bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring and Analysis of Distributed New Energy Resources Based on the Internet of Things
Authors: Cui Hengzhi , Wang Chong , Liu Haixuan 
Published: April 2021

Abstract
In order to accurately monitor and analyze new energy resources in real time, the analysis and design of a distributed new energy resource monitoring device based on the Internet of Things cloud platform is carried out, and a Hadoop distributed new energy system based on the Internet of Things cloud computing is designed. It analyzes the computing architecture of parallel collection and distributed storage of new energy resource monitoring data, analyzes the infrastructure system of the distributed system, and builds the big data processing architecture and computing service architecture for the electricity information collection system based on the Hadoop cluster. Tasks are processed in parallel to improve the computing efficiency of electricity consumption big data; at the same time, in order to solve the problem of insufficient storage space caused by the sharp increase in the amount of data in the electricity consumption information collection system and the difficulty of data interaction at all levels, a distributed database is developed. The modular design of the parallel data collection system of HBase and the data warehouse tool Hive, and the distributed data calculation design based on the MapReduce method have improved the efficiency of data collection and the unified storage of heterogeneous data. The research provides reference for realizing an efficient and safe new energy resource monitoring data processing system.
Experimental study on cooling effect and improving comfort of cooling vest
Authors: Yuan Shuo , Zhang Mingrui , Zhang Ningning 
Published: April 2021

Abstract
In order to provide a comfortable working space in a warm or hot environment, it is necessary to cool these spaces to consume energy. In the context of global warming, the ability to provide comfort is becoming more and more challenging. With the increase of energy consumption, the demand for cooling is also increasing [1]. In previous studies, different types of individual and local cooling methods have been used to reduce the thermal stress of outdoor workers [1-7] and improve the comfort of indoor workers in office and commercial buildings. Local cooling can improve the macro climate air temperature, because the microclimate of workers is cooled, so the space air conditioning system needs less energy [1]. In addition, the thermal comfort of the transition space can be improved by using local passive cooling technology.
Numerical simulation study on Optimization of spray cooling mode in high temperature operation
Authors: Zhang Ningning , Zhang Cong , Yuan Shuo 
Published: April 2021

Abstract
Taking a single mine roadway in a metal mine as the research object, the distribution of wind temperature and wind speed in a single heading is studied by numerical simulation method under the condition of different ventilation in the roadway. The influence rule of different spray angles on the temperature distribution of the roadway is discussed, and the conclusion that the spray angle of the case reaches the optimum cooling effect is 15 degrees. Numerical simulation results show that spray cooling can make up for the defects of traditional pressing ventilation mode and achieve better cooling effect. It should be widely applied in non coal and gas outburst roadway.
Research and Analysis of Nonlinear Model Identification Control Algorithm Based on Improved Neural RBF For Short Term Heat Load Forecasting of Heat Supply Network
Authors: Wang Xuan , Zhang WanJun , Zhang Feng , Gou Xiaoping , Zhang Jingxuan , Zhang Jingyi 
Published: April 2021

Abstract
Aiming at the mismatch between heat supply and demand of heating system, a nonlinear model identification control algorithm based on improved neural network for short-term heat load prediction of heat supply network is proposed by using the characteristics that heat load and temperature of heating system will not change dramatically in a short period of time By using MATLAB simulation, short-term heat load rolling prediction is realized. From the experimental results, this algorithm is better than the traditional RBF neural network in the prediction accuracy, and can accurately predict the trend of heat load.
Research and Analysis on The Identification Technology of User Group Network in Distribution Station Area
Authors: Zuo Yue , Cui Shijie , Zhang Qi , Zhu Lianyong 
Published: April 2021

Abstract
Due to frequent line reconstruction in the distribution station area, the lines between adjacent lines in the distribution station area are messy and the paths are illegible, so that it is difficult for power grid companies to obtain accurate line losses and cannot balance the load planning, which is not conducive to the station area. Local refined management and service levels have been improved. In order to solve this problem, many identification technologies for users in distribution network stations have been proposed. However, traditional identification technologies have problems such as low accuracy and poor detection failure. The most important thing is that it is difficult to demodulate and identify signals. In order to solve this problem, this paper uses an improved differential cross-correlation algorithm to demodulate and identify the signal, and the power communication technology that carries information by artificially generating small distortions of the grid voltage and current. The experimental results prove the feasibility of the method proposed in this paper. Sex and effectiveness.
Analysis of Energy Structure in Northeast China
Authors: Lin Mingwei 
Published: April 2021

Abstract
As the old industrial base of our country, the utilization of energy in Northeast China has a certain influence on the implementation of the overall strategy of our country. After comparing and analyzing the data, it is concluded that the primary energy sources such as coal and oil account for a large proportion in the energy production and consumption structure of Northeast China, and after SPSS time series forecast, it is known that the energy structure will not change much in the short term. In view of this problem, we can promote the improvement and development of energy structure in Northeast China by developing new energy economy, perfecting the system of laws and regulations related to energy, and developing or introducing energy saving and efficiency-enhancing technology to improve energy utilization efficiency.Energy is the material basis for the survival and development of human society, and the revolution and innovation of energy is also an important manifestation of a country’s comprehensive strength. As the old industrial base of our country, Northeast China has abundant energy reserves such as coal and oil, and its energy utilization has a certain influence on the implementation of the overall strategy of our country. In October 2003, the CPC Central Committee and the State Council issued “Some Opinions on the Implementation of the Revitalization Strategy of the Old Industrial Base in Northeast China”, which clarified the guiding ideology, principles, tasks and policy measures for the implementation of the revitalization strategy. How to optimize the energy structure and make rational use of the energy in Northeast China will be an important issue to be considered in the energy innovation revolution in Northeast China. This paper will analyze the energy structure of Northeast China by means of data analysis, and then find out the problems and solutions[1].
A bi-level model for distributed generation optimal operating considering benefits of park power distribution company
Authors: Yin Shuo , Wang Shiqian , Yang Meng , Qiu Fengkai , Lin Jialin , Zhang Shuo 
Published: April 2021

Abstract
Distributed power generation market transactions provide a new profit model for park power distribution companies, which stimulates its enthusiasm for investing in distributed generation (DG). This paper integrates the investment income of distributed generation and the operation strategy of the park power distribution company into a bilevel programming problem. The improved particle swarm optimization algorithm is used to solve the model. The results show that the model can increase the comprehensive income of the distribution company, formulate a reasonable DG contract price and interruptible load compensation price, and effectively guide the planning and configuration of distributed generation and the economic efficiency of power distribution companies.
Research on Integrated Energy System of Power Grid Based on Artificial Intelligence Algorithm of Machine Learning
Authors: Zhang Nan , Zhang Wenqiang , Shang Yingnan 
Published: April 2021

Abstract
To advance the revolution in energy production and consumption, and to build a clean, low-carbon, safe and efficient energy system, it is necessary to develop a new generation of smarter power systems and integrated energy systems. Artificial Intelligence (AI) is currently one of the most disruptive science and technology, with strong processing capabilities in computational intelligence, perceptual intelligence and cognitive intelligence. Aiming at practical engineering problems such as the lack of accurate monitoring of the state of terminal equipment in the current comprehensive energy operation and maintenance management and control, the fault diagnosis mechanism is not perfect and the accuracy is low, a comprehensive energy operation and maintenance management and control scheme based on machine learning is proposed. Focusing on comprehensive energy service operation and maintenance management and control, in-depth mining of operation and maintenance and fault diagnosis data, integrating service system related expert information, establishing a comprehensive energy service terminal health evaluation model, and achieving a comprehensive evaluation of the health status of comprehensive energy services.
Research on Key Index System and Investment Scale Calculation Model of Power Grid Investment
Authors: Du Ying , Ma Tiannan , Wan Mingyong , Chen Jinyong , Yu Guangxiu , Sai Yaling , Wu Guangchuan 
Published: April 2021

Abstract
In order to avoid invalid investment and improve the investment efficiency of power grid companies, this paper constructed the power grid investment index system. Then extracted the key indicators by using the grey correlation analysis method. Finally, the regression analysis based on the multi scenario theory is used to predict the investment scale of power grid.
Coordinated Control of Multi-terminal MVDC Distribution Network with Photovoltaic Power Station
Authors: Lian Suo , Ma Yongwei , Li Wenyi , Tao Jun , Wang Biao , Xu Yu , Liu Qiong 
Published: April 2021

Abstract
In order to solve the problem of grid connection and absorption of large-scale photovoltaic power stations, the grid connection scheme of photovoltaic power stations connected to the two-end flexible DC transmission system based on DC voltage, active power and AC voltage control is adopted. Using RTDS simulation software, a DC power distribution system model including a photovoltaic power station and two MMCs was constructed, and the operating characteristics of the system were analyzed in detail. The simulation results show that when the output power of the photovoltaic power station fluctuates or the DC load changes, the system can maintain stable operation.
Comparison of Two Analysis Methods for Piezoelectric Laminated Plates
Authors: Guo Liang , Xing Ruishan 
Published: April 2021

Abstract
In this paper, the quasi-Shannon wavelet collocation precise integration method and the finite element method are used to solve the Hamilton regular equation of piezoelectric laminates. The cautions in the operation process of the two methods are analyzed, and the advantages and disadvantages of the two methods are compared. Numerical examples show that the wavelet collocation precise integration method which belong to the semi-analytical method is more accurate than the finite element method which is the numerical method.
Research and analysis of the control system based on sports running device to assist coaches to adjust speed adaptively
Authors: Zhao Bin , Liu Decheng , Liu Jianping , Zhang Wanjun , Gou Xiaoping , Zhang Feng 
Published: April 2021

Abstract
In this paper, an algorithm of adaptive speed control based on Sports runner assisted coach is proposed, and the control system based on Sports runner assisted coach adaptive speed regulation is established and simulated with MATLAB. The simulation results show that the test curve of the self-adaptive speed regulation of the sports running device is basically consistent with the actual situation of the auxiliary training device, with good stability and strong usability, which meets the requirements of sports running. At the same time, it also has a strong reference significance for the physical education teaching and training in other places.
Magnetic Moment Measurement Method Based on Magnetic Sensor Array
Authors: Sun Hexuan , Liang Jing , Zhi Huiqiang , Pei Dongxing 
Published: April 2021

AbstractThe magnetic moment measurement method based on magnetic sensor array is proposed to solve the problems of cumbersome calculation process and low inversion accuracy in the current magnetic moment calculation methods. Based on the concepts of magnetic field intensity, magnetic gradient tensor and Frobenius norm, this method can use the magnetic field information collected by magnetic sensor array to calculate the magnetic moment vector. The factors that may affect the measurement effect, such as sensor array structure, sensor precision and baseline size, are analyzed by simulation, and the advantages and disadvantages of three magnetic moment measurement methods based on magnetic sensor array are compared. Simulation results show that the proposed method is flexible in use, convenient in measurement, accurate in results, and has strong feasibility and reliability in geological survey and other applications.
Research on Fault Detection Method of Infrared Thermal Imaging for Power Equipment based on Deep Learning
Authors: Li Cheng , Yu Zixuan , Zhuo Mingsong 
Published: April 2021

Abstract
With the emergence of large image sets and the rapid development of computer hardware, especially GPU, it is a challenging problem to deploy convolution neural network (CNN) model on embedded devices with limited computing resources. The overheating fault of power equipment can be identified by collected infrared thermal imaging. Due to the propagation and fading of infrared radiation in the air, the infrared temperature measurement result is lower than the actual temperature value. In this paper, an efficient convolution neural network based on embedded equipment is proposed for thermal fault detection of power equipment. The backbone network in SSD algorithm is replaced by MobileNet, and Batch Normalization is merged with the previous convolution layer, so as to reduce model parameters, improve reasoning speed and make it run on lightweight computing platform. In order to solve the problem of propagation loss of infrared radiation in the air, an infrared temperature measurement correction unit based on BP neural network is proposed. Based on the above innovation, a thermal fault detection system for power equipment is designed. experiments and field applications show that the method has high accuracy and reasoning speed.
Research on Real-time Application of Ubiquitous Power Internet of Things Information Based on Smart Sensor Technology
Authors: Nan Jiangping , Jia Yajuan , Dai Xuezhen , Liu Yinglu , Ren Xiaowen , Feng Zheng , Xu Genqi , Bai Gang 
Published: April 2021

Abstract
In view of the current situation that it is difficult for the power control centre to take into account the multi-source information to conduct effective risk assessment on the dynamic process of the power grid, the challenges and opportunities faced by the power grid risk assessment under the background of the ubiquitous power Internet of Things are pointed out. The framework of the dynamic risk assessment system for the grid of the Internet of Things. At the same time, in view of the monitoring and fault diagnosis functions of sensor technology, especially gas sensor in transformer oil chromatographic monitoring, the application of ubiquitous power Internet of Things sensor technology in online monitoring of power equipment is discussed. First, the application of online monitoring of power equipment is analysed. The inevitable trend will then discuss in detail the monitoring and fault diagnosis functions of gas sensor technology in transformer oil chromatographic monitoring from sensor technology, gas sensor, transformer oil chromatographic device, and gas analysis method.
Discussion of Training Samples-Oreinted Sampling Methods for Data-driven Power Systems Analysis
Authors: Lei Jianglong , Yu Juan , Yang Yan , Xiang Mingxu , Yu Hongxin , Wang Hongbin 
Published: April 2021

Abstract
Data-driven methods such as deep neural networks (DNNs) and Gaussian processes (GPs), have been a promising way to achieve the balance of the calculation accuracy and efficiency in power system analysis. For instance, studies are utilizing the DNN-based method to achieve the fast and accurate calculation of probabilistic power flow. These methods rely on the sample data for training, which is mainly obtained by sampling. However, there is still no guidance on how to select the suitable sampling method to effectively generate the representative training samples. To address this problem, this paper explores the impact of different sampling methods on data-driven methods through theoretical analysis and simulation. Then some reasonable conclusions are drawn in this paper: i) Random sampling (RS) is suitable for data-driven methods that require large-scale training samples. ii) Latin hypercube sampling (LHS) is suitable for data-driven methods that only work well under small-scale training samples. iii) The assumption that the training samples generated by uniform sampling (US), which covers all sampling intervals, could not lead to good performance. Finally, simulations are implemented on the IEEE 39-bus system and the results demonstrate the effectiveness of the proposed conclusions
Research on the technology of Smart Energy Meter integrating time-sharing Metering and Billing
Authors: Liu Xingzhi , Zhou Quan , Qin Qing , Xie Yongming , Pan Yi 
Published: April 2021

Abstract
As one of the most basic and most critical devices in the perception layer of the ubiquitous power Internet of Things, smart energy meters require high reliability, low cost, and low power consumption, as well as certain functional expansion capabilities. This article mainly focuses on the smart energy meter integrating the metering and billing functions with variable tariffs and flexible and expandable electricity price packages, and analyzes the requirements for MCU instruction set, kernel structure, and SOC peripherals of this type of smart energy meter when working with a lightweight microkernel real-time operating system. And put forward the key design of the main frequency and large-capacity storage, which can meet the basic functions of the smart energy meter, while meeting the needs of flexible and expandable functions.
Research on Layout Network Optimization of Public Charging Infrastructure
Authors: Ma Jun , Xiaoyi Yin 
Published: April 2021

Abstract
With the gradual popularity of new energy vehicles in the world, people’s demands for the construction of supporting services such as charging infrastructure are becoming increasingly urgent. The popularity of charging infrastructure also determines the upper limit of the future development of new energy vehicles. This paper starts from the research on user satisfaction of charging infrastructure, finds the key indicator that affects user satisfaction-the layout network of charging stations, establishes a multi-path trajectory node model to quantitatively solve the problem of charging station layout under complex road network conditions, and calculates Example simulations verify the feasibility of the model method.
Analysis of anti-interference detection ability of wave net network signal based on convolution neural
Authors: Chen Tao , Sun Yaxuan , Ding Yulin 
Published: April 2021

Abstract
Deep learning has been widely used in image, speech, natural language, and robot and so on. However, how to use these technologies in radar detection is still very few. There are a lot of artificial design elements in the traditional radar processing, its application range must be considered practically, while the intelligent radar relies more on the self-learning and improvement ability of the algorithm itself. In this paper, a method of target detection based on convolution neural network is proposed. By matching the received signal with the transmitted waveform, the matching feature of the sliding window is extracted. Moreover, the feature information processed by convolution network is connected into a network, and the anti-jamming target detection under any transmitted waveform and given form of interference is completed. As a creative way, this paper compares the signal anti-interference detection and processing ability of convolution network and full connection network on independent distance unit, and finds that convolution network has the best effect.
Research and Implementation of Wind and Solar Energy Storage and Charging Scheme
Authors: Liang Liang , Yang Meiyi 
Published: April 2021

Abstract
In this paper, according to the characteristics of tourist attractions, the old station area and the heavy load station area which is difficult to increase capacity are reconstructed, and the energy saving and loss reduction treatment scheme is proposed. The wind and wind power generation equipment is used and the energy storage equipment is added to realize the power supply stability of the intelligent substation area distributed system. The transformer overload problem in the peak load period of the substation area is solved, and the energy-saving and loss reduction effect of the distribution line is realized.
Grid impedance estimation based on improved firefly algorithm
Authors: Lu Liang , Hu Linfeng , Liu Tianyu 
Published: April 2021

Abstract
Grid impedance has a great influence on the performance of grid-connected inverters in distributed power generation systems, so accurate grid impedance measurement is a key technique to achieve high-performance adaptive control of grid-connected inverters in weak grid situations. Firefly algorithm has the advantages of global search capability and fast convergence speed, and it has been widely used in the field of parameter estimation. In order to estimate grid impedance accurately and quickly, a grid impedance estimation algorithm based on the improved firefly algorithm is proposed. The grid impedance parameters are taken as the individual of the firefly algorithm, and the simulation model is built in the Simulink environment to compare and analyze the grid impedance estimation effect between the firefly algorithm and the successive iteration method. The simulation results show that the improved firefly algorithm has a higher accuracy for grid impedance estimation.
Synthesis and the photoelectrochemical performance of Fe2O3 photoanode through pretreatment
Authors: Wan Lijuan 
Published: April 2021

Abstract
The photo-electrochemical performance of hematite (α-Fe2O3) photoanode was evaluated and the preparation conditions were optimized in terms of maximizing the photoelectrochemical performances of the hematitephotoanodes. The photoelctro chemicalper for mances of hematite photoanode can be improved by the electrochemical surface pretreatment, and a possible mechanism was proposed to explain the reason for the improvement of photoelctro chemicalper for mances.