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IEEE power and Energy Society General Meeting

作者： Xinfei Yan Haiwang Zhong Jianxiao Wang Zhenfei Tan State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Beijing China

With an increasing penetration of distributed energy resources (DERs) in Energy Internet, there is a surge of interest in distributed economic dispatch (DED) problems. The existing literature mainly focuses on average consensus algorithms, the convergence of which remains a bottleneck in practical applications. To improve the convergence rate of DED, this paper proposes a consensus algorithm based on optimized transition matrix (TM) of Markov chain. A DED model is firstly developed under a consensus-based information exchange architecture, in which a generator only communicates with its neighbors. Thus DED is implemented in an iterative manner with generators exchanging information according to a predefined TM. In contrast to the aver-agely weighted TM, we minimize the Frobenius norm (F-norm) of the TM in order to limit the eigenvalues that greatly influence the convergence rate of DED. Additionally, a virtual power method is introduced to meet generators' power limits by reformulating the power allocation ratio. Case studies verify the effectiveness and efficiency of the proposed algorithm.

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The parameter design method of smoothing inductance based on MMC-MTDC with R-type superconducting fault current limiter

The parameter design method of smoothing inductance based on...

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The 16th IET International Conference on AC and DC power Transmission (ACDC 2020)

作者： P. Guo Z. Yuan G. Liu Y. Zhao Z. Shi Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing China Shenzhen Power Supply Corporation Shenzhen China Sichuan Energy Internet Research Institute Tsinghua University Chengdu China

The rapid increase of voltage sourced converter brings the great development of the multi-terminal DC technology, both in the DC transmission and DC distribution fields. However, because of the weak impedance characteristic of the VSC-HVDC system, how to suppress and clear DC fault currents becomes a challenge. Considering the stability, the response speed and the system structure, it is not possible to apply excessive inductance at the DC side, hence, the current limiting effectiveness is relatively restricted. On the one hand, with the effective properties, Resistive type Superconducting Fault Current Limiter (R-SFCL) becomes an effective device to solve the problem of VSC-HVDC system under DC faults. On the other hand, because of dynamic energy-impedance characteristics of R-SFCL, the fixed impedance selection method at a certain time to carry out dynamic current limiting analysis is no longer applicable. Therefore, the DC fault current research and R-SFCL characteristic are comprehensively analyzed firstly in this paper. Based on that, a smoothing inductance determination method is proposed to cut off the DC fault current by DC breaker and ensure the continuous operation of remaining parts. Finally, based on a multi-terminal DC system simulation, the improvement and effectiveness of the proposed method are validated.

关键词： power transmission faults HVDC power transmission superconducting fault current limiters HVDC power convertors voltage-source convertors

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Ultra-short-term Bus Load Forecasting Method Based on Multi-source Data and Hybrid Neural Network

Ultra-short-term Bus Load Forecasting Method Based on Multi-...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Shixiong Fan Xingwei Liu Weiwei Ma Wei Zhang Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China State Key Laboratory of Advanced Power Transmission Technology Global Energy Interconnection Research Institute co.Ltd. Beijing China National Power Dispatching and Control Center State Grid Corporation of China Beijing China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

Bus load forecasting plays an important role in terms of the safety of power grid dispatching and operation and the accuracy of online analysis and decision-making. In order to improve accuracy of bus load forecasting, this paper proposes an ultra-short-term load forecasting method based on multi-type data and hybrid model. Under the background of power big data, the multi-type data such as historical bus load data, date information and weather information are firstly taken as the input features of the prediction model, which is established based on the fusion of back propagation (BP-ANN) neural network and convolutional neural network(CNN). BP-ANN is used to extract the feature vectors of numeric type and category type data, which is concatenated with feature vectors extracted by CNN from image type data. The combined features are fed to a fully connected multilayer Neural Network to predict the bus load. In this paper, the historical data of active power load at the high voltage side of a 220kV substation in a certain area of China and the corresponding weather information are used for example analysis. The analysis of experimental results shows that the proposed method can make full use of the characteristics of multi-source data to conduct ultra-short-term bus load prediction, and it has higher load prediction accuracy compared to the single model prediction of BP-ANN and CNN.

关键词： Load forecasting Neural networks Predictive models Feature extraction Data models Data mining Load modeling

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A comprehensive intention prediction method considering vehicle interaction

A comprehensive intention prediction method considering vehi...

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Conference on Vehicle control and Intelligence (CVCI)

作者： Wenqi Cai Ganglei He Jianlong Hu Haiyan Zhao Yuhai Wang Bingzhao Gao Qingdao Legee Transmission System Technology Co. Ltd Qingdao China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun China Qingdao Automotive Research Institute Jilin University Qingdao China

ISBN: (数字)9781728184975

ISBN: (纸本)9781728184982

In this paper, an interactive intention prediction method is proposed. Firstly, the Hidden Markov Model integrated with Gaussian Mixture Model is modeled for current behavior recognition and its parameters are trained through NGSIM dataset. Then, a trajectory prediction method based on Frenet frame is used to predict the future traffic situation, considering which future behavior reasoning is realized by maximum expected utility theory. The final intention prediction result is a combination of historical trajectory recognition and future behavior reasoning. The simulation results show that the proposed method has the ability of reasonably reflecting the interaction process between vehicles and the prediction performance is good.

关键词： Utility theory simulation Hidden Markov models Prediction methods Cognition Trajectory Gaussian mixture model

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A two-stage optimization model for floating offshore wind farm layout and control

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Renewable Energy 2025年 253卷

作者： Tao, Siyu Yang, Jisheng Zheng, Gang He, Ruiyang Feijóo-Lorenzo, Andrés E. College of Automation Engineering Nanjing University of Aeronautics and Astronautics No. 29 Jiangjun Road Nanjing211106 China Department of Building Environment and Energy Engineering Hong Kong Polytechnic University No. 102 Pokfulam Road Pok Fu Lam Hong Kong 999077 China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing100084 China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Monash Biomedical Imaging Monash University Clayton VIC3800 Australia School of Engineering Cardiff University CardiffCF243AA United Kingdom Department of Electrical Engineering University of Vigo Vigo36310 Spain

The effective planning of wind turbine (WT) positions in a wind farm (WF) plays a crucial role in capturing wind energy and increasing power generation. control optimization of WT attitudes can also help reduce wake effects and increase power generation, thereby maximizing the annual electricity production (AEP) of a WF. In this paper, a two-stage optimization model is proposed for planning the stationary layout of floating offshore wind farms (FOWFs), as well as the positions and attitudes of the floating offshore wind turbines (FOWTs) via optimal control. In the first stage, a competitive particle swarm optimizer (CPSO) is employed to generate multiple FOWF layouts. In the second stage, the genetic algorithm (GA) is utilized to optimize the yaw angles and axial induction factors of the FOWTs for operation control. Unlike the existing approaches that address WT layout design and operation control sequentially and separately, the proposed method integrates these aspects to simplify the FOWTs operation and to improve their performances. Additionally, taking the movable characteristics of the FOWTs into consideration, the proposed model incorporates the positional movement of the FOWTs under varying wind conditions, making the power calculations more realistic. Case studies demonstrate that compared with the traditional layout-only optimization, the proposed two-stage optimization model can help increase the AEP of the FOWFs by 4.72 %. © 2025 Elsevier Ltd

关键词： Genetic algorithms

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Frequency Security Assessment for Receiving-end system Based on Deep Learning Method

Frequency Security Assessment for Receiving-end System Based...

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IEEE/IAS Industrial and Commercial power system Asia (I&CPS Asia)

作者： Changhui Ma Liang Wang Chenhao Gai Dong Yang Pengfei Zhang Hengxu Zhang Changgang Li State Grid Shandong Electric Power Company Electric Power Research Institute Jinan Shandong China State Grid Shandong Electrical Power Company Dispatch and Control Center Jinan Shandong China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan Shandong China State Grid International Development Limited Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

For hours-ahead assessment of power systems with a high penetration level of renewable generation, a large number of uncertain scenarios should be checked to ensure the frequency security of the system after the severe power disturbance following HVDC blocking. In this situation, the full time-domain simulation is unsuitable as a result of the heavy calculation burden. To fulfill the quick assessment of the frequency security, the online frequency security assessment framework based on deep learning is proposed in this paper. The Deep Belief Network (DBN) method is used to establish the framework. The sample generation method is researched to generate representative samples for the purposed of higher assessment accuracy. A large-scale AC-DC interconnected power grid is adopted to verify the validity of the proposed assessment method.

关键词： Industrial power systems Asia Conferences

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A Robust Line Parameter Identification Method Based on LSTM and Modified SCADA Data

A Robust Line Parameter Identification Method Based on LSTM ...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Lingyan Que Liqiang Yang Haifeng Qian Jianqiang Shen Lei Zhang Feiyang Xu Jing Ma Chao Chen Ancheng Xue Electric power dispatching control center State Grid Zhejiang Electric Power Company Limited Hangzhou China Huzhou Power Supply Company State Grid Zhejiang Electric Power Company Limited Huzhou China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source North China Electric Power University Beijing China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

Transmission line parameters are the basis of power system calculation, and their accuracy directly affects the safe and stable operation of the system. At the same time, with the improvement of computing power and the rapid growth of the amount of power grid operation data, deep learning has developed rapidly and applied in power systems. However, there is little research on line parameter identification combined with deep learning. Therefore, from the perspective of line model and deep learning, combined with median estimation and modified Supervisory control And Data Acquisition (SCADA) data based on line model, this paper proposes a robust method for parameter identification of transmission line based on Long Short-Term Memory (LSTM) and modified SCADA data. Speciffically, the overall process of the line parameter identification method based on LSTM is given first. Then the settings of the proposed method are introduced in detail. Combined with the line model, a modified input data based on the SCADA data is constructed, and a multi-case training set considering different operating conditions and different line parameters is established. According to a large number of tests, the optimized parameter configuration of the LSTM is given. Finally, the median estimation is used to give the parameter identification results. Case studies in simulated and measured data verify the effectiveness and robustness of the proposed method.

关键词： Deep learning Training Parameter estimation power transmission lines Estimation Transmission line measurements Data models

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Research on the corrosive effect of inactive sulfur on oil-paper insulation

Research on the corrosive effect of inactive sulfur on oil-p...

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International Conference on High Voltage Engineering and Application, ICHVE

作者： Sihang Gao Jiajun Li Tingjing Ke Yang Liu Dong Ding Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China State Grid Chongqing Electric Power Company Chongqing Chongqing China Baoding Electric Power Corporation Baoding China State Key Laboratory of Transmission & Distribution Equipment and Power System Safety and New technology Chongqing University Chongqing China

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Sulfur corrosion induced by active sulfur has been proved to significantly decrease the insulation performance of oil-immersed equipment. In order to protect the oil-paper insulation from sulfur corrosion, active sulfur is cleared in the refining process of crude oil. Some inactive sulfur with high-efficiency antioxidant is still retained in the mineral oil to improve the oxidation stability of oil, such as thiophenic compounds. However, the corrosive effect of inactive sulfur on the oil-paper insulation has not yet clear. Therefore, thiophene that is the largest content of sulfide in the insulating oil was selected as the research object, a series of accelerated thermal ageing experiments of oil-paper without and with thiophene under the different high temperature were conducted, scanning electron microscope equipped with an energy-dispersive X-ray spectrometer (SEM/EDX) and inductively coupled plasma atomic emission spectrometry (ICP-AES) were used to characterize the corrosion degree of oil-paper insulation. The results show that no corrosive deposit was observed on the surface of oilpaper insulation without thiophene even at very high temperature, while a few corrosive deposit was accumulated on the surface of oil-paper insulation with 500 mg/kg thiophene. The corrosion degree of oil-paper insulation with thiophene had an uptrend as the increase of temperature (130°C-180°C), preliminarily indicating that thiophene may be activated in the oil-paper system under the action of overheating fault of oil-immersed transformer and posed a corrosion threat to oil-paper insulation.

关键词： Copper Sulfur Corrosion Oils Windings power transformer insulation Oil insulation

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Investigation on Insulating Properties of Epoxy Resin Impregnated Paper Affected by Curing Agents and Accelerator Contents

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IEEE Transactions on Dielectrics and Electrical Insulation 2025年

作者： Teng, Chenyuan Ding, Yichao Zhou, Yuanxiang Zhao, Lei Zhang, Yunxiao Chen, Haoran Zhang, Youbing Zhejiang University of Technology College of Information Engineering Hangzhou310023 China Nankai University China and College of Electronic Information and Optical Engineering Tianjin300350 China Zhejiang Testing & Inspection Institute for Mechanical and Electrical Products Quality Co. Ltd Hangzhou310051 China Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100084 China State Grid Xinxiang Electric Power Supply Company Xinxiang453002 China

The curing formula is vital to the performance of epoxy resin impregnated paper (RIP) material. This work explored the effect of curing agents and accelerator contents on the thermal and electrical properties of RIP material. It was found that the RIP material cured with 1phr accelerator has the optimal glass transition temperature, electrical conductivity, dielectric loss and DC breakdown strength compared with RIP material cured by 0.5phr, 2phr, and 3phr accelerator. The RIP material cured with MEHHPA has better thermal and insulating properties compared with the RIP material cured with METHPA. The existence of the crepe paper amplifies the influence of accelerator and curing agent for the hydroxyl groups affect the curing process as well as the chain segment arrangement. This study provides the research support for the design of the curing formula for RIP insulation used in DC bushing. © 1994-2012 IEEE.

关键词： Dielectric losses

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Influence of the pyrolysis of benzotriazole passivator on the characteristics of dissolved gas in the insulating oil

Influence of the pyrolysis of benzotriazole passivator on th...

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International Conference on High Voltage Engineering and Application, ICHVE

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Insulation failures of oil-immersed power transformer induced by sulfur corrosion can be controlled by adding the metal passivator into insulating oil. However, it has been reported that the addition of benzotriazole and its derivative passivators into insulating oil would cause abnormal generation of dissolved gases in the oil during the operation of oil-immersed transformer. Therefore, this paper investigated on the effect of passivator on the characteristics of dissolved gas in the oil under the action of thermal field. Benzotriazole (BTA) that widely used in the oil-immersed transformer was selected as the research object, the thermogravimetric analysis of BTA was conducted, and a series of accelerate thermal ageing experiments of oil-paper insulation with and without BTA were also conducted, the composition and content of dissolved gases in oil were measured and analyzed. The results show that BTA was pyrolyzed continuously as the temperature increase. The addition of BTA in oil accelerated the contents of H2, CO and CO2 and decelerated the content of hydrocarbon gases, which lead to abnormal generation of dissolved gases in oil. All of these may interfere the operation condition evaluation of oil-immersed transformer based on DGA technology.

关键词： Oils Gases Aging power transformer insulation Oil insulation Thermal conductivity Partial discharges

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