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为了满足实时性要求,提出了基于现场可编程门阵列(field-programmable gate array,FPGA)的帧内预测并行化设计架构.通过并行架构来减少运算等待时间,通过查找表简化了参考像素选取过程,通过预测运算单元来降低计算复杂度和硬件实现的难度.实验代码通过Verilog HDL编写,通过Modelsim SE 10.1a进行仿真,并在Xilinx Virtex6 XC6VLX760 FPGA上综合.结果表明,该结构完成32×32块的预测需要570个时钟周期,在100 MHz时钟频率下,可以对60 f/s,分辨率为1 920×1 080的视频帧序列进行实时编码,满足实时性要求. 相似文献
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影响宽带电力线载波通信的关键因素之一是随机突发的脉冲噪声。目前的噪声研究大多停留在理论建模上,缺乏标准化的电力线噪声硬件实现方法。文中深入研究Markov-Middleton脉冲噪声模型,分析产生Markov性质的脉冲序列原理,利用System Generator和Xilinx Vivado联合仿真工具,设计出具有随机突发特性的电力线噪声生成系统,并完成该系统的硬件实现。通过对比现场可编程门阵列(FPGA)输出、Middleton Class A模型仿真与实测电力线噪声的统计特性,证明了该硬件实现方法能够生成具有随机突发性和时间相关性的脉冲噪声。通过搭建实验室环境下的电力线载波通信系统,测试不同参数下噪声对通信成功率的影响程度,对比其他的硬件实现方法,验证了所提方法的工程应用价值。 相似文献
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Yunxuan Dong; Shaodan Ma; Hongcai Zhang; Guanghua Yang 《Journal of Modern Power Systems and Clean Energy》2022,10(5):1184-1193
The seasonality and randomness of wind present a significant challenge to the operation of modern power systems with high penetration of wind generation. An effective shortterm wind power prediction model is indispensable to address this challenge. In this paper, we propose a combined model, i.e.,a wind power prediction model based on multi-class autoregressive moving average（ARMA）. It has a two-layer structure: the first layer classifies the wind power data into multiple classes with the logistic function based classification method; the second layer trains the prediction algorithm in each class. This two-layer structure helps effectively tackle the seasonality and randomness of wind power while at the same time maintaining high training efficiency with moderate model parameters. We interpret the training of the proposed model as a solvable optimization problem. We then adopt an iterative algorithm with a semi-closed-form solution to efficiently solve it. Data samples from open-source projects demonstrate the effectiveness of the proposed model. Through a series of comparisons with other state-of-the-art models, the experimental results confirm that the proposed model improves not only the prediction accuracy,but also the parameter estimation efficiency. 相似文献
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随着风电场装机容量的不断增加,解决大规模风电场并网对电网稳定性的影响问题就显得尤为重要。考虑到风能的特点及我国能源的地理分布情况,首先介绍了风电-火电\"打捆运行\"为电力系统供电的联合运行方式,通过调节火电厂的输送功率对风电进行调度,以实现电网的稳定及对风能接纳能力的最大化。其次,提出了多尺度选择的风电功率预测及误差校正方法,根据不同尺度的风电功率变化规律,可实现对风机组、电力系统的控制,以便于风电调度。最后,配以合适的储能装置、无功补偿设备可进一步增强电网的稳定性。通过假设的算例进行了验证和分析,具有一定的适应性和实用性。 相似文献
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近年来,风力发电逐渐成为可再生能源发电的关键部分.为了提高风力发电功率短期预测的准确度,提出了一种将自适应噪声完备集成经验模态分解与改进时间卷积网络结合的短期风电功率预测模型.首先,利用CEEMDAN对风电功率序列进行分解,得到子序列分量,并分别与关键气象变量数据构成训练集.然后,使用基于时间模式注意力机制的时间卷积网... 相似文献
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为了提高矿用测斜仪在煤矿井下钻探施工时的工作时间,以STM32嵌入式芯片为核心,提出了一种基于低功耗模式的测量方案。利用磁传感器和加速度传感器配合专用驱动芯片感知地球磁场和重力场,从而获得钻孔姿态信息。通过对STM32低功耗模式的研究,使仪器在非测量时间进入休眠状态,从而降低仪器功耗,提高工作时间。通过现场工业性试验表明,在保证测量精度和时间同步性的前提下,仪器单次使用时间超过60 h,完全满足钻探施工时对钻孔轨迹测量的要求。 相似文献
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利用南方某市2010—2012年盛夏期间日用电量和日气温、降水、相对湿度等数据,探索了分位数回归方法在日用电量预测中的应用。均一化处理后得到的日用电量系数序列剔除了经济社会发展和双休日等因素影响,相关分析表明其变化与前日用电量和当日最高气温变化的关系最为密切;将前日用电量和当日最高气温作为预报因子建立分位数回归方程,独立样本检验结果表明预测效果良好;与常用的均值回归等方法相比,分位数回归方法能够给出预测值的条件概率分布情况,可为电力调度和风险管理提供更多参考信息,具有较好的应用前景。 相似文献
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Jiali Ding Xin Wang Yihui Zheng Lixue Li 《IEEJ Transactions on Electrical and Electronic Engineering》2019,14(9):1295-1303
The characteristic impedance value of the overhead line is different from that of the underground cable. Existing traveling wave‐based fault location methods for mixed power transmission systems have setbacks including location error caused by wave velocity and difficulty in detecting wave arrival time. In order to solve these problems, the increase of available information from different locations by installing wire‐based sensors along the power line is a feasible solution. In this paper, a traveling wave‐based fault location system, which is based on the current data measured at the midpoint of the overhead line and the joint point, is introduced. The data at these two locations are measured by the wire‐based current sensor we designed. The whole transmission line system is divided by these two sensors into three segments. The first step of this proposed method is to record the postfault current data at the two measuring devices. Second, by comparing the amplitudes and polarities of the current at these two measurement points, the faulty segment can be identified. Finally, postfault wave propagation paths are ascertained; the accurate velocity values of the waves in the overhead line and underground cable are obtained; and then, the fault point is located without the need of time synchronization. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. 相似文献
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Naohiro Koura Ritsuya Watanabe Shinji Wakao 《IEEJ Transactions on Electrical and Electronic Engineering》2020,15(5):802-808
In our previous study, we carried out confidence interval estimation of next‐day photovoltaic (PV) output with just‐in‐time modeling hour by hour. When the target reliability is high in particular, the width of the confidence interval becomes large certainly. Therefore, in this paper, based on behavior of the measured PV output in the morning of the targeted day, we predict of PV output transition in the estimated confidence interval in the afternoon. The proposed method, which is consistently based on black box modeling, enables us to easily and effectively narrow the confidence interval width, i.e., sharpness, of PV output. Some numerical examples, which demonstrate the effectiveness of the proposed method, are also reported. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. 相似文献
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精确的风电功率预测对保障大规模风电接入电网后电力系统的安全稳定运行具有重要意义。其中,风速的随机变化是引起风电功率波动和影响风电功率预测精度的最主要原因。针对该问题,提出一种基于变尺度时间窗口和波动特征提取的短期风电功率组合预测方法。首先,通过多重分形谱分析不同天气类型下的风速特征。然后,根据当前风速的特征量采用变尺度滑动时间窗口算法,动态地进行特征提取,由提取结果对风电历史数据进行分类,在此基础上选择特定参数建立对应的功率预测模型。为使模型在功率大幅度波动时刻的预测结果更加精确,提出了基于频谱分析的修正方法。最后,将不同天气类型下的功率预测结果与修正结果进行时序组合。算例结果表明,所述变尺度时间窗口与波动特征提取相结合的短期风电功率组合预测方法可有效提高风速波动剧烈的风电场的风电功率预测精度。 相似文献
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380 V 厂用电采用全塑电缆供电,接地电流经固定电缆支架,用具有铁磁材料性质的生根扁铁组成回路,电流衰减快,从而使串级供电回路各断路器之间的保护时间配合不协调,造成部分母线段停电。为解决此问题,建议改选保护装置,配用可广范围调整的时间继电器,以便灵活调整各断路器之间的保护时间配合。 相似文献
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Mohsen Tamaddon Mohammad Yavari 《International Journal of Circuit Theory and Applications》2018,46(3):384-400
In this paper, a new type of an oscillatory noise‐shaped quantizer (NSQ) for time‐based continuous‐time sigma‐delta modulators is presented. The proposed NSQ is composed of an oscillatory voltage‐to‐time converter and a polyphase sampler. Using Tustin's transformation method and through the approximation of the comparator gain, a linearized model of the NSQ is introduced. This way, a novel realization of the first‐ and second‐order NSQ is presented. Its implementation is based on fully passive continuous‐time filters without needing any amplifier or power consuming element. The ploy‐phase sampler inside the NSQ is based on the combination of a time‐to‐digital and a digital‐to‐time converter. The layout of the proposed NSQ is provided in Taiwan Semiconductor Manufacturing Company 0.18 μm complementary metal‐oxide‐semiconductor 1P6M technology. The verification of the proposed NSQ is done via investigating both the system level and postlayout simulation results. Leveraging the proposed NSQ in an Lth‐order time‐based continuous‐time sigma‐delta modulator enhances the noise‐shaping order up to L + 2, confirming its superior effectiveness. This makes it possible to design high performance and wideband continuous‐time SDMs with low power consumption and relaxed design complexity. 相似文献
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Rasoul Faraji Hamid Reza Naji Majid Rahimi‐Nezhad Mohammad Arabnejhad 《International Journal of Circuit Theory and Applications》2014,42(11):1189-1202
In this paper, a new SRAM cell with body‐bias actively controlled by a control circuit and word line is introduced to realize low‐power and high‐speed applications. The cell uses two word lines, which vary between positive and negative voltage levels to control the body bias of cell's transistors. In this design, using a peripheral control circuit with the least possible number of transistors, the access time is decreased and also a trade‐off between static and dynamic power consumption is provided. Compared to a conventional SRAM cell, the proposed cell reduces the static power consumption by 82% and improves the read performance by 40% and the write performance by 27%. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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近年来,我国能效水平不断提升,单位GDP能耗、电耗均呈下降趋势,但是两者并不同频,能耗呈现持续下降趋势,而电耗则呈现波动性下降趋势,且各省之间能效水平差异较大。首先,梳理了我国促进能效提升的重要政策法规,对单位GDP能耗、电耗整体及分省发展情况进行了分析,并从不同维度,由表及里分析了单位GDP能耗、电耗走势的影响因素。然后,对影响能效的几个主要因素进行走势研判,对“十四五”期间能效情况进行了展望预判,预计单位GDP能耗、电耗将呈现下降态势。最后,提出了推广以电为中心的综合能源系统等促进能效提升的相关建议。 相似文献
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Mohsen Sadeghi Mohammad Farrokhi 《International Journal of Adaptive Control and Signal Processing》2019,33(1):157-174
In this article, a real‐time block‐oriented identification method for nonlinear multiple‐input–multiple‐output systems with input time delay is proposed. The proposed method uses the Wiener structure, which consists of a linear dynamic block (LDB) followed by a nonlinear static block (NSB). The LDB is described by the Laguerre filter lattice, whereas the NSB is characterized using the neural networks. Due to the online adaptation of the parameters, the proposed method can cope with the changes in the system parameters. Moreover, the convergence and bounded modeling error are shown using the Lyapunov direct method. Four practical case studies show the effectiveness of the proposed algorithm in the open‐loop and closed‐loop identification scenarios. The proposed method is compared with the recently published methods in the literature in terms of the modeling accuracy, parameter initialization, and required information from the system. 相似文献
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Kazunori Nishimura Yasushi Maehata Wataru Sunayama 《Electrical Engineering in Japan》2015,191(2):47-54
The inspection of power supply facilities can now be conducted with high accuracy using remote monitoring technology. In contrast, it is difficult to install sensors at demand facilities because their scale and installation environment differ among customers. As a result, the demand facilities are inspected at fixed time intervals. In this paper, we propose condition‐based maintenance (CBM), which improves maintenance quality at demand facilities. The proposed method was developed using maintenance data from demand facilities, collected using time‐based maintenance, and we conduct the analysis primarily using failure data. We use data mining to analyze transaction data that we modeled on the basis of the maintenance data and to construct a “failure predictive model” that can predict the failure of facilities and its causes from the results of the analysis. By using the constructed model, we will be able to identify the objects requiring maintenance which may most likely lead to failures in the future, and this study can contribute to improvement of maintenance technologies for demand facilities using the proposed CBM. 相似文献