bluuebunny/crossref_metadata_2025 huggingface dataset:
MATLAB simulation of performance evaluation model of time-frequency analysis method based on SVM
Authors: Gao Zejun , Cao Fei , He Chuan , Song Tianli
Published: April 2022

Time-frequency analysis is a prerequisite for intelligent recognition of radar signal types based on deep learning network. Deep learning uses Convolutional Neural Network (CNN) to automatically extract the time-frequency images (TFIs) features of radar signals to achieve intelligent recognition of radar signal modulation methods. However, the quality of TFI generated by different time-frequency conversions is usually different to a certain extent. At present, the selection of time-frequency analysis methods in many pieces of research is mainly done through the feature differences of TFIs. There are certain subjective factors, which cannot provide a reference for subsequent research. This paper proposes a time-frequency analysis method performance evaluation model based on Support Vector Machine (SVM). The simulation results show that the evaluation model can make an objective and optimal choice based on the data, and can provide a valuable reference for subsequent research.
Parameter Identification of Lithium-ion Battery Equivalent Circuit Model Based on Limited Memory Recursive Least Squares Algorithm with Variable Forgetting Factor
Authors: Peng Xianghua , Yin Jingyuan , Sun Longfei , Ye Zeyu , Wei Tongzhen
Published: April 2022

Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to identify the model parameters in this paper. Firstly, based on the current and voltage data measured from the battery cyclic discharging experiment, the VFF-LMRLS algorithm is used to identify the time-varying parameters of equivalent circuit model. Then, the model verification system is constructed by taking the average value of the identification results in the stable stage as the component parameter value of the equivalent circuit. Finally, through the comparative experiment and analysis with the variable forgetting factor RLS (VFFRLS), it is verified that the terminal voltage error of the proposed method is smaller, indicating that the identified model parameters are closer to the actual parameters.
Research on control of new energy vehicles based on intelligent power conversion
Authors: Wang Yiyun , Feng Ling , Fan Guangfa
Published: April 2022

The conventional control method of new energy vehicles has the problem of imperfect driving motor coupling model, which leads to excessive car current. A control method of new energy vehicles based on intelligent electricity conversion is designed. For lithium battery performance parameters, computing power values change, the drive motor coupling model was established based on intelligent power conversion, the direct superposition of two motor torque, extract the new energy vehicles basic range of needs power, optimization of braking energy recycling process, hierarchical control type, the different working conditions, set up new energy auto control mode. Experimental results: The mean current of the new energy vehicle control method in this paper and the other two methods are 32.94A, 42.46 A, 42.96 A respectively, indicating that the new energy vehicle control method in the text is more effective.
Research on Energy Supply and Demand Forecast and Carbon Neutralization Path Based on Grey-Monarch Butterfly Optimization Model
Authors: Su Qi , Wang Haibo , Shi Xiaochen , Li Guixin , Sun Kuo
Published: April 2022

Energy and electricity are the key areas for China to achieve the double carbon target, and accurate forecasting of future energy supply and demand and carbon emissions is beneficial to develop a feasible path for low carbon transition. The gray prediction model GM (1, 1) is one of the most widely used dynamic prediction models in the field of energy forecasting, but it requires high raw data and the model may fail when the development coefficient of GM (1, 1) is large. On the other hand, the gray action of GM (1, 1) directly determines the model prediction accuracy, this paper introduces a novel population intelligence algorithm monarch butterfly optimization (MBO), which has excellent performance in practical optimization problems, into the optimization process of gray action of GM (1, 1), and proposes a new Gray-Monarch Butterfly optimization prediction model to realize the prediction. By comparing the prediction data with the classical literature, the effectiveness and superiority of the proposed Gray-monarch butterfly optimization prediction model are confirmed.Finally a carbon neutral pathway is given for Tianjin based on the prediction results.
New energy vehicles taking into account user needs participate in the FM model
Authors: Gu Jinhui , Guo Chunlin
Published: April 2022

In this paper, a new energy vehicle participation FM model considering user needs is established and verified by simulation. It has been proved that the model can guarantee user travel needs. The new energy vehicle participation FM model is divided into three parts: energy storage calculation, power constraint and energy constraint. Energy storage calculation is to model and analyse the available energy of new energy vehicles participating in FM, and get the variation of participating FM capacity in a day considering the user SOC demand. Power constraint is the charge and discharge power constraint of new energy vehicles, which is the necessary condition to ensure that new energy vehicles do not violate the technical conditions of new energy vehicles and ensure that the energy constraint of user demand participates in frequency modulation.
Research on technical Optimization of solid regenerative electric Boiler
Authors: Li Ting , Zou TongHua , Li HongXuan
Published: April 2022

This paper briefly introduces the principle and device of solid heat storage in electric boiler, analyzes the advantages and necessity of solid heat storage boiler technology. The development status and application examples of heat storage technology for solid thermoelectric boiler are introduced, and the efficiency of solid heat storage device is verified through experiments.
Research on fracture trend of repeated fracturing
Authors: Liu Mengxuan
Published: April 2022

The fracture trend of repeated fracturing is directly related to the effect of repeated fracturing and whether it can effectively expand the swept volume. In this paper, a large-scale hydraulic fracturing process simulation device is used to conduct laboratory experiments on fractured reservoirs to study the initiation and extension of repeated fracturing fractures under different stress states. The experimental results show that new fractures are easy to extend from the natural fractures near the wellbore, and the initiation pressure of the secondary fracturing is reduced due to the inducing effect of the initial fractures. The conclusion has a certain guiding function for the prediction of repeated fracturing fracture propagation in field fractured reservoirs, and it is of great significance for fracturing construction.
Experimental Study on Flame Propagation Characteristics of Premixed Laminar Combustion of Hydrogen-rich Coke Oven Gas
Authors: Li Ping
Published: April 2022

Coke oven gas (COG) is the main by-product of the coking industry, with a hydrogen content of more than 50%. Upon purification, COG can be used as a hydrogen-rich, efficient, high-quality alternative fuel, to improve the energy structure, alleviate global warming, and reduce polluting emissions. In the present paper, a constant-volume combustion experiment bench was established to carry out the premixed laminar combustion experiments of the COG-air mixture. A high-speed camera was used to record the flame propagation process and the effects of the influencing factors such as fuel-air equivalence ratio, initial pressure and H2 concentration on the flame speed. The results indicated that when Φ= 1.1, i.e., for a relatively concentrated fuel, the flame speeds of the stretched and unstretched flame both reached a maximum. With the increase in initial pressure, the flame speeds of both the stretched and unstretched flame decreased. As the H2 concentration increased, the propagation speeds of the stretched and unstretched flame both increased and the enhancements were more obvious; mainly since hydrogen combusts faster than methane.
Study on the condensable particulate matter removal characteristics of air pollution control devices in a Chinese ultra-low emission coal-fired generating unit
Authors: Zhang Ziwei , Zhao Bing , Wang Haigang , Zhou Baozhu , Zhao Qi , Dong Libin , Li Xukai , Jin Xuliang , Zhang Ziwen , Zhang Meng , Ma Lin , Li Shendong , Jia Jia , Xu Chao
Published: April 2022

Condensable particulate matter (CPM) belongs to PM25. In addition, it is one of PM2.5 main contributors. But CPM emissions are often overlooked in coal-fired power plants. As a result, this paper studies the removal characteristics of (CPM) from air pollution control devices (APCDs) in a Chinese ultra-low emission coal-fired generating unit. The quality and content of flue gas particles, including CPM and filterable particulate matter (FPM), were measured at four points: the selective catalytic reduction (SCR) input, air preheater (APH) inlet, electric precipitator (ESP) outlet, and wet flue gas desulphurization (WFGD) outlet. The removal characteristics of each APCD were studied. Within the scope of this study, it is found that: ® CPM emission concentration accounts for 94.9% of total particle emission concentration, and is higher than the ultra-low particulate matter outflow guidelines for coal-fired power plants in China; ©WFGD has the highest CPM inorganic component removal radio of 97.02%, and ESP has the highest CPM organic component removal radio of 58.46%, among APCDs; ©SO4
2−, NH4
+, F−, and Cl− are the most abundant water-soluble ions in CPM.
Multi-objective distribution network planning method with distributed generation based on non dominated sorting differential evolution algorithm
Authors: Wu Lei , Zhang Hai , Hu Zhaojie , Wang Yinghua , Wang Hairong , Yang Hua , Fan Bin , Chang Hao
Published: April 2022

Combined with the specific problems of distribution network planning with distributed generation, this paper constructs a multi-objective optimization model of distribution network planning with distributed generation. According to the distributed generation distribution network layout planning with distributed generation, under the condition of uncertain load prediction value of distributed generation distribution network, taking the minimum voltage stability index, minimum network loss and minimum investment cost of distributed generation as sub objectives, a multi-objective programming model is established, and the model is solved by non dominated sorting differential evolution (NSDE) algorithm.
Simulation analysis of distribution network with distributed generation based on ADPSS
Authors: Wu Lei , Zhang Hai , Hu Zhaojie , Wang Yinghua , Wang Hairong , Yang Hua , Fan Bin , Chang Hao
Published: April 2022

In this paper, the steady-state and transient models of distributed generation are modeled and simulated based on ADPSS system. Through the analysis of the simulation results, the fault characteristics of the distribution network with distributed generation are extracted. Through the analysis of the steady-state and transient models with distributed generation and the impact of the access of distributed generation on the power quality of the distribution network, the fault characteristics of the distribution network with distributed generation are extracted, which lays a theoretical foundation for the location and capacity determination of distributed generation.
Electron transport at TiO2/perovskite interfaces by considering the defect effects: a first-principles insight
Authors: Pu Wenhua , Wang Jianwei , Xiao Wei , Li Xiaowu , Wang Ligen
Published: April 2022

The interface property of perovskite solar cells (PSCs) is very important, which can influence the electron transmission efficiency and stability of the cells. In this text, we have discussed the stability and bonding characteristics of PbI2/TiO2 interfaces by using the first-principles method. The PbI2/TiO2 interfaces have a high interfacial binding energy of -0.93 J/m2, where the Ti-I and Pb-O bonds could form. Furthermore, the electron transport at the interfaces has been analyzed by the partial density of states by comparing the clean interfaces and interfaces with different defects. The results show that the clean PbI2/TiO2 interfaces could cause a stronger internal electric field, which might make the electron-hole pairs separate more easily at the interfaces. Also, it is found that common defects VI and Ii are relatively easy to form at the interfaces. Some defects at low concentrations might have little effect on the electron transport at the interfaces, while they are harmful only when the concentration increases. However, VPb with a high formation energy could adversely affect the electron transmission even at low concentrations. Controlling the defects at the interfaces is essential to improve the power conversion efficiencies (PCEs) and stability of PSCs.
The Design of Thermodynamic System Instrument & Control for the Daya Bay Turbine High Pressure Cylinder Retrofit
Authors: Hu Yanjun , Wan Tian , Pan Weiwei , Liu Shengzhi , Li Min
Published: April 2022

Before the retrofit, the equipments of the turbine high pressure cylinder of the Daya Bay Nuclear Power Plant is of the old technology. The design of the leaf shape and the steam runner is not advanced, and the equipments are aged after more than 20 years’ operation. From the point of increasing the power and improving the reliability of the equipments, it’s decided to retrofit the turbine high pressure cylinder of Daya Bay Nuclear Power Plant unit 1 and unit 2. The retrofit relates to the design and modification of many secondary loop thermodynamic systems’ instrument & control parameters, in order to match with the first loop reactor control systems, and also the mechanism and electric systems, it’s necessary to verify and optimize these designed parameters of the units after the retrofit. This design and analysis method and experience of the secondary loop thermodynamic systems’ instrument & control parameters can be referred by the similar retrofit of other nuclear power plants.
Influence of electric vehicle distributed energy storage access on safety and stability of distribution network
Authors: Wang Shengfeng , Yang Shaobing
Published: April 2022

This paper proposes a distributed energy storage control strategy for electric vehicles to improve the security and stability of distribution network when electric vehicles are connected. Firstly, the load characteristics of electric vehicles are investigated, and the optimal power flow model including energy storage power station, electric vehicle charging station considering V2G and distribution network is established. The objective function is established to minimize network loss, voltage deviation and load peak to peak. The problem is transformed into a mixed integer second-order cone optimization problem for solution, and based on the analysis of distributed energy storage model and constraints, the distributed energy storage control strategy of electric vehicle is established. Through the solution analysis in IEEE33 node system, it can be concluded that using this strategy can improve the power quality of distribution network and effectively improve the security and stability of distribution network.
Impact of control system on the DC impedance characteristics of low-medium frequency bands and stability of modular multilevel converter based HVDC system
Authors: Lin Xin , Guo Chunyi , Wang Yanning , Yang Shuo , Li Chunhua , Sun Xu
Published: April 2022

The resonance in modular multilevel converter based high voltage direct current (MMC-HVDC) system poses a potential threat to the safe and stable operation of the power grid. The mechanism of the resonance phenomenon is complicated, which is closely related to the impedance characteristics of MMC system. By establishing the DC impedance model of MMC-HVDC system at both ends, the influence of parameters of control system in converter stations on the DC impedance characteristics of MMC system was analyzed, revealing the main influencing frequency bands and effect of each control parameter. The DC impedance characteristics of low and medium frequency bands could be shaped in a targeted manner by adjusting the control parameters, the stability margin of the system will be improved as well. The correctness of the results was verified by time domain simulation. The analysis results of this article can provide reference for the selection of the parameters of control system and the improvement of stability margin of MMC-HVDC system.
Identification method of the feeder-transformer relationship in active distribution network based on power restoration information matrix
Authors: Chen Li , Lin Dongyue , Lin Yan , Chen Xue , Zhang Wei
Published: April 2022

In order to solve the problem of identification and verification of topological relationship between feeder and distribution transformer in distribution network, a new identification method of feeder-transformer relationship in active distribution network based on power restoration information matrix is proposed. Firstly, the identification model of feeder-transformer relationship is established through the distribution network feeder-transformer information matrix. Then, through the identification model of feeder-transformer relationship, the real-time power restoration information matrix (RRIM) and standard power restoration information matrix (SRIM) are established to describe the power restoration distribution transformer under real-time and standard conditions. Finally, the feeder-transformer relationship error information matrix is established through the difference between RRIM and SRIM to describe the name information of distribution transformer with misconnection and leakage on a feeder. The case analysis shows that this method can identify the feeder-transformer relationship of distribution network based on the topology information of DMS and real-time distribution transformer power restoration information. The method is simple and reliable, can better meet the actual needs of the site, and has good popularization value.
Design and application of distributed photovoltaic transaction consensus mechanism based on blockchain
Authors: Han Qi , Qi Yifei , Deng Hua , Liu Han
Published: April 2022

In recent years, distributed photovoltaic power generation has developed rapidly, but it has also brought many problems, such as poor equipment reliability, complex operation control, and many management subjects. Under the situation of the development of the electricity market, it is necessary to solve the problem of ensuring the data security of participating in the electricity market. Blockchain technology has the characteristics of traceability, non-tampering of information, openness and transparency, etc., which can satisfy massive transactions and reduce the burden of traditional power transactions. Therefore, based on the typical characteristics of blockchain, this paper analyzes the common attributes of blockchain and electricity market transactions, and adopts the DPOS (delegated proof of stake) consensus mechanism to realize distributed photovoltaic transactions. On this basis, this paper utilizes the consensus method based on node credit value and applies it to the actual microgrid distributed photovoltaic power station. The experimental results show that the transaction consensus mechanism proposed in this paper has certain advantages in transaction efficiency and transaction cost, which can provide a practical basis for blockchain to realize distributed photovoltaic transactions.
Analysis and research on breakdown cause of lightning arrester at low voltage side of 220kV transformer
Authors: Qu Limin , Li Tong , Wang Chao , Zhang Jian , Zhang Dewen , Zhang Hang , Gong Mingchen
Published: April 2022

This paper describes an event of zinc oxide arrester breakdown at low voltage side due to single-phase grounding at medium voltage side of 220kV transformer. Combined with the system wiring mode, equipment damage, system background and test data, the causes of fault and the transmission mechanism of overvoltage are studied in detail, It is concluded that the single-phase grounding short circuit on the medium voltage side leads to the displacement voltage of the neutral point, and the overvoltage is transmitted to the low voltage side through the capacitive coupling between the transformer windings, resulting in the breakdown of the arrester. The correctness of the conclusion is verified by calculation, and reasonable rectification measures and suggestions are put forward to effectively limit the generation of overvoltage on the low-voltage side of the transformer and ensure the safe and stable operation of the power grid.
Commutation failure detection of DC system based on S transform entropy
Authors: Fang Zhi-wen
Published: April 2022

The failure of commutation will cause the abrupt change of the operating parameters of the DC system. In this paper, the mechanism and physical process of commutation failure are analyzed. In view of the changing characteristics of inverter side valve current and DC current in the case of commutation failure, two kinds of S transform entropy are introduced into the detection of commutation failure of DC system in combination with S transform entropy’s excellent signal change feature recognition ability. In addition, the detection performance of the two s-transform entropies is fully considered in the case of no commutation failure, critical commutation failure and commutation failure. The simulation results based on PSCAD/EMTDC preliminarily verify the validity and accuracy of the two kinds of S transform entropy in dc system fault detection, which provides a basis for the further application of S transform entropy in dc system fault detection field.
Research and application of voltage coordinated control method for distributed photovoltaic connected to low voltage distribution network
Authors: Yin Hongxu , Zhang Bing , Song Liang , Liu Jie , Zhang Yingjie
Published: April 2022

Distributed photovoltaic access is likely to cause the problem of voltage limit violations, which greatly affects the consumption of distributed photovoltaics. At present, the existing methods do not consider the coordinated control of multiple voltage levels. In response to this problem, this article firstly analyzes the multi-voltage coordinated control method of distribution network. On the basis of data analysis, this paper formulates a control method for regulating the low-voltage distribution network by using the medium-voltage network.. In addition, optimized calculations were carried out on the voltage condition range of distributed photovoltaic access to the low-voltage distribution network. Finally, this paper analyzes the impact of distributed photovoltaic access on the voltage level of the distribution network, and provides a technical reference for the economic operation of the distribution network.
A High-Performance Cloud-based Remote Sensing Data Reprojection Method
Authors: Dong Yi , Xu Chen
Published: April 2022

Remote sensing (RS) data are the cornerstone of the digital earth. At present, the productions from Earth observation satellites are updated frequently with refined data quality. However, traditional methods are implemented mostly based on a single machine. When processing large-scale data in batches, there are limitations in computing power and storage, and the expansion is relatively cumbersome. This demands a more efficient and complex computation platform, such as cloud computation. Specifically, the reprojection procedure, unlike other data processing procedures, is both computationally intense and I/O-intense. This paper proposes a high-performance cloud-based RS data reprojection method called OCRM (optimised cloud-based reprojection method). First, the data process flow of reprojection was optimised by improving the I/O efficiency and computational efficiency. Second, with scheduling and controllers under cloud computation, high-performance massive RS data reprojection was achieved. The overall performance of the RS data reprojection module with the optimised algorithm in a single machine considerably outperformed that of the commercial software. The scheduling module can maximise the use of cloud resources to achieve high-performing reprojection calculations. The results indicate the stable performance of the proposed method, and we are working to expand the structure of OCRM to other computationally intensive remote sensing processes, such as data preprocessing and data mining with deep learning.
HBase-based spatial-temporal index model for trajectory data
Authors: Liu Hong , Yan Jining , Huang Xiaohui
Published: April 2022

The development of global positioning technology and the popularization of smart mobile terminals has led to a trend of rapid growth in the data volume and coverage of trajectory data. This type of data has the characteristics of fast update speed, high dimensional characteristics, and a large amount of information that can be mined. Many technology companies will use trajectory data to provide location-based services, such as vehicle scheduling and road condition estimation. However, the storage and query efficiency of massive trajectory data have increasingly become bottlenecks in these applications, especially for large-scale spatiotemporal query scenarios. This paper solves this problem by designing a trajectory data index model based on GeoSOT-ST spatiotemporal coding. Based on this model, the HBase-based trajectory data storage scheme and spatiotemporal range query technology are studied, and MapReduce is used as the calculation engine to complete the query attribute condition filtering in parallel. Comparative experiments prove that the index model proposed in this paper can achieve efficient trajectory data query management.
Study on the Expression of Spatiotemporal Patterns in Marine Ecosystems
Authors: Linchong Kang , Haiyan Huang , Xiaoyi Jiang , Guocheng Zuo , Yi Wang , Chang Liu
Published: April 2022

The ocean is a three-dimensional ecosystem with a wide range of temporal and spatial scales, thus making the visual expression of marine ecological characteristics extremely challenging. What types of marine ecosystems exist in a region, where are they distributed, what is their current status, and what are their changing trends? These are important questions faced by marine managers and decision makers. Based on the analysis of the relationship between biology and environment, this paper conducts ecological classification and data production for various marine elements. This paper expresses spatiotemporal marine ecological characteristics using a four-level general framework, including sea zone, bathymetry space, water space, seabed space. The bathymetry reflects the relevant marine topographic and landscape characteristics, and the water space and seabed space are composed of water environment, sediment environment and living organisms respectively. The framework’s main functions are the display, description, and statistical analysis of ecological characteristics, and display the spatiotemporal distribution pattern. These methods were combined with the construction of a database and R&D of system functions to fill the gap in this field in China and provide decision support for marine ecosystem management.
Active Contour Building Segmentation Model based on Convolution Neural Network
Authors: Liu Mengjia , Liu Peng , Song Bingze , Zhang Yuwei , Zhang Luo
Published: April 2022

In high-resolution remote sensing images, artificial features on the surface account for a large proportion. In artificial features, buildings, as special artificial features, buildings have different shapes. They are easily affected by light, so it takes a long time to extract using traditional image segmentation methods. It can't effectively design feature engineering to depict the high-dimensional features of the target building. We propose an active contour model based on a convolution neural network, which integrates the prior knowledge and constraints of active contour model, such as continuity of boundary, smooth edge, and geometric characteristics of buildings, into the learning process of convolution neural network to realize the close unity of ACM and CNN. According to our work, a fundamental end-to-end trainable image segmentation framework which is composed of convolution neural network (CNN) and ACM with learnable parameters is implemented, the problem of semantic segmentation of buildings in aerial images was dealt with, the model was evaluated on the publicly available dataset called Vaihingen, and some parameters were explained. In building semantics, the active contour model based on a convolution neural network has good performance.
A Standardized GIS Web Service Oriented Shared-nothing Architecture - Taking Species Distribution Modeling as an Example
Authors: Liu X Y , Yu J S D , Wei D D , Tong R J , Li D Y , Luo S
Published: April 2022

The rapid development of big data analytics technologies and tools, particularly the related distributed computing technologies, which divide large problems into smaller ones, provides important technical support for developing big earth data research. To realize the effective utilization of big data computing resources, it is important to overcome the potential incompatibility and inconsistency among the distributed computing nodes. Using standardized GIS web service interfaces is a promising approach to link existing heterogeneous GIS platforms through standardized protocols and establish a universal, platform-independent computing layer to improve the efficiency of computing resources for big earth data analysis. This research analyzed the requirements of distributed computing, and further proposed a standardized GIS web service-oriented shared-nothing architecture by comparing various mainstream distributed computing architectures and related web service specifications in the industry. For example, the prediction of Lophelia pertusa coral distribution by random forest is the application of the method discussed in this paper.
The impacts of trees’ canopy occupation on pedestrian thermal environment of township streets
Authors: Yamin Liu , Ding Lin , Yongbing Zhu , Chongcheng Chen
Published: April 2022

This paper measures the effect of trees’ canopy occupation on township street pedestrian thermal environment by ENVI-met software. The demonstration experiment was conducted in two streets with different features; street A (NE-WS) with 28% buildings coverage and 0.36 AR (street aspect ratios, H/W), street B (N-S) with 63.85% buildings coverage and 1.39 AR. The results show that trees’ canopy occupation ratio (TCR, Vtc/Vstreet) influences the average temperature at pedestrian height. The average temperature increases in the morning, whereas it decreases at noon and in the afternoon. It seems that TCR needs an offset to work on wider street, such as in street A, where the average temperature drops when TCR is greater than 0.15 (noon case, 12:00) and greater than 0.05 (afternoon case, 16:00). For every 0.1 increase of TCR (Vtc/Vstreet), the average temperature drops by 0.06°C(street A, 12:00), 0.118°C(street A, 16:00), 0.124°C(street B, 12:00), 0.1°C(street B), respectively. We can conclude that increasing the space occupation of trees’ canopy in the street can improve the pedestrian thermal environment, especially, the street with a small street aspect ratio. At the same time, we suggest that wider and taller trees shall be planted for street greening.
Optimal spatial resolution of remote-sensing imagery for monitoring cantaloupe greenhouses
Authors: Cui B , Huang W J , Ye H C , Chen Q X , Li Z C , Jiang H Y
Published: April 2022

Plastic greenhouses are vital agricultural facilities to protect cash crops from disease and insects, especially in the Hainan region of China, which has high temperature and high humidity. Remote-sensing technology is an efficient means to quickly determine the spatial distribution of plastic greenhouses on the regional scale. With the rapid development of remote-sensing technology, and especially the increasing types of high-spatial-resolution remote-sensing imagery, many studies have obtained good results by using remote-sensing technology to monitor plastic greenhouses. However, the best spatial resolution of images for monitoring plastic greenhouses has yet to be studied. To address this issue, we use cantaloupe greenhouses as the research object and GF-2 images with 1m spatial resolution as data source. We then use the re-sampling method to generate images from these data with spatial resolutions of 0.5, 2, 3, and 5 m. The details of the spatial distribution (texture features and shape features) and the spectral features of the plastic greenhouses were then extracted from images of varying spatial resolution, and a remote-sensing monitoring method for cantaloupe greenhouses was constructed based on the object-oriented random forest algorithm, which combines spectral, texture and shape features, and the monitoring results are compared. The results show that the use of 2 m spatial resolution provides the highest monitoring accuracy of cantaloupe greenhouses (overall accuracy = 94.85% and KIA = 0.92). This study thus provides a theoretical basis for remote-sensing monitoring of greenhouse cantaloupes that satisfies the current demands of production accuracy.
Remote-sensing monitoring of rubber plantations using object-oriented characteristics from the vigorous period
Authors: Cui B , Huang W J , Ye H C , Chen Q X , Li Z C , Jiang H Y
Published: April 2022

Natural rubber is one of the four major industrial raw materials in China, and the demand for it is increasing rapidly in China. However, due to geographic and climatic limitations, the rate of natural rubber production in China is significantly less than required to satisfy this demand. Therefore, to ensure the healthy development of China’s rubber industry, it is urgent to develop a method to rapidly and accurately monitor the planting and distribution of rubber forests in China. Existing studies have exploited the unique phenological characteristics of rubber plantations manifested by the spectral characteristics of the vigorous growth period and the deciduous period to identify rubber plantations through remote sensing. Unfortunately, the cloudy and rainy climate of rubber-growing regions makes it is difficult to obtain remote-sensing data in the optimal period. Therefore, the present study uses Planet images as the basic data and extracts typical spectral and textural features of rubber forests during the single vigorous growth period to construct a remote-sensing method to monitor rubber forests based on the object-oriented random forest algorithm, which uses all the spectral and texture features. The results show that the proposed random forest classification model achieves a high classification accuracy: the total classification accuracy reaches 89%, and the rubber producer’s accuracy and user’s accuracy both exceed 92%. This study can effectively solve the problem of lack image data with cloudless from deciduous period and provides a good theoretical basis for remote-sensing monitoring of China’s rubber forests, thereby facilitating the development of China’s rubber industry.
Analysis of Ecological Environment Changes and Driving Forces in Boao town of Hainan Province
Authors: Yang J Y , Wang Q J , Li Z C , Xie J J , Chang D K
Published: April 2022

Based on the three phases of remote sensing imageries in 2000, 2010 and 2020, taking Boao town as the study area, this paper analyzed the changes in the ecological environment and the driving forces of ecological environment. The results showed that: (1) The main land use type of Boao town was forest, followed by cultivated land. The main change of land use types in Boao town from 2000 to 2020 is from forest to other land types. (2) The average vegetation coverage of Boao town was 70.68% in 2000, 62.49% in 2010 and 71.65% in 2020, which indicated a trend of first decreasing and then increasing. (3) The changes of landscape pattern index of type level from 2000 to 2020 were as follows: the landscape shape index and landscape fragmentation of cultivated land decreased gradually, while the landscape shape index and landscape fragmentation of construction land and forest land increased. The trend of landscape pattern index of landscape level from 2000 to 2020 was as follows: landscape fragmentation continued to increase, landscape spread continued to decline, landscape separation continued to rise, and landscape diversity and evenness continued to increase. (4) In the driving force analysis of ecological environment changes in Boao Town, the results of principal component analysis showed that human factors were the leading factors of ecological environment changes in Boao Town, and economic factors such as GDP, output value of the third industry and per capita disposable income of farmers were the main driving forces of landscape pattern changes in Boao town.
Research on Disaster Acquisition Method Based on Point and Surface Combination of UAV Technology
Authors: Zhang Xuehua , Deng Duo
Published: April 2022

UAV (Unmanned Aerial Vehicle) remote sensing technology plays an increasingly important role in disaster acquisition. At present, after the disaster occurs, the orthophoto images of the UAV in the disaster area can be quickly obtained, but the bidimensionality of the orthophoto image limits the accuracy of disaster information extraction; it is required to improve the timeliness of the large-area 3D model established using the oblique photography technology in the disaster area. Combining the advantages of orthophoto and 3D models, this paper proposes a method for rapid acquisition of disasters based on point-surface combination. The Tibet Milin M6.9 earthquake is used as an example to analyze the advantages and disadvantages of this method in practical applications.
Analysis of several main hydrogen production technologies
Authors: Wu Qinglin
Published: April 2022

With economic development, social progress, and population growth, mankind’s demand for energy increases. Fossil fuels such as coal, oil, and natural gas are accelerating consumption, and these fossil fuels are non-renewable, and their reserves are very limited. If we continue to use fossil fuels uncontrollably, it will inevitably cause acid rain and global warming. As a renewable energy source, hydrogen energy has the least environmental pollution, and hydrogen energy can be dispersed in large quantities and converted from renewable energy. At present, hydrogen production technology and cost are high. This article briefly explains the principles and advantages, and disadvantages of several hydrogen production technologies, etc., and the cost and work efficiency of various technologies. Studies have shown that biomass pyrolysis and photocatalytic hydrogen production have higher efficiency and lower cost, which can be used as future research directions. However, there are problems such as the unclear hydrogen production mechanism of biological pyrolysis and unstable solar energy. And its future research and development directions are discussed in more detail. The research on hydrogen production technology is to satisfy the requirements of national economic development and social development needs.
Discussion About Carbon-Based Solid-State Hydrogen Storage Materials
Authors: Fan Jingming , Wang Yuechen , Zheng Zexuan
Published: April 2022

Activated carbon, as one type of hydrogen storage material have long been attracted by a measure of researchers. Some of the activated carbon’s properties may fall short compared with other materials; their characteristics like high surface area, easy-to-prepare, pretty small diameters, however, keep their status as one of the best choices for hydrogen storage. Carbon nanotube is considered as a promising candidate for solid-state hydrogen storage, and there is quite much research have been conducted to synthesize low-cost carbon nanotube with low absorption temperatures, high gravimetric and volumetric hydrogen storage densities, flexibility, good resistance to oxidation, high hardness, good reversibility and cyclic ability and moderate thermodynamic stability. Carbon fiber has shown its unique advantages among many other solid-state hydrogen storage materials. Carbon fiber might be the best for hydrogen storage since its low gas-solid interaction, tunable texture, surface area, high pore volume and excellent chemical and thermal stability. Additionally, the carbon fiber could also control its pore size for better absorption of a great number of hydrogen molecules. Based on several indexes, this literature introduce above three types of solid-state hydrogen materials, which hopefully are able to be favorable to further researches on relevant fields.
Advanced separators for lithium-ion batteries
Authors: Chen Kailin , Li Yingxin , Zhan Haoxiang
Published: April 2022

The separator technology is a major area of interest in lithium-ion batteries (LIBs) for high-energy and high-power applications such as portable electronics, electric vehicles and energy storage for power grids. Separators play an essential part that physically prevents direct contact between positive and negative electrodes while acting as an electrolyte reservoir to transport lithium ions. The characteristics of different separators would directly affect the performance under cell abuse; hence separators are crucial for battery safety. This paper introduces the characteristics of separators, means to improve traditional commercial polymeric separators and novel materials for separators. Other novel high-performance separators are also briefly discussed in this paper. Insights from this paper illustrate that various strategies could enhance the performance of separators, and better performance and safety can be achieved in separators in high-energy lithium-ion batteries.
Methodologies of energy system research and analysis by world top energy think tanks
Authors: Chen Chen , Wu Chen , Tan Jian , Gao Lang , Fan Chengliang
Published: April 2022

Think tanks are mainly engaged in policy research, while having influence on public policies, as well as serving policy makers and the public. Exploring the intelligence research methodologies and applications of the world’s top energy think tanks can promote the innovation of Chinese energy think tanks in research methods and can improve the scientificity and objectivity of research results, accelerating the construction of Chinese new energy think tanks. This paper investigates and sorts out the research results and methods of top energy think tanks around the world, and then provides new ideas for the creation of energy think tank research methods suitable for Chinese actual conditions from the strategic and practical levels. The study finds that international authoritative energy think tanks make analysis and predictions mainly through adopting multiple types of investigation method, introducing research models and tools in various disciplines, and combing with visual images, which shows the characteristics of extensiveness, digitizing, and intelligence.
Research on the Mechanism of Aggregate and Distributed Generation Participating in the Power Market
Authors: Li Yongliang , Yan Zhenhua , Xia Xuwei , Ma Junwei , Zhu Dongge , Guo Shaoyong
Published: April 2022

In recent years, distributed power generation has made great progress, but it is still restricted by factors such as low marketlization, lagging public services, and incomplete management systems. This paper studies the trading mechanism of distributed power participation in the market. First, it studies the participation of aggregated distributed power generation resources in the power market; then based on the model of distributed power generation resources that participating in the market through aggregated agents based on this article, the market mechanism is designed.Finally, a calculation example is adopted and the proposed method is verified.
Wind Energy Innovative Application on Shanghai Tower and Analytical Contrast with Other Buildings
Authors: Hu Yiwei
Published: April 2022

In this paper, wind energy as well as its innovative technology (wind turbine) is introduced. Original source, application, categories, principles, products etc are presented as the background introduction. As the typical building that integrates wind turbines on its structure, Shanghai Tower is regarded as the reference group in this research. Bahrain World Center, Strata Tower and Pearl River Tower are three sustainable buildings that utilize wind turbine technology as well, which are comparative groups. The aim of this research is to investigate the effectiveness of wind energy technology and to differentiate between wind turbines on different buildings according to some dimensions such as efficiency, cost and availability. Moreover, the future prospects and probable improvements on the wind turbines will also be discussed in this paper.
Feasibility study on the formulation of air non-point source emission standard in China
Authors: Wang Xiu-Teng , Liu Jing , Yang Shuo , Lin Ling , Huang Jin , Zhang Xiaoxin , Fang Fei
Published: April 2022

Emission standards of air pollutants are the legal basis for environmental management. Compared with the point source emission, the non-point source pollution of the air is mostly unorganized, which has the characteristics of large scope, random, hidden and difficult to control. It is difficult to take effective measures to control pollution, and the emission standard of atmospheric non-point source pollution is basically blank. In order to design a scientific and reasonable standard system, we have summarized the characteristics of atmospheric non-point source pollution, summarized the difficulties that dates back to the atmospheric non-point source emission standard in China, analyses the problems in the process of atmospheric non-point source emissions standards, put forward the principles for atmospheric non-point source emission standards. Finally we present the feasibility of typical atmospheric non-point source emission standards in China.
Fuzz Growth under Fusion Reaction and Estimation of Blanket’s lifespan
Authors: Wang Yilin , Huang Zexi
Published: April 2022

Tungsten has been regarded as a candidate of plasma facing material (PFM) in magnetic fusion reactor (MFR) due to its high strength, high thermal conductivity, and low erosion rates. Alpha particles, as the by-product of the D-T fusion reaction, will collide onto the Tungsten divertor and form nanotendril structures called “fuzz” with an estimation of 3.4 MeV energy. In this paper, we simulated by Stopping and Range of Ions in Matter (SRIM) to investigate the diffusing time and damage rate of the alpha particles on Tungsten. To describe the fuzz generation, the concepts in the diffusion model are utilized to describe the fuzz generation with corresponding techniques (e.g., Fick’s Migration Law). Through this diffusion model, we can derive an estimated lifespan for a divertor blanket that matches the design of general fusion reactors. These results pave a path to investigate the irradiation damage for Tungsten in divertor blankets.