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.

The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements

During the assembly of internal combustion engines, the specific size of crankshaft shell bearing is not known until the crankshaft is fitted to the engine block. Though the build requirements for the engine are consistent, the consumption profile of the different size shell bearings can follow a highly volatile trajectory due to minor variation in the dimensions of the crankshaft and engine block. The paper assesses the suitability of time series models including ARIMA and exponential smoothing as an appropriate method to forecast future requirements. Additionally, a Monte Carlo method is applied through building a VBA simulation tool in Microsoft Excel and comparing the output to the time series forecasts.

Time Series Correlated Error's Simulation Scheme with the Application to Simulate the Ephemerides Error of CHAMP

Computer simulation experiment is very important in the phase of project design, the availability of simulated result highly depends on the scheme of error simulation. Time series observations are normally correlated. This paper first discusses the formula of correlated error propagation, then derives the formula of simulating time series correlated errors. This formula is then used to simulate correlated ephemerides errors of CHAMP, then the ephemerides are used to recover the gravity vector at satellite altitude with finite differential formula. The formulae derived in this paper are verified with the difference between the recovered gravity vectors and the `true values’ which are directly computed with the same gravity model as that generating the ephemerides.

Research on Reduction of Solar Power Curtailment with Grid Connected Energy Storage System Based on Time-Series Production Simulation

Due to the variable output of renewable energy (RE) generation, difficulties of dispatching RE for power system operators could not be avoided. One of possible solutions is the energy storage technology, especially the battery storage system. The large-scale energy storage system is available to support power system reliable flexibility for load following and system frequency regulation. In this paper, the bottlenecks of large-scale solar power generation dispatching and operation in Qinghai grid are discussed, and a new PV-energy storage coordinated dispatching method is proposed for reduction of PV curtailment in Qinghai. Moreover, the validation based on the time-series production simulation is provided using real data from Qinghai. The results indicate that the proposed method can effectively decrease the curtailment of solar power and future vision of large-scale solar power coordinated operation with energy storage system is also presented.

Paradigm of Numerical Simulation of SpatialWind Field for Disaster Prevention of Transmission Tower Lines

Numerical simulation of the spatial wind field plays a very important role in the study of wind-induced response law of transmission tower structures.A reasonable construction of a numerical simulation method of the wind field is conducive to the study of wind-induced response law under the action of an actual wind field.Currently,many research studies rely on simulating spatial wind fields as Gaussian wind,often overlooking the basic non-Gaussian characteristics.This paper aims to provide a comprehensive overview of the historical development and current state of spatial wind field simulations,along with a detailed introduction to standard simulation methods.Furthermore,it delves into the composition and unique characteristics of spatial winds.The process of fluctuating wind simulation based on the linear filter AR method is improved by introducing spatial correlation and non-Gaussian distribution characteristics.The numerical simulation method of the wind field is verified by taking the actual transmission tower as a calculation case.The results show that the method summarized in this paper has a broader application range and can effectively simulate the actual spatial wind field under various conditions,which provides a valuable data basis for the subsequent research on the wind-induced response of transmission tower lines.

Simulation of groundwater table dynamics based on Feflow in the Minqin Basin,China

As groundwater table declination is an important factor resulting in degradation of eco-environment in the Minqin Basin, China, it is significant to investigate and understand the groundwater table dynamics in this area. According to the physical and geographical conditions of the Minqin Basin, a hydrogeological conceptual model and a mathematical model were established, and the mathematical model was figured out by using Finite Element subsurface Flow system （Feflow）. Accurate hydrogeological parameters were acquired, and the spatio-temporal distribution dynamics of groundwater table for 1983-2001 were also simulated. The model performed well with a correlation coefficient of 0.977 and a mean error of 0.9768 m. The inflow and outflow of the groundwater system were predicted by time series analysis, and the groundwater table dynamics for 2011 were further acquired. Gen- erally the groundwater table in the Minqin Basin would continue to decline. The groundwater table would decline during spring and summer irrigation, while it would rise during autumn-winter irrigation. The groundwater depression cones would expand with the increase of center depths. Therefore, regulatory measures should be taken to prevent the declination of groundwater table and improve the eco-environment of this area.

基于水光电力系统时序生产模拟模型的水光优化配比研究

基于考虑系统负荷、新能源发电出力等时序变化特性的时序生产模拟法,建立了水光电力系统时序生产模拟模型;从系统结构性、经济性、灵活性与可靠性方面综合确定最佳水光容量配比,并通过金沙江上游川藏段水光系统验证了模型的合理性。金沙江上游川藏段光伏电站与水电站出力具有较好的年内、日内互补特性;对于2030年水平年,考虑枯期水电留存,913.6万kW水电配套400万kW光伏的方案综合性能更优,其新增非水可再生电量约60亿kW·h。

Multi-Dimensional Traffic Flow Time Series Analysis with Self-Organizing Maps

The two important features of self-organizing maps （SOM）, topological preservation and easy visualization, give it great potential for analyzing multi-dimensional time series, specifically traffic flow time series in an urban traffic network. This paper investigates the application of SOM in the representation and prediction of multi-dimensional traffic time series. Ffrst, SOMs are applied to cluster the time series and to project each multi-dimensional vector onto a two-dimensional SOM plane while preserving the topological relationships of the original data. Then, the easy visualization of the SOMs is utilized and several exploratory methods are used to investigate the physical meaning of the clusters as well as how the traffic flow vectors evolve with time. Finally, the k-nearest neighbor （kNN） algorithm is applied to the clustering result to perform short-term predictions of the traffic flow vectors. Analysis of real world traffic data shows the effec- tiveness of these methods for traffic flow predictions, for they can capture the nonlinear information of traffic flows data and predict traffic flows on multiple links simultaneously.

面向新型电力系统的时序生产模拟应用与求解技术综述

在建设新型电力系统背景下,时序生产模拟技术依托电网数字化转型赋能,成为了新型电力系统运行评估与规划决策的重要工具。文中总结了国内外对于时序生产模拟相关问题的研究成果,以及时序生产模拟在新型电力系统中的应用与求解技术。首先,介绍了时序生产模拟的结构及特点,从电力电量平衡测算、“双碳”措施量化分析、未来电网形态与演化路径等方面综述了时序生产模拟的应用场景。然后,根据现有时序生产模拟求解技术特点将其分类介绍,并讨论了不同求解技术的局限性。最后,对新型电力系统时序生产模拟研究进行了展望。

基于EtherCAT总线的八轴七联动高级海况环境仿真平台

针对水流模拟海况时存在的运动不受控以及常规海况模拟平台模拟海况等级低,运动自由度不足等问题,提出利用八自由度运动平台模拟高级海况环境进行海浪涌动测试的方法。设计了由直线运动平台、旋转机构和6自由度(6-DOF)并联机构组成的串并联混合八自由度高级海况环境仿真平台,其运动加速度大,自由度多,运动方式多样。基于Ether CAT实时总线技术设计了八轴七联动的运动控制算法,并采用惯量匹配技术抑制抖动和噪声,实现了宽惯量范围的精确、稳定、同步(小于1μs)控制。设计了基于外部信号接收器的实时精密补偿技术和双齿轮消隙技术,提高了速率精度和平稳性,定位精度达到10μm。设计了复合叠加摇摆、文件仿真、复合叠加摇摆与文件仿真叠加运动和实时仿真运动方式,可模拟到五级高海况或将实航数据回灌后模拟水下、水面或机载的运动,用于导航系统的姿态模拟测试。

拟稳平差法在GNSS时间序列修复中的研究与应用

针对CORS坐标时间序列的缺失问题提出一种基于GNSS网拟稳平差的时间序列插值方法。在区域内选择相对稳定的测站构建基线网,根据稳定测站的趋势变化对缺失序列进行修复。模拟实验对比分析证明,拟稳平差法的修复效果最好,平均误差在5 mm以内,并保留了原始数据的运动趋势。使用拟稳平差法对待求点365 d的坐标序列进行仿真处理,并与真实序列进行对比分析。结果表明,仿真序列与真实序列变化趋势基本一致,E、N方向上的平均误差在5 mm以内,U方向上的平均误差在10 mm以内。

基于分段特征提取的仿真模型结果验证方法

校核、验证与确认(verification,validation,and accreditation,VV&A)是保证仿真模型可信度的关键手段,其中模型验证是核心环节。针对导弹飞行仿真模型结果验证存在的参考数据不可获得、参考数据来源多样、专家验证主观性强等问题,提出一种基于时间序列分段特征提取的导弹飞行仿真模型结果验证方法。提出了一种综合的时间序列分段线性方法,由基于二阶导数提取趋势边缘点的线性分段算法和基于极值点优化的Top-Down线性分段算法两部分组成,以实现对导弹飞行仿真数据和参考数据进行有效的线性分段表示。基于上述分段结果,对各段时间序列的均值、方差、斜率等特征进行提取,以辅助专家进行验证,从而降低验证中的主观性;或者直接利用TIC系数法、动态时间规整(dynamic time warping,DTW)等方法进行客观的相似性分析。通过充分利用时间序列的分段特征,可实现各种情形下的导弹飞行仿真模型结果验证。通过一个导弹模型结果验证案例演示了所提方法的可行性和有效性。

基于生产模拟的受端电网新能源发展场景研究

“双碳”目标驱动下,受端电网新能源大规模并网,加之外来电力比重加大,电力平衡难度增加,受端电网实现清洁替代面临多重困难。基于实际运行数据,分析了新能源低出力特性及其与负荷的匹配特性,总结了高比例新能源电力系统面临的关键问题。在此基础上,建立电力系统时序生产模拟模型,基于2030年预测数据的标幺化,设计2060年案例场景,量化分析典型受端省级电网的新能源、煤电和调节资源的配置问题,以及不同新能源发展场景下实现清洁替代的方案,并提出相关措施和建议。

基于概率性时序生产模拟的光储网协调规划

针对传统规划方法难以实现不确定性资源与负荷特性的时序匹配问题,提出基于概率性时序生产模拟的光储网协调规划方法。首先,考虑负荷与分布式光伏出力的不确定性建立概率性时序序列模型,利用生产模拟求取配电系统年运行概率状态;其次,综合考虑光储网的投资与运行损耗、停电损失、弃光损失及向上级电网的购电成本,建立基于随机优化的协调规划模型,通过投资决策与运行模拟迭代寻优获得最优规划方案;最后,以某个20节点的实际算例验证了所提方法的有效性。

基于SIMULINK的列车半主动隔振系统建模与仿真

在推导列车隔振系统运动微分方程的基础上,应用MATLAB/SIMULINK仿真模块建立被动和半主动隔振系统仿真模型。对列车的隔振性能(如隔振位移、隔振加速度等)进行仿真计算和时域分析,结果表明,列车采用半主动隔振系统,能有效改善隔振性能,提高行驶的平顺性。

基于Simulink的污水管网节点流量随机模拟器设计

为了合理评价污水管网的运行工况和服务性能,采用非平稳时序分析方法对其中节点入流序列进行了随机建模.首先,奇异点识别采用Tukey提出的方法,趋势项识别采用基于逐步回归分析的曲线拟合法,周期项识别采用累积周期图法.其次,平稳时序模型类型识别采用自相关图和偏相关图,阶数确定采用信息准则方法,参数估计采用最小二乘法.模型通过了残差检验和实用性检验.最后,根据随机建模结果在Matlab/Simulink上设计了污水管网节点流量随机模拟器的结构图,可实现污水管网节点入流序列的蒙特卡罗模拟,并在示波器窗口对模拟流量序列和原始流量序列进行了比较.

高比例可再生能源电力系统中火电深度调峰改造经济性分析

随着可再生能源的大规模渗透,电力系统的调峰压力越来越大。为此提出了采用时序生产模拟对建立的模型进行仿真,以燃煤发电成本以及机组启停成本的经济性最优作为目标函数,然后围绕目标函数建立约束。结果表明:对机组本身进行改造,效益远高于加储能装置,而且机组节省启停的费用远高于增发的可再生能源收益。

基于时序分解与机器学习的非平稳径流序列集成模型与应用

揭示变化环境下非平稳径流序列波动特征,可为提高径流预测精度和涉水工程规划提供支撑。针对径流序列具有非平稳性、周期性和异方差性的特征,收集长江流域攀枝花、城陵矶和大通站2008—2018年实测径流资料,基于周期趋势分解法(STL)将原始数据分解为周期项、趋势项和剩余项,结合各子序列特征采用多模型集成获取未来径流的综合预测值,并将预测结果与Prophet、LSTM和GARCH等单一模型进行对比。结果表明:联合机器学习和时序分解的集成模型在多个评价指标上均优于单一模型,且对异方差效应显著的站点模拟精度提升明显;验证期内3个站点的纳什效率系数分别为0.96、0.95和0.93,表明该模型能有效模拟长江流域径流波动过程。

灌区多水源联合利用的模拟-优化耦合模型研究

【目的】构建灌区多水源联合利用的模拟-优化耦合模型,实现灌区多水源的合理配置。【方法】以不同水源的引水比例为决策变量,以用水成本最小、用水效率最高以及在约束范围内地下水位抬升幅度最大为目标,基于半分布式水量平衡模型与Pareto遗传算法构建灌区多水源联合利用的模拟-优化耦合模型,并对东北三江平原水稻灌区典型区域进行典型年与长时间序列的多水源优化配置。【结果】本研究构建的模拟-优化耦合模型得出的典型年内配水方案可以很好地处理目标函数间的复杂关系,得出倾向于不同目标的多水源配置方案;长时间序列多水源优化配置可实现灌区年际间的水资源调控,在控制用水成本与提高用水效率的同时,对地下水位进行长期调控,实现地下水采补动态平衡;通过调整目标函数,模型可以根据地下水位恢复时间的快慢制定出多水源配置方案;与现有配水方案相比,常规灌溉与控制灌溉条件下优化方案的用水效率基本保持不变,但用水成本分别降低4.3%与23.8%,净地下水补给量分别增加0.52×105 m3/hm2和1.73×105 m3/hm2。【结论】在综合考虑用水效率、用水成本的前提下,本研究建立的灌区多水源联合利用的模拟-优化耦合模型可得出有利于灌区地下水可持续发展的多水源配水方案,为灌区多水源配水技术提供理论支持。