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Optimal Operation with Dynamic Partitioning Strategy for Centralized Shared Energy Storage Station with Integration of Large-scale Renewable Energy

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 359-370页

作者： Jianlin li zhijin Fang Qian Wang Mengyuan Zhang Yaxin li Weijun Zhang Beijing Future Technology Innovation Centre for Electrochemical Energy Storage System Integration North China University of Technology Beijing China State Grid Fujian Electric Power Research Institute Fuzhou China

As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system development.To effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of entities.In this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power plants.We implement a multi-entity cooperative optimization operation model based on Nash bargaining theory.This model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining problem.The distributed alternating direction multiplier method(ADMM)is employed to address the subproblems separately.Simulations reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating entity.The results confirm the practicality and effectiveness of the strategy.

关键词： Shared energy storage(SES) dynamic partitioning strategy optimal operation Nash bargaining theory actual utilization rate of energy storage

Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application

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Science China Earth Sciences 2022年第10期65卷 1961-1971页

作者： Zengliang ZANG Yanfei liANG Wei YOU Yi li Xiaobin PAN zhijin li College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China No.32145 Unit of PLA Xinxiang 453000China Department of Atmospheric and Oceanic Sciences Fudan UniversityShanghai 200433China Joint Institute for Regional Earth System Science and Engineering University of California Los AngelesCalifornia 91109USA

With an increasing number of air quality monitoring stations installed around the Chinese mainland,high-resolution aerosol observations become available,allowing improvements in air pollution monitoring and aerosol forecasting.However,the multi scales(especially small-scale)information included in high-resolution aerosol observations could not be effectively utilized by the traditional three-dimensional variational method(3DVAR).This study attempted to extend the traditional 3DVAR to a multi-scale 3DVAR with two iteration steps,two-scale-3DVAR(TS-3DVAR),to improve the effectiveness of assimilating high-resolution observations.In TS-3DVAR,the large-scale and small-scale components of observation information were decomposed from the original high-resolution observations using a Gaussian smoothing method and then assimilated using the corresponding large-scale or small-scale background error covariances which were derived from the partitioned background error samples.The data assimilation(DA)analysis field generated by TS-3DVAR is more accurate than 3DVAR in reproducing the field’s multi-scale characteristics,which could thus be used as the initial chemical field of the air quality model to improve aerosol forecasting.Particulate matter with an aerodynamic diameter of less than 2.5μm(PM_(2.5))and 10.0μm(PM_(10)) from the surface air quality monitoring stations from November 01 to November 30,2018 at 00:00 were assimilated daily to verify the effects of TS-3DVAR and 3DVAR on the aerosol analysis and forecast accuracy.The results showed that TS-3DVAR better constrained both large-scale and small-scale,especially the spatial wavelengths in a range of 54-216 km and those above 351 km.The average power spectra of the TS-3DVAR assimilation increment in the two wavelength ranges were 71.70%and 35.33%higher than those of 3DVAR.As a result,the TS-3DVAR was more effective than 3DVAR in improving the accuracy of the initial chemical field,and thereby the forecasting capability for PM_(2.5).In the initial chemical field,the 30-

关键词： Multi-scale 3DVAR Data assimilation Aerosol forecast WRF-Chem

Exploring centimeter-sized crystals of bismuth-iodide perovskite toward highly sensitive X-ray detection

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Chinese Chemical Letters 2024年第6期35卷 185-188页

作者： Xin Dong Jing liang zhijin Xu Huajie Wu Lei Wang Shihai You Junhua Luo lina li College of Chemistry Fuzhou UniversityFuzhou 350116China State Key Laboratory of Structure Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China University of Chinese Academy of Sciences Beijing 100049China

Lead-halide perovskites exhibit outstanding performance in X-ray detection due to their intrinsic features such as high charge carrier mobility,large atomic number,and long carrier lifetime,but the toxicity of lead is regarded as the major factor hindering their development.Here,we introduce organic molecule(R)-(-)-2-methylpiperazine(R-MPz)into the bismuth-based structure to synthesize lead-free(R)-(H_(2)MPz)BiI_(5)(R-MBI).The high-quality centimeter-sized single crystals have been obtained,which show a low dark current and superior environmental stability.Particularly,the single-crystal device of R-MBI exhibits a highμτproduct up to 1.88×10^(-4)cm^(2)/V and a low trap density of 1.21×10^(10)cm^(-3).Further,the detector displays excellent detection sensitivity of 263.58μC Gy_(air)^(-1)cm^(-2)and a favorable low detection limit of 4.35μGyair/s,both of which meet the requirement for medical diagnostics.These findings shed light on the exploration of innovative bismuth-based hybrid perovskites for high-performance X-ray detection.

关键词： Perovskite Lead-free Bismuth-based X-ray detection Sensitivity

基于迭代式粒子群优化的永磁同步电机热网络模型参数辨识研究

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电机与控制学报 2024年第1期28卷 1-11页

作者：孟治金刘宇阳陈俐上海交通大学海洋智能装备与系统教育部实验室上海200240

针对集总参数热网络模型未知参数多、参数辨识收敛困难的问题,利用永磁同步电机在不同工况下的特性,提出迭代式粒子群优化辨识框架,用实验测量的电机温度场数据,以各节点估计温度与实测温度的均方误差作为目标函数,将并行优化转化为三... 详细信息

针对集总参数热网络模型未知参数多、参数辨识收敛困难的问题,利用永磁同步电机在不同工况下的特性,提出迭代式粒子群优化辨识框架,用实验测量的电机温度场数据,以各节点估计温度与实测温度的均方误差作为目标函数,将并行优化转化为三步串行迭代优化,减少每一步优化变量数,缩小种群规模,避免陷入局部最优。应用于某额定功率70 kW电机,得到一般热阻和热容随温度变化的规律,电机损耗、绕组涡流系数和气隙热阻随转速变化的规律。台架实验表明,在综合驾驶工况下,以槽内绕组、端部绕组、永磁体、定子齿和定子轭的温度估计最大误差和平均误差作为评价指标,与实测结果以及传统的采用固定参数的集总参数模型相比,提出的模型精确度高,工况适应性好。

关键词：永磁同步电机集总参数热网络温度实时估计温度依赖性参数辨识迭代式粒子群优化

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基于归一化循环前缀相关谱的无人机识别技术

西安电子科技大学学报 2024年第2期51卷 68-75页

作者：张涵硕李涛李勇朝温志津西安电子科技大学通信工程学院陕西西安710071 电磁空间认知与智能控制技术实验室北京100191

基于射频的无人机识别技术具有探测距离长、环境依赖性低的优点,已成为无人机监控系统不可或缺的技术手段。如何在低信噪比条件下有效识别无人机是当前热点问题。为保证良好的图传质量,无人机通常采用带有循环前缀结构的正交频分复用(OF... 详细信息

基于射频的无人机识别技术具有探测距离长、环境依赖性低的优点,已成为无人机监控系统不可或缺的技术手段。如何在低信噪比条件下有效识别无人机是当前热点问题。为保证良好的图传质量,无人机通常采用带有循环前缀结构的正交频分复用(OFDM)调制作为图传链路的调制方式。据此特性,首先提出一种基于归一化循环前缀相关谱和卷积神经网络的无人机识别算法。依据对无人机信号的OFDM符号周期和循环前缀长度的分析结果,计算信号归一化循环前缀相关谱。当归一化循环前缀相关谱的计算参数与无人机信号的调制参数匹配时,谱线中会出现若干相关峰,峰的位置分布反映了无人机信号帧结构、突发规则等协议特征。然后,利用卷积神经网络对归一化循环前缀相关谱进行特征分析和提取,从而识别无人机。最后,利用通用软件无线电平台USRP X310对5款无人机的射频信号进行采集,构建实验数据集。实验结果表明,该算法优于基于频谱和基于时频谱的算法,且在低信噪比下仍然有效。

关键词：无人机射频信号 OFDM 归一化循环前缀相关谱

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人机互动中社交机器人的社会角色及人类的心理机制研究

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学术研究 2024年第1期 18-25页

作者：钟智锦李琼中山大学新闻传播学院广东广州510006

通过网络爬虫软件获得三个小组共600条豆瓣社区帖子,并对15位豆瓣用户进行深度访谈,有助于探讨豆瓣社区中人机互动的特征和人类的心理机制。研究发现,豆瓣社交机器人在人机互动中表现出类社会化行为、非人格特质和薄弱的自我建构能力,... 详细信息

通过网络爬虫软件获得三个小组共600条豆瓣社区帖子,并对15位豆瓣用户进行深度访谈,有助于探讨豆瓣社区中人机互动的特征和人类的心理机制。研究发现,豆瓣社交机器人在人机互动中表现出类社会化行为、非人格特质和薄弱的自我建构能力,在虚拟社区中承担着互动参与的激励者和符号象征的结构角色。人类用户在与机器人的准社会交往中实现身份认同与社群归属,收获单向的“拟情关系”。人类在追求人工智能技术走向深度智能化的同时,又对其保持警惕,显示出对技术可供性边界的反思。

关键词：人机交互社交机器人媒介等同理论结构角色

Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts

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Advances in Atmospheric Sciences 2018年第7期35卷 813-825页

作者： Chaoqun MA Tijian WANG Zengliang ZANG zhijin li School of Atmospheric Sciences Nanjing University Nanjing 210023 China CMA-NJU Joint Laboratory for Climate Prediction Studies Nanjing 210023 China jiangsu Collaborative Innovation Center for Climate Change Nanjing 210023 China Institute of Meteorology and Oceanography PLA University of Science and Technology Nanjing 210000 China Joint Institute for Regional Earth System Science and Engineering University of California Los Angeles 90001 California USA

Atmospheric chemistry models usually perform badly in forecasting wintertime air pollution because of their uncertainties. Generally, such uncertainties can be decreased effectively by techniques such as data assimilation（DA） and model output statistics（MOS）. However, the relative importance and combined effects of the two techniques have not been clarified. Here,a one-month air quality forecast with the Weather Research and Forecasting-Chemistry（WRF-Chem） model was carried out in a virtually operational setup focusing on Hebei Province, China. Meanwhile, three-dimensional variational（3 DVar） DA and MOS based on one-dimensional Kalman filtering were implemented separately and simultaneously to investigate their performance in improving the model forecast. Comparison with observations shows that the chemistry forecast with MOS outperforms that with 3 DVar DA, which could be seen in all the species tested over the whole 72 forecast hours. Combined use of both techniques does not guarantee a better forecast than MOS only, with the improvements and degradations being small and appearing rather randomly. Results indicate that the implementation of MOS is more suitable than 3 DVar DA in improving the operational forecasting ability of WRF-Chem.

关键词： data assimilation model output statistics WRF-Chem operational forecast

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基于边缘计算的轻量化识别方法

计算机工程 2024年第6期50卷 287-295页

作者：李致金汤佳辉闫金凤南京信息工程大学人工智能学院江苏南京210044

“新零售”模式的出现,对传统零售业的转型以及提升用户消费体验具有重要意义。然而,目前市场上的无人水果秤大多存在一些问题,如识别率低、模型结构复杂、部署困难、模型推理实时性差等。针对这些问题,提出一种基于边缘计算的轻量化识... 详细信息

“新零售”模式的出现,对传统零售业的转型以及提升用户消费体验具有重要意义。然而,目前市场上的无人水果秤大多存在一些问题,如识别率低、模型结构复杂、部署困难、模型推理实时性差等。针对这些问题,提出一种基于边缘计算的轻量化识别方法。选用MobileNext作为主干网络,引入轻量型的注意力模块CBAM改进MobileNext中的SandGlass模块。利用Ghost模块替换SandGlass模块中的标准1×1卷积,以压缩模型的参数量和运算量。在此基础上,使用迁移学习的策略搭配NAdam优化器训练改进后的MobileNext模型,进一步提高模型的识别精度。在Fruit Recognition数据集上的实验结果表明,该方法在水果识别任务中达到了98.95%的识别准确率,优于原MobileNext、MobileNetV2和EfficientNet-B0等轻量级模型。相较于原MobileNext模型,改进后的MobileNext模型识别准确率提高了1.17个百分点,参数量仅为1.775×106,推理时间仅为16.5 ms。在实际的零售场景中,所提方法只需很小的参数量和运算量就能实现较好的识别效果,并能够部署在边缘设备上。

关键词：深度学习注意力模块轻量级模型迁移学习边缘设备

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沥青拌合设备的维修保养与技术改造措施分析

模具制造 2024年第6期24卷 256-258页

作者：李志金山东高速青岛发展有限公司山东青岛266000

现阶段,我国交通运输行业的发展效果较好,在道路工程建设的过程中,沥青混凝土作为主要的施工材料,有着较为广泛的应用,发挥着重要的作用。为了保证施工顺利落实,在工程准备阶段中,需要确保沥青混凝土的生产和使用效果,从多个方面保证沥... 详细信息

现阶段,我国交通运输行业的发展效果较好,在道路工程建设的过程中,沥青混凝土作为主要的施工材料,有着较为广泛的应用,发挥着重要的作用。为了保证施工顺利落实,在工程准备阶段中,需要确保沥青混凝土的生产和使用效果,从多个方面保证沥青混凝土材料的质量和效果,才能进一步促进工程建设效果提升。对此,需要针对沥青拌合设备的维护保养与技术改造措施进行分析。

关键词：沥青拌合设备维修保养技术改造改造措施

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