Higher-order expansions of powered extremes of logarithmic general error distribution

In this paper,Let M_(n)denote the maximum of logarithmic general error distribution with parameter v≥1.Higher-order expansions for distributions of powered extremes M_(n)^(p)are derived under an optimal choice of normalizing constants.It is shown that M_(n)^(p),when v=1,converges to the Frechet extreme value distribution at the rate of 1/n,and if v>1 then M_(n)^(p)converges to the Gumbel extreme value distribution at the rate of(loglogn)^(2)=(log n)^(1-1/v).

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Evaluation of Generalized Error Function via Fast-Converging Power Series

A generalized form of the error function, Gp(x)=pΓ(1/p)∫0xe−tpdt, which is directly associated with the gamma function, is evaluated for arbitrary real values of p>1and 0x≤+∞by employing a fast-converging power series expansion developed in resolving the so-called Grandi’s paradox. Comparisons with accurate tabulated values for well-known cases such as the error function are presented using the expansions truncated at various orders.

Reliability analysis of structure with random parameters based on multivariate power polynomial expansion

A new method for calculating the failure probabilityof structures with random parameters is proposed based onmultivariate power polynomial expansion, in which te uncertain quantities include material properties, structuralgeometric characteristics and static loads. The structuralresponse is first expressed as a multivariable power polynomialexpansion, of which the coefficients ae then determined by utilizing the higher-order perturbation technique and Galerkinprojection scheme. Then, the final performance function ofthe structure is determined. Due to the explicitness of theperformance function, a multifold integral of the structuralfailure probability can be calculated directly by the Monte Carlo simulation, which only requires a smal amount ofcomputation time. Two numerical examples ae presented toillustate te accuracy ad efficiency of te proposed metiod. It is shown that compaed with the widely used first-orderreliability method （ FORM） and second-order reliabilitymethod （ SORM）, te results of the proposed method are closer to that of the direct Monte Carlo metiod,and it requires much less computational time.

Measurement Quantization Describes History of Universe—Quantum Inflation, Transition to Expansion, CMB Power Spectrum

Developing a comprehensive model of the early universe that describes events and conditions prior to recombination has proved difficult. Using a new approach, we express Heisenberg’s uncertainty principle in terms of measures and counts of those measures to resolve an expression consisting entirely of counts. The description allows us to resolve explicit values for discrete measures. With these values, we present new expressions describing the earliest epoch and the transition event that initiates expansion. We determine the quantity, age, density, and temperature of the cosmic microwave background (CMB). Moreover, we approach the CMB power spectrum anew, describing each mass/energy distribution, its physical significance, its peak temperature, and the effects of relativity. We do not engage in fitting or modification of the existing laws of physics. The approach is classical and correlates both quantum and cosmological phenomena with descriptive expressions that are measurable, verifiable, and falsifiable.

A New Model for Transmission Network Expansion and Reactive Power Planning in a Deregulated Environment

Transmission network expansion planning (TNEP) is a challenging issue especially in new restructured electricity mar-kets environment. TNEP can be incorporated with reactive power planning in which the operating conditions will be satisfied. In this paper a combinatorial mathematical model has been presented to solve transmission expansion and reactive power planning problem (TEPRPP) simultaneously. The proposed model is a non-convex problem having a mixed integer nonlinear nature where the number of candidate solutions to be evaluated increases exponentially according to the system size. The objective function of TEPRPP comprises the new circuits’ investment and production costs as well as load curtailment penalty payments. A real genetic algorithm (RGA) aimed to obtaining a significant quality solution to handle such a complicated problem has been employed. An interior point method (IPM) is applied to solve the proposed concurrent optimization problem in the solution steps of TEPRPP model. This paper proposes a new methodology for the best location as well as the capacity of VAr sources;it is tested on two well-known systems;the Garver and IEEE 24-bus systems. The obtained results show the capability and the viability of the proposed TEPRPP model incorporating operating conditions.

Research on Meteorological Administrative Power and Its Expansion and Control

At first, we briefly introduced fuzzy sets and related concepts of meteorology and meteorological administrative power to build the basic theoretical framework of the meteorological administrative power. Then, the attributes of meteorological administrative power were analyzed, espe- cially implementation and functions, and it was divided into five types like supervisory power for meteorological forecast. Finally, meteorological ad- ministrative power＇s expansion and control methods were discussed. It acts as the research foundation in practice to improve the meteorological ad- ministrative law enforcement and achieve meteorological public interest better.

Power Generation Expansion Planning Using an Interior Point with Cutting Plane （IP/CP） Method

The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point with cutting plane （IP/CP） method is proposed to solve the mixed-integer optimization problem of the electrical power generation expansion planning. The IP/CP method could improve the overall efficiency of the solution and reduce the computational time. Proposed method is combined with the Bender＇s decomposition technique in order to decompose the generation expansion problem into a master investment problem and a slave operational problem. The numerical example is presented to compare with the effectiveness of the proposed algorithm.

Optimization Study on Expansion Energy Used Air-Powered Vehicle with Pneumatic-Hydraulic Transmission

Pneumatic-hydraulic transmission has been developed for years. However, its dynamic properties are not good enough for application. In this paper, in order to increase the output characteristics, a late-model air-powered vehicle using expansion energy is proposed which can boost energy through a pneumatic-hydraulic transmission. The dynamic characteristics of the air-powered vehicle is modeled and verified by conducting experiment. In addition,the influence of the key parameters of the air-powered vehicle is researched for the optimization of the system performance. Through the results, the author got the conclusion that, firstly, comparison of the results of model and experiment proves the built model to be effective; secondly, input air pressure should be set according to the request of the practical loads, and range of 0.65 to 0.75 MPa can be chosen; thirdly, as a key structure parameter of the airpowered vehicle, ratio of the areas is considered to be set to approximate 8; what’s more, a bigger orifice with a limit will promote the system dynamic characteristic property, and the limit is about 3.5 mm; last but not the least, not too farther position of the rings will increase the quality of output dynamic characteristics. This paper can be a reference for system design of air-powered vehicle and dynamic improvement.

高压管汇材料疲劳性能测试及P-S-N模型曲线的拟合

高压管汇作为压裂设备中的主要易损件之一,其失效危害较大。它的失效原因主要是疲劳、冲蚀、腐蚀或者材料缺陷引起的刺漏和爆裂,其中尤以疲劳失效最不可预估。目前,对于高压管汇材料的疲劳性能研究不够深入,为解决高压管汇材料疲劳寿命的准确描述问题,以某国产高压管汇材料为例,进行了一系列疲劳试验,并基于试验数据,采用多种分布模型和不同S-N模型进行拟合分析,得出综合评价拟合能力最强的P-S-N模型。结果表明,该材料在中长疲劳寿命区,Weibull三参数模型在7级应力水平下综合评价能力最好;在存活率分别为50%、90%、99%、99.9%时,指数S-N模型的拟合系数均大于0.98,拟合能力最好。得出的P-S-N模型曲线可以为高压管汇的疲劳寿命以及安全设计提供依据。

车辆主动悬架自适应变论域T-S模糊控制研究

针对传统变论域模糊控制存在过度依赖专家经验、伸缩因子参数不能自适应调整的问题,提出一种车辆主动悬架自适应变论域T-S模糊控制策略,从而提高车辆的行驶平顺性。结合神经网络和T-S模糊推理建立基于自适应神经模糊推理的一阶T-S模糊控制器,利用神经网络的自学习特性产生完善的模糊规则,进而在传统函数型伸缩因子的基础上,将系统误差和误差变化率作为动态参数引入伸缩因子中,实现伸缩因子参数的自适应调整,解决了传统函数型伸缩因子因参数确定难度大导致控制效果差的问题。通过随机工况下的仿真分析和基于相似理论的缩尺实验,对所提出算法的有效性和工况自适应性进行了验证。结果表明,所提出的自适应变论域T-S模糊控制策略具有较强的工况适应性,在不同车速、路面激励下均可有效提高车辆的平顺性并保证轮胎接地安全性。

经验小波变换和改进S变换结合的电能质量检测与识别方法

为分析不确定干扰因素影响下的实际电力网络电能质量问题,提出一种经验小波变换(EWT)和改进S变换相结合的电能质量检测与识别方法。该方法一方面利用EWT联合归一化直接正交(NDQ)算法和奇异值分解(SVD)算法准确提取调幅-调频分量的频率、幅值和时间参数,另一方面考虑到EWT算法在高噪声环境下瞬时幅值波动的问题,引入改进S变换提取高噪声干扰下的电能质量扰动时频信息,最后,基于EWT和改进S变换提取的扰动特征向量,利用基于改进粒子群优化算法(IPSO)优化支持向量机(SVM)的电能质量扰动识别分类器实现扰动类型的精确识别。仿真和实验表明所提方法在复合扰动识别分类时平均识别准确率为93.23%,且能够准确识别4种实测扰动信号。

Thermal Expansion Coefficients of Thin Crystal Films

The formulas for atomic displacements and Hamiltonian of a thin crystal film in phonon occupation number representation are obtained with the aid of Green's function theory. On the basis of these results, the formulas for thermal expansion coefficients of the thin crystal film are derived with the perturbation theory, and the numerical calculations are carried out. The results show that the thinner films have larger thermal expansion coefficients.

基于Stacking多模型融合的极端天气短期风电功率预测方法

为了解决极端天气下样本稀缺和单一模型预测精度不高的问题,提出一种基于Stacking多模型融合的极端天气短期风电功率预测方法。首先,提取极端事件的原始数据,通过考虑格兰杰因果的最大相关-最小冗余(maximal relevance minimal redundancy, mRMR)特征选择策略降低数据特征冗余和复杂性;其次,针对极端天气数据稀缺的问题,采用捕捉数据时间动态特性的时间序列生成对抗网络(time-seriesgenerativeadversarialnetwork,TimeGAN)算法进行扩充;最后,考虑到各单一模型的差异性及优势性,构建以卷积神经网络、长短期记忆网络、极端梯度提升树、K最近邻算法、支持向量机为基学习器,以轻量梯度提升机为元学习器的Stacking集成模型对未来3d的风电功率进行预测。实验结果表明,所提方法能够有效提升极端天气下的短期风电功率预测精度,与其他预测模型相比,其归一化平均绝对误差和均方根误差分别改善了2.48%和3.47%。

考虑整流性负载特性的LCC-S型无线电能传输系统优化设计

无线电能传输系统中的整流性负载具有非线性特征,而对系统传输特性分析和谐振参数设计时常采用基波分析法,将整流性负载等效为纯电阻,导致理论分析与实际存在一定偏差、系统偏离谐振状态。针对该问题,以LCC-S型无线电能传输系统为研究对象,考虑谐波以及整流性负载的非线性,对系统传输特性进行分析,进而提出基于整流性负载补偿的负载阻抗和接收端串联谐振电容参数的计算方法,并对逆变电路开关特性进行分析验证。所提接收端谐振参数设计方法能够使系统接收端回路谐振,提高系统的输出功率;降低逆变电路开关管的关断电流,提升系统的传输效率。搭建了一套2.5 kW的LCC-S型无线电能传输实验平台,验证了理论分析与所提参数设计方法的有效性和正确性。

基于T-S模糊逻辑的混合储能孤岛直流微电网功率分配控制

在含混合储能的直流微电网中,传统阻容下垂控制无法解决由线路电阻和负荷功率波动导致的系统功率分配失衡问题。为此,提出一种基于Takagi-Sugeno(T-S)模糊逻辑的自适应阻容下垂控制方法以实现混合储能的分频分配。根据蓄电池和超级电容的物理特性,建立单个蓄电池支路输出电压、蓄电池组间输出功率差额和阻性下垂系数之间的T-S模糊逻辑关系,以及单个超级电容支路输出功率及其变化率、超级电容组间功率差额和容性下垂系数之间的T-S模糊逻辑关系,并由此构建基于T-S模糊逻辑的阻容下垂控制器。推导含混合储能的直流微电网中各部分的平均阻抗模型,并采用阻抗比分析法对微电网的小信号稳定性进行研究。MATLAB/Simulink仿真结果表明,基于T-S模糊逻辑的阻容下垂控制可保证在线路电阻和负荷功率波动情况下系统功率的合理分配。

ON AN EXTENSION OF ABEL-GONTSCHAROFF'S EXPANSION FORMULA

We present a constructive generalization of Abel-Gontscharoff＇s series expansion to higher dimensions. A constructive application to a problem of multivariate interpolation is also investigated. In addition, two algorithms for constructing the basis functions of the interpolants are given.

Unifying the theory of integration within normal-,Weyl- and antinormal-ordering of operators and the s-ordered operator expansion formula of density operators

By introducing the s-parameterized generalized Wigner operator into phase-space quantum mechanics we invent the technique of integration within s-ordered product of operators （which considers normally ordered, antinormally ordered and Weyl ordered product of operators as its special cases）. The s-ordered operator expansion （denoted by s…s ） formula of density operators is derived, which isρ=2/1-s∫d^2β/π〈-β｜ρ｜β〉sexp{2/s-1（s｜β｜^2-β＊α＋βa-αα）}s The s-parameterized quantization scheme is thus completely established.

基于S-SSHI和SECE混合的压电阵列能量俘获电路设计

串联同步开关电感(Series Synchronous Switch Harvesting on Inductor,S-SSHI)电路输出功率高整流电压范围窄,而同步电荷提取(Synchronous Electric Charge Extraction,SECE)电路则输出功率低整流电压范围宽。提出了一种基于S-SSHI和SECE混合的压电阵列能量俘获接口电路,以实现整流器峰值输出功率和最佳整流电压范围之间的平衡。所提出的电路去除了整流桥结构,而采用简单的无源峰值检测器设计,且可以在任意相位差(0~2π)下从多个压电换能器中提取能量。仿真和实验结果表明,所提出的电路具有较高的输出功率和较宽的整流电压范围,与多输入全桥整流器相比,最大输出功率提升了3.04倍。

基于多MEMS梁的微波功率检测芯片

为了优化MEMS微波功率检测芯片的微波性能,提高其制备的可靠性,建立了悬臂梁结构在线式MEMS微波功率检测芯片的S参数模型,研究了悬臂梁的数目对微波功率检测芯片微波性能的影响。对多梁结构微波功率检测芯片微波性能进行理论推导和仿真,制备了单梁、双梁结构MEMS微波功率检测芯片样品,并进行了测试。结果表明,在8~12 GHz的频率范围内,单梁结构的微波功率检测芯片回波损耗小于-27 dB,双梁结构的微波功率检测芯片回波损耗小于-18.5 dB,单梁、双梁微波功率检测芯片传输特性变化趋势与理论值基本一致,验证了S参数模型的正确性。