Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.

A power function model for simulating creep mechanical properties of salt rock

In this paper,a new micro-creep model of salt rock is proposed based on a linear parallel bonded model(LPBM)using the two-dimensional particle flow code(PFC2D).The power function weakening form is assumed to describe the variation of the parallel bonded diameter(PBD)over time.By comparing with the parallel-bonded stress corrosion(PSC)model,a smaller stress fluctuation and smoother creep strain−time curves can be obtained by this power function model at the same stress level.The validity and adaptability of the model to simulate creep deformation of salt rock are verified through comparing the laboratory creep test curves and the Burgers model fitting result.The numerical results reveal that this model can be capable of capturing the creep deformation and damage behavior from the laboratory observations.

Modeling Distortion Signals of Power Grid Based on Wiener-G Functionals

The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.

Computational Precision of the Power Function for Conditional Tests of Assumptions of the Rasch Model

Draxler and Zessin [1] derived the power function for a class of conditional tests of assumptions of a psychometric model known as the Rasch model and suggested an MCMC approach developed by Verhelst [2] for the numerical approximation of the power of the tests. In this contribution, the precision of the Verhelst approach is investigated and compared with an exact sampling procedure proposed by Miller and Harrison [3] for which the discrete probability distribution to be sampled from is exactly known. Results show no substantial differences between the two numerical procedures and quite accurate power computations. Regarding the question of computing time the Verhelst approach will have to be considered much more efficient.

Lattice Boltzmann simulations of high-order statistics in isotropic turbulent flows

The lattice Boltzmann method （LBM） is coupled with the multiple-relaxation- time （MRT） collision model and the three-dimensional 19-discrete-velocity （D3Q19） model to resolve intermittent behaviors on small scales in isotropic turbulent flows. The high- order scaling exponents of the velocity structure functions, the probability distribution functions of Lagrangian accelerations, and the local energy dissipation rates are investi- gated. The self-similarity of the space-time velocity structure functions is explored using the extended self-similarity （ESS） method, which was originally developed for velocity spatial structure functions. The scaling exponents of spatial structure functions at up to ten orders are consistent with the experimental measurements and theoretical results, implying that the LBM can accurately resolve the intermittent behaviors. This valida~ tion provides a solid basis for using the LBM to study more complex processes that are sensitive to small scales in turbulent flows, such as the relative dispersion of pollutants and mesoscale structures of preferential concentration of heavy particles suspended in turbulent flows.

Study on Volterra-Laguerre behavioral model for RF power amplifier

Voherra series behavioral model for radio frequency （RF） power amplifier （PA） has been widely used in system-level simulation, however, high computational complexity makes this kind of model limited to ＂weak＂ nonlinearity. In order to reduce the computational complexity and the number of coefficients of Volterra series kernels, a Volterra series improved behavioral model based on Laguerre orthogonal polynomials function, namely Voherra-Laguerre behavioral model, is proposed. Mathematical expressions of Volterra-Laguerre behavioral model is derived, and accuracy of the model is verified through comparison of measured and simulation output data from a freescale PA using MRF21030 transistor. Mathematical analysis and simulation results show that Voherra-Laguerre behavioral model has a simple structure, much less coefficients and better modeling performance than general Volterra series model. The model can be used more correctly for system-level simulation of RF PA with wideband signal.

Exact Dynamic Modeling of PWM DC-to-DC Power Converters—Part II: Discontinuous Conduction Mode

This paper follows on from the first paper, Part I, where a general formulation of a describing function approach to frequency response determination of switched linear networks, such as PWM converters, was simplified and updated. The models assume a piecewise linear state space equation description of the system and results in a closed form solution for the sought after frequency response. In Part I, model derivation was demonstrated for the case of PWM converters operating in the continuous conduction mode (CCM). This operating mode does not feature any state dependent switching times. In this paper, Part II, frequency response models for any transfer function for PWM converters operating in discontinuous conduction mode (DCM) are derived based on the theory presented in Part I. This operating model features state dependent switching times. The describing function models developed are exact and therefore, in terms of accuracy, are to be preferred over averaged models which are widely used. The example of a boost dc-to-dc converter operating in DCM is simulated to obtain the control to output and input to output frequency responses and are compared with the models derived here. Excellent agreement between the simulated and model responses was found. Matlab code implementing the analytical models is also presented which the user can adapt for any other PWM converter topology. The models derived here may be used as a basis from which simplified models may be derived while still preserving required accuracy.

Exact Dynamic Modeling of PWM DC-to-DC Power Converters—Part I: Continuous Conduction Mode

A general approach is presented by which the exact frequency response of any transfer function of switched linear networks can be determined. This is achieved with a describing function approach using a state space equation formulation. This work presents a somewhat simplified set of equations to one previously given by one of the authors. To demonstrate application of the general formulation, the frequency responses of switched networks used as PWM DC-to-DC converters operating in continuous conduction mode (CCM) under voltage mode control are derived. (The accompanying paper, Part II, will present results for converters operating in discontinuous conduction mode (DCM)). From the general sets of equations developed here, both the control to output and input source variation to output frequency responses are derived. The describing function approach enables exact frequency response determination, even at high frequencies where the accuracy using average models may be compromised. Confirmation of the accuracy of the derived models is provided by comparing the responses with those obtained using the commercial simulator PSIM on a PWM boost converter. The magnitude and phase responses are shown to match perfectly over the full range of frequencies up to close to half the switching frequency. Matlab code that implements the models is given such that the user can easily adapt for use with other PWM converter topologies.

K-power双线性系统基于Laguerre函数的保结构模型降阶方法

针对K-power双线性系统,提出一种基于Laguerre函数的保结构模型降阶方法.该方法首先将K-power双线性系统转化为一般的双线性系统,再利用矩阵指数函数的Laguerre函数展开,计算出双线性系统交叉Gram矩阵的近似低秩因子,从而构造K-power双线性系统各子系统相应的投影变换,进而生成该系统的近似平衡系统.然后,通过截断较小的奇异值对应的状态,得到降阶模型.该降阶过程计算高效,且具有一定的自适应性.最后,数值实验验证了算法的有效性.

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。

基于低风速功率修正和损失函数改进的超短期风电功率预测

风电功率具有较强的波动性和随机性。为进一步提升风电功率的预测精度,提出一种基于低风速功率修正和损失函数改进的超短期风电功率预测模型。该模型采用卷积神经网络、自注意力机制和双向门控循环单元捕获风电功率序列的长期时序依赖关系。为了解决低风速下待风状态神经网络难以精确拟合的问题,模型通过预测风速并结合当前时段的风电功率对低风速段的预测功率进行修正。针对参数训练的稳定性问题,模型通过改进预测策略和共享权重,引入一种多元非线性的损失函数来提取序列间的关联性。结果表明,所提模型在多项误差指标中均优于对比模型,能够有效提升超短期风电功率的预测效果。

数模—动模混合仿真系统的接口建模与稳定性分析

为满足现代电力系统实时仿真的发展需求,数模-动模混合仿真系统结合实时数字仿真和物理动态模拟仿真的优点,成为现代电力系统研究的重要仿真方法。接口系统是混合仿真系统设计中的核心与难点。为了深入分析混合仿真系统的稳定性,对接口系统各个组成环节进行建模得到系统开环传递函数,分别根据劳斯判据和奈奎斯特判据研究开环传递函数中不同参数对系统稳定性的影响。理论推导表明接口系统中滤波器截止频率、接口延时和阻抗模拟比对系统的稳定性影响较大,并通过所搭建的混合仿真系统进行实验,实验结果表明不同参数对系统的稳定性影响与理论推导一致。

面向数字孪生模型应用的油浸式变压器绕组温度POD-RBFLP降阶计算方法

了解油浸式电力变压器绕组的温度情况是保证其运行稳定性的关键,也是当前针对油浸式变压器数字孪生分析的必然需求。为了快速地获得变压器绕组的稳态温度,该文提出一种基于本征正交分解(proper orthogonal decomposition,POD)和包含线性多项式的径向基函数响应面法(radial basis function response surface method including linear polynomial,RBFLP)的降阶计算模型。首先,讨论POD方法的降阶特性,并设计一种基于留一法交叉验证的自适应获得快照矩阵方法,以提高计算精度及效率;其次,采用响应面方法建立POD模态系数与绕组工况的相关关系,旨在实现通过绕组工况快速获得POD模态系数,从而跳过对降阶模型的复杂非线性计算,进而高效重构绕组温度场。相关算例表明,该方法具有较好的计算精度和效率,在50组测试工况下,与全阶计算相比,误差不超过2.5 K,且总计算时间仅为1.45 s;最后,基于110 kV变压器绕组搭建温升试验平台,试验结果表明,降阶计算结果相较于试验结果,平均计算误差不超过2 K,且单步计算时间仅为0.03 s,相较于同等规模的全阶计算,计算效率有较大幅度地提升。

基于投资组合高阶矩分析的电力系统灵活性评估

针对现有灵活性指标形式主要集中于低阶统计量,仅能反映系统灵活性的平均水平与集中程度,而忽视了灵活性的高阶特征这一问题,引入投资组合高阶矩分析理论对电力系统灵活性进行刻画,以揭示系统灵活性的调节潜力与风险。首先,通过分析投资组合的均值-方差-偏度-峰度模型(mean-variance-skewness-kurtosismodel,MVSK Model),给出了灵活性单元组合的定义,基于多元Copula函数构建考虑空间相关性的灵活性单元概率模型。其次,基于灵活性单元组合的各阶矩建立灵活性评估指标,并给出基于核密度估计与蒙特卡洛模拟的指标计算方法。最后,通过FTS-213测试系统与德国某电网的历史数据对所提指标进行了测算和验证。算例表明所提指标能够反映系统灵活性调节能力的平均水平、稳定程度、潜力与风险,且能量化评估灵活性资源种类与投建地区对系统灵活性的影响,为后续的灵活性资源规划提供理论支持。

海上风电与海洋牧场融合发展趋势与技术挑战

[目的]在“双碳”目标及“海洋强国”战略背景下,以海上风电为代表的海洋可再生能源和以海洋牧场为代表的海洋资源融合发展是未来海洋资源开发利用的新方向、新形势、新机遇。文章针对海上风电与海洋牧场融合发展模式及关键技术进行了综述分析,以向国内相关研究和工程项目提供技术参考。[方法]以我国海洋资源融合开发需求为导向,分析海上风电与海洋牧场融合全球发展趋势,明确我国风渔融合发展的现状与短板;在此基础上,重点剖析了海上风电与海洋牧场融合发展的融合模式、装备设计、工程案例及关键技术问题,最后对我国海上风电与海洋牧场融合发展进行了未来展望。[结果]通过对海上风电与海洋牧场融合发展模式及关键技术问题进行梳理分析,阐明了瓶颈问题及技术挑战,指出了未来突破方向,为我国海上资源综合开发利用提供了科学指导和参考依据。[结论]文章说明了海上风电与海洋牧场融合发展的必要性和可行性,提出了我国海上风电与海洋牧场融合的可行途径。

采用改进MPC提高储能系统电压暂态特性研究

储能系统通过换流器实现并网运行,常规换流器因为其开关频率低,在采样、计算环节存在延时导致储能系统暂态特性差,甚至引起整个电网不稳定。本文采用模型预测控制MPC(model predictive control)来实现储能系统功率快速响应,避免延时影响。引入功率权重价值函数在有功、无功MPC控制中,计算储能换流器输出电压最优值。针对因为滤波电感参数偏移导致的MPC模型不准确问题,本文采用电感误差补偿控制来提高模型精度。通过Matlab/Simulink仿真和实验来验证本文所提方案可提高储能系统暂态特性,有效消除误差对MPC控制性能的影响。

基于多保真度模型的高比例新能源配电网潮流不确定性表征方法

在能源生产和消费低碳化转型的背景下,如何量化源-荷不确定性的影响,高效、准确地实现配电网潮流不确定性表征,对配电网的安全、可靠运行具有重要意义。该文从计算效率和准确性两方面出发,将现有基于概率潮流的不确定性表征方法分为高、低保真度模型两类,综合分析了两种方法存在的问题。在此基础上,提出一种基于多保真度模型的高比例新能源配电网潮流不确定性表征方法,以实现潮流状态变量矩信息的高精度估计与概率分布函数的刻画。在矩信息估计方面,提出结合高、低保真度模型特点的最优输入样本数量分配方法,在给定总计算负担下实现了输出变量矩信息的无偏估计。在概率分布函数刻画方面,提出基于综合启动函数的概率分布函数刻画方法,利用多保真度模型提供的先验信息,提升概率分布函数拟合的准确性。通过118节点配电网的仿真计算,验证所提方法的有效性。

考虑温度作用的岩石统计损伤本构模型及验证

为了预测和评估深部高温岩体的稳定性,运用理论推导的方法研究温度作用下(后)岩石的本构关系。首先,基于已有的岩石统计损伤本构模型,考虑温度对岩石损伤变量的影响,引入了损伤变量修正系数、损伤起裂应力和起裂应变等参数;其次,假设微元体强度服从幂函数分布,并符合Hoek-Brown(H-B)强度准则,针对统计损伤本构模型无法反映峰前较强的微裂纹压密效应的弊端,引入了相应的模型修正系数;再次,建立了考虑温度作用的岩石统计损伤本构模型,并确定了模型参数的表达式;最后,对比不同温度作用下(后)的花岗岩在单轴和常规三轴压缩试验条件下所得的结果与文献中模型的计算结果,验证本文模型的准确性。研究结果表明:所提出的模型的计算结果与文献的试验结果在数值、分布规律和趋势上具有良好的一致性;对于全过程σ-ε曲线的各阶段,本文模型的计算效果较文献中本构模型计算效果更好,与试验曲线的贴合度更高,能够更好地反映高温作用下(后)岩石的损伤本构特征。该模型的参数具有常规性,适用于各类温-压组合作用工况下的岩石。

电场实时加载下煤层气解吸-扩散特性实验研究

为探究电场实时加载下煤层气解吸-扩散特性,揭示电场强化煤层气高效抽采的机理影响特征,设计并研发了可控电场强度下煤层气解吸-扩散实验系统;实验探究了电场加载下煤体的CH4和CO_(2)解吸-扩散变化特征,并通过幂函数扩散模型计算各场强作用下的CH4扩散系数。结果表明:不同吸附质在电场实时加载下煤层气解吸量均得到一定程度提升,但电场对CO_(2)解吸量影响特征更加明显,同时电场能够强化煤体瓦斯的初始解吸速度;与未加电场相比,特征场强为30、60、90 kV/m时CH4初始解吸速率提升了6.9%、15.3%、14.6%,而CO_(2)依次提升了3.4%、6.7%、9.2%;电场加载下煤体CH4幂函数扩散模型能够高度的与实验值相吻合,扩散系数具有随着加载场强的增大而逐渐增大变化特征,电场有利于煤中甲烷的解吸、扩散。

中国要素错配的时空演变研究

随着中国经济进入高质量发展阶段,提高要素配置效率成为当前发展的重要任务之一。基于多部门一般均衡模型,引入时空异质产出弹性生产函数,考虑资本、电力资源和异质性技能劳动力,量化分析2009—2021年中国284个地级以上城市要素错配的时空演化特征。研究发现:要素错配程度和方向存在较大时空异质性,资本、高技能劳动力和中等技能劳动力呈配置过度状态,电力资源和低技能劳动力呈配置不足状态。高技能劳动力配置呈空间收敛趋势,其他类型要素配置呈空间扩大趋势。资本和电力资源配置空间差异扩大源于西部地区配置过度加剧,低技能劳动力配置空间差异扩大源于西部地区配置不足加剧,中等技能劳动力配置空间差异较大源于东北地区配置不足严重。资本配置过度增加的城市数量大于配置不足增加的城市数量,电力资源配置过度增加的城市数量远大于配置不足减少的城市数量,高技能劳动力配置不足和配置过度的城市数量大幅下降,中等技能、低技能劳动力配置不足的城市数量增加。资源型城市要素错配问题比非资源型城市严重,尤其是成长型、成熟型资源城市。