effective way is to reform price models for DH. This work proposed a new dynamic price mode ...

Published
2019
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49. A Rolling Global Optimization Method of EV Fleet for Peak-valley Shaving Considering the Uncertainty of EV Behavior

Author

Kun Fu, Yu Wang, Qie Sun, Haiyang Lin, and Ronald Wennersten

Subjects
Smart control, Optimization problem, Trustworthiness, Computer Science::Systems and Control, Computer science, Peaking power plant, Vehicle-to-grid, Power engineering, Grid, Global optimization, Automotive engineering
Abstract

To smoothen the power fluctuation of the grid, various smart control methods, e.g. vehicle-to-grid (V2G), are developed to rearrange charging and discharging behaviors of Electric Vehicles (EVs) for peak shaving and valley filling. In this paper, a rolling global optimization method is proposed to control the charging/discharging behavior of the EV fleet. Coupled with thorough EV behavior simulation through a trip chain model, the optimization results are more trustworthy and the optimized charging/discharging arrangement could flatten the fluctuation of the grid observably. It proves that the proposed rolling global optimization method could solve the multi-period optimization problem resulted from the uncertainty of EV behavior.

Published
2021
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