Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Estimation of Daily Global Solar Radiation with Different Sunshine-Based Models for Some Burundian Stations

Sunshine duration (S) based empirical equations have been employed in this study to estimate the daily global solar radiation on a horizontal surface (G) for six meteorological stations in Burundi. Those equations include the Ångström-Prescott linear model and four amongst its derivatives, i.e. logarithmic, exponential, power and quadratic functions. Monthly mean values of daily global solar radiation and sunshine duration data for a period of 20 to 23 years, from the Geographical Institute of Burundi (IGEBU), have been used. For any of the six stations, ten single or double linear regressions have been developed from the above-said five functions, to relate in terms of monthly mean values, the daily clearness index () to each of the next two kinds of relative sunshine duration (RSD): and . In those ratios, G0, S0 and stand for the extraterrestrial daily solar radiation on a horizontal surface, the day length and the modified day length taking into account the natural site’s horizon, respectively. According to the calculated mean values of the clearness index and the RSD, each station experiences a high number of fairly clear (or partially cloudy) days. Estimated values of the dependent variable (y) in each developed linear regression, have been compared to measured values in terms of the coefficients of correlation (R) and of determination (R2), the mean bias error (MBE), the root mean square error (RMSE) and the t-statistics. Mean values of these statistical indicators have been used to rank, according to decreasing performance level, firstly the ten developed equations per station on account of the overall six stations, secondly the six stations on account of the overall ten equations. Nevertheless, the obtained values of those indicators lay in the next ranges for all the developed sixty equations:;;;, with . These results lead to assert that any of the sixty developed linear regressions (and thus equations in terms of and ), fits very adequately measured data, and should be used to estimate monthly average daily global solar radiation with sunshine duration for the relevant station. It is also found that using as RSD, is slightly more advantageous than using for estimating the monthly average daily clearness index, . Moreover, values of statistical indicators of this study match adequately data from other works on the same kinds of empirical equations.

Estimating Critical Clearing Time of Grid Faults Using DA of State-Reduction Model of Power Systems

This paper proposes a critical clearing time (CCT) estimation method by the domain of attraction (DA) of a state-reduction model of power systems using sum of squares (SOS) programming. By exploiting the property of the Jacobian matrix and the structure of the boundary of the DA, it is found the DA of the state-reduction model and that of the full model of a power system are topological isomorphism. There are one-to-one correspondence relationships between the number of equilibrium points, the type of equilibrium points, and solutions of the two system models. Based on these findings, an expanding interior algorithm is proposed with SOS programming to estimate the DA of the state-reduction model. State trajectories of the full model can be transformed to those of the state-reduction model by orthogonal or equiradius projection. In this way, CCT of a grid fault is estimated with the DA of the state-reduction model. The calculational burden of SOS programming in the DA estimation using the state-reduction model is rather small compared with using the full model. Simulation results show the proposed expanding interior algorithm is able to provide a tight estimation of DA of power systems with higher accuracy and lower time costs.

Prediction model for the initial seed clearing angles of a precision seed meter based on vector fields

Seed clearing is a critical stage during precision seed metering process to ensure high seed singulation.However,there is a lack of understanding of the dynamics in the seed clearing process.In this study,a model was developed to predict initial seed clearing angle,in the seed clearing process using vector fields.The model was applied to an existing high-speed metering device and soybean seeds,and the model was evaluated with bench testing results.Results showed that dynamic changes in forces and constraints of seeds during the seed clearing process could be abstracted as vectors,and the changes of vector directions could be described by their phase angles.The phase angles were functions of the rotational angle of the seed meter.The phase angle of the constraint boundary linearly increases with the increase of the rotational angle.The phase angle of the force fluctuates,as the rotational angle changes.Initial seed clearing angle obtained from the phase angles varies from 8°to 59°,depending on the seeder travel speed.When comparing the values of the initial seed clearing angles predicted by the model with those from the bench tests,the root mean square error(RMSE)were from 2.73 to 3.14,and the correlation(r)between predict and observer were all higher than 0.98,indicating that the model had reasonably good accuracy.

Trends and Features of China's Inter-Provincial Trade:1987-2007

With today's economic globalization,inter-provincial trade plays an important role in a country's economy.This paper is the first to adopt the input-output tables of 30 Chinese provinces and to summarize the evolution of China's inter-provincial trade from1987 to 2007.This paper reaches the following conclusions.First,China's inter-provincial trade has sustained a period of rapid growth.In 2007,the total volume of inter-provincial trade was twice the amount of international trade,with the eastern region accounting for the majority of the inter-provincial trade volume.GDP may have a greater effect on interprovincial trade than geographic distance does.Second,inter-provincial trade maintains a high level of concentration and overlaps with the high concentration of GDP.Third,the inter-provincial trade dependence of Chinese provinces tends to increase,an indication of the growing domestic market integration.Moreover,the eastern region's dependence on inter-provincial trade is higher than the central and western regions'.Fourth,the share of inter-provincial trade in the overall external trade of Chinese provinces has a declining tendency,which indicates a slower process of China's domestic market integration compared with international market integration.However,in terms of proportion,the external trade of most Chinese provinces is still dominated by inter-provincial trade.Fifth,most provinces with longstanding inter-provincial trade deficits are in the central and western regions.

CLEARⅠ夜晚模式和Hufnagel-Valley(5/7)模式的存疑

本文分析了几种有代表性的C2n廓线模式,计算了这些模式的相干长度、等晕角以及不同大气层湍流贡献百分比。提出了修正的CLEARⅠ夜晚模式,并对Hufnagel-Valley(5/7)模式进行了讨论。

战略需求导向下的资金集中管理模式变革研究——基于美的集团的纵向案例分析

基于美的集团纵向单案例,分析企业资金集中管理模式随战略需求变化而动态调整的实施效果。研究发现,从机会成长阶段—规模成长阶段—优化升级阶段,美的集团战略需求呈现出“异地扩张—产业扩张—国际化与多元化扩张”的变化态势,其资金集中管理模式经历了“结算中心异地结算模式—数据大集中模式—财务公司”的动态调整,资金集中管理模式对应职能也在动态调整中完成了“异地资金管理能力—跨业务协调能力—金融发展能力”的叠加。美的集团根据战略需求变化动态调整资金集中管理模式是资金集中管理活动成功的关键,这一研究发现对战略需求影响资金集中管理模式的理论解释提供了案例依据,也为集团企业的资金集中管理模式选择提供了启示。

电力现货市场交易运营的未来重大需求与关键技术

中国正在全面开展电力现货市场建设,现货试点地区结合当前市场规则及电力系统现状构建了较为完善的现货市场运营支撑体系,支撑了当前电力现货市场有效运行。随着新能源占比逐步提升的新型电力系统构建及“双碳”目标国家战略的实施,现有的运营技术支撑体系将无法适应未来市场发展需要。文中在总结中国电力现货市场技术实践的基础上,分析了电力现货市场特征发生的变化及面临的技术挑战,探讨了未来在多元主体建模接入、市场出清算法、市场风险分析、可信交易环境、市场仿真等方面的关键技术,部分技术已经取得初步应用。

风力发电参与调频市场的机制优化及收益研究

随着风力发电并网容量日益增加,传统能源提供的调频容量已无法满足系统调频需求,目前政策允许风电参与系统调频,但现有调频辅助服务机制无法有效衡量风电参与调频的真实容量,对系统安全稳定运行带来了严峻挑战。在现有调频辅助服务机制基础上,引入风电调频可信度指标及综合调频性能指标对调频市场主体报价进行调整以衡量风电参与调频的真实容量,同时优化现有调频辅助服务机制的补偿细则。针对上述优化部分,建立风电参与调频市场的出清模型。算例结果表明,优化后的机制能够有效衡量风电提供的真实调频容量,促使优质的调频资源优先出清,同时风电可提高调频可信度指标及综合调频性能指标以获得较高的调频收益。

全国统一电力市场演进过程下省间-省内市场出清及定价模型

为了促进电力资源在省间的余缺互济和在全国范围内的优化配置,我国正有序推进电力市场改革,逐步实现省间-省内市场的耦合和全国统一市场的演进。根据省间-省内市场耦合程度的不同,该文将演进过程划分为三个阶段:分层阶段、松耦合阶段和紧耦合阶段。进一步考虑跨区、跨省以及省内输电的输电费回收问题,跨区直流输电线路与区域内交流输电线路按照传输电量收费,省内线路按照用户负荷用电量收费。构建了面向不同输电费收取方式的出清模型与定价机制,分层阶段采用顺序出清,松耦合阶段采用双层迭代出清,紧耦合阶段采用统一出清,定价机制均采用节点电价定价机制。最后,利用IEEE 39节点和118节点系统进行仿真计算,验证了出清模型和定价机制的有效性,并分析了输电费对出清和定价结果的影响。

基于多种交易方式的省间省内现货市场双层出清模型

新能源比例不断提升,省间消纳需求不断增加,构建满足全局资源优化运行的省间市场是促进市场效率提升的关键。文中基于多种块交易及小时交易的时间耦合关系,建立了省间省内两级现货市场出清模型。首先,构建了包含普通小时交易、灵活小时交易、常规块交易、可移动式块交易和扩展链接式块交易多种交易方式的混合整数线性规划模型。其次,为解决省间市场主体较多、块交易时间耦合复杂带来的出清难度大的问题,提出了基于省内出清结果的参与省间市场主体的筛选机制,进一步实现基于各省筛选出主体的省间市场出清,通过融合省间、省内出清结果形成最终中标结果。最后,通过多区域互联的IEEE RTS-96系统算例验证该模型的合理性及其作用效果。结果表明,相较于各省单独出清,省间省内两级市场出清提升了整体社会福利。所提方法在提高求解效率的同时,尽量逼近省间整体出清的全局最优解,实现了社会福利最大化。

计及动态碳排放对新能源消纳市场的价格研究

通过丰富电力市场交易方式,可有效提高新能源消纳水平。针对现有电力市场无法有效控制碳排放的特点,提出计及动态碳排放的电力市场出清方法,将火电碳排放成本动态传导到电价中,从而使部分发电权向新能源转移。同时,当发生弃能时,对弃能机组引入价格因子替换报价,进行电力市场二次出清,深度促进新能源应发尽发,以激励相容机制平衡发电权转受让方收益。采用改进的IEEE 30节点系统进行仿真验证,提出的电力市场交易机制能有效降低火电机组的碳排放并促进风光消纳,验证了该方法的有效性。

基于MRI-DWI不同指数模型构建的列线图模型对肾透明细胞癌与肾错构瘤的鉴别诊断价值

目的:基于磁共振-弥散加权成像(MRI-DWI)不同指数构建列线图模型,探讨其对肾透明细胞癌(ccRCC)与肾错构瘤的鉴别诊断价值。方法:回顾性选择医院经病理确诊的85例ccRCC或肾错构瘤患者作为建模组,其中肾错构瘤54例,ccRCC 31例;选择经病理确诊的105例ccRCC或肾错构瘤患者作为验证组,其中肾错构瘤59例,ccRCC 46例。基于建模组数据比较肾错构瘤与ccRCC组MRI-DWI不同指数模型参数,采用多因素Logistic回归分析筛选鉴别诊断ccRCC与肾错构瘤的影响因子,并建立列线图模型进行内部验证及外部验证。结果:ccRCC组MRI-DWI参数微循环灌注相关快速表观弥散系数(ADC)(Dt)、扩散异质性指数(α)值高于肾错构瘤组,表观弥散系数(ADC)值、单纯扩散相关慢速表观弥散系数值(Dp)、灌注分数(fp)、扩散分布指数(DDC)值低于肾错构瘤组(P<0.05)。经Logistic回归分析显示,Dt、α值是鉴别诊断ccRCC与肾错构瘤的危险因子(OR>1,P<0.05),ADC值、Dp、fp、DDC值是保护因子(OR<1,P<0.05)。根据以上参数建立的列线图模型在建模组与验证组C指数分别为0.941、0.903,校准曲线与理想曲线接近;ROC曲线显示,建模组与验证组的ROC曲线下面积(AUC)分别为0.962(95%CI为0.921~1.000)、0.903(95%CI为0.846~0.961),敏感度分别为0.907、0.898,特异度分别为0.935、0.804,约登指数分别为0.842、0.702。结论:基于MRI-DWI不同模型参数构建的列线图模型具有良好的区分度、准确性,对ccRCC与肾错构瘤具有较高的鉴别诊断价值。

欧洲日前统一电力市场耦合出清机制分析及启示

欧洲统一电力市场发展的经验对中国电力市场建设具有重要的借鉴意义。日前电力市场是欧洲统一电力市场建设的基础环节和重要组成部分。首先,梳理了欧洲日前统一电力市场的基本情况,介绍了主要报价形式的概念,进一步总结和对比分析了主要报价形式的特点与应用情况;然后,建立了欧洲日前电力市场出清的基本模型,给出了算法求解的主要流程并分析了其基本原理。同时,进行了算例分析与应用拓展。最后,结合欧洲日前电力市场的研究焦点,分析其未来发展趋势,总结提出了对中国电力市场建设的启示与建议。

自主最大笑容三维面像与数字化三维牙列模型整合方法的建立及其准确性研究

目的拟建立一种将自主最大笑容(AMS)三维面像与数字化三维牙列模型整合的方法,以实现在三维面像背景下显示数字化正畸终末位设计的目的。方法利用Geomagic Studio软件,通过手动注册和全局注册功能,将AMS三维面像和初始牙列模型进行配准对齐,然后用终末位牙列模型在原位替换初始牙列模型,并去除AMS三维面像口内区域,从而实现AMS三维面像和终末位牙列模型的融合显示。计算AMS三维面像和初始牙列模型上4组对应标志点对间的距离,通过配对t检验评估配准操作的准确性。结果该方法成功实现了AMS三维面像与初始、终末三维牙列模型的整合。两次配准对齐后,点对间的平均距离分别为(1.19±0.55)mm和(1.55±0.59)mm。两次测量结果的差异无统计学意义(P>0.05),且具有很高的一致性(组内相关性系数=0.914)。结论本研究建立了AMS三维面像与数字化初始、终末三维牙列模型整合的方法。该方法具有较高的准确性,有助于实现在三维面像背景下数字化正畸终末位设计效果的显示,从而提升以隐形正畸为代表的数字化正畸终末位设计的质量。

基于FY-4A和机器学习的太阳辐照度超短期预测

针对中国西部地区辐射资源充沛但观测资料匮乏的特点,提出一种基于辐照度观测数据、遥感数据、McClear和随机森林算法的太阳辐照度超短期预测方法,并重点分析遥感数据对辐照度预测效果的影响。结果表明:添加遥感数据能够优化不同时间步长的辐照度预测效果,并能显著降低平均绝对百分比误差(MAPE)值高于40%的预测大误差出现概率。同时,添加遥感数据对预测效果的提升随时间步长呈线性增加关系,nRMSE的差值变化范围从2.08%变为13.81%;nMAE的差值从1.64%变化为14.52%;R2的差值随时间步长的变化最为明显,从-0.03变为-0.43。但值得注意的是,添加卫星数据会显著增加模型的建立和超参寻优时间。

基于糖代谢相关基因的肾透明细胞癌预后模型的构建与评价

目的:构建肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)的糖代谢相关基因(carbohydrate metabolism-related genes,CRGs)预后模型并探索其临床意义。方法:选取TCGA数据库中ccRCC的mRNA表达数据,从MSigDB和KEGG数据库获取CRGs。通过LASSO回归建立CRGs预后模型并计算风险评分(RS)。按照RS中位数将患者分为高、低风险组,利用Kaplan-Meier曲线和生物信息学方法分析两组间的生存、免疫浸润、突变和免疫应答之间的差异。依据RS与临床特征构建诺模图,验证其预后预测效能。利用RT-qPCR检测ccRCC样本中CRGs表达量。结果:8个CRGs用于构建ccRCC预后风险模型,生存分析显示低风险组的患者预后较好(P<0.001)。生物信息学分析表明RS与免疫浸润、突变和免疫应答相关。根据RS与临床特征构建的诺模图具有良好的预后预测性能。体外实验证实上述8个CRGs在ccRCC组织和癌旁组织之间的表达存在显著的差异。结论:基于CRGs的预后模型可以用于ccRCC患者的预后预测。

考虑分布式资源交易的气电综合能源配网系统出清模型

随着分布式能源设备大量接入配电网并逐步参与分布式交易,配电网运行向着分布式、互动化的方向发展而呈现出更灵活多变的趋势。近年来,综合能源系统快速发展,配网层面电力系统和天然气系统耦合程度日益加深,独立运行模式已无法满足边界匹配要求。文中设计了考虑分布式资源参与的配电网集中交易市场模式,对分布式光伏、分布式储能、电动汽车等建立了交易模型。进而,构建了考虑分布式资源交易的气电综合能源配网系统联合出清模型,采用二阶锥松弛法及泰勒级数展开对配电网潮流约束和配气网潮流约束进行线性化处理,通过配电网节点电价和配气网分时气价反映气电联合系统价格信号。最后,基于改进的气电联合系统对文中所提市场机制模型的有效性进行了验证。

考虑合约转让的风-水-火中长期交易出清模型

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