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13th International Conference on Genetic and Evolutionary Computing, ICGEC 2019

作者： Hua, Jielin Zheng, Rongjin Deng, Huiqiong Chen, Siyu Fujian Institute of Engineering Smart Grid Simulation Analysis and Integrated Control of Fujian University Engineering Research Center FuzhouFujian350118 China Fujian Shuikou Power Generation Group Corporation FuzhouFujian350004 China

ISBN: (纸本)9789811533075

Aiming at the investment cost and safety, a mathematical model for giving the grounding point configuration is established for the TN-C grounding system of the power system, and a complete solution method is given. Firstly, based on the analysis of the characteristics of the TN-C grounding system, a mathematical model for configuring the grounding position to meet the lowest investment cost and the lowest contact voltage is presented. Aiming at the requirement of meeting the minimum contact voltage in this model, this paper gives a detailed calculation method for the contact voltage in the TN-C grounding system. Then combined with the actual characteristics of the model, this paper gives an unconstrained form and further The idea of using particle swarm optimization to solve the problem is given. Finally, a case study system is designed in this paper. The analysis program is compiled in MATLAB and the case analysis is carried out. The results show that the proposed method is feasible and effective. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Electric grounding

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Coordination and Optimization of Multi-controller Parameters in power System Based on a Sphere Artificial Immune Algorithm

Coordination and Optimization of Multi-controller Parameters...

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第40届中国控制会议

作者： Yu Miao Du Weijie Li Jinglin School of Mechanical-electronic and Automobile Engineering Beijing University of Civil Engineering and Architecture Beijing Engineering Research Center of Monitoring for Construction Safety State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University

Interconnected power system is becoming more and more complex, in order to improve the performance of power system, the number and type of controllers are increasing. The interaction among controllers may be detrimental to the performance of power system, which would weak the performance of controllers. The purpose of this paper is to solve the problem of coordination control among controllers, firstly, a multi-controller parameter coordination model is given. Then, a spherical artificial immune algorithm is proposed to coordinate and optimize parameters among multi-damping controllers. This algorithm can reduce the computational complexity and optimize parameters globally. Finally, this algorithm is verified by the simulation of the four-machine two-area system. Compared with one similar method, simulation results show that this algorithm can effectively realize the coordination control among multi-damping controllers.

关键词： Sphere artificial immune system power system coordination control parameter optimization

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Design and simulation of Adaptive Internal Model control Algorithm

Design and Simulation of Adaptive Internal Model Control Alg...

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IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Xie Ming Gao Chunyu Liu Baojie Dong Ze Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Ltd Beijing China Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (数字)9781728190266

ISBN: (纸本)9781728190273

In the actual industrial control, many objects have the characteristics of large delay and parameter time-varying, which makes the traditional PID control difficult to obtain satisfactory control effect. The internal model control has many advantages, such as intuitive design, strong practicability, simple structure, few on-line adjusting parameters and no need of accurate object model. Especially for the improvement of robustness and anti-interference and the control of the system with large time delay, the control effect is particularly significant. But the system model of internal model control is not easy to get, and it is difficult to get a more accurate internal model. In order to obtain a more accurate internal model, improve the control effect of the internal model control system and improve the dynamic characteristics of the control system, it is necessary to identify the model parameters of the controlled object efficiently. In this paper, the improved particle swarm optimization (PSO) algorithm is used to identify the system online and combined with the internal model control method to control the controlled object.

关键词： internal model control particle swarm optimization large time delay parameter identification internal model control control effect Parameter identification Particle swarm optimization control systems Adaptive internal model control controlled object Online Systems time delay suppression of interference

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Prediction of NOx in SCR Inlet of Thermal power Plant Based on Mutual Information and Long Short-Term Memory Network

Prediction of NOx in SCR Inlet of Thermal Power Plant Based ...

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IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Gao Chunyu Xie Ming Jiang Wei Dong Ze Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Ltd Beijing China Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (数字)9781728190266

ISBN: (纸本)9781728190273

NOx produced by thermal power plant incineration is one of the main sources of atmospheric pollutants. Most thermal power plants use selective catalytic reduction (SCR) technology to denitrate. The current NOx concentration sensor has a large delay and cannot accurately reflect the real-time change of the NOx concentration at the SCR inlet, which will affect the economy and safety of the denitration control. This paper uses balanced mutual information feature selection (BMIFS) for feature extraction. Driven by historical data, a long short-term memory network (LSTM) model of inlet NOx concentration was established. By comparing the error with the field measured data, the accuracy of the prediction model and the effectiveness of the prediction method are verified. The conclusion shows that the balanced mutual information feature selection method can reduce the coupling degree and data dimension between the input variables, and achieve the purpose of improving modeling accuracy and reducing computational complexity.

关键词： Computational modeling Feature extraction Data models Safety Thermal pollution Mutual information power generation

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research on Predictive control Based on LongShort-Term Memory Network

Research on Predictive Control Based on LongShort-Term Memor...

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Advances in Electrical engineering and Computer Applications( AEECA), 2020 IEEE International Conference on

作者： Chunyu Gao Ming Xie Wei Jiang Ze Dong Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Ltd. Beijing China Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (数字)9781728165219

ISBN: (纸本)9781728165226

Predictive control has the advantages of low model accuracy requirements, ability to handle multivariables, and ability to handle constraints. This paper expounds the basic principles of long- and short-term memory networks, and combines its advantages in modeling time series data with a recursive multi-step model to establish a prediction model. The golden section method is used to dynamically solve the control quantity. Correct the error of the prediction model in real time through feedback correction. The design of predictive control algorithm based on long and short-term memory network is completed. The simulation verifies the feasibility and antidisturbance of the algorithm.

关键词： Predictive models Logic gates Predictive control Mathematical model Prediction algorithms Neurons Optimization

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NO_x emission model for coal-fired boilers using partial least squares and extreme learning machine

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Journal of Southeast University(English Edition) 2019年第2期35卷 179-184页

作者： Dong Ze Ma Ning Li Changqing Hebei Engineering Research Center of Simulation and Optimized Control for Power Generation North China Electric Power UniversityBaoding 071003China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the NOx emission model of utility boilers is ***,the initial input variables of the NOx emission model are determined according to the mechanism ***,the initial input data is extracted by ***,the extracted information is used as the input of the ELM model.A large amount of real data was obtained from the distributed control system(DCS)historical database of a 1 000 MW power plant boiler to train and validate the PLS-ELM *** modeling performance of the PLS-ELM was compared with that of the back propagation(BP)neural network,support vector machine(SVM)and ELM *** mean relative errors(MRE)of the PLS-ELM model were 1.58%for the training dataset and 1.69%for the testing *** prediction precision of the PLS-ELM model is higher than those of the BP,SVM and ELM *** consumption time of the PLS-ELM model is also shorter than that of the BP,SVM and ELM models.

关键词： NOx emission partial least squares extreme learning machine coal-fired boiler

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Experimental Investigation of Fuel Starvation on Industrial-Sized Solid Oxide Fuel Cells Using Segmented Cathodes and Area Specific Resistances

SSRN

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SSRN 2022年

作者： Zhang, Jihao Guo, Huding Lei, Libin Shen, Shuanglin Zheng, Keqing Han, Minfang Laboratory of Hydrogen Energy and Fuel Cells School of Low-Carbon Energy and Power Engineering China University of Mining and Technology Xuzhou221116 China Xuzhou Huatsing Jingkun Energy Co. Ltd. Xuzhou221005 China Smart Energy Research Center School of Materials and Energy Guangdong University of Technology Guangzhou510006 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Energy and Power Engineering Tsinghua University Beijing100084 China

Fuel starvation needs to be timely detected to avoid anode oxidation, especially for industrial-sized Solid oxide fuel cells (SOFCs). In this work, a novel and useful segmented cell measurement method is developed to detect fuel starvation occurring in local regions. For this developed method, the cathode of SOFCs is segmented and only the voltage signal is measured in the segments. Then, the local current-voltage (I-V) curve of each segment is determined using the measured voltage together with the global I-V curve. To validate the data reliability, area specific resistances (ASRs) are calculated and compared among different segments. Varieties of current loading rates and fuel flow rates are correspondingly investigated. Furthermore, the occurrence of fuel starvation is identified using the rapid voltage drop in I-V curves as well as the rapid ASR increment in I-ASR curves. The results show that compared to the voltage drop, the intrinsic ASR increment is a more sensitive and robust criterion to identify the occurrence of fuel starvation. This work will considerably benefit the progress of segmented cell measurements and local fuel starvation identifications. © 2022, The Authors. All rights reserved.

关键词： Cathodes

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Application of Virtual Reality Technology in the Maintenance of Steam Turbine

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Journal of Physics: Conference Series 2021年第1期1966卷

作者： Zijie Pan Hairong Sun Li Li School of Control and Computer Engineering North China Electric Power University Baoding 071000 China Hebei Engineering Research Center of Simulation Optimized Control for Power Generation North China Electric Power University Baoding 071003 China

Traditional steam turbine maintenance work has many shortcomings, such as poor effectiveness, high cost, and long cycle. In order to solve this problem and improve the professional skills and maintenance efficiency of steam turbine maintenance personnel, we first collect steam turbine equipment drawings and 3D dimension data of parts, and use 3D modeling software to establish augmented reality scene model. Then combined with the virtual reality technology and image fusion technology to realize the maintenance procedure training and maintenance auxiliary guidance of the steam turbine unit. The practical application results show that this technology can realize the virtual and real operation of the model by users in augmented reality scenes, bring interactive and immersive experience to operators, and improve the work efficiency of maintenance personnel.

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Evaluation Model for Smart Distribution Network Planning under Energy Interconnection 3

Evaluation Model for Smart Distribution Network Planning und...

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3rd International Symposium on Resource Exploration and Environmental Science, REES 2019

作者： Zhang, Yan Jiang, Zefu Liu, Jinsen Liu, Wenxia Gao, Hua Wang, Yanmin Power Grid Planning Research Center of Guizhou Power Grid Co. Ltd Guiyang Guizhou550003 China State Key Laboratory of Power System and Power Generation Equipment Control and Simulation Department of Electrical Engineering Tsinghua University Haidian Beijing100084 China

Due to the development of the energy interconnection, smart distribution networks (SDNs) should needs be transformed and upgraded to meet new demands. In order to assess the SDN planning, a new index system was conducted from the five attributes. The quantitative methods of all criteria were also defined. An evaluation model was proposed based on AHP weighting and TOPSIS methods. Empirical analysis was performed to verify the feasibility of the evaluation system. © Published under licence by IOP Publishing Ltd.

关键词： Interconnection networks (circuit switching)

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Flexible unbalanced control with peak current limitation for virtual synchronous generator under voltage sags

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Journal of Modern power Systems and Clean Energy 2018年第1期6卷 61-72页

作者： Tianwen ZHENG Laijun CHEN Yan GUO Shengwei MEI State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Tsinghua University Qinghai Key Lab of Efficient Utilization of Clean Energy New Energy Photovoltaic Industry Research Center Qinghai University

Virtual synchronous generator(VSG)is gridfriendly for integrating distributed generations(DGs)since it can emulate the operation mechanism of traditional synchronous generator(SG).However,the traditional VSG control strategy,which is mainly suitable for balanced voltage conditions,may lead to power oscillations,current unbalance and even overcurrent under unbalanced voltage *** overcome this difficulty,a flexible unbalanced control with peak current limitation for VSG under unbalanced operating conditions is *** on the basic VSG control algorithm,the control strategy integrates two novel control modules,which are current reference generator(CRG)and power reference generator(PRG).The proposed control strategy can flexibly meet different operation demands,which includes current balancing,constant active or reactive *** the injected currents are kept within safety values for a better utilization of the VSG power ***,the experimental platform is *** results demonstrate the validness and effectiveness of the proposed control strategy.

关键词： Virtual synchronous generator Unbalanced control Current reference generator power reference generator Voltage sags

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