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Hierarchical Game Approach for Optimization of Regional Integrated Energy System Clusters Considering Bounded Rationality

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 302-313页

作者： Lei Dong Mengting Li Junjie Hu Sheng Chen Tao Zhang xinying wang Tianjiao Pu school of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China Department of Artificial Intelligence Application Research China Electric Power Research InstituteBeijing 100192China Key Laboratory of Smart Grid of Ministry of Education Key Laboratory of Smart Energy&Information Technology of Tianjin MunicipalityTianjin UniversityTianjin 300072China

Regional integrated energy system(RIES)cluster,i.e.,multi-source integration and multi-region coordination,is an effective approach for increasing energy utilization efficiency.The hierarchical architecture and limited information sharing of RIES cluster make it difficult for traditional game theory to accurately describe their game behavior.Thus,a hierarchical game approach considering bounded rationality is proposed in this paper to balance the interests of optimizing RIES cluster under privacy protection.A Stackelberg game with the cluster operator(CO)as the leader and multiple RIES as followers is developed to simultaneously optimize leader benefit and RIES utilization efficiency.Concurrently,a slight altruistic function is introduced to simulate the game behavior of each RIES agent on whether to cooperate or not.By introducing an evolutionary game based on bounded rationality in the lower layer,the flaw of the assumption that participants are completely rational can be avoided.Specially,for autonomous optimal dispatching,each RIES is treated as a prosumer,fexibly switching its market participation role to achieve cluster coordination optimization.Case studies on a RIES cluster verify effectiveness of the proposed approach.

关键词： Bounded rationality coordinated optimization evolutionary game regionaIilntegrated energysystem stackelberg game

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Humic acid-mediated transport of a typical soil passivation remediation product(chloropyromorphite)in saturated porous media

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Journal of Environmental Sciences 2024年第7期141卷 51-62页

作者： xinying Li Mengjia Zhang Siyuan Li Wei Wei School of Environment Jiangsu Engineering Lab of Water and Soil Eco-remediationJiangsu Province Engineering Research Center of Environmental Risk Prevention and Emergency Response TechnologyNanjing Normal UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China

Conversion of labile Pb species into chloropyromorphite(CPY)using phosphorus-bearing amendments was considered to be an ideal strategy in soil passivation remediation.However,the fate and transport of CPY in the soil are poorly understood.This study aims to fill the knowledge gap by evaluating the fate and transport of CPY under environmentally relevant conditions of humic acid(HA),pH,electrolyte concentration,and species through the saturated sandy medium.Results showed that bare CPY colloids are basically immobile in sandy porous media while the co-existence of HA made the transport of CPY improved by30%-93.5%.Facilitated transport of CPY was attributed to the increased stability of CPY and the repulsive interaction between CPY particles and sands due to HA adsorption.The mobility of CPY was also increased with increasing pH from 5.0 to 9.0.When the pH was 9 with a10 mmol/L NaCl background solution,the stronger energy barrier between CPY and sand led to enhanced transport behavior.The divalent Ca^(2+)had a more dramatic effect than monovalent Na^(+)on the aggregation and sedimentation of CPY colloids due to its effectivescreening of the surface charge of CPY and bridging interaction with CPY particles.Derjaguin-LandauVerwey-Overbeek theory and attachment efficiency calculation indicated that high energy barriers were responsible for the high mobility of CPY colloids,while the retention of CPY in sands was mainly caused by secondary energy minimum and physically straining.The findings of this work can help to evaluate the fate of soil passivation remediation products in natural water and soil.

关键词： Chloropyromorphite DLVO theory Stability Saturated porous medium Transport

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Assessment of cheese sign and its association with vascular risk factors: Data from PUMCH dementia cohort

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中华医学杂志(英文版) 2024年第7期137卷 830-836页

作者： Huang xinying Hou Bo wang Jie Li Jie Shang Li Mao Chenhui Dong Liling Liu Caiyan Feng Feng Gao Jing Peng Bin Department of Neurology State Key Laboratory of Complex Severe and Rare Disease Peking Union Medical College Hospital Chinese Academy of Medical Science and Peking Union Medical College Beijing 100730 China Department of Radiology Chinese Academy of Medical Sciences and Peking Union Medical College

Background: In the clinic, practitioners encounter many patients with an abnormal pattern of dense punctate magnetic resonance imaging (MRI) signal in the basal ganglia, a phenomenon known as "cheese sign". This sign is reported as common in cerebrovascular diseases, dementia, and old age. Recently, cheese sign has been speculated to consist of dense perivascular space (PVS). This study aimed to assess the lesion types of cheese sign and analyze the correlation between this sign and vascular disease risk factors.Methods: A total of 812 patients from Peking Union Medical College Hospital (PUMCH) dementia cohort were enrolled. We analyzed the relationship between cheese sign and vascular risk. For assessing cheese sign and defining its degree, the abnormal punctate signals were classified into basal ganglia hyperintensity (BGH), PVS, lacunae/infarctions and microbleeds, and counted separately. Each type of lesion was rated on a four-level scale, and then the sum was calculated; this total was defined as the cheese sign score. Fazekas and Age-Related White Matter Changes (ARWMC) scores were used to evaluate the paraventricular, deep, and subcortical gray/white matter hyperintensities.Results: A total of 118 patients (14.5%) in this dementia cohort were found to have cheese sign. Age (odds ratio [OR]: 1.090, 95% confidence interval [CI]: 1.064-1.120,P <0.001), hypertension (OR: 1.828, 95% CI: 1.123-2.983,P = 0.014), and stroke (OR: 1.901, 95% CI: 1.092-3.259,P = 0.025) were risk factors for cheese sign. There was no significant relationship between diabetes, hyperlipidemia, and cheese sign. The main components of cheese sign were BGH, PVS, and lacunae/infarction. The proportion of PVS increased with cheese sign severity.Conclusions: The risk factors for cheese sign were hypertension, age, and stroke. Cheese sign consists of BGH, PVS, and lacunae/infarction.

关键词： Dementia Cerebrovascular disease Cheese sign Dense punctate lesions Basal ganglia Risk factor White matter

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Comprehensive understanding of the thriving electrocatalytic nitrate/nitrite reduction to ammonia under ambient conditions

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Journal of Energy Chemistry 2024年第5期92卷 459-483页

作者： xinying Zhao Yuzhuo Jiang Mengfan wang Yunfei Huan Qiyang Cheng Yanzheng He Tao Qian Chenglin Yan Collaborative Innovation Center of Suzhou Nano Science and Technology College of EnergySoochow UniversitySuzhou 215006JiangsuChina School of Chemistry and Chemical Engineering Nantong UniversityNantong 226019JiangsuChina School of Petrochemical Engineering Changzhou UniversityChangzhou 213164JiangsuChina

Ammonia(NH_(3))is a multifunctional compound that is an important feedstock for the agricultural and pharmaceutical industries and attractive energy storage medium.At present,NH_(3)synthesis is highly dependent on the conventional Haber–Bosch process that operates under harsh conditions,which consumes large quantities of fossil fuels and releases a large amount of carbon dioxide.As an alternative,electrosynthesis is a prospective method for producing NH_(3)under normal temperature and pressure conditions.Although electrocatalytic nitrogen reduction to ammonia has attracted considerable attentions,the low solubility of N_(2)and high N≡N cracking energy render the achievements of high NH_(3) yield rate and Faradaic efficiency difficult.Nitrate and nitrite(NO_(x)^(-))are common N-containing pollutants.Due to their high solubilities and low dissociation energy of N=O,NO_(x)^(-)−are ideal raw materials for NH_(3) production.Therefore,electrocatalytic NO_(x)^(-)−reduction to NH_(3)(eNO_(x)RR)is a prospective strategy to simultaneously realise environmental protection and NH_(3) synthesis.This review offers a comprehensive understanding of the thriving eNO_(x)RR under ambient conditions.At first,the popular theory and mechanism of eNO_(x)RR and a summary of the measurement system and evaluation criteria are introduced.Thereafter,various strategies for developing NO_(x)−reduction catalysts are systematically presented and discussed.Finally,the challenges and possible prospects of electrocatalytic NO_(x)^(-1) reduction are outlined to facilitate energy-saving and environmentally friendly large-scale synthesis of NH_(3) in the future.

关键词： Electrocatalytic nitrate reduction Electrocatalytic nitrite reduction Ammonia synthesis Pollutant removal Electrosynthesis

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Cobalt-Catalyzed Switchable[4+1]and[4+1+1]Spirocyclization of Aromatic Amides with 2-Diazo-1H-indene-1,3(2H)-dione:Access to Spiro Indene-2,1'-isoindolinones and Spiro Isochroman-3,1'-isoindolinones

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Chinese Journal of Chemistry 2024年第4期42卷 363-369页

作者： Bin Li Mengmeng Xie Jingyu Li Nana Shen xinying Zhang Xuesen Fan State Key Laboratory of Antiviral Drugs Pingyuan LaboratoryKey Laboratory of Green Chemical Media and ReactionsKey Laboratory for Yellow River and Huai River Water Environmental Pollution ControlMinistry of EducationSchool of EnvironmentSchool of Chemistry and Chemical EngineeringHenan Normal UniversityXinxiangHenan453007 China

Herein,we report a condition-controlled divergent synthesis of spiro indene-2,1'-isoindolinones and spiro isochroman-3,1'-isoindolinones through cobalt-catalyzed formal[4+1]and[4+1+1]spirocyclization of aromatic amides with 2-diazo-1H-indene-1,3(2H)-dione.When the reaction is carried out under air in ethyl acetate,spiro indene-2,1'-isoindolinones are formed through Co(II)-catalyzed C—H/N—H[4+1]spirocyclization.When the reaction is run under O2 in CH3CN,on the other hand,spiro isochroman-3,1'-isoindolinones are generated through Baeyer-Villiger oxidation of the in situ formed spiro indene-2,1'-isoindolinones with O2 as a cheaper and environmental-friendly oxygen source.In general,these protocols have advantages such as using non-precious and earth-abundant metal catalyst,no extra additive,high efficiency and regioselectivity.A gram-scale synthesis and the removal of the directing group further highlight its utility.

关键词： Spiro indene-2,1'-isoindolinones Spiro isochroman-3,1'-isoindolinones 3d Transition metals Cobalt-catalyzed C-H Activation Switchable[4+1]and[4+1+1]spirocyclization Aromatic amides 2-Diazo-1H-indene-1,3(2H)-dione

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Load Shedding Control Strategy in Power Grid Emergency State Based on Deep Reinforcement Learning

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1175-1182页

作者： Jian Li Sheng Chen xinying wang Tianjiao Pu China Electric Power Research Institute Haidian DistrictBeijing 100192China

In viewing the power grid for large-scale new energy integration and power electrification of power grid equipment,the impact of power system faults is increased,and the ability of anti-disturbance is decreased,which makes the power system fault clearance more dificult.In this paper,a load shedding control strategy based on artificial intelligence is proposed,this action strategy of load shedding,which is selected by deep reinforcement learning,can support autonomous voltage control.First,the power system operation data is used as the basic data to construct the network training dataset,and then a novel reward function for voltage is established.This value function,which conforms to the power grid operation characteristics,will act as the reward value for deep reinforcement learning,and the Deep Deterministic Policy Gradient algorithm(DDPG)algorithm,with the continuous action strategy,will be adopted.Finally,the deep reinforcement learning network is continuously trained,and the load shedding strategy concerning the grid voltage control problem will be obtained in the power system emergency control situation,and this strategy action is input into the Pypower module for simulation verification,thereby realizing the joint drive of data and model.According to the numerical simulation analysis,it shows that this method can effectively determine the accurate action selection of load shedding,and improve the stable operational ability of the power system.

关键词： Artificial intelligence deep reinforcement learning load shedding control power system emergency state

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Wood use and forest management by Neolithic millet farmers at the Xinglong site,northern China

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Science China Earth Sciences 2024年第6期67卷 1910-1921页

作者： Hui SHEN Zhenwei QIU Keliang ZHAO xinying ZHOU Xiaoqiang LI Key Laboratory of Vertebrate Evolution and Human Origins Institute of Vertebrate Paleontology and PaleoanthropologyChinese Academy of SciencesBeijing 100044China National Museum of China Beijing 100006China University of Chinese Academy of Sciences Beijing 100049China

The origin and development of agriculture and its relationship with climate change are hotly debated topics among environmental archaeologists.In this study,we analyzed wood charcoal materials from the Neolithic Xinglong site in northern China in order to understand the woody vegetation around the site and how early millet farmers shaped local woodlands.Our results suggest that the area around the Xinglong sites during 8700-7000 yr BP was primarily woodlands,including Prunus sibirica shrubs,Ulmus and Acer forests,and Populus stands near waterways.From 8000 to 7000 yr BP,the warm and humid climate probably contributed to the expansion of Acer,Rhamnus,and Juniperus,and may have facilitated the development of early millet agriculture.Among these ancient wood fragments that we studied,the high percent of Prunus charcoal appears to indicate an abundance of fruit trees,which might have constituted the main component of local vegetation.Meanwhile,the wood taxa illustrate the existence of a variety of ecological habitats,and it is logical to assume that people made full use of the locally available wood resources.Notably,Populus and Ulmus were the dominant sources of fuel.The results of tree-ring curvature analyses indicate that people mainly collected trunks or large branches of Ulmus,Populus,Acer,and Juniperus timbers.We interpret the increasing use of Prunus twigs and the declining percentage of Prunus charcoal in the period between 8000-7000 yr BP as indicating that people started to protect and manage wild fruit trees.They may have started pruning to acquire more food resources as part of the cultural responses and adaptation strategies employed by these early millet cultivators.

关键词： Xinglong site Wood charcoal Wood use Woodland management

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Distributed optimization of electricity-Gas-Heat integrated energy system with multi-agent deep reinforcement learning

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Global Energy Interconnection 2022年第6期5卷 604-617页

作者： Lei Dong Jing Wei Hao Lin xinying wang School of Electric Engineering North China Electric Power UniversityChangping DistrictBeijing 102206P.R.China China Electric Power Research Institute Haidian DistrictBeijing 100192P.R.China

The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.

关键词： Integrated energy system Multi-agent system Distributed optimization Multi-agent deep deterministic policy gradient Real-time optimization decision

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Spatio-temporal Convolutional Network Based Power Forecasting of Multiple Wind Farms

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 388-398页

作者： Xiaochong Dong Yingyun Sun Ye Li xinying wang Tianjiao Pu the School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China he China Electric Power Research Institute Beijing 100192China

The rapidly increasing wind power penetration presents new challenges to the operation of power systems.Improving the accuracy of wind power forecasting is a possible solution under this circumstance.In the power forecasting of mul-tiple wind farms,determining the spatio-temporal correlation of multiple wind farms is critical for improving the forecasting accuracy.This paper proposes a spatio-temporal convolutional network(STCN)that utilizes a directed graph convolutional structure.A temporal convolutional network is also adopted to characterize the temporal features of wind power.Historical data from 15 wind farms in Australia are used in the case study.The forecasting results show that the proposed model has higher accuracy than the existing methods.Based on the structure of the STCN,asymmetric spatial correlation at different temporal scales can be observed,which shows the effectiveness of the proposed model.

关键词： Deep learning spatio-temporal correlation wind power forecasting graph conventional network(GCN).

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Successive MISOCP Algorithm for Islanded Distribution Networks with Soft Open Points

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 209-220页

作者： Tao Zhang Yunfei Mu Hongjie Jia xinying wang Tianjiao Pu Key Laboratory of Smart Grid of Ministry of Education Key Laboratory of Smart Energy&Information Technology of Tianjin MunicipalityTianjin UniversityTianjin 300072China e China Electric Power Research Institute Beijing 100192China

An optimal operation scheme is of great significance in islanded distribution networks to restore critical loads and has recently attracted considerable attention.In this paper,an optimal power flow(OPF)model for islanded distribution networks equipped with soft open points(SOPs)is proposed.Unlike in the grid-connected mode,the adequacy of local power generation in distribution networks is critical for islanded systems.The proposed approach utilizes the power output of local distributed generations(DGs)and the benefits of reactive power compensation provided by SOPs to allow maximum loadability.To exploit the available resources,an optimal secondary droop control strategy is introduced for the islanded distribution networks,thereby minimizing load shedding.The formulated OPF problem is essentially a mixed-integer nonlinear programming(MINLP)model.To guarantee the computation efficiency and accuracy.A successive mixed-integer second-order cone programming(SMISOCP)algorithm is proposed for handling the nonlinear islanded power flow formulations.Two case studies,incorporating a modified IEEE 33-bus system and IEEE 123-bus system,are performed to test the effectiveness of the proposed approach.

关键词： Distribution network islanded operation second-order cone programming soft open points successive approximation

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