Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

Accumulative deformation in railway track induced by high-speed traffic loading of the trains

Prediction and control of the permanent settlement of a track caused by traffic loading from trains is crucial to high-speed railway design and maintenance. In this study, a unified prediction model of accumulative deformation of geomaterials used in railway construction subjected to cyclic loadings is introduced and calibrated using physical model testing. Based on this versatile model, a calculation approach to determine the track structure settlement under repeated loadings caused by the movement of the wheel axle of the train is proposed. Regression analysis on the physical model testing is adopted to determine the parameters involved in the computational approach. Comparison of model test data and computed results shows that the parameters obtained from the back-analysis are consistent throughout the various testing conditions, and the proposed calculation approach is capable of satisfactorily predicting the accumulative settlement of the railway roadbed and subgrade soil for various axle loads and loading cycles. A case study of a high-speed railway is performed to demonstrate the feasibility of the proposed approach in realistic engineering applications. The computation results from the settlement development of a roadbed and subgrade soil are presented and discussed.

Effects of sediment load on the abrasion of soil aggregate and hydraulic parameters in experimental overland flow

The breakdown of soil aggregates under rainfall and their abrasion in overland flow are important processes in water erosion due to the production of more fine and transportable particles and,the subsequent significant effect on the erosion intensity.Currently,little is known about the effects of sediment load on the soil aggregate abrasion and the relationship of this abrasion with some related hydraulic parameters.Here,the potential effects of sediment load on soil aggregate abrasion and hydraulic parameters in overland flow were investigated through a series of experiments in a 3.8-m-long hydraulic flume at the slope gradients of 8.7 and 26.8%,unit flow discharges from 2×10^-3 to 6×10^-3 m^2 s^-1,and the sediment concentration from 0 to 110 kg m-3.All the aggregates from Ultisols developed Quaternary red clay,Central China.The results indicated that discharge had the most significant(P<0.01)effect on the aggregates abrasion with the contributions of 58.76 and 60.34%,followed by sediment feed rate,with contributions of 39.66 and 34.12%at the slope gradients of 8.7 and 26.8%,respectively.The abrasion degree of aggregates was found to increase as a power function of the sediment concentration.Meanwhile,the flow depth,friction factor,and shear stress increased as a power function along with the increase of sediment concentration at different slope gradients and discharges.Reynolds number was obviously affected by sediment concentration and it decreased as sediment concentration increased.The ratio of the residual weight to the initial weight of soil aggregates(Wr/Wi)was found to increase as the linear function with an increasing flow depth(P=0.008)or Reynolds number(P=0.002)in the sediment-laden flow.The Wr/Wi values followed a power function decrease with increasing friction factor or shear stress in the sediment-laden flow,indicating that friction factor is the best hydraulic parameter for prediction of soil aggregate abrasion under different sediment load conditions.The information regarding the soil aggregate abrasion under various sediment load conditions can facilitate soil process-based erosion modeling.

How Load Aggregators Avoid Risks in Spot Electricity Market:In the Framework of Power Consumption Right Option Contracts

There is uncertainty in the electricity price of spot electricity market,which makes load aggregators undertake price risks for their agent users.In order to allow load aggregators to reduce the spot market price risk,scholars have proposed many solutions,such as improving the declaration decision-making model,signing power mutual insurance contracts,and adding energy storage and mobilizing demand-side resources to respond.In terms of demand side,calling flexible demand-side resources can be considered as a key solution.The user’s power consumption rights(PCRs)are core contents of the demand-side resources.However,there have been few studies on the pricing of PCR contracts and transaction decisions to solve the problem of price forecast deviation and to manage the uncertainty of spot market prices.In addition,in traditional PCR contracts,PCRs are mostly priced using a single price mechanism,that is,the power user is compensated for part of the electricity that was interrupted or reduced in power supply.However,some power users might engage in speculative behaviours under this mechanism.Further,for load aggregators,their price risk avoidance ability has not substantially improved.As a financial derivative,options can solve the above problems.In this article,firstly,the option method is used to build an option pricing optimization model for power consumption right contracts that can calculate the optimal option premium and strike price of option contracts of power consumption rights.Secondly,from the perspective of power users and load aggregators,a simulation model of power consumption right transaction decision-making is constructed.The results of calculation examples show that(1)Under the model in this article,the pricing of option contracts for power consumption rights with better risk aversion capabilities than traditional compensation contracts can be obtained.(2)The decision to sell or purchase the power consumption rights will converge at respective highvalue periods,and option contracts will expedite the process.(3)Option contracts can significantly reduce the loss caused by the uncertainty of spot electricity prices for load aggregators without reducing users’willingness to sell power consumption rights.

Experimental study on lightweight expanded clay at particle level:Breakage of isolated grains

In this study,more than 1500 particles of lightweight expanded clay aggregate(LECA)are individually loaded up to breakage,following different patterns of contact(from 2 to 7)using a purpose-built apparatus.Consequently,a statistical model for predicting the number of fragments into which a grain breaks as a function of the number of contacts and their diameter is proposed.The number of fragments is found to follow a statistical binomial-type distribution function that depends on the number of contacts.In addition,a model based on Bayesian networks,capable of assessing the number of fragments and their size(measured as normalized weight)as a function of the number of contacts,is implemented.The proposed method is applicable when performing discrete element method(DEM)simulations on granular media in which grain breakage plays a relevant role.

再生粗骨料混凝土应力-应变关系

再生粗骨料混凝土应力-应变关系是实现其材料到结构力学分析的桥梁纽带,成为再生粗骨料混凝土结构基础理论的基石。介绍了作者团队多年来在再生粗骨料混凝土应力-应变关系方面取得的研究进展:采用模型化再生粗骨料方法,研究了复杂界面过渡区对再生粗骨料混凝土破坏行为的影响,揭示了再生粗骨料混凝土细观损伤本质与演化机理;从静力作用到动力作用,系统地开展了不同工况下再生粗骨料混凝土应力-应变行为试验研究,探明了载荷条件对再生粗骨料混凝土应力与变形的影响规律并建立了相适应的力学与数学模型;进一步考虑再生粗骨料性能时空变异性,发现了再生粗骨料混凝土力学响应的概率分布特征,提出了再生粗骨料混凝土随机损伤本构关系;基于获得的本构模型,完成了再生粗骨料混凝土构件时变可靠度分析和结构动力非线性分析,为再生粗骨料混凝土在实际工程中的安全应用提供了理论支撑;提炼了相关研究结论并对未来研究工作进行了展望。

ADAFT:SDN大规模流表的适应性深度聚合存储架构

为解决软件定义网络(SDN)数据平面中的三态内容可寻址存储器(TCAM)资源紧张问题,提出了一种基于内容表项树的SDN流表深度聚合方法,进而构建一种SDN大规模流表的适应性深度聚合存储架构ADAFT。该架构放宽了聚合表项之间的汉明距离要求,构建内容表项树聚合动作集不同的流表项,显著提高了流表聚合程度。设计了一种TCAM装载率感知的内容表项树动态限高机制,以降低流表查找开销。同时,提出了一种TCAM装载率感知的表项聚合适应性选择策略,以均衡流表聚合程度和查找开销。实验结果表明,ADAFT架构的流表压缩率明显高于现有方法,最高可达65.74%。

考虑居民用户可调节潜力的负荷聚合商日前投标决策优化模型研究

负荷聚合商能够充分挖掘居民用户资源参与需求响应,深化居民用电可调节潜力量化分析对负荷精准调控与负荷聚合商模式智能推广具有重要作用。首先,基于居民用电负荷调控差异性,考虑居民典型用电电器综合满意度计量,构建居民柔性负荷可调节潜力分析模型;然后,考虑负荷聚合商参与市场交易的运营模式,构建基于非合作博弈理论的日前投标决策优化模型;最后,通过算例仿真验证模型的有效性及适用性。结果表明该模型能够兼顾调控潜力,有效支撑负荷聚合商最优投标决策,为负荷聚合商推广下统筹资源优化调控提供借鉴与参考。

考虑响应违约风险的聚合商双重市场投标策略

负荷聚合商(load aggregator,LA)集成需求侧资源参与双重市场(能量市场和备用市场)投标,需要根据市场运营规则对具有不同行为特性的需求侧资源优化组合。文章考虑双重市场对响应资源的技术要求,从负荷削减量和响应时间2个方面体现需求侧资源的不确定性,引入条件风险价值(conditional value at risk,CVaR)理论,考虑备用市场响应超时的违约风险,制定其在双重市场的资源集成优化投标策略,以响应电量不足期望评估聚合商参与双重市场的响应可靠性。算例分析不同风险偏好系数下聚合商利润与风险的动态关系,优化需求侧资源的容量配置,为聚合商双重市场的投标和风险度量提供参考。

分级加载下不同骨料粒径的混凝土声发射波速分析

目前利用声发射技术对混凝土结构进行损伤定位时,采用固定表面波速进行损伤定位,没有考虑混凝土声发射信号是从混凝土内部传播出来以及混凝土材料在不同的阶段产生的损伤对声发射波速的影响,导致检测结果与实际产生一定的偏差。以3种不同类型的弹性波速变化将混凝土的损伤化为5个阶段。利用波速的变化结合经典材料损伤力学从而进行材料损伤的定量分析。通过试验结果分析得出:当水灰比一定时,随混凝土粗骨料粒径的增大弹性波波速呈上升的趋势,但波速上升的趋势随粒径的增大而相对减小。随着应力的增加,波速降低时,波速与应力阶段存在一定的线性关系。采用不同加载阶段波速的不同进行变波速定位,定位精度更接近实际损伤位置,可有效提高定位精度。试验得出的结果为混凝土桥梁结构无损检测提供了新的思路方向为其安全检测提供了参考价值。

多类型灵活资源的建模与分层式协调控制架构

电力需求侧可控的负荷、发电和储能资源统称为灵活资源,这些资源对智能电网的优化运行和消纳新能源发电具有重要作用。首先提出了一种通用灵活资源模型,该模型能够统一描述需求侧居民、商业、工业多类型灵活资源的特性,并能同时描述大规模灵活资源的集总用电需求。基于所提的通用灵活资源模型,构建了一种包含日前和实时阶段大规模多类型需求侧灵活资源的分层协调控制架构,该构架考虑了垂直调度和电力市场条件下电力系统的运行机制,在2种运行机制下都能够有效地利用多类型灵活资源的可调节能力提升电网整体的运行效率。将所提灵活资源模型嵌入到IEEE 30节点系统的机组组合问题中进行仿真,验证了所提分层式协调控制架构的有效性。

反复荷载下方钢管型钢再生混凝土组合柱抗震性能试验研究

为研究方钢管型钢再生混凝土组合柱的抗震性能,通过对9个组合柱试件进行低周反复荷载试验,对其地震破坏特征进行分析,并详细探究再生粗骨料取代率、型钢配钢率、方钢管宽厚比和轴压比等影响参数对组合柱承载力、延性及耗能能力等抗震性能指标的影响。研究结果表明:在反复水平荷载作用下组合柱呈现典型的压弯塑性铰破坏模式。组合柱的荷载-位移滞回曲线呈饱满“纺梭形”,具有较好的耗能能力。再生粗骨料取代率对组合柱的承载力的影响较小,随着再生粗骨料取代率的增加,组合柱的延性和耗能能力逐渐下降,延性和耗能能力最大分别下降7.83%和7.6%,组合柱试件承载力先升高后下降,承载力最大变化幅值为1.98%,影响幅值较小。随着方钢管宽厚比的减小或型钢配钢率的提高,组合柱的承载力和延性均得到提高,宽厚比从100降至33,承载力提高了57.44%,而型钢配钢率从4.2%增长至6.3%,承载力和延性则分别提高了21.45%和20.44%,说明方钢管宽厚比和型钢配钢率对组合柱抗震性能影响较大。另外,增大轴压比对组合柱试件的抗震性能不利,随着轴压比的增大,组合柱的滞回曲线饱满度下降,延性降低,轴压比从0.2提高到0.6,延性降低了11.11%。研究结论可为方钢管型钢再生混凝土组合柱的抗震设计提供参考。

一种无线传感器网络节能负载平衡树型数据聚合方案

为了延长无线传感器网络的生命周期,并从节点能耗负载均衡的角度进行数据传输,提出了一种高效的基于负载均衡树的数据聚合方案(LB-TBDAS)。该方案将传感区域划分为网格中的多个单元,选出剩余能量最大的传感器节点作为每个单元中的头部单元;利用最小生成树算法建立树状路径。在数据传输过程中,头部单元负责采集每个单元内的传感数据,采集到的数据沿树状路径传输到基站。仿真结果表明,提出的LB-TBDAS方案的总能耗明显低于GB-PEDAP和PED-AP。与GB-PEDAP和PEDAP相比,LB-TBDAS方案延长了一倍以上无线传感器网络的生命周期,可以避免传感器节点在多跳数据传输过程中产生过多的能量消耗。

多品种电力市场交易下负荷聚合商投标策略及市场均衡分析

中国新型电力系统建设正面临灵活资源短缺等问题,亟须发挥负荷侧调节能力。随着电网与负荷双向交互越发频繁,更多负荷聚合商通过整合辖区灵活资源参与市场交易,导致以往由发电侧占主导的市场均衡被打破。为研究多主体负荷聚合商博弈策略,构建了能量-备用电力市场下负荷聚合商双层投标模型,并引入多场景描述非决策者投标不确定性对市场均衡的影响。通过强平稳算法(SSM)将多个双层模型转化为带均衡约束的均衡问题(EPEC)模型,并采用大M法、二进制展开法等线性化方法进行线性化。算例结果验证了模型及求解算法的合理性和有效性,表明基于EPEC模型的负荷聚合商最优投标策略更加契合实际市场规则,有助于系统优化负荷曲线,缓解灵活资源供需紧张。

考虑空气源热泵负荷聚合参与的需求响应

基于“电网-聚合商-负荷”三级架构,提出空气源热泵负荷聚合参与需求响应的控制策略。供暖运营商作为热泵负荷的聚合商,在保证用户热舒适度的基础上,利用建筑本身的蓄能能力,结合分时电价最小化供热成本,并对负荷可调节潜力进行评估。当电网调度部门下发调控指令后,考虑用户舒适度和电网调节需求,基于多目标遗传算法分配各负荷调节量,在满足调控目标的同时可改善调控带来的聚合功率振荡、反弹负荷大等问题。最后,仿真验证所提策略的有效性。

基于低代码云平台的低碳园区负荷聚集商系统的研究及实现

中小型负荷分布不集中,弹性水平低是造成负荷侧能源利用效率低、调度困难及需求侧响应难以有效开展的因素之一。针对上述问题,将新兴IT技术与智能电网、虚拟电厂建设等电力行业的需求结合起来,梳理并完成负荷聚集商业务主线逻辑设计,并充分利用低代码云平台上开发效率高、开发周期短、架构灵活、扩展性强和运营维护成本低的特点,基于低代码云平台,设计出一套完整的负荷聚集商系统并加以实现。该系统完整实现了负荷聚集商的业务逻辑,验证了基于低代码云平台系统研发的技术可行性,为负荷聚集商技术支持系统的建设提供了有价值的参考方案。

基于区块链的负荷聚合商及居民用户多方共治交易模式

居民用户以负荷聚合商为中介参与需求响应,在交易中往往不具有话语权和选择权,由此产生信息不透明、第三方权力过大等信任问题;同时,居民用户因信息获取能力差以及负荷实时控制能力弱,难以在聚合响应中享受平等决策权、知情权和话语权。因此,基于区块链技术设计负荷聚合商及居民用户多方共治交易模式,针对包含3类柔性负荷的居民用户及聚合商的区块链节点,以自治共享为基本原则建立区块链节点模型和配置方法;基于负荷聚合商及居民用户节点间的聚合响应新模式,构建了基于聚合商非合作博弈、居民用户间演化博弈及聚合商与居民用户间主从博弈的激励机制,设计了激励相容的智能合约算法和区块数据结构,并提出响应标识因数和激励理性系数来评估所提交易模式的有效性;最后,经算例仿真验证表明,所提交易模式在保证各交易节点效用的基础上,可确保聚合服务高效可信,有利于唤醒海量需求侧沉睡资源。

Permanent deformation and deformation compliance of guss-asphalt for orthotropic steel deck plate surfacing

Indentation test and bending test were adopted to investigate permanent deformation and deformation compliance of guss-asphalt for orthotropic steel deck plate. Factors of mastic Epure content, fine to coarse aggregate proportion, temperature and loading pressure were investigated. It is pointed out that mastic Epure content, temperature and loading pressure are the main factors influencing permanent deformation of guss-asphalt; fine to coarse aggregate proportion influences its maximum bending strain and crack energy at low temperature. The results indicate that there exists an optimum mastic Epure content, and a critical operation temperature as well as a critical loading pressure for guss-asphalt in operation.

基于聚合二次模态分解及Informer的短期负荷预测

针对区域级负荷的非平稳性及长序列预测精度低的问题,该文提出了一种基于聚合二次模态分解及Informer的短期负荷预测方法。首先,运用改进完全集合经验模态分解(improved complete ensemble empirical mode decomposition with adaptive noise,ICEEMDAN)对负荷序列进行初步分解,削弱原始序列的随机性与波动性;其次,根据子序列的样本熵计算结果进行聚合,并通过比较不同的聚合方式选出最优重构方案;然后,利用变分模态分解对高复杂度的合作模态函数进行二次分解;充分考虑到电价、气象等因素对负荷的影响,采用随机森林(random forest,RF)算法进行相关性分析,从而为每个子序列构建不同的高耦合度特征矩阵并输入Informer进行建模,并通过其多层次编码及稀疏多头自注意力机制等方式提高对负荷序列的预测效率;最后采用巴塞罗那区域级负荷数据集进行实例验证,结果显示所提框架有效解决了模态分解过程中的模态混叠以及高频分量问题,并且其长序列预测均方根误差相比其他经典深度学习模型最高降低了65.28%。