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The 11th IET International Conference on Advances in power System control, Operation and Management (APSCOM 2018)

作者： Qunli Lin Xinwei Shen Yinliang Xu Yong Sun Zhenyuan Li Qinglai Guo Hongbin Sun Shenzhen Environmental Science and New Energy Technology Engineering Laboratory Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen China Jilin Power Grid Company State Grid Corp. of China Jilin China State Key Lab of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (数字)9781839530043

Integrated Energy System (IES), which plays a vital role in the development of Energy Internet (EI), can improve the efficiency of energy utilization and integration of renewable energy. However, the coupling between multiple energy systems will bring new challenges to the security control of the IES, such as combined heat and power (CHP) system. For IES, the preventive control is the first line of defense to ensure that the system can keep stable operation when contingencies such as the transmission outage or generator outage happen. This paper proposes a preventive control approach for CHP system, in which a day-ahead security constrained economic dispatch (SCED) model of CHP system considering the coupling of heat and electric is formulated. The model aims to minimize the cost of the whole system, while the preventive control of the system can be achieved with the constraints considering the normal states and contingencies states. Case studies based on the IEEE 9-bus system with CHPs are presented to illustrate the approach. The case result shows that the combined electric and heat optimal dispatch is more economical than when two systems are independently optimized and operated. And the proposed preventive control approach of the CHP system can satisfy both the electric and heat demand, and system security is ensured when the N-1 contingencies happened.

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Maximum flow algorithm based on adjustment of net flow on nodes and its application

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Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering 2008年第SUPPL.期28卷 31-34页

作者： He, Guang-Yu Sun, Ying-Yun Chen, Chao State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China

For calculating the maximum capacity transported from source node to sink node in a network, a maximum flow algorithm was proposed. Based on the concept of net flow on nodes (NFN) and layered increment network (LIN), the plus flow process (PFP) and minus flow process (MFP) on LIN were defined. By performing PFP and MFP on NLP over and over, the maximum flow problem was solved when the sink node can't get a mark again. Compare to the existing max flow algorithm, the proposed method needs no complex data structure in processing, which makes the algorithm implemented easily. Based on the algorithm, a thermal economic dispatch software package which includes fixed electricity plant was developed and had been put into practice and had a good performance. Furthermore, the algorithm runs in O(n2m) (n, m is the number of nodes and arcs of the network) was proved.

关键词： Scheduling

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An Abnormal state Forecasting Method for Substation Equipment based on Improved LSTM

An Abnormal State Forecasting Method for Substation Equipmen...

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Sustainable power and Energy Conference (iSPEC)

作者： Tong Li Shimao Yu Chunhe Song Tongwei Yu Peng Zeng Li Shen Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China

Abnormal state accumulation over a long period will cause an electrical equipment fault. Therefore, Substation equipment state forecasting plays a vital role in smart grids. Fault forecasting method based on deep learning have been put forward in recent years, but they have deficiencies dealing with temporal features. This paper proposes an abnormal forecasting method for substation equipment based on improved LSTM, and temporal features of power equipment fault can be extracted effectively for a long-time span. The method reads secondary equipment information through SCADA system, then extracts feature to carry out deep learning training. In this paper, RNN and LSTM are firstly compared, and then the structure and algorithm of improved LSTM are given. This method increases coupling between forget gate and cell state compared with the standard LSTM structure, so as to make better use of information at previous moment. Meanwhile problems of network training and overfitting are discussed. Experiments are conducted to demonstrate that improved LSTM is capable of forecasting accurately the complex electric equipment state with a long forecasting horizon. The accuracy of abnormal state forecasting can reach more than 93% which has a better performance compared with many other methods.

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Intelligence Uv Absorption Spectroscopy Analysis of So2, H2s, Cs2 Mixed Gases Based on Symmetrized D

SSRN

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SSRN 2024年

作者： Chen, Peiying Cao, Yupeng Yu, Miao Wang, Qiao Luo, Lin School of Information and Control Engineering Liaoning Petrochemical University Liaoning Fushun113001 China State Key Laboratory of Industrial Control Technology Institute of Cyber-systems and Control Zhejiang University Zhejiang Hangzhou310027 China Beijing Electric Transmission and Transformation State Grid Jibei Electric Power Company Beijing Beijing100054 China

The accurate quantification of SO2, CS2, and H2S, as significant breakdown components of insulating gas sulfur hexafluoride, is critical for determining the type and severity of internal flaws in insulating equipment. This paper proposes a technique for quantitative detection of multi-component gas mixes on the UV absorption spectroscopy platform that combines symmetry dot pattern with deep learning. The approach uses symmetrized dot pattern analysis to fuse local UV spectral information, which may be used to identify trace gas mixes with overlapping absorption peaks. To detect the symmetry dot pattern diagrams, a deep network based on DenseNet is developed, achieving feature representation from multiple scales. The outstanding performance of this method is illustrated and compared to the existing models using the receiver operating characteristic curve. The platform's experimental results reveal that the suggested technique can quantitatively detect the amounts of SO2, H2S, and CS2 ternary gas mixtures online. © 2024, The Authors. All rights reserved.

关键词： Sulfur hexafluoride

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Eigenvalue analysis of multi-mode sub-synchronous resonance for multimachine plant-to-grid transmission systems with fixed series compensation

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Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering 2008年第SUPPL.期28卷 13-18页

作者： Zhang, Shu-Qing Xie, Xiao-Rong Yang, Ting-Zhi Liu, Shi-Yu State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China

For some domestic large thermal power plants delivering electric energy over long distances, the sub-synchronous resonance (SSR), which is induced by the fixed series compensation (FSC), attracts much attention. Eigenvalue analysis is one of the primary methods to assess the risk and explore the countermeasure. However, for handling multi-machine and multi-mode SSR problems, no practical toolkit based on eigenvalue analysis is on hand for the moment. In this paper, a systematic modeling approach and analysis flows for the purpose of eigenvalue analysis of multimachine plant-to-grid transmission systems with FSC were proposed. The equating technique of machines and networks was presented, and the effect of the q-axis damping windings on the SSR was also explored. The applicability of the proposed method was verified with an actual multimachine system. Furthermore, its advantage over existing SMIB based eigenvalue analysis was clarified by a comparative study between the original multi-machine system and the simplified single-machine system.

关键词： Eigenvalues and eigenfunctions

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Optimal Model and Dispatch Strategy of a Multi-Energy Microgrid Based on Hybrid Pumped Hydro-Battery Storage and Ground Source Heat Pump

SSRN

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SSRN 2023年

作者： Li, Xinyue Wang, Honglei Li, Bin Tan, Zhukui Electrical Engineering College Guizhou University Guiyang550025 China Key Laboratory of "Internet+" Collaborative Intelligent Manufacturing in Guizhou Provence Guiyang Guizhou550025 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Electric Power Research Institute Guizhou Power Grid Co. Ltd Guiyang550002 China

The carbon neutrality target and the carbon emission problem caused by the ever-increasing energy demand necessitate the extensive use of renewable energy (RES) generation technologies. Multi-energy microgrid (MEMG) become effective vehicles for managing RES generation and storage. However, the uncertainty of RES and the randomness of load demand poses a challenge to the design and operation of MEMG. This study proposes a MEMG including combined cooling, heating, power system, pumped hydro storage, and ground source heat pump to solve the problem. Combined with demand-side management strategies, a system is designed considering complementary configuration and energy conversion management. A corresponding optimization model is established to minimize the total cost and maximize the island operation while satisfying the demand. The experimental results show that the established model and scheduling method improves the system’s ability to cope with the RES’ uncertainty and reduces the capacity of the energy storage system. In summer, the daily investment cost is saved by 1439RMB, and the utilization rate of clean energy reaches 96%. Compared with the uncombined system, the MEMG reduces 1620.02kg of carbon dioxide per day, realizing the full utilization of clean energy and having the role of demonstration and promotion. © 2023, The Authors. All rights reserved.

关键词： Battery storage

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The HEFT Algorithm Based on Node Merging

The HEFT Algorithm Based on Node Merging

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control Engineering and Advanced Algorithms (IWCEAA), International Workshop on

作者： Ying Huang Yuanhong Lu Jie Zhang Jingyue Zhang Haiping Guo National Energy Power Grid Technology R&D Centre Guangzhou 510663 State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

The task scheduling problem in power systems is complex, especially when communication costs exceed computation costs. This paper proposes an improved HEFT algorithm with a node merging mechanism, merging nodes through hierarchical traversal to assign high-communication-cost tasks to the same processor, reducing communication overhead. Experiments with 499-dimensional and 1614-dimensional matrices from the power system show that the improved algorithm reduces completion time by 5ms and 2ms, respectively, compared to standard HEFT.

关键词： Costs control engineering Processor scheduling Conferences Merging power systems Standards

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Wind farm HVRT capability improvement based on coordinated reactive power control strategy

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The Journal of Engineering 2017年第13期2017卷 756-761页

作者： Yuandong Zhang Qing Li Jinping Zhang Shiyao Qin State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems People's Republic of China CEPRI Inspection and Certification (Beijing) Co. Ltd People's Republic of China Renewable Energy Center Electric Power Research Institute People's Republic of China

Voltage swells after grid fault clearance is one of the major causes of large-scale wind power tripping accidents in China. In this study, reasons that led to overvoltage phenomena were researched, and factors that influence the grid overvoltage during grid fault were quantitatively analysed through simulation. A coordinated reactive power control strategy combined the control of wind turbines with reactive power compensation devices was proposed to prevent the occurrence of high voltage and improve the high-voltage ride through capability of wind power plant. Finally, the effectiveness of the proposed control strategy was indicated by the simulation results in DIgSILENT/powerFactory.

关键词： wind power plants reactive power control power generation control accidents power generation faults power generation reliability DIgSILENT-powerFactory wind power plant high-voltage ride through capability reactive power compensation devices wind turbine control grid fault grid overvoltage overvoltage phenomena China large-scale wind power tripping accidents grid fault clearance voltage swells coordinated reactive power control strategy wind farm HVRT capability improvement

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Application Research of Ensemble Learning Frameworks

Application Research of Ensemble Learning Frameworks

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Chinese Automation Congress (CAC)

作者： Kunkun Wang Xianda Liu Jianming Zhao Hongwei Gao Zhen Zhang Key Laboratory of Networked Control Systems Shenyang Ligong University College of Automation and Electrical Engineering Shenyang China Key Laboratory of Networked Control Systems Shenyang Insitute of Automation Chinese Academy of Sciences College of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Information & Telecommunication Branch State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In the field of artificial intelligence, machine learning is a hot research direction. With the improvement of computing power, machine learning has been better developed in the era of big data. A single machine learning algorithm has some shortcomings. Multiple simple base learning methods are combined to form an ensemble learning through a certain strategy, and meanwhile the performance of the ensemble learning will be greatly improved. The ensemble learning framework includes three integration modes: boosting, bagging, and stacking. This article introduces the development process of ensemble learning and studies the principles of the three ensemble methods, summarizes the existing ensemble learning algorithms, summarizes the characteristics and applications of the ensemble algorithms, and finally discusses the improvement and future development of the algorithms.

关键词： Training Classification algorithms Bagging Boosting Machine learning algorithms Stacking Prediction algorithms

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Kinetic Evaluation and Applicability Analysis on Direct Aqueous Carbonation of Industrial/Mining Solid Wastes

SSRN

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SSRN 2023年

作者： Li, Zijian Chen, Jie Cheng, Yiming Ran, Jingyu Qin, Changlei Key Laboratory of Low-grade Energy Utilization Technologies and Systems of Ministry of Education School of Energy and Power Engineering Chongqing University Chongqing400044 China State Key Laboratory of Coal Mine Disaster Dynamics and Control School of Resources and Safety Engineering Chongqing University Chongqing400044 China

CO2 mineralization combined with goaf backfilling provides an efficient pathway for CO2 emission reduction and alkaline solid waste recycling. Thus, it is of significance to reveal kinetics of solid waste mixtures in direct aqueous carbonation. Herein, a kinetic model based on the two-film theory is used to investigate carbonation behavior and kinetics of carbide slag and its mixtures with iron tailing. The influence of key operation parameters are evaluated and model fitted as well. Results show that there is an excellent fitting accuracy to the carbonation of carbide slag and its 50% mixtures by the model (average R2=0.999) although a limitation is observed when the IT blending ratio is very high. Additionally, reaction temperature of 65 °C, solid-liquid ratio of 100 g/L and CO2 concentration of 15% are determined to the optimal parameters and the variation of gas-liquid mass transfer flux [[EQUATION]] is consistent with the theory. The difference between the experimental value and the predicted value is controlled within 10%. The above results are beneficial to understand the carbonation mechanism of mixed solid waste at micro scale, and could provide theoretical support for industrial applications. © 2023, The Authors. All rights reserved.

关键词： Kinetics

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