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International Conference on Renewable power Generation (RPG 2015)

作者： Kangping Li Fei Wang Zhao Zhen Yujing Sun Zengqiang Mi Hongbin Sun Chun Liu Bo Wang Jing Lu State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric Power University) Baoding 071003 Hebei Province China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Haidian District Beijing 100084 China China Electric Power Research Institute Haidian District Beijing 100192 China)

ISBN: (纸本)9781510821415

Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.

关键词： Feature Extraction Loss quantity of electricity Operating Statuses Identification Support Vector Machine

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Cloud identification model for sky images based on Otsu

Cloud identification model for sky images based on Otsu

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International Conference on Renewable power Generation (RPG 2015)

作者： Hongping Li Fei Wang Hui Ren Hongbin Sun Chun Liu Bo Wang Jing Lu Zhao Zhen Xiaoli Liu State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric Power University) Baoding 071003 Hebei Province China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Haidian District Beijing 100084 China China ElectricPowerResearch Institute HaidianDistrict Beijing 100192 China

Irradiance changes caused by clouds movement are the main factors, which lead to mutation of photovoltaic power. In order to increase the accuracy of the ultra-short-term photovoltaic power prediction, based on of clouds images, the cloud identification for sky images is one of the primary aspects for improving photovoltaic power accuracy. A cloud identification model for sky images is established based on Otsu. Firstly, a series of sky images are collected by Total Sky Imager (TSI) with the regions of clouds and sky are distinguished. Secondly, the color features (based on RGB values) of pixels in sample images and the spectral and texture features of the whole image are extracted; Finally, we established a cloud identification model for sky images based on Otsu according to the clouds' and sky areas' division and the general characteristics featured by pixels and images. The simulated results show that the model in this paper can identify the clouds in a sky images effectively.

关键词： Otsu cloud identification texture threshold Clouds sky images texture textures pixel

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Electro-peroxone degradation of diethyl phthalate: Cathode selection, operational parameters, and degradation mechanisms

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Journal of hazardous materials 2016年 319卷 61-8页

作者： Meifang Hou Yaofei Chu Xiang Li Huijiao Wang Weikun Yao Gang Yu Seiichi Murayama Yujue Wang School of Ecological Technology and Engineering Shanghai Institute of Technology Shanghai 201418 China. School of Ecological Technology and Engineering Shanghai Institute of Technology Shanghai 201418 China School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. Power and Industrial Systems R&D Center Toshiba Corporation Fuchu-shi Tokyo Japan. School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. Electronic address: wangyujue@***.

This study compares the degradation of diethyl phthalate (DEP) by the electro-peroxone (E-peroxone) process with three different carbon-based cathodes, namely, carbon-polytetrafluorethylene (carbon-PTFE), carbon felt, and reticulated vitreous carbon (RVC). Results show that the three cathodes had different electrocatalytic activity for converting sparged O2 to H2O2, which increased in order of carbon felt, RVC, and carbon-PTFE. The in-situ generated H2O2 then reacts with sparged O3 to yield OH, which can in turn oxidize ozone-refractory DEP toward complete mineralization. In general, satisfactory total organic carbon removal yields (76.4-91.8%) could be obtained after 60min of the E-peroxone treatment with the three carbon-based cathodes, and the highest yield was obtained with the carbon-PTFE cathode due to its highest activity for H2O2 generation. In addition, the carbon-PTFE and carbon felt cathodes exhibited excellent stability over six cycles of the E-peroxone treatment of DEP solutions. Based on the intermediates (e.g., monoethyl phthalate, phthalic acid, phenolics, and carboxylic acids) identified by HPLC-UV, plausible reaction pathways were proposed for DEP mineralization by the E-peroxone process. The results of this study indicate that carbon-based cathodes generally have good electrocatalytic activity and stability for application in extended E-peroxone operations to effectively remove phthalates from water.

关键词： Electrocatalytic ozonation Electrode Hydrogen peroxide Ozone Phthalates

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Robust mean-variance optimization for self-scheduling of thermal producer and its price of robustness

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Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering 2015年第2期35卷 319-326页

作者： Ding, Tao Bo, Rui Sun, Hongbin Huang, Can Li, Fangxing State Key Lab of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China Midwest ISO Street Paul MN55108 United States Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN37996 United States

In deregulated electricity markets, generation companies with the aim of maximum revenue need to provide trading strategies to the electricity trading market, which contributed to a self-scheduling model. When considering the uncertainty of price, the trading strategies are required to maximize the revenue as well as minimizing the risks brought by uncertainties. In this paper, a multi-objective robust mean-variance model was proposed to solve the above problem and the Pareto frontier of the multi-objective optimization was obtained. Moreover, the proposed robust mean-variance model could be equivalently transformed into a non-robust mean-variance model which was casted as a second-order cone programming (SOCP) optimization. The price of robustness to benefits, risks, and the Pareto frontier were analyzed. Finally, the robust mean-variance model based self-scheduling model optimization and its budget of robustness were tested on a 30-bus system. The simulation results demonstrate the effectiveness of the proposed method and analysis. © 2015 Chin. Soc. for Elec. Eng.

关键词： Second-order cone programming

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Modeling and Analysis of Unit Commitment Considering RCAES System 33

Modeling and Analysis of Unit Commitment Considering RCAES S...

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第三十三届中国控制会议

作者： LIU Bin CHEN Laijun ZHANG Yu FANG Chen MEI Shengwei ZHOU Yuan State Key Lab of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua University Electric Power Research Institute State Grid Shanghai Municipal Electric Power Company Key Laboratory of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of Sciences

ISBN: (纸本)9781479947249

Regenerative compressed air energy storage(RCAES) system is a practical and efficient solution to large-scale integration of renewable energy problems faced by power systems currently. Appropriately modeling of RCAES system is critical to its practical application, whereas research in this area has been very limited. According to the energy storage and transformation process, a concise model of RCAES system applicable to power scheduling field is proposed. Then, a unit commitment model with RCAES system is formulated as a MILP problem which can be accurately solved with high computation efficiency by CPLEX. A modified IEEE 39 bus system is used to study the impacts of parameters of RCAES system on unit commitment and the effectiveness of the proposed model is then validated. Furthermore, the proposed model can also be employed to optimize key parameters of RCAES system, e.g. efficiency and capacity of each part in an integrated way.

关键词： unit commitment,regenerative,CAES,efficiency analysis,schedule

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Optimization of tool-path generation for material extrusion-based additive manufacturing technology

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Additive Manufacturing 2014年 1卷 32-47页

作者： Jin, Yu-an He, Yong Fu, Jian-zhong Gan, Wen-feng Lin, Zhi-wei The State Key Lab of Fluid Power Transmission and Control Systems Department of Mechanical Engineering Zhejiang University Hangzhou310027 China Zhejiang Province's Key Laboratory of 3D Printing Process and Equipment Department of Mechanical Engineering Zhejiang University Hangzhou310027 China

In this study, we propose a tool-path generation approach for material extrusion-based additive manufacturing (AM) that considers the machining efficiency and fabrication precision, which are inherent drawbacks of general AM techniques compared with conventional manufacturing methods. The proposed approach aims to tackle the generation of direction-parallel tool-paths for the interior filling of simple connected areas, which comprises three main steps: (1) determining the inclination of reference lines;(2) generating and grouping tool-path segments into individual sub-paths;and (3) linking sub-paths based on specific requirements. These three modules interact to affect the efficiency and precision of AM significantly. In order to find an optimal inclination, we first analyze the impacts on the fabrication efficiency and manufacturing accuracy with different inclinations. A comparatively accurate building time model is developed subsequently to obtain the optimal tool-path inclination, but without compromising the machining precision, based on the analysis of a geometrical accuracy model. The proposed approach employs different inclinations in distinct layers according to specific manufacturing scenarios and technological requirements. After determining the reference lines, the tool-path segments are selected and grouped based on some characteristics (e.g., the number of intersections between reference lines and boundaries) to make up individual sub-paths, which are then connected to a zigzag-shaped path with short line segment connections. In the module for sub-path linking, some strategies are introduced to decrease the number of useless tool-paths, i.e., uncut paths, which could jeopardize the manufacturing quality by frequently turning the print head on and off. In addition, parametric curves are used to link the final sub-paths to avoid deceleration/acceleration processes in the end/starting parts of the sub-paths. The proposed approach has been used in practice

关键词： 3D printers

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Probabilistic substation fault diagnosis considering instrumentation channels and heterogeneous information: A unified Bayesian network model

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Qinghua Daxue Xuebao/Journal of Tsinghua University 2014年第10期54卷 1384-1390页

作者： Mu, Jianan Sun, Hongbin Wu, Wenchuan Guo, Qinglai Zhang, Boming State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Tsinghua University Beijing100084 China

Fault diagnosis plays an important role in improving power network troubleshooting capability. Conducting local fault diagnosis in substations can make full and quick use of abundant local information. A substation fault diagnosis method was presented based on Bayesian network to adapt to a wealth of information and distributed autonomy under smart grid environment. The method is effective in dealing with uncertainties induced by malfunctions of protection relays and circuit breakers as well as instrumentation channel errors. Heterogeneous information available in substations, such as sequence of events (SOEs), wave records and blocking signals, was also integrated into the method, with the junction tree algorithm used to conduct probabilistic reasoning. The results show that breaker SOEs can be better utilized when considering instrumentation channels. Furthermore, introduction of wave records and blocking signals can significantly improve diagnosis accuracies. ©, 2014, Press of Tsinghua University. All right reserved.

关键词： Bayesian networks

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Development of a frequency dependent network equivalent based RTDS-TSA hybrid transient simulation platform with heterogeneous architecture

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Dianli Xitong Zidonghua/Automation of Electric power systems 2014年第16期38卷 88-93页

作者： Hu, Yizhong Wu, Wenchuan Zhang, Boming Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing100084 China

For the simulation of large-scale AC/DC hybrid systems, both the precision of the DC parts and the efficiency of the whole system should be considered. Thus a real-time hybrid transient simulation platform is proposed by combining the real-time digital simulator (RTDS) and a transient stability analysis (TSA) program. A latest GTFPGA card is used to realize the high speed digital communication between RTDS and the computer deploying TSA program. Moreover, the frequency dependent network equivalent (FDNE) is implemented in this simulation platform to improve the accuracy of simulation results. By simulating a modified New England 39-bus test system incorporating high-voltage direct current (HVDC) components, the validity of the proposed simulation platform is verified.

关键词： Transient analysis

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Real-time charging optimization method considering vehicle charging prediction

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Dianli Xitong Zidonghua/Automation of Electric power systems 2014年第9期38卷 61-68页

作者： Li, Zhengshuo Guo, Qinglai Sun, Hongbin Xin, Shujun Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing100084 China

With large-scale electric vehicles (EVs) integrated into the power system, how to optimize EV charging power in real time to avoid incremental peak load and achieve valley-filling will be important. The regular real-time charging optimization as well as the vehicle charging prediction method is reviewed at first. Since vehicle charging (especially vehicle fleet charging) is predictable, a new real-time charging optimization model is proposed on the basis of the regular method with the consideration of the prediction model of incoming EVs. The new model is solved with receding horizon optimization, obtaining the current optimized charging power of plugged EVs. Through case study with various prediction accuracies, it can be seen that the proposed method always approaches the optimal solution to valley-filling. Moreover, compared with regular method, the proposed method would make a greater improvement of optimization result in the case of more diverse EV plug-in time. ©2014 state Grid Electric power Research Institute Press.

关键词： Forecasting

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A look-ahead generation dispatch method considering discrete generation regulation constraints with large-scale wind power integration

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Dianli Xitong Zidonghua/Automation of Electric power systems 2014年第10期38卷 36-42页

作者： Li, Zhigang Wu, Wenchuan Zhang, Boming Sun, Hongbin Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing100084 China

Look-ahead generation dispatch is a critical measurement to accommodate large-scale integration of wind power generation. In real application, the model for conventional generators should involve generation regulation constraints including regulation frequency constraints and discrete output constraints. Look-ahead generation dispatch with regulation constraints is a large-scale nonlinear mixed-integer programming problem, and it could be hardly solved strictly within acceptable time. An efficient three-stage method for solving this problem is developed, together with a forward-backward-pass dynamic programming approach for handling generation regulation constraints. Numerical tests are taken on IEEE 31-bus systems and a large-scale 264-bus power system to verify the high efficiency and practicability of the proposed method.

关键词： Wind power

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