bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on power-load matching dispatching of Hydro-Wind-PV hybrid system in cascade
Authors: Liu Fang , Wang Yunling , Su Yunche , Xu Ke , Chen Wei , He Xingqi , Wu Gang , Ju Chengqian 
Published: February 2023

Abstract
With the goal of “double carbon,” wind power and PV are connected to the grid on a large scale, which poses a great challenge to the safe operation of the grid. The synergistic optimization of “hydro-wind-PV hybrid systems” can bring into play the ability of coordination and mutual assistance between different types of power sources, which is one of the important measures to increase the safe operation of the power grid and reduce abandoned wind and photovoltaic power. Based on the analysis of the characteristics of hydro-wind-PV power, the “hydro-wind-PV” integrated network-source cooperative optimization scheduling model is constructed to maximize the source-load matching and the consumption of clean energy. Finally, the results of a case study of a hydropower-wind power-photovoltaic cluster project in southwest China are used to verify the rationality and feasibility of the model.
Improvement of Grid-connected Reactive Power Compensation for Wind Farms Based on STATCOM
Authors: Lan Ying , Du Shang 
Published: February 2023

Abstract
Due to the recent rapid development of wind power generation, people have higher requirements for the stability of wind power systems. The randomness and intermittency of wind farms are strong. When the system is disturbed, or the line fails, it is easy to cause voltage instability. In order to ensure the stable operation of the power system, it is necessary to set up a static reactive power compensation device (STATCOM) to provide reactive power in the power system. This paper simulates and analyzes the wind power generation system with a STATCOM device. The results show that the operation process of the wind power system with STATCOM is more stable.
A Novel Ultra-short-term Photovoltaic Power Generation Forecasting Method Based on Seasonal Autoregressive Integrated Moving Average
Authors: Wang Xueying , Gao Yuan , Long Xuanchen 
Published: February 2023

Abstract
This study suggests an ultra-short-term photovoltaic (PV) energy generation forecasting model based on Seasonal Autoregressive Integrated Moving Average (SARIMA) and Support Vector Machine (SVM). It can further increase the predictive performance of PV electricity generation electrical output and address the issue of significant fluctuation and instability of PV power generation output power. To achieve combined prediction, SVM is employed in this study to model the nonlinear SARIMA prediction residuals. In comparison to the traditional SVM method and the SARIMA method, the mixed forecasting method has a good forecasting consequence and can serve as a favorable basis for the safe operation and scheduling of the PV grid, according to the results of the simulation of actual data.
Research on Power Sensing Data Quality Assessment Method Based on Hierarchical Analysis Method
Authors: Liu Weixin , Zhang Xiaolei , Zhuang Yajie , Ding Yang , Liu Xiaojian , Yang Jijun 
Published: February 2023

Abstract
Various types of sensors deployed in power networks are susceptible to bad weather, intrinsic defects, and other effects to produce missing, duplicate, and other abnormal data, which reduces the accuracy of equipment condition evaluation results. Power sensing data is an important way for operation and maintenance personnel to understand the status of the equipment, but there is less research on data quality assessment. This paper addresses this deficiency, designs evaluation rules based on sorting out data characteristics, and constructs a quantitative data evaluation model based on the hierarchical analysis method. Based on the model in this paper, the data quality assessment of the measured micro-meteorological sensor data is carried out, and the data scores are given quantitatively. The conclusions of this paper show that the constructed quantitative data assessment model can effectively achieve sensing data quality scoring, which can assist operation and maintenance personnel in understanding the status of sensing equipment.
Abnormal Operation Detection of Access Equipment in Dispatching Exchange Network Based on Data Mining
Authors: Zhai Hongting , Zhang Qingrui , Sun Lili , Zhang Yantong , Zhai Qi 
Published: February 2023

Abstract
To meet the requirements of a power dispatching service, a dispatching switching network has been widely used instead of circuit switching technology. However, with the growth of the number of access devices, the problem of network security is becoming more and more serious. At present, the commonly used access equipment abnormal operation detection method mainly relies on a two-stage clustering method to identify the abnormal operation state, but the processing effect is not good in the face of a large number of data, resulting in a low F1 value of the final detection result. Therefore, aiming at the access equipment of the dispatching exchange network, an abnormal operation detection method based on data mining is proposed. Scapy, a network tool, is used to capture the traffic data of access devices, and the collected data are normalized and fused. Data feature information is extracted through time sliding window and incremental calculation mode. With the clustering algorithm and related rules in data mining as the core, the abnormal operation detection method of access equipment is designed to obtain accurate abnormal detection results. Finally, based on the recursive graph structure, the detection results are visualized. The experimental results show that the average F1 value of the detection results of the proposed method is 0. 98, which indicates that the detection results of the proposed method have higher accuracy, and based on this, the network security isolation is carried out, which effectively improves the security of dispatching switching network.
Photovoltaic Power Prediction Based on EMD-BLS Model
Authors: Bao Yang , Guo Wei 
Published: February 2023

Abstract
While the energy consumption structure is changing in this world, the consumption rate of renewable energy is gradually increasing. This paper takes photovoltaic power as the research object, analyses the power curve characteristics in different climatic change situation and the correlation between different weather factors and photovoltaic(PV) power output, and then puts forward a photovoltaic power prediction model based on empirical mode decomposition-broad learning system (EMD-BLS). First, the PV power historical sequence needs to be reconstructed after pretreatment, then the EMD method is used to decompose the reconstructed output sequence. The broad learning system model is established for each subsequence. Finally, the prediction results of each sub-series are superimposed to get the prediction of photovoltaic generation. The model is tested with a genuine data of photovoltaic power generation in a region of our country. Compared with the traditional broad learning system (BLS), extreme learning machine (ELM), LSTM, and other prediction models, The prediction error of the proposed model is lower, which can effectively improve the prediction accuracy of photovoltaic power generation.
Research on the control strategy of LCL-type PV grid-connected inverter
Authors: Li Tao , Fu Liyou 
Published: February 2023

Abstract
This paper examines a three-phase grid-connected photovoltaic inverter using LCL technology. Circuit for a full-bridge inverter with three phases and a filter of type LCL are used, and the control strategy consisting of two closed-loop loops is used to remove the effects caused by harmonics on the system. Finally, the simulation and analysis are carried out by MATLAB software to express the possibility of inverter system operation in a more intuitive way, such as a waveform diagram, to verify the rationality of the paper.
Double power sliding mode control of permanent magnet synchronous motor based on high-order sliding mode method
Authors: Li Zhenghao , Wang Ying 
Published: February 2023

Abstract
In view of the shortcomings of traditional sliding mode control of permanent magnet synchronous motor (PMSM), such as slow convergence, serious speed overshoot and outstanding chattering, an improved dual power approach law is proposed. Combined with the equivalent control, a high-order sliding mode rotor is designed by using the second-order nonsingular terminal sliding surface, which greatly improves the dynamic and static performance of the motor and effectively suppresses chattering. The simulation results show that the convergence speed of the improved dual-power reaching law is faster and the anti-disturbance ability of the system is significantly improved.
Research on Visual Inspection System of Distribution Network Based on Unmanned Aerial Vehicle
Authors: Wang Yi , Wang Yong , Zhang Lei , Liu Siyuan , Li Quan 
Published: February 2023

Abstract
The increasing data acquisition information in the distribution network brings new challenges to the monitoring and management of the distribution network. Therefore, this paper proposes a visual inspection system of a distribution network based on UAVs. The overall system hardware and UAV flight control power supply hardware are designed. The distance between the UAV and the obstacles is calculated by detecting the duration of laser signal reception. The visual inspection of the UAV obstacle avoidance power distribution network is carried out. The visible light, infrared, and laser data are fused, multi-source data are processed cooperatively, and the visual inspection information is collected and summarized. The test results show that the system has high efficiency and can provide accurate information for power system operators and managers in a relatively timely manner.
Short-term wind power prediction model based on ARMA-GRU-QPSO and error correction
Authors: Wu Xinhua , Chen Nan , Du Qianyun , Mao Shuangshuang , Ju Xiaoming 
Published: February 2023

Abstract
Power system dispatch benefits from accurate wind power predictions. To increase the prediction precision for wind power, this paper proposes a combined model for predicting short-term wind power based on the autoregressive moving average-gated recurrent unit (ARMA-GRU). Firstly, we build the ARMA model and GRU model respectively to predict wind power. Then we optimize the combined model’s weights by quantum particle swarm algorithm (QPSO). Finally, we build an error correction model for the prediction errors to acquire the final results for the wind power predictions. Our experimental results prove the model’s reliability and the model’s high predictability is verified by comparing different prediction models.
Research on Energy Dissipation Technology and AC Overvoltage Suppression of Sending End in UHVDC Transmission
Authors: Huang Yongrui , Han Kun , Hu Qiuling , Zhang Wenbo , Yuan Hongtao , Shao Zhuke , Cui Xiaochen 
Published: February 2023

Abstract
For suppress the amplitude of overvoltage from HVDC sending terminal, an overvoltage suppression scheme based on the principle of controllable energy dissipation was proposed. The overvoltage mechanism of a weak AC system under the fault of the DC system was analyzed, and the method and operating principle of the CSREDD were proposed. Prototype of the develop CSREDD was tested, which proved correctness about the design. The controllable energy dissipation device has been successfully applied to the ±800kV Lu-Gu UHVDC transmission project. The operation results show that the controllable energy dissipation device can effectively suppress the AC overvoltage.
Optimal scheduling of power system with wind power considering deep peak regulation of fire-storage and demand response
Authors: Zhang Shi-qi , Yin Chang-yong 
Published: February 2023

Abstract
In the context of the integration capacity of wind power has increased rapidly, because the large sporadic and instability characteristics of wind power machinery, it has brought challenges in peak adjustment of power equipment machinery. Therefore,if we want to increase the peak load capacity of the electric power channel, we should improve the consumption of new energy. This constructs a electric power channel optimization model with demand response and a unit-peaking output model. The validity of the example is verified.
Intraday rolling optimal dispatch model of power system considering supply-demand interaction
Authors: Han Yaxuan , Dong Zhixin , Liu Dunnan , Wang Xuanyuan , Ning Bu , Liu Zhen 
Published: February 2023

Abstract
The participation of demand-side resources in grid operation and regulation, in coordination with the generation side, can jointly ensure a stable supply of electricity. The application of control technology in the energy field makes demand-side resource control methods more flexible and intelligent, thus providing a technical guarantee for demand-side resources to participate in the power market. This paper discusses the interaction between demand-side resources and the generation side and establishes an intraday rolling optimal dispatch model for demand-side resources. Finally, it is demonstrated through simulation that refining the multi-dimensional response characteristics of demand-side resources in the intraday dispatch model can improve the operational economy of the system and the flexibility of the scheduling model to cope with uncertainties.
Transformer state prediction based on CSSA-BP neural network algorithm
Authors: Jing Zhipeng , Chai Linjie , Hu Shiyao , Wu Yuchen , Pan Sichao , Wang Xi 
Published: February 2023

Abstract
As an important part of the power system, it is particularly important for the monitoring of the status of the power transformer in real time opearation. A transformer winding temperature prediction method through swarm intelligent optimization algorithm (CSSA) and BP neural network is proposed. Firstly, the CSSA-BP prediction model of the winding’s temperatur of dry-type transformer is established, and the existing 300 groups of data on the cloud platform are used for simulation analysis. The results show that, through the optimization by sparrow algorithm, the proposed model has a good prediction performance and is of great significance for realizing transformer winding temperature monitoring.
Analysis and Design of Integrated Intelligent Anti-error System for Substation
Authors: Huang Jin , Shan Changwang , Dong Kang , Zhang Yang , Yu Hao 
Published: February 2023

Abstract
A new comprehensive intelligent anti-error system that meets the requirements of smart substations is proposed. This new system can overcome the problem that the microcomputer anti-error system lacks operation error prevention technology for secondary equipment and also lacks operation and maintenance operations under the integrated control operation mode. Firstly, this paper analyzes the characteristics of the anti-error system, and the principle function of the judgment model. And then, an anti-misoperation process system is established for work scenarios such as information collection and monitoring, remote control operation error prevention, sequential control operation error prevention, local operation error prevention, secondary equipment, operation, and maintenance. This paper finally builds a realtime online anti-error system that can be intelligently analyzed for the whole business process to ensure the safety of intelligent substation equipment operation.
Multi-objective Optimization of Relay Protection Setting Based on MOAHA Algorithm
Authors: Li Hao , Wang Haotian 
Published: February 2023

Abstract
With the expansion of the power grid scale, more and more relay protection devices exist in the power system, and the optimization of node protection setting values has also begun to receive attention. Conventional genetic algorithm is mainly used in the current multi-objective optimization solution of relay protection fixed value, and its multi-objective optimization procedure is relatively complicated, resulting in low optimization solution efficiency. Therefore, applying the multi-objective artificial hummingbird algorithm (MOAHA) to the optimization process is proposed to obtain a new fixed-value multi-objective optimization method for relay protection. According to the set value requirements of the relay protection, a multi-objective optimization model of the set value of the relay protection is established, and the constraints are determined. Regarding the grid vulnerability coefficient, calculate the weighting factor corresponding to each constraint condition. Then, the multi-objective artificial hummingbird algorithm is applied to design a simple multi-objective optimization mode, including two stages of self-search and guided search to obtain fixed-value optimization results. The results of the example analysis show that the proposed optimization method only needs 20 iterations to output the optimal solution, and the average time spent to obtain the optimal solution is 17.6s. It can play a prominent role in the global optimization and tuning of relay protection in large power systems.
Fuse welding and tin integration automatic machining device
Authors: Chen Jingmao , Huang Zhenyuan , Kuang Kongcai , Chen Jian 
Published: February 2023

Abstract
In order to solve the problems of low efficiency and difficulty in adding tin to the end cap in the production process of the fuse, the unstable amount of tin resulted in over-welding and fake-welding. This paper designed and manufactured a set of automatic equipment for welding and adding tin to the fuse. The feeding device can accurately feed the end cap; a set of disc cutter structures with a feeding machine is used to cut the tin wire, and the cut tin wire accurately falls into the end cap of the fuse. The heating device is designed to melt the tin wire into liquid in the end cap. The cooling device makes the liquid tin condense into a solid in the end cap to realize the function of automatically adding tin to the end cap of the fuse. Through the actual production verification, it is proved that the equipment structure is reasonable and can meet the actual production requirements.
Design and Implementation of Protocol Conversion of Intelligent Power Distribution Equipment for New Power System
Authors: Shao Zhimin , Peng Ganrong , Sun Jinhua , Zhang Ruobing 
Published: February 2023

Abstract
A protocol conversion method of intelligent distribution equipment for a new power system is proposed to aim at the problems of short data reading distance and high data packet loss rate in the current protocol conversion process of intelligent distribution equipment. The protocol conversion process of the equipment is divided into two parts, the uplink channel, and the downlink channel. The multi-protocol conversion process of the intelligent distribution equipment is designed. A data-based protocol conversion scheme is set up to realize the bidirectional conversion of the protocol. The original protocol conversion gateway is replaced by the CAN-PROFINET protocol conversion gateway to control the network message throughput and realize the protocol conversion of the intelligent power distribution equipment. The experimental results show that the method can effectively extend the data reading distance and reduce the data packet loss rate to a certain extent, which provides a new development direction for the new power system network control technology.
Bit-Serial Logical Operation Processor Based on Shift Registers and Mealy Machine
Authors: Shen Luyi 
Published: February 2023

Abstract
With the rapid development of modern processors, logical operation processors could not only process data by logical operations but also store the data. The logical operation processor designed in this paper will be the bit-serial logical operation processor. In order to build the processor, four units should be designed first: the Shift Register Unit, Computation Unit, Routing Unit, and Control Unit. Among them, the Register Unit and the Control Unit are the most important. For the Register Unit, there will be two 4-bit registers. For the Control Unit, this circuit will implement a Mealy machine to determine the output and state of the circuit. The input to the processor will first get into the Control Unit, and then the data given outside will be stored in the Shift Register Unit and will be input to the Computation Unit and finally returned to the Shift Register Unit after Routing Unit. Since the processor is operating in series, the Control Unit and the Shift Register Unit should work synchronously.
Design and implementation of electrical engineering experiment based on the Arduino platform
Authors: Chen Yuxuan , Li Yi , Shi Xinyi , Zhang Chengyi 
Published: February 2023

Abstract
Arduino platform is a new hardware and software combination platform that is widely used, flexible, easy to operate, and rapidly developing. In this paper, the design and implementation of the DC chopper circuit were conducted based on the Arduino platform. Firstly, the power signal and trigger signal are output in the form of programming on the Arduino platform, and the rest of the circuit is built on the breadboard in the form of hardware. Finally, the design waveform is obtained. This paper introduces the basic working principles of four power conversion circuits, conducts circuit simulation on MATLAB software and obtains the ideal output waveform, and uses C language programming to trigger control signal generation, generates corresponding electrical signals through compilation and USB wire transmission to Arduino controller, and builds relevant circuits. This paper makes use of the advantages of the breadboard, fully combines the theoretical knowledge and circuit connection, and finally observes the output waveform through an oscilloscope, and compares the waveform of the actual circuit with the simulation results of MATLAB.
Urban Intersection Simulation and Verification via Deep Reinforcement Learning Algorithms
Authors: Liao Hanlin 
Published: February 2023

Abstract
Reinforcement Learning (RL) uses rewards to have iteration and update the next state for training in an unknown and complex environment. This paper aims to find a possible solution for the traffic congestion problem and train four Deep Reinforcement Learning (DRL) algorithms to verify the urban intersection simulation environment in the different discussed dimensions, including practicability, efficiency, safety, complexity, and limitation. The experiment result shows that the four DRL algorithms are efficient in the RL intersection simulation. This paper has succeeded in verifying this RL environment in the comparison and expands the experiment with three conclusions: The agent can train by Deep Q-network(DQN), DoubleDQN, DuelingNet DQN, and Categorical DQN algorithms to be practical and efficient. As the experiment results show, DuelingNet takes less time to finish the training, and Categorical DQN has reduced the collision rate after a while. However, the RL simulation environment lacks complexity, causing limitations in solving more complex problems, including the lack of simulation of pedestrian behaviors and the prediction of emergency events. This paper recommends creating a more complex urban intersection simulation that includes exceptional cases for the RL agent environment and more traffic pressure for the intersection to improve the faster and safer response in future automatic driving.