基于多模型长短时记忆神经网络的电力负荷预测方法研究

提出了一种基于多模型长短时记忆神经网络(LSTM)的电力负荷预测方法,该方法通过对历史电力负荷日曲线进行密度聚类,根据聚类结果以及历史日期的特征因素训练高斯朴素贝叶斯分类器,进而分类训练神经网络预测的输入,采用长短时记忆神经的深层网络对所述历史时刻的电力负荷数据和日期特征因素进行训练建模,以训练生成深度神经网络负荷预测模型。通过算例仿真,发现该方法相比于典型方法,能够精确预测出对应日期的用电负荷,提升预测效果,同时缩短网络训练时间,提升程序运行速度。     

基于MEA-Elman神经网络的电力日负荷预测

Elman神经网络是一种动态反馈网络,对历史状态敏感,具有短期记忆功能和处理动态信息的能力,可以建立动态、非线性电力负荷预测模型。由于Elman神经网络采用BP算法,容易陷入局部极小解,迭代次数多且学习效率低,该文利用思维进化算法(MEA)优化Elman神经网络的方法,提出基于MEA-Elman神经网络的电力负荷预测模型。实验表明,该方法能够避免不成熟收敛问题,减少迭代次数,有效提高了配电网短期负荷的预测精度,对电力系统合理调度与规划具有重要意义。     

基于改进深度稀疏自编码器及FOA-ELM的电力负荷预测

智能电网的发展使得电网获取的数据逐渐增多,为了从多维大数据中获取有用信息并对短期内电力负荷进行准确的预测,提出了一种基于改进的深度稀疏自编码器(IDSAE)降维及果蝇优化算法(FOA)优化极限学习机(ELM)的短期电力负荷预测方法。将L1正则化加入到深度稀疏自编码器(DSAE)中能够诱导出更好的稀疏性,用IDSAE对影响电力负荷预测精度的高维数据进行特征降维,消除了指标间的多重共线性,实现高维数据向低维空间的压缩编码。采用FOA优化算法优化ELM的权值和阈值,得到最优值,能够克服因极限学习机随机选择权值和阈值导致预测精度低的缺点。首先将气象因素通过IDSAE降维,得到稀疏后的综合气象因素特征指标,协同电力负荷数据作为FOA优化的ELM预测模型的输入向量进行电力负荷预测。通过与DSAE-FOAELM、DSAE-ELM和IDSAE-ELM等模型的对比实验,证明了提出的预测模型能有效提高预测精度,经计算得出预测精度提升大约8%。     

面向智能物联的动态负荷预测量子进化方法

物联网与智能制造的结合导致大量制造数据的产生,为了实现基于大数据的智能制造电力负荷预测,提出并实现了一种智能物联云计算平台,实现用户与智能物联网之间双向通信控制的快速响应。提出一种基于改进外加输入的自回归滑动平均模型的短期动态负荷预测模型,结合平台中的智能传感设备和历史负荷、天气变化等综合数据,作为预测模型的外部输入变量,并利用改进的实数编码量子进化算法对预测模型进行参数估计以提高动态负荷预测的准确性。利用智能制造企业的实际负荷数据,采用所提方法进行预测并与实际负荷数据及传统方法的预测结果进行比较,实验结果表明,所提方案和算法能够有效提高智能制造过程中短期动态负荷预测的精度,同时通过并行化计算提升负荷预测的速度。     

机械振动下交流接触器电寿命预测失效特征量提取

针对机械振动环境下交流接触器电寿命预测中的失效特征量进行研究,提出了一种基于优化小波去噪与核主成分分析 皮尔逊相关系数法相结合的方法以获取有效的失效特征量。首先,分别在常规与振动环境下进行交流接触器全寿命试验,并选取多个退化参数作为分析对象;其次,针对实测数据,采用多指标综合评价方法优化小波去噪,对退化参数进行去噪平滑,并结合参数的退化趋势,分析振动对接触器电寿命的影响;最后,针对退化参数及其核主成分,构建全信息特征量,计算各特征与剩余电寿命的皮尔逊相关系数。在振动环境下,结合所提方法最终提取累积燃弧能量、第一核主成分、吸合电压和接触电阻作为交流接触器电寿命预测的失效特征量。     

基于粒子群算法的极限学习机短期电力负荷预测

为了优化极限学习机的参数,提高短期负荷预测的准确率,提出一种改进粒子群算法的极限学习机(CSPSO-ELM)预测模型。该模型利用粒子群算法(particleswarmoptimization,PSO)寻找极限学习机(ELM)网络中最优的输入权值和隐层偏差值,得到输出权值矩阵,以达到减少随机参数误差的目的。同时引入混沌自适应策略,增强粒子群算法的多样性,防止粒子群陷入局部收敛。在充分考虑天气、湿度、假日因素和当地工业产值对预测结果的影响下,提出一种基于该方法的极限学习机预测模型。最后,针对扬州市高新区用电总量预测问题,通过与其它模型的对比实验,证明了改进的粒子群算法优化了极限学习机的参数结构,提高了电力负荷预测的精准度。     

混沌预测模型改进及在电力日负荷预测中的应用

针对电力日负荷预测中基于最大Lyapunov指数的传统混沌预测模型的缺陷,提出以下改进思想:采用微分熵法同时确定嵌入维数和延迟时间,改善相空间重构质量的同时,有效减少计算量;引入夹角参数,在与中心点距离最短的点中,筛选夹角最小的点作为最终邻近点;基于相似性原理,引入取舍规则,使得计算结果唯一确定。本文方法解决了传统预测模型计算量大、运算速度慢、预测精度不高以及正负号选取等问题。通过对典型混沌系统数值验证和某地区实际电力负荷系统的预测分析证明了本文方法的可靠性和高效性,为电力日负荷预测提供了一种新的有效途径。     

电力负荷与气象因子因果关系分析及预测研究

短期电力负荷预测是电力部门生产调度的重要参考,不同地区影响电力负荷的因素有所不同,因此,为探索电力负荷与气象因子之间的因果关系,以某变电站逐小时电力负荷和气象要素数据为基础,采用格兰杰因果检验分析气象要素与电力负荷的因果关系。采用ADF检验验证气象因子与电力负荷数据的平稳性,将通过ADF检验的平稳性变量进行格兰杰因果检验。结果显示,温度、相对湿度和风速均是电力负荷的格兰杰原因,温度和相对湿度对电力负荷变化的影响是实时的,风速对电力负荷变化的影响具有1 h以上的滞后性。采用灰色关联度和余弦相似度建立综合相似性指标,基于相似日法提出一种短期电力负荷预测模型,以2018—2020年的气象数据和电力负荷数据作为样本库,采用2021年的数据对模型预测准确性进行检验。经验证,模型在天气因子变化不明显或变化缓慢情况下预测准确率为90%以上,可作为电力部门生产调度参考。     

基于LMBP神经网络的故障预报方法及其应用

利用具有二阶收敛效应的Levenberg-M arquardt(L-M)算法优化BP的权值修正量,提出了一种快速收敛的LMBP学习算法,给出了基于LMBP神经网络的故障预报方法,并应用于某陀螺仪的故障预报。结果表明:较之BP和传统改进BP网络,LMBP网络有着更高的收敛速度;基于该网络的时间序列预测模型可以实现性能优越的非线性预报器,将其应用于非线性系统的故障预报能够取得良好的效果。     

改进灰色模型在电力负荷中的预测分析及实现

深入研究了基于灰色系统理论的电力负荷预测方法,剖析了灰色预测GM(1,1)模型应用的局限性及其改进方法,在对原始数据序列进行插值平滑处理的基础上建立了等维新信息灰色预测模型,并用此方法对某地区的电力负荷进行预测分析,结果表明:模型精度较高,预测误差较小,该方法可以作为电力负荷预测的理想工具。     

On the Relation of Load to Average Gap in the Contact Between Surfaces with Longitudinal Roughness

A computer simulation model for the contact between longitudinally-oriented rough surfaces has been formulated. This model closely duplicates the actual surf ace contact deformation behavior by taking into account the elastic interactions between the asperities. There were no assumptions made about the shapes, or any deformation behavior of the asperities, except for their obeying the laws of elasticity. The plastic deformations on the high asperity peaks were taken into account by setting a ceiling on their contact pressures at the material hardness value. The simulations used real surface profiles which were digitized from unworn circumferentially ground steel surfaces. Each pair of these profiles was mathematically combined to form an equivalent rough profile pressing against an infinitely rigid flat and having the appropriately adjusted elastic modulus. A total of 28 different pairs of profiles were used in the simulations. Each contacting pair was subjected to 30 different load levels and the local contact pressures and deformations were calculated. The contact simulations yielded some important mathematical relationships between parameters, such as the real area of contact, average gap, and average asperity load through statistical curve fitting. Two analytical functions were generated to relate the average load to average gap and the real area of contact to load.     

三绕组变压器的双绕组等效建模及在Matpower中的应用

针对实际电网存在着大量的三绕组变压器,但国际上一些著名商业软件,如BPA仿真软件、Matpower这一权威潮流计算开源软件,均只提供双绕组变压器模型,限制了其在具有三绕组变压器的电力系统中的应用的问题,潮流计算是自主开发的电力系统各种应用软件的核心模块,因此依托国际权威开源程序进行二次开发,是一种较好的选择。对Matpower要求的数据格式进行了归纳,对变压器的一般的等值电路及带理想变压器的等值电路和带标幺值的等值电路进行了分析研究,提出了三绕组变压器转换为双绕组等效模型的建模方法,使得原先只适应双绕组变压器的潮流计算软件可以适用于三绕组变压器电网的潮流计算;最后以Matpower软件为例进行了案例计算,并用PSASP仿真软件进行对比验证。研究结果证明,所提出的建模方法是有效的。     

电站锅炉模糊风险评价方法研究与应用

针对电站锅炉风险等级评价问题,将模糊综合评价技术应用到电站锅炉风险等级评价中。开展了电站锅炉失效影响因素及模糊评价因素的重要程度分析,建立了一套科学合理适于在线评价的电站锅炉风险评价体系,提出了模糊综合评价技术与改进的模糊层次分析法相结合的模糊风险评价方法,利用改进的模糊层次分析法计算了指标体系中各层指标权重。对某一台电站锅炉的实际运行工况影响子因素进行了模糊风险评价,采用模糊合成算子进行模糊综合运算得到电了站锅炉运行工况影响子因素的评价向量。研究结果表明:电站锅炉的运行工况影响子因素的风险评价等级为第6级,失效可能性等级为小,该电站锅炉运行工况良好。     

交通荷载作用下桥梁结构参数识别方法

应用动力节点加载法,将作用在桥梁上的交通荷载转化为等效节点荷载,再用两步构造法识别结构物理参数.第1步,用Newmark-β方法变换结构运动方程,并用结构的加速度响应求得变换空间内的位移、速度和加速度响应;第2步,基于最小二乘原理,构造出变换空间内求解结构参数的递推式,进行结构物理参数识别.数值模拟结果表明,在交通荷载作用下,该方法能够快速、准确地进行桥梁结构参数识别.     

Quantum Cooperative Robotics and Autonomy

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper.The two areas are brought together in establishing an interdisci...     

考虑进油孔有限长滑动轴承油膜力的近似解析解

针对具有进油孔的有限长滑动轴承油膜力求解问题,采用变分原理和分离变量法,求得了有限长滑动轴承油膜压力分布的近似解析表达式。将油膜压力分布的近似解析表达式在油膜存在区域上进行积分,即得到了油膜力。将提出的计算有限长滑动轴承油膜力方法与无限长轴承模型、有限元方法的计算结果进行了比较,发现了提出的方法与有限元方法的计算结果很接近。最后,研究了进油孔位置和进油压力对油膜存在区域、油膜力等的影响,研究结果表明进油孔位置和进油压力对油膜存在区域和油膜力有较大的影响。     

RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.     

Robust Impedance Control of Robots Using an Adaptive Interaction Force Observer

For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type ...     

Research on key techniques of expendable conductivity temperature depth measuring system

This paper analysis the developing of expendable conductivity temperature depth measuring system(XCTD)and introduce its principle of measuring about temperature,salinity and depth of ocean.Some key techniques are put forward.According to the real needs of XCTD,conductivity sensor with high sensitivity is designed by principle of electromagnetic induce,the ocean conductivity from induced electromotive force has been calculated.Adding temperature correction circuit would help to reduce error of conductivity measurement because of sharply changing temperature.Advanced temperature measuring circuit of high precision and the constant current source is used to weaken effect of self-heating of resistance and fluctuation of the source.On respect of remote data transmission,LVDS is a good choice for the purpose of guarantee the quality of data transmitted and the transmission distance is reaching to thousand meters in the seawater.Modular programming method is also brought into this research aimed at improve the stability,reliability and maintainability of the whole measuring system.In February,2015,the trials in South China Sea demonstrate that the developed XCTD realize effective measurement at a speed of 6 knots and detection depth at 800 m.The consistency coefficient of the acquired data is greater than 0.99 and the success rate of probe launching is above 90%.     

CHARACTERISTCS OF FLUID FILM IN OPTIMIZED SPIRAL GROOVE MECHANICAL SEAL

In order to investigate the sealing performance variation resulted from the thermal deformation of the end faces, the equations to calculate the fluid film pressure distribution, the bearing force and the leakage rate are derived, for the fluid film both in parallel gap and in wedgy gap. The geometrical parameters of the sealing members are optimized by means of heat transfer analysis and complex method. The analysis results indicate that the shallow spiral grooves can generate hydrodynamic pressure while the rotating ring rotates and the bearing force of the fluid film in spiral groove end faces is much larger than that in the flat end faces. The deformation increases the bearing force of the fluid film in flat end faces, but it decreases the hydrodynamic pressure of the fluid film in spiral groove end faces. The gap dimensions which determine the characteristics of the fluid film is obtained by coupling analysis of the frictional heat and the thermal deformation in consideration of the equilibrium condition of the bearing force and the closing force. For different gap dimensions, the relationship between the closing force and the leakage rate is also investigated, based on which the leakage rate can be controlled by adjusting the closing force.