Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

Electric Vehicle Charging Load Optimization Strategy Based on Dynamic Time-of-Use Tariff

Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.

基于TimeSVD++与DPC的推荐算法研究

针对使用奇异值分解(SVD)方法时需要填充矩阵的内容较多以及K-means算法受到K值的影响且数据集形状限制等问题,提出一种将TimeSVD++与改进的密度峰值聚类结合的方法。首先在SVD++的基础上引入参数时间因子,构建TimeSVD++模型;其次,采用将相似系数引入高斯核函数的方法,对密度峰聚类算法中的局部密度公式进行修正;引入信息熵确定最优截断距离,最后在数据集MovieLens-1M和MovieLens-100k上验证,并将实验结果与其它算法进行对比。结果表明:所提出的方法在MAE,RMSE,Recall和F1值指标上均优于其它的算法。

Aggregator-based demand response mechanism for electric vehicles participating in peak regulation in valley time of receiving-end power grid

With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.

Mapping winter wheat using phenological feature of peak before winter on the North China Plain based on time-series MODIS data

By employing the unique phenological feature of winter wheat extracted from peak before winter （PBW） and the advantages of moderate resolution imaging spectroradiometer （MODIS） data with high temporal resolution and intermediate spatial resolution, a remote sensing-based model for mapping winter wheat on the North China Plain was built through integration with Landsat images and land-use data. First, a phenological window, PBW was drawn from time-series MODIS data. Next, feature extraction was performed for the PBW to reduce feature dimension and enhance its information. Finally, a regression model was built to model the relationship of the phenological feature and the sample data. The amount of information of the PBW was evaluated and compared with that of the main peak （MP）. The relative precision of the mapping reached up to 92% in comparison to the Landsat sample data, and ranged between 87 and 96% in comparison to the statistical data. These results were sufficient to satisfy the accuracy requirements for winter wheat mapping at a large scale. Moreover, the proposed method has the ability to obtain the distribution information for winter wheat in an earlier period than previous studies. This study could throw light on the monitoring of winter wheat in China by using unique phenological feature of winter wheat.

Trans-Thoracic Echocardiographic Aortic Blood Flow Peak Velocity Variation, Distance Minute, Aortic Velocity Time Integral and Postoperative Outcome in Pediatric Surgical Patients—An Observational Pilot Study Protocol

Background: A Randomized Controlled Trial (RCT) has been elaborated where goal directed fluid and hemodynamic therapy (GDFHT) will be realized with trans-thoracic echocardiographic aortic blood flow peak velocity variation (ΔVpeak) and distance minute (DM) to guide fluid therapy and hemodynamics in high risk pediatric surgical patients. This RCT will clarify the impact of GDFHT with ΔVpeak and DM on postoperative outcome in terms of morbidity, length of stay in the intensive care unit (LOSICU), length of mechanical ventilation (LMV) and length of hospital stay (LOS) in children. To determine values of ΔVpeak, DM and VTI predictive of these postoperative outcomes, an observational pilot study will be realized. This pilot study is described here. The primary objective of this study is to determine values of ΔVpeak, DM and ITV predictive of postoperative outcome in children in terms of morbidity. The secondary objectives are to determine values of ΔVpeak, DM and ITV predictive of LOSICU, LMV, LOS, intraoperative, postoperative fluid administration and vasoactive-inotropic therapy. Methods: 500 - 1000 children aged less than 18 years will be included prospectively. Statistic analysis will be realized with XLSTAT 2019.4.2 software or plus. Results and Conclusions: This trial protocol will determine values of ΔVpeak, DM and ITV with echocardiography predictive of postoperative outcome in children.

The Prediction of the Peak Time of People Taking School Bus Based on Martingale Process

As the main tool for students and professors to come and go to different districts in-campus, the school bus is of great importance. In order to improve its efficiency and convenient students and professors, a rational schedule of departure is badly needed. A model is established to predict the peak time of people taking school bus based on martingale process, and it is solved according to stopping time of martingale. Then it is applied to Wuhan University of Technology. A large amount of data is collected and the peak time for each day is predicted combined with the actual situation of the college. In doing so, suggestions are given for those who are in charge of the school buses.

Simultaneous Prediction of Retention Times and Peak Shapes of Sulfonamides in Reversed-Phase High-Performance Liquid Chromatography

In this paper, we propose a novelmethod based on the plate theory to simultaneously predict retention times and peak shapes under gradient elutions and different flow rates by reversed-phase high-performance liquid chromatography. The proposed method yielded excellent retention prediction results in experiments with 16 common sulfonamides under 18 gradient conditions and four different flow rates, including 0.7, 1.0, 1.3, and 1.5 mL/min. The mean absolute deviation was 0.70%, which indicates accurate prediction. Moreover, the proposed method predicts the change wellin peak shapes caused by the expansion or compression ofpeaks under different gradient conditions.

增强CT定量参数诊断胃肠道间质瘤危险度的价值及与预后不良的关系

目的 研究增强CT定量参数诊断胃肠道间质瘤(gastrointestinal stromal tumor, GIST)危险度的价值及与预后不良的关系。方法 选取2020年3月-2022年3月收治的GIST 120例,根据术后危险度分级分为非高危组68例和高危组52例,比较2组术前增强CT定量参数,分析增强CT定量参数与GIST术后危险度的相关性,通过受试者工作特征曲线分析增强CT定量参数诊断GIST术后危险度的价值;并比较术后1年不同预后患者术前临床资料、增强CT定量参数,采用多因素Logistic回归分析GIST预后不良的影响因素。结果 高危组增强起始时间、达峰时间短于非高危组,增强强度值、强度半降时间高于或长于非高危组(P<0.01)。增强起始时间、达峰时间与GIST术后危险度呈负相关(r=-0.426、-0.470,P<0.01),增强强度值、强度半降时间与GIST术后危险度呈正相关(r=0.518、0.635,P<0.01)。增强起始时间、增强强度值、达峰时间、强度半降时间联合诊断GIST患者术后危险度为高危的曲线下面积大于单独参数诊断(P<0.05)。肿瘤直径、增强起始时间、增强强度值、达峰时间、强度半降时间是GIST患者术后预后不良的影响因素(P<0.01)。结论 GIST患者增强CT定量参数与术后危险度、预后密切相关,各定量参数诊断GIST患者术后危险度具有一定价值,且对患者预后评估具有一定指导意义。

碳移除下全球地表气温峰值出现时间的主要影响因子:能量平衡模型研究

碳移除是21世纪末实现巴黎气候协定温度目标的关键手段。在其开展后,全球地表气温将在随后的若干年达峰。目前,耦合模式比较计划第六阶段(CMIP6)开展碳移除试验的数值模式较少,限制了科学界对碳移除下全球地表气温峰值出现时间的理解。本文发现,基于强迫—响应能量框架的两层能量平衡模型能够很好地重现出:1)大气CO_(2)浓度变化对全球地表气温的影响;2)碳移除过程中全球地表气温的峰值出现时间。因此,该模型可作为CMIP6碳移除试验的补充,能够胜任峰值出现时间的影响因子研究。该能量平衡模型的结果显示,在碳移除过程中,不考虑深层海洋的情况下,对全球平均地表气温的峰值出现时间影响最大的因子为平衡气候敏感度,其次为地表热容量;当深层海洋存在时,影响最大的因子为深层海洋热容量,其次为平衡气候敏感度,之后为地表热容量。这些因子主要通过改变碳移除开始时地表净能量收入的大小来影响全球地表气温峰值的出现时间。相比不考虑深层海洋的情况,深层海洋的存在可以略微提前全球温度峰值出现的时间,并使得碳移除后CO_(2)强迫对地表净能量的下降幅度的贡献较大。

iFlow彩色血流编码成像技术在下肢动脉硬化闭塞症诊断中的应用价值

目的研究iFlow彩色血流编码成像技术在下肢动脉硬化闭塞症(LEASO)诊断中的应用价值。方法选择2022年3月至2023年10月期间确诊的106例LEASO患者作为本研究的LEASO组,以一般资料与LEASO组匹配且无动脉病变的80例志愿者作为对照组。两组受试者均进行数字减影血管造影(DSA)并采用iFlow彩色血流编码成像技术检测股骨头区域和踝关节区域达峰时间(TTP)、计算踝关节区域与股骨头区域TTP的差值,测量踝肱指数(ABI)。结果两组研究对象年龄、性别、体质量指数、吸烟史、高血压病史、糖尿病史、冠心病史、股骨头区域TTP的比较,差异无统计学意义(P>0.05);LEASO组踝关节区域TTP及TTP差值均高于对照组,差异有统计学意义(P<0.05);LEASO组中不同Rutherford分类患者股骨头区域TTP的比较以及左侧病变患者与右侧病变患者股骨头区域TTP、踝关节区域TTP、TTP差值的比较,差异无统计学意义(P>0.05),Rutherford分类越高,踝关节区域TTP及TTP差值越低(P<0.05);经Pearson检验,LEASO患者的踝关节区域TTP、TTP差值与ABI呈负相关(P<0.05);经受试者工作特征(ROC)曲线分析,踝关节区域TTP、TTP差值对LEASO具有诊断效能;经Delong检验,TTP差值诊断的ROC曲线下面积高于踝关节区域TTP(P<0.05)。结论iFlow彩色血流编码成像技术测定踝关节区TTP及TTP差值是诊断LEASO的量化指标。

基于自适应短时傅里叶变换的品质因子Q值估算方法

品质因子Q是描述地下介质对地震波吸收衰减强弱程度的参数,同时也是地层含油气性的重要标志。在地震资料Q估算中,常用的方法是短时傅里叶变换方法,当窗函数被选定以后,其时频分辨率就固定了。针对该问题,提出一种自适应窗短时傅里叶变换的方法,以获得更准确的瞬时中心频率,并利用峰值频移法来估算品质因子Q。首先,利用固定窗长的短时傅里叶变换来提取信号的瞬时中心频率作为初始频率;然后,根据初始频率自适应计算不同频率的窗长,并利用自适应窗长短时傅里叶变换来求取瞬时中心频率;最后,结合峰值频移法得到高分辨率的品质因子Q值。利用合成数据和实际数据进行了测试,结果表明,相比于固定时窗短时傅里叶变换方法,自适应短时傅里叶变换方法具有更好的时间和频率分辨率,可以获得更高分辨率的品质因子Q值。该结果可以为地下介质的研究提供更准确、可靠的工具,有助于更好地了解地下结构和油气资源分布情况。

基于峰值比拟合匹配的时差式气体超声波流量计

时差式气体超声波流量计的回波信号在气体中传播时能量衰减严重,且存在着不同程度的幅值晃动问题。因此如何在幅值晃动的气体回波信号中确定特征点,以准确测量回波信号渡越时间及其顺、逆流渡越时间差,是当前时差式气体超声波流量计信号处理方法的主要研究热点。该文基于超声回波信号的数学模型,研究构建了一种基于峰值比拟合匹配的信号处理方法,利用拟合指标来筛选符合匹配条件的波形。并且通过实际数据验证了该方法的有效性和优越性。

考虑时段划分的高风电渗透率系统储能配置

随着风电渗透率不断升高,其波动性、随机性的特点使得电力系统出现严重的弃风及调峰困难问题。为此,提出一种考虑时段划分的高风电渗透率系统储能优化配置模型。首先,在净负荷的基础上计算峰谷隶属度,综合考虑风电消纳、峰谷差和用户满意度,采用量子粒子群算法寻优;其次,在最优时段的基础上综合考虑火电机组和储能的成本及收益,以净成本最小为目标函数优化出最优储能配置方案;最后,通过不同风电渗透率的算例分析验证所提优化模型的合理性和有效性。

超声造影时间-强度曲线相关参数鉴别诊断肝细胞癌与转移性肝癌价值研究

目的探讨超声造影(CEUS)时间-强度曲线(TIC)相关参数鉴别诊断肝细胞癌(HCC)与转移性肝癌的价值。方法2021年3月~2023年3月我院诊治的106例肝癌患者,均接受CEUS检查,记录造影剂到达时间(AT)、达峰时间(TTP)、峰值强度(PI)和上升斜率(RS)等TIC相关参数,均进行肝穿刺组织病理学检查。绘制受试者工作特征(ROC)曲线,以曲线下面积(AUC)评估TIC参数的鉴别诊断效能。结果在106例肝癌患者中,经病理学检查诊断为HCC者44例(41.5%)和转移性肝癌者62例(58.5%);HCC病灶AT和PI分别为(9.1±2.2)s和(41.7±5.1)dB,均显著低于转移性肝癌病灶【分别为(13.4±2.6)s和(45.8±5.5)dB,P<0.05】,而TTP为(24.8±4.7)s,显著慢于转移性肝癌病灶【(18.9±3.4)s,P<0.05】;HCC患者血清AFP水平为(226.7±37.5)ng/mL,显著高于转移性肝癌患者【(73.1±14.6)ng/mL,P<0.05】;ROC曲线分析显示,采用AT、TTP和PI联合诊断HCC的AUC为0.89(95%CI:0.83~0.96),其敏感度(Se)和特异度(Sp)分别为70.5%和95.2%,显著优于血清AFP诊断【其AUC为0.78(95%CI:0.68~0.79),其Se和Sp分别为56.8%和78.8%,P<0.05】。结论使用CEUS检测的TIC相关参数鉴别诊断HCC与转移性肝癌有一定的临床应用价值,值得进一步研究。

帝视观察用内窥镜辅助喉罩置入的临床效果

目的探讨帝视观察用内窥镜引导喉罩置入的效果,为临床麻醉气道管理提供依据。方法选择2022年3月至2024年3月在揭阳市人民医院行喉罩置入全身麻醉患者60例,采用随机数字表将纳入研究患者分为观察组和对照组,每组30例。观察组使用帝视观察用内窥镜辅助喉罩置入,对照组使用传统徒手喉罩置入法。记录两组患者喉罩置入成功总时间(喉罩进入口腔到判定喉罩置入成功)、喉罩首次置入成功率、气道峰压、口咽漏气压以及喉罩置入损伤并发症发生情况,包括麻醉恢复室拔除喉罩后喉罩表面有无血迹、术后24 h内咽痛发生率。结果与对照组比较,观察组喉罩置入成功总时间明显缩短(P<0.001),喉罩首次置入成功率明显升高(P<0.05),两组喉罩型号比较差异无统计学意义(P>0.05);与对照组比较,观察组气道峰压明显降低(P<0.001),口咽漏气压明显升高(P<0.001);两组喉罩表面有血迹、术后24 h内咽痛发生率比较差异无统计学意义(P>0.05)。结论帝视观察用内窥镜引导喉罩置入,可以提高喉罩首次置入成功率,缩短喉罩置入成功总时间,降低气道峰压,升高口咽漏气压,有较高安全性,值得推广。

某液体火箭发动机用起动器峰值压力时间超差故障研究

针对某液体火箭发动机用起动器峰值压力时间超差故障,进行了原因分析,提出了改进措施并对其有效性进行了试验验证。结果表明:造成起动器峰值压力时间超差故障的原因为起动器内膜片与端盖间的焊接强度不足,在高温燃气冲击下膜片过早脱落、烧蚀,从而导致压力提前泄放。提出将1圈焊接改进为2圈焊接、将点焊改进为连续焊接,焊接后增加气密性及承压性能检测,以及加强削弱槽深度检测等改进措施。验证试验表明上述改进措施可有效避免起动器出现峰值压力时间超差故障。

经阴道彩色多普勒超声在子宫内膜病变患者中的应用价值

目的分析经阴道彩色多普勒超声在子宫内膜病变患者中的应用价值。方法选取2021年2月至2022年4月南昌大学第四附属医院收治的88例子宫内膜病变患者作为研究对象,所有患者均接受经阴道彩色多普勒超声及病理学检查,按照病理学检查结果将患者分为息肉组与癌变组,每组44例。比较两组二维超声子宫内膜情况、病灶血流动力学情况、经阴道彩色多普勒超声血流相关参数;以病理学检查结果为金标准,分析经阴道彩色多普勒超声对子宫内膜癌变的诊断效能。结果癌变组子宫内膜厚度厚于息肉组,内膜-肌层分界清晰、病灶回声均匀占比均低于息肉组,差异有统计学意义(P<0.05);癌变组血流丰富占比高于息肉组,差异有统计学意义(P<0.05);癌变组血流阻力指数(RI)、搏动指数(PI)均低于息肉组,时间平均峰值流速(TAP)慢于息肉组,差异有统计学意义(P<0.05);经阴道彩色多普勒超声对子宫内膜癌变的诊断灵敏度为86.36%,特异度为84.09%,准确度为85.23%;诊断息肉的灵敏度为84.09%,特异度为86.36%,准确度为85.23%。结论经阴道彩色多普勒超声对子宫内膜病变的诊断准确率较高,能通过血流动力学、RI、PI、TAP及影像学表现鉴别息肉或癌变。

建立一种适合本实验室快速检测产KPC酶肺炎克雷伯菌的方法

目的运用基质辅助激光解吸电离飞行时间质谱技术(MALDI-TOF MS)检测产肺炎克雷伯菌碳青霉烯酶(KPC)耐碳青霉烯类肺炎克雷伯菌(CRKP),筛选并验证其特征峰,建立一种适用于本实验室快速检测产KPC酶型CRKP的方法。方法收集临床耐碳青霉烯类肺炎克雷伯菌39株,运用PCR方法检测出其中23株产KPC酶,再采用MALDI-TOF MS技术检测KPC酶阳性CRKP菌株,得到质谱图后用Flex Analyst软件分析筛选出其中特征峰,并进行重复性实验和临床验证评估。结果综合筛选出产KPC酶CRKP最佳特征峰为m/z 6432,特征峰验证实验和重复性实验的特异性和敏感性分别为96.67%和100%。临床验证评估特异性和敏感性分别为92.31%和100%。结论利用MALDI-TOF MS技术可检出产KPC酶CRKP的最佳特征峰为m/z 6432,经实验证实该特征峰特异性和敏感性高,可为临床快速诊断和治疗产KPC酶CRKP提供理论基础。

基于全局时序因子分析的中国区域绿色技术创新环境评价

为探究绿色技术创新环境水平及其提升路径,基于2017—2021年中国31个省份的数据样本,从区域层面构建绿色技术创新环境评价指标体系,引入全局时序因子分析法识别其中实际起作用的主要维度,对绿色技术创新环境水平进行评分,并用蝴蝶模型对比区域间差异。结果表明:基本公共服务、城市发展、政策效率、资源供给与绿色生活是影响绿色技术创新环境的4个主要维度;各区域绿色技术创新环境水平整体差异大,资源供给与绿色生活和城市发展方面差异最显著。建议通过政策引导、加大投入、扩大开放等措施实现资源跨区域流动,提升绿色技术创新环境。