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Optimisation method for carbon black distribution of polypropylene-based semi-conductive screen materials and its effect on charge emission behaviour at screen/insulation interface

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High Voltage 2023年第2期8卷 239-250页

作者： Jiaming Yang Rui Zhang Xu Yang Zhi Sun Xindong Zhao Hong Zhao Xuan Wang Lin Li Heqian Liu Key Laboratory of Engineering Dielectrics and Its Application Harbin University of Science and TechnologyHarbinChina State Grid Heilongjiang Electric Power Company Limited Electric Power Research Institute State Grid Corporation of ChinaHarbinChina

The semi-conductive(SC)screen materials used in polypropylene(PP)-based cables are usually multi-component *** shows poor compatibility with carbon black(CB),and CB particles tend to disperse in the elastomer phase,which results in CB non-uniform dispersion in screen *** non-uniform distribution of CB will cause abnormal electric fields at the screen/insulation interface and affect insulation *** paper prepared modified PP grafted by molecule maleic anhydride,and four PP-based SC shielding materials were blended in combination with PP,PP-g-MAH,and thermoplastic elastomer(POE)as matrix *** CB distribution,electrical conductivity,and basic physical properties of the shielding material were *** screen materials were served as electrodes to test their effects on the space charge and conductivity characteristics of *** relationship between the macroscopic properties and the distribution characteristics of CB was *** show that the selective dispersion of CB in screen material was improved by PPg-MAH and the surface electric potential distribution was *** emission at the screen/insulation interface and conductivity can be reduced by homogenising the CB ***/PP-g-MAH/POE prepared in this paper exhibits relatively uniform CB distribution,which can reduce the charge emission from the screen/insulation interface.

关键词： insulation distribution interface

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Transformer multimodal data and knowledge encoding method based on attention model 2

Transformer multimodal data and knowledge encoding method ba...

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2nd International Conference on Electrical, Electronics, and Information Engineering, EEIE 2023

作者： Zhang, Peng Zhang, Guoliang Fan, Xiaoyu Gan, Jinrui Wu, Peng Zhou, Fei Lv, Shunli Chen, Long Liu, Xin State Grid Laboratory of Grid Advanced Computing and Applications State Grid Smart Grid Research Institute Co. Ltd. Beijing102209 China NARI Group Corporation State Grid Electric Power Research Institute Nanjing215200 China State Grid Anhui Electric Power Co. Ltd. Hefei230061 China

ISBN: (纸本)9781510672840

Transformers are key hub equipment in the power system, and their operation reliability is directly related to the stability of the power grid. In order to ensure the safe and stable operation of the transformer, monitoring devices such as dissolved gas analysis (DGA), partial discharge (PD), and voiceprint vibration are installed to obtain multimodal data such as structured data, visible light pictures, atlas pictures, and voiceprint data. However, existing fault diagnosis methods cannot integrate these multi-modal features to evaluate the health state of the transformer. In order to solve these problems, a transformer multi-modal data knowledge fusion coding method based on attention model is proposed. For structured state quantities such as online monitoring state quantities and test state quantities, Bi-LSTM is used for encoding to obtain structured state quantity codes. For the partial discharge state quantity, multi-dimensional structured data is extracted from the n-q-φ spectrum and discharge waveform spectrum, and Bi-LSTM is used to obtain the partial discharge structured state quantity codes. For RGB images, an encoding structure including a convolution layer, a pooling layer and a coding layer is constructed to obtain partial discharge image codes. Then, structured state quantity codes, partial discharge structured state quantity codes and partial discharge image codes were fused based on the Attention model, and the fused multi-modal data knowledge codes were used in the fault diagnosis process of the transformer. Multimodal data knowledge encoding technology is applied to transformer fault diagnosis. The application results show that the fault diagnosis accuracy can be significantly improved after fusion and encoding of multimodal data. Compared with the traditional structured state quantity diagnosis model, the accuracy of fault diagnosis is improved. 8.75%, up to 92.50%. © 2024 SPIE.

关键词： Failure analysis

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Research on Capacity Configuration Method of Underwater Compressed Air Energy Storage Considering Offshore Wind power 4

Research on Capacity Configuration Method of Underwater Comp...

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4th International Conference on Energy Engineering and power Systems, EEPS 2024

作者： Shao, Ming Lou, Suhua Wu, Yaowu Lin, Yong Wu, Weijie Zuo, Zhengmin Liu, Peiyu Mo, Mingshan Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan430074 China Power grid planning research center Guangdong power grid corporation Guangzhou China

ISBN: (纸本)9798350366914

In order to cope with the challenges brought by the volatility and randomness of new energy output such as offshore wind power, underwater compressed air energy storage (UCAES) has been widely concerned and has broad development and application prospects. A capacity configuration model of underwater air compressor considering offshore wind power is presented in this paper. Firstly, the model of underwater compressed air energy storage and wind power output is established. Then, the capacity optimization configuration model of UCAES is constructed with the goal of optimal economic benefit. Finally, the model is analyzed according to the solving results, and the results show that the validity of the model is verified. © 2024 IEEE.

关键词： Windmill

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Long-distance power-over-Fiber system based on single-mode optical fiber

Long-distance Power-over-Fiber system based on single-mode o...

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2022 Conference on Infrared, Millimeter, Terahertz Waves and applications, IMT 2022

作者： Niu, Xiaochen Huang, Jie Chen, Shuo Liu, Zhanyuan Lu, Lifeng State Grid Smart Grid Research Institute Co. Ltd. China Electric Power Intelligent Sensing Technology Application of State Grid Corporation Joint Laboratory China

ISBN: (纸本)9781510662476

A system of long-distance power-over-fiber (PoF) was developed, with the research of the nonlinear effect of single-mode fiber, 1550nm photovoltaic cell and power supply. The distance of energy and information transmission is more than 20km. Two low-loss windows of single-mode fiber are separated by a WDM. The band of 1550nm is used for energy transmission and 1310nm for communication. A 1550nm photovoltaic cell with multi junctions was customized, and the photoelectric conversion efficiency reaches 39.8%. Two stage boost circuit are used for maximum energy capture, and the super capacitor is used to achieve stable power supply. The system realizes the shooting of a picture every 10 seconds, and sends back with the data of temperature and humidity. © 2023 SPIE.

关键词： Photovoltaic effects

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Research on Transfer Printing Process Optimization for Flexible Piezoelectric Energy Harvester

Research on Transfer Printing Process Optimization for Flexi...

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2023 Panda Forum on power and Energy, PandaFPE 2023

作者： Gao, Zhidong Li, Chunlong Huang, Hui Zeng, Pengfei Tian, Haoyang State Grid Smart Grid Research Institute Co. Ltd Elec. Power Intelligent Sensing Technology and Application State Grid Corporation Joint Laboratory Beijing China State Grid Shanghai Electric Power Research Institute Shanghai China

ISBN: (纸本)9798350321173

With the rise and development of flexible energy harvester, transfer printing has become the key technology affecting the success rate of flexible energy harvester manufacturing. And some brittle micro structures are very easy to fail in the complex transfer printing, resulting in the transfer success rate has been very low. In this paper, optimized seal transfer printing process is proposed, and the transfer release time is shorten to 10min by studying the influence of different sacrificial layer materials and different ratios of corrosion liquid on the release time of the structure from the rigid substrate, meanwhile, the corrosion resistance of the photoresist protective layer is improved by studying the influence of different coating rotation speed on the glue floating time, then, through the above work, the success rate of the seal transfer printing process is improved. © 2023 IEEE.

关键词： Photoresists

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Pre-trained Language Model for Chinese Frame Semantic Parsing based on Electric power Dataset 4

Pre-trained Language Model for Chinese Frame Semantic Parsin...

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4th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2023

作者： Wang, Xiaohui Liang, Yundan Gui, Chenwei Wang, Boya Wang, Gaozhou State Grid Laboratory of Grid Advanced Computing and Applications Beijing China State Grid Corporation of China Beijing China University of International Relations Lab of Intelligent Social Computing Beijing China State Grid Shandong Electric Power Company Information and Telecommunications Company Shandong China

ISBN: (纸本)9798350373233

In the operational landscape of the electric power industry, a wealth of events, operations, and fault reports generates substantial textual data. The application of frame semantic parsing to the power grid system presents challenges, especially given the distinctive characteristics of Chinese text, including entity ambiguity, word segmentation issues, and a misalignment with knowledge in the power systems field. In response to these challenges, we introduce an innovative pipeline specifically designed for Chinese semantic analysis based on an electric power dataset, showcasing significant enhancements over the baseline. This research strives to drive technological advancements, fostering a more sophisticated understanding of textual data within the intricate domain of the Chinese electric power industry, with a particular focus on natural language processing. © 2023 IEEE.

关键词： Pipelines

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Energy Loss Analysis of Distributed Rooftop Photovoltaics in Industrial Parks

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Energy Engineering 2023年第2期120卷 511-527页

作者： Yu Xiao Kai Li HongqiaoHuang Haibo Tan Hua Li State Grid Hunan Electric Power Corporation Limited ChangshaChina Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology ChangshaChina Hunan Institute of Metrology and Inspection ChangshaChina

The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users,energy-saving service companies,and power grid companies,so it has always been the focus of the industry and society in some manner or ***,the related analysis for an actual case that considers different cooperative corporations’benefits is lacking in the presently available *** paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object,studies the analysis and calculation methods of line loss and transformer loss,analyzes the change of transformer loss under different temperatures and different load rates,and compares the data and trend of electricity consumption and power generation in industrial parks before and after the photovoltaic *** paper explores and practices the analysis method of the operating loss of distributed photovoltaic power generation and provides an essential reference for the benefit analysis and investment cost estimation of distributed photovoltaic power generation systems in industrial *** analyzed results reveal that the change loss is stable after the photovoltaic is connected,and there is no additional transformer *** before and after the photovoltaic system installation,there was no significant change in the total monthly data difference between the total meter and the sub-meter.

关键词： Distributed photovoltaic generation line loss transformer loss power generation

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Communication Protocol Optimization of Electric Low power Wireless Sensor Network Based on Active Wakeup 1

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10th Frontier Academic Forum of Electrical Engineering, FAFEE 2022

作者： An, Chunyan Huang, Ziwei State Grid Smart Grid Research Institute Co. Ltd. Beijing102209 China Electric Power Intelligent Sensing Technology and Application of State Grid Corporation Joint Laboratory Beijing102209 China

ISBN: (数字)9789819934089

ISBN: (纸本)9789819934072

Most electric sensors are powered by battery and have strict requirements on energy consumption. The existing communication protocol of electric low power wireless sensor network (e-LPWSN) usually periodically wakes up sensors to save energy. This paper studies the communication protocol optimization of existing e-LPWSN based on active wakeup, where energy consumption is further reduced by minimizing not only the wake-up times, but also the retransmission due to channel collision. Besides, the proposed method can support both ACK and alarm transmission. Simulation results have shown that the proposed method can greatly improve data transmission success rate, and can reduce the energy consumption of sensors by more than 20%. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Energy utilization

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Seasonal Forecasting Model of Data Center Net Load Based on LSTM-Attention Fusion Neural Network

Seasonal Forecasting Model of Data Center Net Load Based on ...

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IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Zhichao Li Shuya Lei Qifeng Huang Fei Zhou Meimei Duan Yixuan Huang Kaijie Fang Lan Ren State Grid Corporation Laboratory of Power Grid Advanced Computing and Application Technology (State Grid Smart Grid Research Institute Co. Ltd) Beijing China State Grid Jiangsu Electric Power Company Marketing Service Center Nanjing China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

Accurate load forecasting of data centers is an important supporting means for them to participate in demand response or power market. In view of the problems such as large errors and poor stability existing in current load forecasting methods of data centers, and considering the differences of cooling loads in different seasons, in this paper, a LSTM-Attention fusion neural network model based on Attention mechanism is proposed for the net load prediction of data centers. LSTM neural network is used to extract the time series characteristics of data center loads, and then the Attention mechanism is added to capture the fluctuation characteristics to improve the prediction accuracy. Based on the data set provided by the National Renewable Energy laboratory (NREL), seasonal forecasting is carried out in this paper. The results show that the introduction of the Attention mechanism in the model can effectively improve the accuracy of data center load forecasting, and the model has transferability.

关键词： Data centers Load forecasting Cooling Neural networks Time series analysis Predictive models Data models

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Traceability technology of DC Electric Energy Metering for On-Site Inspection of Chargers

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Energy Engineering 2023年第3期120卷 715-727页

作者： Hua Li Dezhi Xiong Zhi Wang Hunan Institute of Metrology and Inspection Changsha410018China State Grid Hunan Electric Power Corporation Limited Changsha410001China Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha410001China

The on-site inspection of high-power DC chargers results in new DC high-current measurement and DC energy traceability system *** paper studies the traceability technology of electric energy value for automotive high-power DC chargers,including:(1)the traceability method of the built-in DC energy meter and shunt of the charger;(2)precision DC high current and small precision DC voltage output and measurement *** paper designs a 0.1 mA∼600 A DC high current measurement system and proposes a 0.005 level DC powermeasurement traceability *** uncertainty evaluation experiment of theDC powermeasurement calibration system and the high-power DC charger’s on-site calibration experiment results verify the method’s effectiveness and feasibility in this *** experimental results show that the combined standard uncertainty of the DC power metering verification system can be 0.0451%.

关键词： DC electric energy measurement charger traceability calibration

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