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Chinese control and Decision Conference, CCDC

作者： Dianyang Li Meishan Zhang Junjie Sun Qingsong Zhao Ning Zhao Bowen Wang State Grid Liaoning Electric Power Co.LTD Power Dispatching Control Cener Shenyang China College of Information Science and Engineering Northeastern University Shenyang China Power System and New Energy Technology Research Center State Grid LiaoNing Electric Power Supply Co. LTD Electric Power Research Institute Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Frequency stability is the most important prerequisite for the safe operation of the power grid. To ensure the safe and stable operation of all kinds of power equipment in the power supply system. The frequency of the power supply system must be maintained within a reasonable range. In this paper, a simulation study on the frequency modulation performance of the combined automatic generation control system based on the improved particle swarm optimization is proposed, and the bidding constraints of the energy storage market are introduced. In the aspect of regulation strategy, the thermal power unit is mainly responsible for the low frequency command, and the energy storage system is responsible for the high frequency command. The real-time management of state of charge can not only improve the performance index of frequency modulation, but also ensure the efficient and stable operation of energy storage system. The operation strategy of energy storage power station to participate in the market in real time. The influence of different types of disturbances and the demand of intraday frequency modulation market are also fully considered. Through the above methods, the frequency modulation performance index can be improved, the wear degree of thermal power units can be reduced, and the reliability of operation can be improved.

关键词： Frequency modulation Power supplies Heuristic algorithms Automatic generation control Real-time systems Performance analysis state of charge

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Load Shedding Risk Mechanism Embedded Operational Reliability Evaluation of Power systems Under Renewable Energy Fluctuations

Load Shedding Risk Mechanism Embedded Operational Reliabilit...

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Power systems and Smart Grid Technologies (PSSGT), IEEE International Conference on

作者： Zheng Dong Xie Kaigui Shao Changzheng Chang Dongxu Lingzi Zhu Xu Longxun State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing China Electric Power Research Institute China Southern Power Grid Guangzhou China Power Dispatching Control Center Guizhou Power Grid Company Ltd. Guiyang China

ISBN: (数字)9798331511401

ISBN: (纸本)9798331511418

Recently, the proportion of renewable energy in power systems has been continuously increasing. The operational reliability evaluation of power systems with a high proportion of renewable energy encounters the challenge of the dimensionality curse. Fortunately, advances in deep learning (DL) techniques have brought new opportunities for operational reliability evaluation of power systems. A load shedding risk mechanism embedded operational reliability evaluation method based on the Physics-Informed Neural Networks (PINN) is proposed in this paper. The physics-informed loss function is carefully designed based on the duality theory. The proposed method can reveal the underlying mechanism of load shedding risk and achieve a high accuracy within a remarkably short computation time. The proposed method has a very broad application prospect in the field of operational reliability evaluation.

关键词： Deep learning Renewable energy sources Accuracy Fluctuations Neural networks Load shedding Reliability theory Power system reliability Smart grids Reliability

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Optimization strategies for clearing the electric energy and FM market with combined thermal energy and storage

Optimization strategies for clearing the electric energy and...

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Chinese control and Decision Conference, CCDC

作者： Dianyang Li Junjie Sun Qingsong Zhao Huanyu Guo Yunning Feng Bowen Wang Power Dispatching Control Cener State Grid Liaoning Electric Power Co. LTD College of Information Science and Engineering Northeastern University Shenyang China Power System and New Energy Technology Research Center State Grid LiaoNing Electric Power Supply Co. LTD Electric Power Research Institute Shenyang China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

As a new type of regulation resource with two-way regulation function, energy storage is increasingly involved in automatic generation control and has become the key to the future frequency modulation (FM) auxiliary service market. In this paper, we propose an optimization strategy for market clearing of electric energy and frequency modulation based on the combination of thermal storage, which uses the security constrained unit combination (SCUC) model to determine the unit output plan and storage charging and discharging plan, and is based on the security constrained economic dispatch (SCED) model, with the objective of minimizing the total cost of the electric power system for market clearing. The system frequency stability is maintained by adjusting the output of generating units in order to respond quickly to changes in the system frequency. In this paper, we study the issues related to the participation of solo energy storage in the electric energy and frequency modulation market, including the market demand for frequency modulation auxiliary services, resource allocation strategy, security constrained unit combination (SCUC), and security constrained economic dispatch (SCED), etc., and utilize the data of frequency modulation auxiliary services provided by each unit in the power system to calculate the frequency modulation mileage and the capacity clearing price of each unit, as well as to construct the arithmetic example and evaluate its feasibility and economic benefits.

关键词： Frequency modulation Power system stability Regulation Security Thermal loading Thermal energy Optimization

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Obtaining Soil Moisture Data Using an L-Band Passive Microwave Radiometer Based on Unmanned Aerial Vehicles

Obtaining Soil Moisture Data Using an L-Band Passive Microwa...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yawei Xu Jinyang Du Hui Lu Jiaxin Tian Kaixun He Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing China Numerical Terradynamic Simulation Group W.A. Franke College of Forestry & Conservation The University of Montana Missoula United States State Key Laboratory of Hydroscience and Engineering Tsinghua University Beijing China Department of Earth System Science Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Tsinghua University Beijing China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Unmanned aerial vehicles (UAVs) can offer higher spatial resolution images compared to satellites. In this experiment, an L-band microwave radiometer named PoLRa was equipped on an UAV to detect surface soil moisture and a new soil moisture retrieval algorithm was developed for it. Compared with the algorithm provided by suppliers of PoLRa, the new algorithm can significantly improve the accuracy of soil moisture and enhance spatial details. A comparison with ground-based soil moisture measurements showed that the UAV's spatial resolution reached 10 meters with an accuracy of 0.08 m 3 /m 3 . This demonstrates significant advantages for monitoring soil moisture at the farmland scale, making it applicable to precision agriculture, flash flood warnings, and drought monitoring in the future.

关键词： Accuracy Soil measurements Soil moisture Surface soil Autonomous aerial vehicles Microwave radiometry Spatial resolution

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The 2022 report of synergetic roadmap on carbon neutrality and clean air for China:Accelerating transition in key sectors

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Environmental Science and Ecotechnology 2024年第3期19卷 4-18页

作者： Yu Lei Zhicong Yin Xi Lu Qiang Zhang Jicheng Gong Bofeng Cai Cilan Cai Qimin Chai Huopo Chen Renjie Chen Shi Chen Wenhui Chen Jing Cheng Xiyuan Chi Hancheng Dai Xiangzhao Feng Guannan Geng Jianlin Hu Shan Hu Cunrui Huang Tiantian Li Wei Li Xiaomei Li Jun Liu Xin Liu Zhu Liu Jinghui Ma Yue Qin Dan Tong Xuhui Wang Xuying Wang Rui Wu Qingyang Xiao Yang Xie Xiaolong Xu Tao Xue Haipeng Yu Da Zhang Ning Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Xin Zhang Zengkai Zhang Bo Zheng Yixuan Zheng Jian Zhou Tong Zhu Jinnan Wang Kebin He Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100041China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100041China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of HealthFudan UniversityShanghai200032China School of Economics and Management Beijing University of Chemical TechnologyBeijing100029China Department of Earth System Science University of CaliforniaIrvineCA92697USA National Meteorological Center China Meteorological AdministrationBeijing100081China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Policy Research Center for Environment and Economy Ministry of Ecology and Environment of the People's Republic of ChinaBeijing100029China Jiangsu Key Laboratory of Atmospheric Environment Monitoring

China is now confronting the intertwined challenges of air pollution and climate *** the high synergies between air pollution abatement and climate change mitigation,the Chinese government is actively promoting synergetic control of these two *** Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key *** Synergetic Roadmap 2022 report is the first annual update,featuring 20 indicators across five aspects:synergetic governance system and practices,progress in structural transition,air pollution and associated weather-climate interactions,sources,sinks,and mitigation pathway of atmospheric composition,and health impacts and benefits of coordinated *** to the comprehensive review presented in the 2021 report,the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant *** milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time,a decline in the production of crude steel and cement after years of growth,and the surging penetration of electric ***,in 2022,China issued the first national policy that synergizes abatements of pollution and carbon emissions,marking a new era for China's pollution-carbon *** changes highlight China's efforts to reshape its energy,economic,and transportation structures to meet the demand for synergetic control and sustainable ***,the country has witnessed a slowdown in carbon emission growth,improved air quality,and increased health benefits in recent years.

关键词： Synergetic roadmap Carbon neutrality Clean air

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Integrated Capacity Analysis Model and Optimization Based on Conflict Resolution for High-Speed Railway

Integrated Capacity Analysis Model and Optimization Based on...

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Chinese Automation Congress (CAC)

作者： Yuan Wei Lin Ma Jiateng Yin National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

With the increased demand of passengers, the capacity analysis of high-speed railways has attracted much attention for serving more passengers with limited line resources. Existing methods mainly focused on the capacity analysis of rail sections or stations, separately. Our study first addressed the integrated capacity analysis of high-speed railways. We established an integrated capacity analysis model by combining the signal control of track sections, the overtaking of trains and the capacity of rail stations. Then this paper proposed a conflict resolution strategy based on multi-objective optimization. A real-world case study on the Beijing-Shanghai high-speed railway demonstrated that our approach can better model the influencing factors in high-speed railways and can further improve the line capacity compared with existing approaches.

关键词： Rails Analytical models Automation Rail transportation Optimization Signal resolution

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The 2023 report of the synergetic roadmap on carbon neutrality and clean air for China: Carbon reduction, pollution mitigation, greening, and growth

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Environmental Science and Ecotechnology 2025年第1期23卷 1-18页

作者： Jicheng Gong Zhicong Yin Yu Lei Xi Lu Qiang Zhang Cilan Cai Qimin Chai Huopo Chen Renjie Chen Wenhui Chen Jing Cheng Xiyuan Chi Hancheng Dai Zhanfeng Dong Guannan Geng Jianlin Hu Shan Hu Cunrui Huang Tiantian Li Wei Li Xiaomei Li Yongsheng Lin Jun Liu Jinghui Ma Yue Qin Weiqi Tang Dan Tong Jiaxing Wang Lijuan Wang Qian Wang Xuhui Wang Xuying Wang Libo Wu Rui Wu Qingyang Xiao Yang Xie Xiaolong Xu Tao Xue Haipeng Yu Da Zhang Li Zhang Ning Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Zengkai Zhang Hongyan Zhao Bo Zheng Yixuan Zheng Tong Zhu Huijun Wang Jinnan Wang Kebin He State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100041China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100041China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of HealthFudan UniversityShanghai200032China School of Economics and Management Beijing University of Chemical TechnologyBeijing100029China Department of Earth System Science University of CaliforniaIrvineIrvineCA92697USA National Meteorological Center China Meteorological AdministrationBeijing100081China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Institute of Eco-Environmental Management and Policy Chinese Academy of Environmental PlanningBeijing100041China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Contr

The response to climate change and air pollution control demonstrates strong synergy across scientific mechanisms,targets,strategies,and governance *** report,based on a monitoring indicator system for coordinated governance of air pollution and climate change,employs an interdisciplinary approach combining natural and social *** establishes 20 indicators across five key areas:air pollution and climate change,governance systems and practices,structural transformation and technologies,atmospheric components and emission reduction pathways,and health impacts and *** report tries to provide actionable insights into the interconnectedness of air pollution and climate *** highlights key policy gaps,presents updated indicators,and offers a refined monitoring framework to track progress toward China's dual goals of reducing emissions and improving air *** to previous editions,this year's report has updated four key indicators:meteorological impacts on air quality,climate change and its effects,governance policies,and low-carbon building energy *** aim is to further refine the monitoring framework,track progress,and establish a comprehensive theory for collaborative governance while identifying challenges and proposing solutions for China's pathway to carbon neutrality and clean *** report comprises six *** executive summary chapter is followed by analyzing air pollution and climate change *** systems and practices are discussed in the third chapter,focusing on policy implementation and local *** fourth chapter addresses structural transformations and emission reduction technologies,including energy and industrial shifts,transportation,low-carbon buildings,carbon capture and storage,and power *** fifth chapter outlines atmospheric component dynamics and emission pathways,presenting insights into emission drivers and future *** sixth chapter assesses he

关键词： Synergetic roadmap Carbon neutrality Clean air

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Long-term change in low-cloud cover in Southeast China during cold seasons

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Atmospheric and Oceanic Science Letters 2022年第6期15卷 9-14页

作者： Zhe Chen Minghuai Wang Haipeng Zhang Shuheng Lin Zhun Guo Yiquan Jiang Chen Zhou Institute for Climate and Global Change Research School of Atmospheric SciencesNanjing UniversityNanjingChina Department of Atmospheric and Oceanic Science&Earth System Science Interdisciplinary Center University of MarylandCollege ParkMDUSA School of Atmospheric Sciences Sun Yat-sen UniversityZhuhaiChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

Southeast China has comparable stratus cloud to that over the oceans,especially in the cold seasons(winter and spring),and this cloud has a substantial impact on energy and hydrological ***,uncertainties remain across datasets and simulation results about the long-term trend in low-cloud cover in Southeast China,making it difficult to understand climate change and related physical *** this study,multiple datasets and numerical simulations were applied to show that low-cloud cover in Southeast China has gone through two stages since 1980—specifically,a decline and then a rise,with the turning point around *** regional moisture transport plays a crucial role in low-cloud cover changes in the cold seasons and is mainly affected by the Hadley Cell in winter and the Walker Circulation in spring,*** moisture transport was not well simulated in CMIP6 climate models,leading to poor simulation of the low-cloud cover trend in these *** study provides insights into further understanding the regional climate changes in Southeast China.

关键词： Low-cloud cover Large-scale circulation Hadley cell Pacific walker circulation

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AGI in Metaverse for Smart Cities and Societies: A Cyber Physical Social Approach

AGI in Metaverse for Smart Cities and Societies: A Cyber Phy...

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control Conference (ANZCC), Australian and New Zealand

作者： Xiao Wang Jun Huang Yong-Lin Tian Fei-Yue Wang Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Faculty of Innovation Engineering Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China Macao Institute of Systems Engineering Macau University of Science and Technology Macao China

The development of artificial general intelligence (AGI) and metaverse technologies hold great potential to enhance the effectiveness of smart cities and societies. we present a cyberphysical-social approach to integrating AGI into metaverse-based smart cities and societies, with a specific focus on parallel intelligence. The proposed approach considers the interplay between the physical environment, digital systems, social dynamics, and emerging forms of parallel intelligence, as well as swarm intelligence and collective intelligence. By leveraging these forms of parallel intelligence, the integration of AGI can create more responsive and proactive infrastructure, personalized and efficient services, and foster greater community engagement. The metaverse acts as a platform for simulating real-world scenarios and testing and refining AGI models before deployment in the physical world, while also facilitating the development and coordination of parallel intelligence. However, ethical considerations must be taken into account to ensure responsible deployment and avoid exacerbating existing societal inequalities or infringing upon individual privacy rights. This report provides a comprehensive framework for the integration of AGI and parallel intelligence into metaverse-based digital and smart organizations, while emphasizing the importance of human ethics, social responsibility, and ecological sustainability.

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Adaptive Variable Step Size Photovoltaic MPPT Algorithm Based on Light Intensity Prediction

Adaptive Variable Step Size Photovoltaic MPPT Algorithm Base...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Ba Gui Jingtian Bi Haoqing Xiong Ping Wu Jie Wu Jianping Yu Dispatch Control Center State Grid Tibet Electric Power Company Limited Lhasa Tibet China Power System Research Department China Electric Power Research Institute Beijing China Power System Research Department State Grid Tibet Electric Power Company Limited/State Grid Henan Electric Power Company Lhasa Tibet/Zhengzhou Henan China College of Energy and Electrical Engineering Hohai University Nanjing Jiangsu China

To enhance the efficiency and stability of maximum power point tracking (MPPT) in photovoltaic (PV) power generation systems, and to address the issue of misjudgment in the traditional perturbation and observation method (P&O), an adaptive MPPT control approach based on light intensity prediction is proposed. Firstly, the correlation between the input and output of the system is analyzed to determine the necessary input terms. Secondly, the multi-time series LSTM algorithm is utilized to select pertinent historical PV sequence information according to the correlation analysis results, enabling short-term prediction of PV output. Finally, the Boost circuit is employed as the control object, with the light intensity prediction result serving as the input to adaptively adjust the step size of the P&O. Through the MATLAB/Simulink simulation platform, the results demonstrate that the adaptive variable step size photovoltaic MPPT algorithm based on light intensity prediction can effectively mitigate power oscillation in steady state while exhibiting good tracking speed and accuracy.

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