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Analysis on carbon emission reduction intensity of fuel cell vehicles from a life-cycle perspective

Frontiers in Energy 2024年第1期18卷 16-27页

作者： Ziyuan TENG Chao TAN Peiyuan LIU Minfang HAN Fuel Cell and Energy Storage Center Department of Energy and Power EngineeringState Key Laboratory of Control and Simulation of Power Systems and Generation EquipmentTsinghua UniversityBeijing 100084China

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and *** paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys,including hydrogen production and packing in chlor-alkali plants,transport by tube trailers,storage and refueling in hydrogen refueling stations(HRSs),and application for use in two different *** also conducted a comparative study for battery electric vehicles(BEVs)and internal combustion engine vehicles(ICEVs).The result indicates that hydrogen fuel cell vehicle(FCV)has the best environmental performance but the highest energy ***,a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current *** carbon emission for FCV application has the potential to decrease by 73.1%in City A and 43.8%in City *** only takes 11.0%–20.1%of the BEV emission and 8.2%–9.8%of the ICEV *** cost of FCV driving can be reduced by 39.1%in City *** improvement can be obtained with an economical and“greener”hydrogen production pathway.

关键词： hydrogen energy life-cycle assessment(LCA) fuel cell vehicle carbon emission energy cost

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Combustion modeling for utility boiler based on multi-output least squares support vector machine

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International Journal of Advancements in Computing Technology 2012年第14期4卷 60-68页

作者： Han, Pu Gao, Fang Zhai, Yong-Jie Zhuo, Yue Lu, Yuan Hebei Engineering Research Center of Simulation and Optimized Control for Power Generation North China Electric Power University Baoding China College of Electronics and Information Engineering Hebei University Baoding China Tianjin SDIC Jinneng Electric Power Company Limited Tianjin China

A novel regression algorithm of multi-output least squares support vector machine is proposed for the modeling of multi-output systems. The fitting error of each dimension output and the fitting error of overall output are defined. And combined with the equality constraints of least squares support vector machine, the linear equation of multi-output least squares support vector machine is deduced. A multioutput combustion system model for utility boiler is established based on above algorithm and the prediction of NOx emission, carbon content of fly ash, exhaust flue gas temperature and desuperheating water of reheater is achieved. In addition, the parameters of the multi-output model are optimized by particle swarm optimization. The performance of the multi-output least squares support vector machine model and multiple single-output least squares support vector machine are compared. The effectiveness of the multi-output model is verified and it provides a good foundation for combustion optimization.

关键词： Fly ash

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A method for generating wind power output scenarios based on improved conditional generative diffusion model

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electric power Systems Research 2025年 247卷

作者： Liu, Wei Wang, Changgang Cao, Yu Liang, Dong Li, Yang Mo, Jingshan Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Jilin132012 China School of Electrical Engineering Northeast Electric Power University Jilin Jilin132012 China Jilin Power Supply Company Substation Secondary Maintenance Center Jilin Province Jilin132012 China

With the large-scale integration of wind power into the grid, accurately characterizing wind power uncertainty is crucial for power system *** address this, we propose an improved conditional generative diffusion model(ICGDM) for generating wind power output *** model is built upon a theoretical framework combining Markov chains and variational inference. First, a forward process transforms historical data into pure noise. Then, a reverse process, guided by conditional information, reconstructs scenarios that conform to the target distribution. Additionally, the noise schedule is modified to a cosine function, enhancing the quality of generated ***, the method is applied to wind power output data from the Flanders region. Results demonstrate that the proposed approach effectively and reliably generates wind power output scenarios with strong adaptability. © 2025 Elsevier B.V.

关键词： Markov chains

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Overview of power quality analysis and control technology for smart grid

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Journal of Modern power Systems and Clean Energy 2016年第1期4卷 1-9页

作者： An LUO Qianming XU Fujun MA Yandong CHEN National Electric Power Conversion and Control Engineering Technology Research Center(Hunan University) ChangshaChina

With the wide application of non-linear loads and the large-scale access of distributed energy generations based on power electronics equipments, power quality problems in the distribution network are increasingly serious with new characteristics. Further in-depth research is of great significance in theory and practice. This paper provides an overview of power quality analysis, compensators, and control technologies under the new situation of smart grid. It focuses on the topologies and control methods for power quality conditioners, especially new characteristics of power quality and applicable control technologies in microgrids and distributed power ***, trends and prospects of power quality control technology are introduced, which is important to achieve security and efficient operation of smart grid.

关键词： power quality Smart grid Active control Passive control

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Measurement-based solution for low frequency oscillation analysis

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Journal of Modern power Systems and Clean Energy 2016年第3期4卷 406-413页

作者： Chen SHEN Zhi AN Xianzhong DAI Wei WEI Lijie DING Department of Electrical Engineering Tsinghua UniversityBeijingChina State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua UniversityBeijingChina Electric Power Research Institute of Sichuan Electric Power Company ChengduChina

This paper presents a measurement-based solution for low frequency oscillation(LFO) analysis in both real time monitoring and off-line case study. An online LFO property discrimination method is developed first,which alternately uses empirical mode decomposition(EMD)/Hilbert transform(HT) and square calculation to process the measurement data. The method magnifies the variation trend of oscillating variables to accurately discriminate the property of the oscillation. Subsequently, an oscillation source locating method for the forced oscillation(FO) and a strongly correlated generator identification method for the weak damping oscillation(WDO) are proposed. Finally, numerical study results on a test system of the isolated Changdu grid in Tibet validate the proposed methods.

关键词： Low frequency oscillation Oscillation property discrimination Oscillation source location Strongly correlated generator identification

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Identification of thermal process using hammerstein model based on particle swarm optimization algorithm

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2012 International Conference on electrical and Electronics engineering, ICEE 2012

作者： Wang, Dong Feng Ren, Yan Yan Liu, Chang Liang Han, Pu Hebei Engineering Research Center of Simulation and Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (纸本)9781461449805

In order to identify the controlled objects which are nonlinear time-delay processes with slow time-varying in the thermal system accurately, the Hammerstein model and particle swarm optimization (PSO) algorithm were used in this paper. For the Hammerstein model discussed in this paper, the polynomial and difference equations were used to express the nonlinear part and linear part of Hammerstein model, respectively. This study used the PSO algorithm to find the optimal solution of Hammerstein model's undetermined parameters in the parameters space. For illustration, an example of main-steam temperature system identification was utilized to show the feasibility of the Hammerstein model based on PSO algorithm in identifying the thermal system processes. The PSO-based Hammerstein model can effectively represent the controlled objects which are nonlinear time-delay processes in the thermal system and thus a class of identification problems with nonlinearity in thermal system can be solved. © 2014 Springer Science+Business Media New York.

关键词： Difference equations

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Design of a coal quality detection management system for power plants based on UML

Design of a coal quality detection management system for pow...

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International Conference on Testing and Measurement: Techniques and Applications, TMTA 2015

作者： Liu, Z. Hebei Engineering Research Center of Simulation & Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (纸本)9781138028128

The coal quality detection is an integral part of the fuel management, including coal sampling, coal sample preparation, and coal detection three parts. Based on the idea of object-oriented analysis and design, the requirements analysis model for a Coal Quality Detection Management System (CQDMS) is established by using the Unified Modeling Language. Three-level electronic coding based on bar code technology is designed and the statistic model and the dynamic model of the system are visually modeled using UML. Finally, the CQDMS is developed by the *** technology. © 2015 Taylor & Francis Group, London.

关键词： Unified Modeling Language

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Transient Stability Analysis of Large-scale power Systems:A Survey

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CSEE Journal of power and Energy Systems 2023年第4期9卷 1284-1300页

作者： Qing-Hua Wu Yuqing Lin Chao Hong Yinsheng Su Tianhao Wen Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China the Power Dispatching and Control Center China Southern Power GridGuangzhou 510530China

Transient stability analysis is a key problem in power system operation and *** paper aims at giving a comprehensive review on the modeling ideas and analysis methods for transient stability of large-scale power *** model construction,the general modeling of traditional power systems and special modeling for renewable generations and high-voltage direct-current transmissions are *** transient stability analysis,Lyapunov based methods and non-Lyapunov based methods are thoroughly *** Lya-punov based methods,we focus on the energy function method,the sum-of-squares based method and decentralized stability analysis ***,in non-Lyapunov based methods,the time-domain simulation,extended equal-area criterion and data-driven based methods are *** basic working principles,features and recent research progresses of all the above-mentioned methods are described in *** particular,their performances on several aspects,such as computational speed,conservativeness of stability region estimation or stability margin calculation,and adaptability to various types of system models,are ***,a brief discussion of potential directions for future research on transient stability analysis of large-scale power systems is *** Terms-connective stability,large-scale system analysis,Lyapunov functions,power systems,transient stability analysis.

关键词： connective stability large-scale system analysis Lyapunov functions power systems transient stability analysis

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Ultra-short-term wind speed and power forecast based on dynamic selective neural network ensemble

Ultra-short-term wind speed and power forecast based on dyna...

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作者： Liu, Yan Hua Dong, Ze Hebei Engineering Research Center of Simulation and Optimized Control for Power Generation North China Electric Power University Baoding China

ISBN: (纸本)9783038351382

With the scale of grid-connected wind farms increasing, accurate forecast of ultra-short-term wind speed and wind power is very important to the stable operation of power systems. This paper presents a dynamic selective neural network ensemble (DSNNE) forecast method, which makes use of K nearest neighbor algorithm to collect the generalization errors of certain different BP neural networks and RBF neural networks into a performance matrix and then the neural networks with low local generalization errors are dynamically selected and locally dynamic averaging is applied to the neural networks in order to conduct the final results of the ensemble. Then this method is applied to realize the wind speed and power ultra-short-term advance forecast, taking the wind speed and wind turbine power output from a wind farm in China as the original data. The research results show that DSNNE improves the generalization ability of the neural network system and the prediction accuracy of wind power and wind speed significantly. It proves the validity and effectiveness of the DSNNE with controlling the biggest mean relative error of 2 minutes ahead wind power and wind speed forecast as low as 25% and 16% respectively. © (2014) Trans Tech Publications, Switzerland.

关键词： Wind speed

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Active Dynamic Aggregation Model for Distributed Integrated Energy System as Virtual power Plant

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Journal of Modern power Systems and Clean Energy 2020年第5期8卷 831-840页

作者： Haotian Zhao Bin Wang Xuanyuan Wang Zhaoguang Pan Hongbin Sun Zhen Liu Qinglai Guo State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical EngineeringTsinghua UniversityBeijingChina State Grid Jibei Electric Power Co. Ltd.BeijingChina

Distributed integrated multi-energy systems(DIMSs)can be regarded as virtual power plants to provide additional flexibility to the power *** paper proposes a robust active dynamic aggregation model for the DIMSs to describe the maximum feasible *** aggregation model includes the power constraints,energy constraints,and ramping constraints to aggregate different types of resources in the *** proposed generator-like and storage-like model does not depend on the ancillary service market and can be directly incorporated into the economic dispatch model of the power system.A novel algorithm based on the column-and-constraint generation algorithm and convex-concave procedure is proposed to solve the two-stage robust optimization problem,which is more efficient than the KKT-based ***,a case study of an actual DIMS is developed to demonstrate the effectiveness of the proposed model.

关键词： Aggregation distributed integrated energy system(DIMS) robust optimization virtual power plant

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