bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Self-Configuration Technology of Intelligent Recorder Based on Graph and Model Integration
Authors: Chen Xu , Zhang Chi , Huang He , Xu Peng , Yang Jingchao , Xu Zhongnan 
Published: February 2021

Abstract
Intelligent recorder configuration related to smart operation and maintenance of secondary equipment has a large workload and a long configuration cycle, and it is difficult to guarantee and verify the correctness. Based on analysis of intelligent recorder function model including smart operation and maintenance, fault recording, network message analysis. This paper defines the requirements of self-configuration of intelligent recorder. On this basis, it puts forward the information model foundation that self-configuration depends on, including primary equipment model, correlation model between primary and secondary equipment, relays’ ICD information model, intelligent recorder acquisition unit, management unit model, and finally gives the self-configuration technique scheme in order to effectively improve the configuration efficiency of the intelligent recorder based on graph and model integration configuration, by which the RCI model file of the intelligent recorder and the SVG graphic file of the protection panel are formed.
Emergency control strategy of power system transient instability based on DBN
Authors: Qiang Ziyue , Wu Junyong , Li Baoqin , Zhang Ruoyu , Qin Liuyun 
Published: February 2021

Abstract
In order to satisfy the real-time emergency control decision-making after power system transient instability, an emergency control strategy based on deep belief network is proposed in this paper. Firstly, the DBN instability degree prediction model is established to fit the mapping relationship between generator power angle characteristics and transient stability coefficient; secondly, according to the fitting instability degree index, the sensitivity of generator tripping is solved to determine the generator tripping control action bus; finally, according to the emergency control optimization model and transient stability constraints, the optimal generator tripping strategy is solved and verified in New England 10-machine and 39-node system. The results show that the proposed method has high prediction accuracy and
efficiency, which can make the unstable system quickly resume stable operation.
Research and implementation of condition monitoring and evaluation for process switch of intelligent substation
Authors: Liu Haitao , Zhang Shuang , Xue Fei , Niu Jian , Xu Zhongnan , Han Yehong 
Published: February 2021

Abstract
There are some problems in the regular inspection of switch, such as lack of real-time, lack of maintenance and over maintenance, this paper proposes a method for monitoring and evaluating the status of process layer intelligent switches . According to IEC61850 standard, the information model of switch is established to obtain the status information of the switch. The status information data is analyzed through the monitoring model of over-limit, synchronization, mutation and trend warning, and the status of switch is quantitatively evaluated by the fuzzy comprehensive evaluation algorithm. The example shows that this method can effectively evaluate the state of switch, which provides application technical support for state maintenance of process layer intelligent switches.
Data-driven management mechanism of demand response resources in active distribution networks
Authors: Yin Jianbing , Xu Zeyu , Chen Lin , Li Dairui 
Published: February 2021

Abstract
As power distribution networks have been transferring from passive to active, conventional physical-driven models are incompetent to deal with the challenges of flexible and fast-changing operating conditions. Alternatively, data-driven methods, especially deep learning methods, have unique advantages in tackling those challenges. To this end, the paper first introduces the opportunities brought by the massive amount of data in active distribution networks (ADNs). Then the paper employs neural networks to identify load categories and their potential capacity of demand response to interact with ADNs. Furthermore, a generalized dispatch framework is presented to coordinate flexible loads for peak-valley electricity alleviation, with long-short-term-memory networks as an example. Last, the paper sheds light on the limitations of deep learning applications such as data cleaning and cybersecurity attacks.
Integrated pricing mechanism for combined electric and heat systems considering heat time delays.
Authors: Xie Pingping , Mao Tian , Xuan Peizheng , Zou Jin , Lu Siyu 
Published: February 2021

Abstract
Combined electric and heat systems can significantly improve fuel efficiency and reduce carbon emission by making use of complementary properties of electricity and heat. However, many current papers on the energy market mechanism do not consider the heating price, while some do not address the challenges of heat time delays on prices, which may impede the benefits of system operators as well as users. Therefore, in this paper, we extend the electric local marginal price (LMP) to the integrated LMP (ILMP) for electricity and heat in combined electric and heat systems considering heat time delays and network constraints. The results of case studies demonstrate the proposed mechanism can provide fair electricity and heat prices which can reflect generation cost, power loss, network congestion, and time delays.
FPGA-based Adaptive Variable Step MPPT Real Time Simulation for Photovoltaic Systems
Authors: He Ruxun , Wang Shouxiang , Zhang Chunyu , Ma Qi 
Published: February 2021

Abstract
In order to obtain more output power, maximum power point tracking (MPPT) control technology is usually designed to track the maximum power of photovoltaic (PV) array. The traditional power disturbance observation method tends to cause power oscillation loss, so an adaptive variable step algorithm is presented to balance the tracking accuracy and speed of PV system. Different from off-line simulation, the overall model is built on FPGA to complete the real time digital realization of MPPT control for PV system. Finally, the model is simulated and verified by ModelSim software. The experimental results show that the system can track the maximum power more quickly and accurately in real time.
Research on the Structure and Control Strategy of Energy Storage Grid Connected Inverter
Authors: Wang Cunping , Yu XiJuan , Li Hongtao 
Published: February 2021

Abstract
This paper studied the structure of energy storage grid connected inverter which is composed of super capacitor, bi-directional DC/DC converter, and voltage type DC/AC converter. The working principle of bi-directional DC/DC converter and DC/AC converter was separately analyzed. Then a joint control strategy of DC/DC converter and DC/AC converter was proposed with the main control objective of maintaining DC bus voltage. According to the different states of DC bus voltage and super capacitor voltage, five control modes of energy storage inverter were set. Besides, the DC/AC converter was controlled to compensate the reactive power and harmonics, and provide certain active power for the power grid according to the actual situation. Finally, the effectiveness of the proposed energy storage inverter structure and control strategy were verified through simulation analysis.
An Real-Time Emergency Control Method Based On Unbalanced Transient Energy Function
Authors: Huang Dan , Zhao Shanshan , Zhang Yichi , He Hailei 
Published: February 2021

Abstract
In this paper, an emergency control strategy by combining generator tripping and load shedding is presented. Firstly, the unbalanced transient energy function of power system is defined, and its key features are analysed. Then, by combining the unbalanced power characteristics for power system in steady state operation condition, the method for calculating the control quantities of generator tripping and load shedding is proposed. Furthermore, a realtime closed-loop emergency control strategy is proposed. Since the proposed method by only using measurement data is based on the essential of transient instability, the accurate control quantities can be obtained. Compared with single generator tripping control, the low frequency and low voltage problem of system can be improved effectively with the combined emergency control strategy. Simulation results of New England 39-bus system validate the effectiveness of the proposed control strategy.
Analysis and countermeasures of delayed action of generator stator grounding protection
Authors: Liu Shifu , Qian Zhunli 
Published: February 2021

Abstract
The friction between the iron core and the wire rod caused insulation damage, which caused the wire rod to discharge to the ground, the generator stator ground protection action, and the generator stopped, through the analysis of the reasons, the generator operation preventive measures were formulated, and the delay time of the stator grounding protection was shortened and neutrality was adjusted. The improvement measures for shortening the delay time of stator grounding protection, adjusting the neutral point TV transformation ratio, increasing the impedance of the secondary load, and unified protection clock are proposed. These improvement measures provide useful experience for engineering and technical personnel to deal with related similar problems.
Research on optimal allocation of protective resources of power network under malicious attacks
Authors: Xiong Jingyi , Hou Benwei , Du Xiuli 
Published: February 2021

Abstract
With the increase of global malicious activities, it is particularly necessary to optimize the allocation of limited urban protective resources and protect power network from malicious attacks. There is plenty of research on evaluating the risks of malicious attacks on electricity network, however, conventional risk-based approach does not take strategic adjustment of malicious into account, nor can it determine the optimal allocation of global protective resources. In this paper, an optimal allocation of protective resources based on game theory was proposed, which combined game theory with risk assessment, taking full account of strategic interaction between defender and attacker. IEEE 30-bus network was taken as an example to verify the applicability and reliability of the method, so as to confirm the advantages of the method in determining the global optimal allocation of protective resources.
Energy Internet Security Risk Evaluation Index System
Authors: Li Jing , Shang Zhijie , Qiang Ren , Pang Jin , Guo Han , Wang Jingchu , Niu Haihang 
Published: February 2021

Abstract
As the construction of the Energy Internet has launched into a novel method, the dependence on energy and information networks has been greatly increased. The interaction of energy and information flow has become recurring, and the deep coupling of energy and information flow has been realized. As a result, security risk factors have increased substantially. Given that, this article from the perspective of energy and information flow, combined with the “Source-Grid-Load-Storage” coordination scenario of the energy Internet and the actual development needs of the information network, this article proposes a risk assessment for many security risks that threatens the stable construction of the energy Internet Index system and corresponding index analysis.
A Short-Term Optimal Dispatch Model Considering Uncertain Wind Power Output
Authors: Zhang Xuan , Wei Hua , Gao Wei , Su Xianxin 
Published: February 2021

Abstract
Aiming at the security and economic problems caused by wind power connected to the grid, a short-term optimal dispatch model for power system considering the uncertain wind power output is proposed. Although wind power is an important clean energy source, wind power output is characterized by volatility and randomness, which damages the system power balance and brings difficulties to dispatching. In this paper, wind power output characteristics are described by uncertain sets of wind power output. Considering the positive and negative spinning reserve constraints, a bi-level optimization model is constructed. According to the dual principle, the bi-level optimization model can be transformed into a solvable robust optimization scheduling model. Finally, the numerical simulation shows that the proposed method can realize the utilization of wind power, rationally arrange the commitment operation and output of thermal power units, which has good robustness to wind power output fluctuations to ensure the safe and economic operation of the system.
Face recognition technology based on CNN, XGBoost, model fusion and its application for safety management in power system
Authors: Xu Xianghai , Wang Xuan , Sun Zhiqing , Wang Shouxiang 
Published: February 2021

Abstract
The safety maintenance of operating site is important for safety management in power system. With the development of artificial intelligence (AI) and popularization of monitoring camera, face recognition technology is widely utilized in operating site of power system. To improve the capability for safety management of operating site in power system, a face recognition model based on convolutional neural network (CNN), eXtreme gradient boosting (XGBoost) and model fusion is built. Firstly, pre-processed images are input into CNN to obtain the recognition probabilities of various face and the extracted face features. Secondly, the extracted features of CNN are input into XGBoost to obtain the recognition probabilities of various face recognized by XGBoost. Finally, above two groups of probabilities are weighted by model fusion technology to obtain the final recognition probabilities of various face, and the final face recognition results are output. Simulation results show that CNN has better capability of feature extraction, and the proposed face recognition model has the highest recognition accuracy among those advanced face recognition models. In addition, this paper describes the application based on the proposed face recognition model in non-working personnel recognition, trajectory tracking of operators, etc, so as to greatly improve the safety management of operating site in power system, which not only ensures safety, but also reduces unnecessary management expenses.
Analysis on propagation characteristics of voltage sag through different types of transformers
Authors: Jiang Jiandong , Gao Ang 
Published: February 2021

Abstract
Transformer is a key factor that can not be ignored in the process of voltage sag propagation. In this paper, the transmission characteristics of voltage sag caused by different types of short circuit are analyzed through the different transfer matrix of transformer with different connection methods, including amplitude change, waveform distortion and phase jump. The distribution network model is established by PSCAD, and the propagation characteristics are verified. The conclusion has certain significance for judging the type of voltage sag from the load side, evaluating the degree of voltage sag, and selecting the treatment measures of voltage sag.
Fault identification based on BP neural network and wavelet packet in power systems
Authors: Tao Fang , Qian Sun , Hangli Jian , Ning Li , Yan Zhou , Yanjie She , Zhangao Li , Ying Cai , Leiyu Zhao , Jiang Li 
Published: February 2021

Abstract
This paper proposes a fault identification method based on BP neural network and wavelet packet, which extracts the fault transient eigenvalues of the three-phase current and zero-sequence current from measurement data under the fault conditions. Firstly, the eigenvalues of three-phasors are sampled under the typical faults, such as single-phase ground fault, two-phase short-circuit fault, two-phase ground short-circuits fault, and three-phase short-circuit fault. Secondly, the three-phase current and the zero-sequence current are subjected to wavelet packet transform to extract the eigenvalues, which are viewed as the input of the neural network to determine the fault type. Finally, simulation results show that the proposed method can give reliable identification results under different fault conditions.
Fractional Order PID PLL Controller Based on Particle Swarm Optimization Algorithm
Authors: Tang Yun , Xiong Hejin , Ye Qian 
Published: February 2021

Abstract
In this paper, a Fractional Order PID PLL controller based on particle swarm optimization algorithm is proposed for power grid system. The parameters of Fractional Order PID controller are optimized by particle swarm optimization algorithm, so as to control the orthogonal signal generator in PLL, realize accurate phase discrimination and effectively suppress grid harmonics.In this paper, firstly, the mathematical model of PLL is established, and then the PID controller and Fractional Order PID controller are compared and controlled. Finally, the parameters of Fractional Order PID controller are optimized by particle swarm optimization algorithm to achieve the optimal control.In this paper, the simulation of PLL controller is completed based on MATLAB / Simulink. The simulation results show that the Fractional Order PID based on PSO algorithm can automatically find the optimal control parameters, realize the precise control of PLL, and improve the ability of filtering harmonic and dynamic performance of power grid.
Detection method of voltage sag disturbance based on improved HHT
Authors: Fang Yisheng , Pang Hongyuan , Chen Yong 
Published: February 2021

Abstract
In order to improve the detection accuracy of Hilbert Huang transform (HHT) for voltage sag signal, an improved HHT method is proposed: the boundary local feature scale method is combined with CEEMDAN, the former is used to suppress the end effect in the EMD process, and the latter is used to improve the mode aliasing between IMF components. The simulation results show that the improved method can extract the instantaneo us characteristics of the disturbance signal more accurately and quickly, and realize the accurat e positioning of the start and end moments of the sag. Finally, the measured data is used to compare the traditional HHT and the improved HHT method. The results show that the improved HHT method improves the detection accuracy of the sag signal, and has certain reference value for the study of voltage sag feature extraction.
The effect of PSS on the synchronous condenser to reduce a wind farm included system oscillation
Authors: Maoqing Wang , Wenfeng Li , Shijun Ma , Zongxi Zhang 
Published: February 2021

Abstract
Distributed condenser will be used on wind farm in the future to supply reactive power support to the power system. How would the power system stabilizer (PSS) on the condenser effect the stability of the power system? How to configure PSS parameters to make PSS have better effec? These questions are researched in this paper.
A Recognition Method for Time-domain Waveform Images of Electric Traction Network Overvoltage Based on Deep Learning
Authors: Junyi JIA , Mingli WU , Qi WANG 
Published: February 2021

Abstract
A large amount of time-domain waveform images of overvoltage of electric traction network are collected during the on-board test of EMU. The traditional time-domain or frequency-domain analysis and classification method can’t be directly applied to time-domain waveform images. In order to analyze these images, firstly, image preprocessing is carried out. Then, the data set of time-domain waveform images is established. Finally, the CNN (convolutional neural network) classification model is trained based on data set. The results show that the sensitivity of recognition is above 81%, and this method is suitable for the time-domain waveform image of overvoltage of electric traction network.
Study on generation expansion planning evaluation method based on envelope optimization model
Authors: Maowen ZHOU , Jin CHEN , Zhengsheng WU , hangyu Wan 
Published: February 2021

Abstract
Participants involved in power generation construction were incomplete information and decision-making with bounded rational. Their motivations and behaviours may deviate from environment-friendly and social-welfare generation expansion planning. This paper proposes an envelope optimization model, which aims to meet the goals of minimizing the amount of abandoned water and maximizing the proportion of non-fossil power generation. And it presents a method for evaluating a certain generation expansion planning scheme quantitatively by using this model to calculate non-fossil power sources proportion and abandoned water electricity indicators. Finally, this evaluation method is proved by a regional power system’s generation expansion planning scheme example. The generation expansion planning evaluation method presented in this paper is flexible and practical, which is conducive to guiding and evaluating short-term and long-term regional power development schemes.
Research on battery pack fault pre diagnosis method
Authors: Dong Dong , Tian Yu , Liu Shuangyu , Qian Dongpei , Wang Jonggeng , Lin Decai , Xu Junjie , Yan Guanglong , Lin Xile , Liu Zhongcai 
Published: February 2021

Abstract
At present, most of the BMS in the market set a constant fault threshold, but with the increase of the number of power battery recycling, the external characteristics of the battery will also change. A constant fault diagnosis threshold may also occur after battery aging diagnosis is not timely. Battery cell voltage is the direct embodiment of the external characteristics of battery cell, so the fault diagnosis of battery cell voltage is the most important. Too high or too low cell voltage is the most obvious fault. Normally, this should not happen. Of course, due to the gradual aging of the battery pack, the inconsistency between the monomers and the charged state of each cell, the inconsistency of the voltage of each cell can not be avoided. However, the voltage difference caused by cell manufacture or inconsistency is limited in the case of aging degree.Based on the battery discharge data, the purpose of this study is to propose a method to identify the gradual fault signal in advance and reduce the problems caused by the sudden failure of the battery by detecting and diagnosing the change trend of the extreme value difference of the historical operation data.
Prediction Methods for Energy Internet Security Situation Based on Hybrid Neural Network
Authors: Liu Dongmei , Cheng Jie , Yuan Zilong , Wang Chan , Huang Xingjie , Yin Hongshan , Lin Nan , Niu Haihang 
Published: February 2021

Abstract
Under the duplex framework of the rapid transformation of the conventional power grid to the energy Internet and the swift development of network attack technologies, the security and protection of the energy Internet are becoming increasingly precarious. The energy Internet attack prediction method has become a current research hotspot. The current research in this area is predominantly focused on security to protect and reduce losses, it is impossible to counter the attacks faced by the Energy Internet promptly, and there is a lack of online predictive security analysis methods and tools. Aiming at the shortcomings of traditional research and the current stage, this paper proposes an online prediction and analysis method of energy Internet security situation based on the combination of temporal convolutional neural network (TCN) and gated recurrent neural network (LSTM). This method which based on the security status data set can predict and analyse the region Energy Internet security, and the mean absolute error and mean squared error are 0.352 and 0.2714 respectively. The results show that the prediction performance of the algorithm has been improved, the stability is robust, and it can be applied to the energy Internet security situation prediction.