Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.

Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales

With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.

Multi-time scale analysis of precipitation variation in Guyuan, China:1957-2005

Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.

Research on multi-time scale doubly-fed wind turbine test system based on FPGA+CPU heterogeneous calculation

As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.

FGOALS-s2 Simulation of Upper-level Jet Streams over East Asia: Mean State Bias and Synoptic-scale Transient Eddy Activity

Upper-level jet streams over East Asia simulated by the LASG/IAP coupled climate system model FGOALS-s2 were assessed, and the mean state bias explained in terms of synoptic-scale transient eddy activ- ity （STEA）. The results showed that the spatial distribution of the seasonal mean jet stream was reproduced well by the model, except that following a weaker meridional temperature gradient （MTG）, the intensity of the jet stream was weaker than in National Centers for Environment Prediction （NCEP）/Department of Energy Atmospheric Model Inter-comparison Project II reanalysis data （NCEP2）. Based on daily mean data, the jet core number was counted to identify the geographical border between the East Asian Sub- tropical Jet （EASJ） and the East Asian Polar-front Jet （EAPJ）. The border is located over the Tibetan Plateau according to NCEP2 data, but was not evident in FGOALS-s2 simulations. The seasonal cycles of the jet streams were found to be reasonably reproduced, except that they shifted northward relative to reanalysis data in boreal summer owing to the northward shift of negative MTGs. To identify the reasons for mean state bias, the dynamical and thermal forcings of STEA on mean flow were examined with a focus on boreal winter. The dynamical and thermal forcings were estimated by extended Eliassen-Palm flux （E） and transient heat flux, respectively. The results showed that the failure to reproduce the tripolar-pattern of the divergence of E over the jet regions led to an unsuccessful separation of the EASJ and EAPJ, while dynamical forcing contributed less to the weaker EASJ. In contrast, the weaker transient heat flux partly explained the weaker EASJ over the ocean.

颗粒煤基质尺度计算新方法及应用

煤基质内部富含复杂孔隙,为瓦斯提供了大量的存储空间和运移通道。孔隙内的瓦斯流进裂隙需要经过扩散过程,基质尺度在一定程度上决定了扩散到裂隙的阻力,影响着瓦斯扩散的难易程度。研究以瓦斯扩散与煤基质尺度内在联系为出发点,通过处理颗粒煤解吸瞬态过程数据得到不同解吸时刻煤的双重孔隙结构内的瓦斯浓度与质量交换速率的定量关系,结合时变扩散系数对基质形状因子进行计算,提出了基于瞬态扩散的颗粒煤基质尺度计算方法,并进行了试验验证。结果表明:与较小颗粒煤相比,保存完整基质形态的大颗粒煤初始扩散系数基本不变,因此初始扩散系数的值在一定程度上可以表征基质的破坏程度。基质形状因子随解吸时间的延长而减小,可划分为急降阶段、缓降阶段和稳定阶段,其中稳定阶段基质形状因子能够准确反映扩散后期拟稳态下的基质形态,最适合求解基质尺度。该方法可以反映颗粒煤粉化损伤过程中的基质尺度变化规律,为解释扩散极限粒径的存在提供依据。糯东煤样的3种试验粒径基质尺度随煤颗粒的增大而增大,分别为0.059、0.287、0.457 mm,并且在大粒径范围具有无差性,证明了该方法的准确性。颗粒煤基质尺度可以用来修正K1值的计算参数,使瓦斯损失量计算模型在粉化程度高的煤样中同样具有很好的适用性。

计及锁相环非线性特性的跟网型逆变器暂态稳定性分析

锁相环作为跟网型逆变器实现相位同步的关键环节,由于其本身所固有的非线性特性,在弱电网情况下,传统小信号模型可能存在不能准确预测锁相环暂态稳定性的问题。为保证受扰后锁相环的稳定运行,提出了一种基于非线性数学模型的稳定性分析方法。首先,根据锁相环工作原理,建立其二阶非线性微分方程,通过相平面法对锁相环输出特性进行定性分析,评估不同参数对锁相环暂态特性的影响;然后,基于等面积法则分析锁相环暂态失稳机理,鉴于传统等面积法则可能导致稳定性的误判,采用非线性动力学多尺度法对锁相环受扰后的暂态时域表达式进行求解,明确锁相环暂态稳定边界;最后,通过Matlab仿真和RT⁃LAB半实物平台验证了所得解析解和锁相环暂态稳定域的准确性,为弱电网条件下锁相环控制参数及电路参数选取提供一定参考。

交直流电网多时间尺度暂态仿真接口综述

为满足大规模交直流电网多时间尺度动态过程的准确、高效仿真需求,已有研究结合不同仿真建模理论深入讨论了多时间尺度分区仿真方法。对于多时间尺度分区仿真,不同分区间的仿真接口是决定仿真成败的关键。首先,分析了交直流电网的多时间尺度特性及分区多时间尺度仿真的分类。然后,梳理了机电-电磁暂态离线仿真接口设计的关键问题。进一步,归纳了多速率电磁暂态仿真接口和移频-常规电磁暂态混合仿真接口的研究现状。最后,对多时间尺度分区协同仿真接口设计的未来研究方向进行了展望。

时域动载荷作用下多微结构多尺度并行动力学拓扑优化

采用拓扑优化方法对含多种多孔材料的结构进行结构与材料微结构构型一体化设计,可以获得具有优良力学性能的结构设计。该文面向多晶胞双尺度结构的时域动刚度最优设计问题,考虑不同晶胞间的可连接性,并行设计微结构的构型及其宏观布局。首先,引入双Helmholtz平滑-分块投影方案,识别不同多孔材料的宏观结构域。其次,通过均匀化方法计算多孔材料的宏观等效力学性能,利用有序SIMP(soid isotropic material with penalization)方法优化不同微观结构的宏观布局。同时,为了保证不同晶胞间的可连接性,在不同多孔材料微结构的边界区域设置为相同拓扑描述的可设计连接域。然后,基于先离散-后微分的伴随敏度分析方法,实现了时空离散动力系统的一致性敏度计算。最后,以双尺度结构动柔度最小化为目标,以材料用量为约束条件,提出了时域动载荷作用下多微结构多尺度并行动力学拓扑优化方法。数值算例结果表明,提出的优化方法能够实现多晶胞结构的构型与宏观布局设计,充分提高了多孔结构的承载性能,同时保证不同晶胞之间的几何连续性,研究结果可为高承载多孔材料结构设计提供理论参考。

缩尺车轮-环轨滚动接触与磨耗特性仿真分析

为了研究缩尺车轮-环轨滚动接触与磨耗特性,基于轮轨滚动行为(WRRB)模拟试验台参数,利用ANSYS/LS-DYNA建立瞬态滚动接触有限元模型,集成弹性蠕滑率求解程序和Tγ磨耗模型,通过试验验证模型的正确性.重点分析轮轨力、蠕滑率、接触应力和钢轨磨耗深度,并考虑车轮驱动扭矩和速度的影响规律.结果表明:缩尺车轮-环轨结构的高频弹性振动造成轮轨垂向力波动;在比例载荷作用下,纵向动力学行为和钢轨磨耗深度变化趋势与服役轮轨一致;由于环轨的极小曲线半径,自由滚动工况下的横向蠕滑力/率、自旋蠕滑率、钢轨磨耗深度偏大,切向接触应力峰值出现在接触斑后沿两侧;车轮驱动扭矩和速度的影响规律可拟合为一组经验公式.研究可以为此类试验台的设计与应用工作提供理论依据.

基于暂态能量辨识的含规模化储能的新能源电力系统暂态稳定控制方法

风电等新能源的大规模并网严重影响了电力系统的暂态稳定性。针对新能源电力系统暂态稳定问题,提出基于暂态能量辨识的含规模化储能的新能源电力系统暂态稳定控制方法。首先,构建新能源电力系统的线路稳定裕度和系统暂态稳定裕度指标,准确辨识系统暂态稳定性;然后,提出附加线路暂态能量控制的改进储能控制策略,更好提升系统暂态稳定性;最后,在New England10机39节点系统中进行仿真验证。算例分析表明,所提方法能准确辨识系统暂态稳定分布情况,有效改善新能源电力系统暂态稳定性。

寄生入侵对循环竞争系统动态的影响

寄生感染能够通过调节宿主种群的种间竞争关系影响种群动态,进而干扰整个竞争群落的稳定性与物种多样性。通过构建寄生物种干扰下的循环竞争系统,探讨不同时间尺度上的种群动态与物种续存对寄生特征的响应机制。模拟结果显示,寄生物种的入侵是影响循环竞争系统不稳定性的重要驱动因素之一。首先,寄生的入侵能够显著改变种群周期振荡模式,导致寄生调节的竞争系统在大时间尺度上呈现群落水平上的周期振荡,小时间尺度上呈现单种群的周期振荡。同时,种群生物量的时间序列自相关性和偏自相关性分析显示,大时间尺度上的群落周期振荡和小时间尺度上的种群周期振荡动态均是平稳的时间序列。其次,寄生入侵可导致阶段性平衡动态下的两物种灭绝,续存单物种的周期振荡动态,而局部稳定状态下,寄生入侵可引起循环竞争系统中三物种呈现完全一致的周期性振荡。同时,寄生循环竞争系统在达到平稳的过程中,产生生态系统中的瞬时动态行为,即两种动力学行为上突然转变的现象。此外,寄生物种的三个主要特征参数(传播率,脱落率以及致死率)均被证实能够改变大时间尺度或小时间尺度上的周期大小以及对应的物种丰富度。总之,寄生物种的入侵能够显著地改变竞争群落的稳定性与物种多样性,具有一定的研究意义。

基于尺度分析的CMA-GFS全球能量评估

全球模式能量循环和能量转换规律可准确反映模式动力和物理过程相互作用的物理机制,是诊断大气环流特征的重要方法。基于混合时空域能量循环框架,采用尺度分析方法,利用2022年中国气象局全球数值预报系统(CMA Global Forecast System,CMA-GFS)全球预报产品及欧洲中期天气预报中心第5代再分析资料(ECMWF reanalysis version 5,ERA5),考察CMA-GFS不同尺度下的能量蓄能及转换特征,以此诊断模式的误差来源。结果表明:CMA-GFS可有效预报大气能量循环基本特征,但其对斜压性的高估导致平均环流有效位能偏强,且具有随预报时效逐渐增长的趋势。定常和瞬变涡动能量分别受行星尺度和天气及以下尺度分量主导。涡动有效位能误差由模式斜压性决定,其中CMA-GFS的定常涡动有效位能偏高而瞬变涡动有效位能偏低。定常和瞬变涡动动能均存在系统性低估,负误差主要集中在副热带急流和极夜急流中心附近,偏强的正压输送使更多能量向平均环流转换,涡动能量偏弱。CMA-GFS的4种涡动能量在冬季预报偏低,而在夏季偏高或略偏低,严重削弱了季节变化影响。

灰阶超声及彩色多普勒血流分级在儿童一过性髋关节滑膜炎临床分期中的诊断价值分析

目的:研究灰阶超声及彩色多普勒血流分级在儿童一过性髋关节滑膜炎临床分期中的诊断价值。方法:选取一过性髋关节滑膜炎患儿80例,均为一侧发病,选取健侧作为对照组。根据患病时长、症状、体征、影像学结果等将患儿病情分为Ⅰ~Ⅳ期,测量颈前间隙、滑膜厚度、彩色多普勒血流分级,分析以上指标在临床分期中的相关性。结果:患侧的颈前间隙、彩色多普勒血流分级高于健侧(P<0.05)。患侧的颈前间隙、髋关节腔积液、彩色多普勒血流分级与临床分期均呈显著正相关(P<0.05)。逐步回归分析显示,患儿年龄、患病时间、患侧彩色多普勒血流分级为临床分期的危险因素。结论:灰阶超声及彩色多普勒血流分级可为儿童一过性髋关节滑膜炎提供影像学指标,彩色多普勒超声血流显像可反映髋关节增厚的滑膜内微血流情况,在诊断儿童一过性髋关节滑膜炎及其临床分期中有重要价值。

Yizhi Xingnao prescription improves the cognitive function of patients after a transient ischemic attack

Patients with mild cognitive impairment after a transient ischemic attack were included in this study. They were treated with Yizhi Xingnao prescription, ergoloid mesylates or aspirin for 60 days. Evaluation using the Montreal Cognitive Assessment Scale showed that cognitive function was significantly improved in all patients, especially after the combined treatment of Yizhi Xingnao and aspirin. The scores from the Montreal Cognitive Assessment Scale were improved overall and the effective treatment rate was as high as 79%, which was higher than patients treated with a combination of ergoloid mesylates and aspirin, or aspirin alone. Our experimental findings indicate that YizhiXingnao prescription can improve mild cognitive impairment after a transient ischemic attack, and that it is more effective than ergoloid mesylates.

大规模风电场并网暂态保护技术综述

大规模风电场并网会出现频率偏移、弱馈性和高谐波等暂态稳定问题,对系统的安全运行造成影响。因此,很有必要研究大规模风电场并网暂态保护技术。对大规模风电场的并网技术和暂态保护技术进行了全面评述,分析了每种并网技术的拓扑结构,对比了基于双馈异步风力发电机、直驱永磁同步发电机、传统同步电源系统3种发电系统的故障特性,同时阐述了陆上风电场和海上风电场暂态量保护的研究现状,最后对未来大规模风电场的暂态保护的发展提出了展望,可为未来风电场并网的研究提供参考。

基于多尺度卷积神经网络的管道泄漏检测模型研究

如何有效检测管道泄漏是节水型社会建设迫切需要解决的关键和热点问题之一。近年来基于深度学习的管道泄漏检测方法发展迅速,本文针对传统单尺度卷积神经网络对泄漏特征提取不充分的问题,提出一种基于多尺度一维卷积神经网络(MS1DCNN)的管道系统泄漏检测模型。该方法利用多个不同卷积尺度的卷积通路并行提取管道泄漏的特征并进行泄漏信息的分类预测。基于经典的管道系统布置,利用瞬变流模型生成管道泄漏工况下的三个水压数据集对模型进行验证,三个数据集分别用于预测管道的泄漏位置、泄漏量和非恒定摩阻系数,对应样本数为39601、3980、4900,并将预测结果与其他深度学习方法和传统的机器学习方法进行对比分析。结果表明:MS1DCNN模型对数据集样本下泄漏位置、泄漏量、非恒定摩阻系数的分类准确率达到99.96%、98.48%、100%,三者平均预测精度比传统一维卷积神经网络(1DCNN)、BP神经网络、支持向量机(SVM)和k近邻算法(KNN)提高0.31%、2%、1.27%、22.8%;MS1DCNN在信噪比为-4~12 dB的噪声环境下各数据集的平均F_(1)分数分别为99.2%、97.02%、100%,三者平均值分别比1DCNN、BP、SVM、KNN模型提高0.61%、2.3%、2.78%、28.59%,证明了MS1DCNN模型的预测性能。本文方法在管道泄漏参数、非恒定摩阻的同步预测方面有一定的潜力。

颈动脉斑块灰阶中位数对短暂性脑缺血发作进展为脑梗死的评估价值

目的研究颈动脉斑块灰阶中位数(GSM)对短暂性脑缺血发作(transient ischemic attack,TIA)进展为脑梗死的评估价值。方法收集2020年2月—2022年3月我院收治的156例存在颈动脉斑块患者的临床资料,根据既往是否有TIA病史分为TIA组和非TIA组,比较两组患者颈动脉斑块体积、厚度及GSM的差异,比较TIA组中不同临床特征患者颈动脉斑块体积、厚度、GSM及ABCD2评分;记录TIA患者随访1年内脑梗死的发生情况,采用受试者工作特征(ROC)曲线分析GSM对脑梗死的预测价值。结果TIA组患者GSM明显低于非TIA组(t=2.638,P<0.05);TIA组中不同持续时间、不同发作次数患者颈动脉斑块GSM及ABCD2评分差异有显著性(t=2.271~3.324,P<0.05);与TIA组中1年内未发生脑梗死患者比较,1年内发生脑梗死患者GSM明显降低,ABCD2评分明显升高(t=3.494、2.435,P<0.05)。ROC曲线分析显示,颈动脉斑块GSM及ABCD2评分预测TIA患者发生脑梗死的曲线下面积分别为0.765及0.739。结论TIA患者颈动脉斑块GSM显著降低,且与病情加重、1年内进展为脑梗死有关,GSM对脑梗死的预测价值与ABCD2评分相当。

千米钻机电控系统二次回路瞬态干扰分析与抑制

千米钻机电控系统工况复杂、负载多变,并且融合多个一次回路,从而使瞬态干扰频谱分布随机性高,易出现模态混叠现象。为提升智能感知精度,千米钻机电控系统二次回路往往采用高带宽增益运算放大器,已有适用于二次侧端口设备的模型不再适用于小信号检测电路的稳定性分析。千米钻机电控系统瞬态干扰频域分布范围广泛,要求电路在很宽的频域内有较强的抗干扰能力。传统抗干扰措施存在频带较窄、高频抑制作用不佳的缺陷;多级RC、LC滤波电路存在阻抗不匹配、体积大的问题。针对上述问题,以15000型千米钻机电控系统的二次回路信号采集电路为研究对象,对二次回路中瞬态干扰进行分析。采用无参尺度空间表达的经验小波变换(EWT)算法,利用尺度空间变换划分得到频谱分割点,进而提取出具有紧支撑框架的模态分量,引入模态分量的峭度指标特征划分瞬态干扰信号与白噪声信号,确定瞬态干扰的频域分布。通过构建电控系统二次回路含寄生参数的小信号电路等效模型,探寻反馈回路引脚寄生电容与触发振铃或自激振荡的干扰信号频率阈值的规律,分析瞬态干扰频域特征对电路稳定性的影响。结果表明:在输入输出存在30 pF引脚寄生电容时,传导进入瞬态干扰信号使稳定性下降,且引起失稳的触发频率随引脚寄生电容增加而降低。利用铁氧体磁珠类似并联谐振的高阻特性,设计了一种二阶滤波电路。实验室试验结果表明:当干扰经过含铁氧体磁珠的二阶滤波电路后,在信号采样电路敏感的0.2 MHz以上频段,干扰幅值均抑制在-35 dBV以下,信号采样电路无异常输出。工业样机运行数据中敏感频段干扰幅值均抑制在-35 dBV以下,与实验室试验结果基本一致,满足抗干扰要求。