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Study on the operating parameters of the 10 kW SOFC-CHP system with syngas

International Journal of Coal Science & Technology 2021年第4期8卷 500-509页

作者： Biao Li Zewei Lyu Jianzhong Zhu Minfang Han Zaihong Sun State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Energy and Power EngineeringTsinghua UniversityBeijing 100084China Suzhou Huatsing Power Co. LtdJiangsu 210094China

Solid oxide fuel cell combined with heat and power(SOFC-CHP)system is a distributed power generation system with low pollution and high *** this paper,a 10 kW SOFC-CHP system model using syngas was built in Aspen *** operating parameters,such as steam to fuel ratio,stack temperature,reformer temperature,air flow rate,and air preheating temperature,were *** was conducted based on the simulation *** suggest that higher steam to fuel ratio is beneficial to the electrical efficiency,but it might decrease the gross system *** stack and reformer temperatures contribute to the electrical efficiency,and the optimal operating temperatures of stack and reformer when considering the stack degradation are 750℃and 700℃,*** air preheating temperature barely affects the electrical efficiency but affects the thermal efficiency and the gross system efficiency,the recommended value is around 600℃under the reference condition.

关键词： SOFC-CHP system Operational parameters Optimization Efficiency

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Phase Segmentation of Ni/YSZ Anode for Solid Oxide Fuel Cells by Deep Learning

Phase Segmentation of Ni/YSZ Anode for Solid Oxide Fuel Cell...

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243rd ECS Meeting

作者： Wang, Y. Matsui, Y. Hosomizo, A. Kishimoto, M. Han, M. Iwai, H. Department of Mechanical Engineering and Science Kyoto University Nishikyo-ku Kyoto615-8540 Japan State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Energy and Power Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9781607685395

A deep learning network is implemented for the phase segmentation of Ni/YSZ anode of solid oxide fuel cells (SOFCs), as manual segmentation of focused ion beam-scanning electron microscopy (FIB-SEM) images is time-consuming. Segmentation is performed on two samples with different volume ratios of Ni to YSZ. The mean intersection over union (mIoU) reaches 0.9363, indicating good agreement between the predicted images and the manually segmented images. Furthermore, the impact of image augmentation on segmentation accuracy is investigated, and it is found that augmentation is necessary when the number of images in the training set is small or the training and testing sets come from different samples. Furthermore, mixing a sixth of manually segmented images from a new sample into the training set can significantly improve the accuracy of automated segmentation for the new sample. This strategy reduces the number of images requiring manual segmentation and improves processing efficiency. © The Electrochemical Society.

关键词： Solid oxide fuel cells (SOFC)

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Modeling the dynamic impacts of maritime network blockage on global supply chains

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The Innovation 2024年第4期5卷 103-109,102页

作者： Shen Qu Yunlei She Qi Zhou Jasper Verschuur Lu-Tao Zhao Huan Liu Ming Xu Yi-Ming Wei Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China School of Management Beijing Institute of TechnologyBeijing 100081China Beijing Key Lab of Energy Economics and Environmental Management Beijing 100081China Oxford Programme for Sustainable Infrastructure Systems(OPSIS) Environmental Change InstituteUniversity of OxfordOX12JD OxfordUK State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China School of Environment Tsinghua UniversityBeijing 100084China

Recent phenomena such as pandemics,geopolitical tensions,and climate change-induced extreme weather events have caused transportation network interruptions,revealing vulnerabilities in the global supply chain.A salient example is the March 2021 Suez Canal blockage,which delayed 432 vessels carrying cargo valued at$92.7 billion,triggering widespread supply chain *** ability to model the spatiotemporal ramifications of such incidents remains *** fill this gap,we develop an agent-based complex network model integrated with frequently updated maritime *** Suez Canal blockage is taken as a case *** results indicate that the effects of such blockages go beyond the directly affected countries and *** Suez Canal blockage led to global losses of about$136.9($127.5–$147.3)billion,with India suffering 75%of these *** losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post *** proposed model can be applied to diverse blockage scenarios,potentially acting as an earlyalert system for the ensuing supply chain ***,high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

关键词： chains valued extreme

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A Novel Potential Line Strategy for Autonomous Vehicle control in Lane-Free Traffic

A Novel Potential Line Strategy for Autonomous Vehicle Contr...

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International Conference on Intelligent Transportation

作者： Hanwen Zhang Majid Rostami-Shahrbabaki Dimitrios Troullinos Klaus Bogenberger Chair of Traffic Engineering and Control Technical University of Munich Germany Dynamic Systems and Simulation Laboratory Technical University of Crete Chania Crete Greece

Recent developments in vehicular traffic have brought about the concept of lane-free traffic, challenging the traditional notion of parallel lanes, allowing vehicles to potentially drive at any arbitrary lateral location of the road. In this paper, we investigate the potential lines strategy proposed in our previous study for an efficient lateral distribution of vehicles in automated lane-free freeways. Potential lines allow for structured lane-free traffic where each vehicle receives a desired lateral location based on its desired speed. To this end, we mimic the behavior of conventional driving by assigning the right side of the road to slower vehicles while faster vehicles are led toward the left. As a result, the road surface effectively forms a speed-based hierarchy, with vehicles flowing smoothly from right to left in a monotonic increase of speed. We utilize the Probability Integral Transform approach to have a uniform lateral distribution of potential lines despite different distributions of desired speed. In addition, we show that the potential lines are efficient means of handling different maneuvers such as merge, diverge, and emergency vehicle preemption on a freeway. The simulation results for a relatively long freeway demonstrate that potential lines can minimize unnecessary lateral movement during overtaking, creating a more structured and efficient driving environment. Furthermore, results show that potential lines can smoothly guide vehicles to take off-ramps or merge from on-ramps in high-density traffic conditions.

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Wind Power Forecast Based on Dimensionality Reduction Using Ridge Regression 5

Wind Power Forecast Based on Dimensionality Reduction Using ...

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5th International Conference on Renewable Energy and Power Engineering, REPE 2022

作者： Sun, Shuxin Wu, Fubao Qiao, Ying Lu, Zongxiang Hao, Yuchen Tsinghua University State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Beijing100084 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Nanjing China Control Ctr State Grid Jiangsu Elect Power Co Ltd Nanjing210017 China

ISBN: (数字)9781665482066

ISBN: (纸本)9781665482066

In order to reduce the randomness and fluctuation of wind power, numerical weather prediction is usually used to forecast power generation. Due to the redundancy of numerical weather prediction factors, dimensionality reduction is carried out to improve the effectiveness of data processing and reduce the complexity of algorithm. In this paper, the multicollinearity diagnosis is carried out to show the existence of multicollinearity among numerical weather prediction variables. The ridge regression method is adopted to screen variables, so as to reduce the dimension of numerical weather prediction data, which are trained later by back propagation neural network or convolutional neural network to fit corresponding power data. In comparison with results using training data without preprocessing, dimensionality reduction can improve predicting effect in most cases and reduce the error caused by improper selection of neural network. © 2022 IEEE.

关键词： Regression analysis

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Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

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Energy 2025年 328卷

作者： Yang, Mao Jiang, Renxian Yu, Xinnan Wang, Bo Su, Xin Ma, Chenglian The Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing100912 China

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind Power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind Power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively. © 2025 Elsevier Ltd

关键词： Iterative methods

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Nonlinear E-field simulation of HVDC Converter Transformer Busing and Its Structure Optimization With RBF Neural Network and NSGA-II Algorithm 13

Nonlinear E-field Simulation of HVDC Converter Transformer B...

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13th International Conference on Power and Energy systems, ICPES 2023

作者： He, Yongsheng Zhang, Shiling Lu, Zongxiang Wang, Pengbo State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Haidian China Transmission Equipment and System Security and New Technology Dept Name of State Key Laboratory of Power Chongqing China

ISBN: (纸本)9798350345063

Static DC and PR are typical operation conditions of HVDC converter transformer bushing outlet device, moreover, the electrical parameters of RIP, transformer oil and OIP have the nonlinear relationship with E-field stress and temperature. Under the temperature gradient, the electrical parameters will modify the static DC and PR E-field distribution of the composite insulation. In order to simulate static DC and PR electric field of the composite insulation structure, this paper established the full model of the converter transformer outlet. Then, the structure parameters of converter transformer outlet have been optimized using combined RBF neural network and NSGA-II algorithm. Moreover, electric field verification calculation has been carried out under AC and PR conditions. The results show that under uniform temperature condition, E-field strength is larger than that under iso-thermal condition. The overshoot coefficient of the bushing end and barrier reach 65% and 45%, respectively. The study can provide reference for the design of outlet structure of the converter transformer. © 2023 IEEE.

关键词： DC transformers

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Short-term Power Prediction Based on Improved NWP Data Considering Wind Speed Distribution Inner Wind Farm 6

Short-term Power Prediction Based on Improved NWP Data Consi...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Ma, Wei Qiao, Ying Lu, Zongxiang Liang, Zhifeng Li, Jiaming Hao, Yuchen Tsinghua University State Key Laboratory of Control and Simulation Power Systems and Generation Equipments of Electrical Engineering Beijing China State Grid Corporation of China Beijing China State Grid Jiangsu Power Grid Corporation Nanjing China

ISBN: (纸本)9798350347159

The wind farm has only one NWP data point, which cannot accurately reflect the wind resources inside the wind farm. To solve the problem of a poor match between short-term wind power prediction numerical weather forecast and wind farm measured weather. Put forward a kind of based on clustering and temporal characteristics of the modified liters of scale wind power prediction method, first of all, using EOF orthogonal decomposition method to extract the features of each fan, using hierarchical analysis method of the characteristics of the data matrix clustering, and then, each cluster sample selected representative of a fan, using the error transfer characteristic of the NWP data sequence is modified. Finally, The CNN prediction model is used for power prediction, and the weight is determined according to the cluster sample size. A wind farm in northern Hebei, China, is used to verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Weather forecasting

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AI-Optimized Genetic Algorithm for Enhancing Resource Recovery in the Circular Economy

AI-Optimized Genetic Algorithm for Enhancing Resource Recove...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Abderrahman Mansouri Bellat Abdelouahad Idriss Bennis Ali Siadat Fatiha Akef Modeling and Simulation of Intelligent Industrial Systems Laboratory (M2S2I) ENSET Mohammedia Hassan II University Casablanca Morocco Laboratory of Design Manufacturing and Control Arts et Metiers ParisTech Metz France Laboratory of Mechanical and Thermal Processes and Control (PCMT) ENSAM Rabat Mohammed V University in Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This paper presents a Genetic Algorithm (GA)- based optimization approach aimed at improving circular economy strategies by optimizing recyclability and economic value, while minimizing disassembly complexity and environmental impact. A multi-objective function is established, incorporating essential parameters such recyclability rate, component reuse value, disassembly expenses, carbon footprint, and waste minimization. The GA investigates an optimal balance between sustainability and economic viability using an evolutionary search method that identifies and enhances solutions throughout several generations. The dataset comprises 50 components of end-of-life products, categorized as metals (40%), plastics (30%), and electronic materials (30%), exhibiting recyclability rates between 35% and 95%. The results indicate that the GA attains a 25% enhancement in recyclability, a 30% reduction in disassembly complexity, and a 20% decrease in carbon footprint relative to traditional approaches. The suggested method offers a versatile and scalable decision-making instrument for manufacturers, recyclers, and policymakers, enhancing a more sustainable resource recovery system.

关键词： Systematics Instruments Computational modeling Search methods Decision making Complexity theory Sustainable development Optimization Carbon footprint Genetic algorithms

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A framework of day-ahead wind supply power forecasting by risk scenario perception

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IEEE Transactions on Sustainable Energy 2025年

作者： Yang, Mao Huang, Yutong Wang, Zhao Wang, Bo Su, Xin Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Contr Ol of Renewable Energy & Storage Systems Beijing100912 China

Wind power forecasting (WPF) systems are essential to maintain the safe and stable operation of the power system in case of large-scale grid-connected wind farms. However, the current forecasting has the problem of disunity between statistical value and application value, that is, it only pays attention to its forecasting accuracy and ignores the risks caused by it in the power system. In order to solve the above problems, this study proposes a framework of wind supply power forecasting (WSPF) for wind farm cluster, which takes into account the risk scenario perception. First of all, aiming at the predicted risk phenomenon in WPF, TimesNet combined with the fluctuation information of Numerical Weather Prediction (NWP) wind speed is used to identify the corresponding risk scenarios. Secondly, the effective consumption area and power supply risk area evaluation index, as well as the accuracy of WSPF are defined, and the optimal forecasting curve correction scheme is fitted according to the index. Thirdly, taking into account the correction scheme and identification results, a variety of predictors are used to verify the WSPF according to the above framework. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia Autonomous region of China, the average accuracy of WSPF has increased by 37%, which verifies the effectiveness and universality of this method. © 2010-2012 IEEE.

关键词： Wind forecasting

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