对居民用电进行准确的短期负荷预测是电力部门合理制定每日调度计划的重要依据。提出了一种基于BIRCH(balanced iterative reducing and clustering using hierarchies)聚类算法-卷积神经网络(convolutional neural network, CNN)-门控...对居民用电进行准确的短期负荷预测是电力部门合理制定每日调度计划的重要依据。提出了一种基于BIRCH(balanced iterative reducing and clustering using hierarchies)聚类算法-卷积神经网络(convolutional neural network, CNN)-门控循环单元(gated recurrent unit, GRU)的短期电力负荷预测方法。根据智能电表采集的历史负荷数据,该方法首先采用BIRCH聚类算法分析不同用户的用电习惯,将用户聚类为多个用户群;然后构建由负荷数据和时间以及气候信息组成的多特征时间序列数据集,并采用训练集进行CNN-GRU预测模型构建。训练集首先输入到基于一维卷积层设计的CNN网络,以提取不同特征变量之间的非线性关系;之后将数据输入GRU网络,以提取数据在时间维度上的时序特性,最后由全连接层输出短期负荷预测结果。以爱尔兰能源管理委员会提供的公开数据集作为实际算例,以ANN网络、CNN网络及CNN-GRU网络为对比模型,实验结果表明,所提出方法的平均绝对百分比误差达到了2.932 1%,有较高的预测精度和较快的模型训练速度。展开更多
This paper presents a cascode configuration synchronous rectifier device based on silicon MOSFET and Schottky diode,which can replace traditional power diode directly.This structure has self-driven ability with simple...This paper presents a cascode configuration synchronous rectifier device based on silicon MOSFET and Schottky diode,which can replace traditional power diode directly.This structure has self-driven ability with simple external circuit,and the conduction characteristic is preferable to a power diode.Static characterization and switching behavior analysis of proposed structure are conducted in this paper.The switching process is illustrated in detail using real model which considers the parasitic inductances and the nonlinearity of junction capacitors.The real time internal voltage and current value during switching transition are deduced with the equivalent circuit.To validate the analysis,two voltage specification rectifiers are built.Finally,double-pulse test results and the practical design example verify the performance advantages of proposed structure.展开更多
文摘对居民用电进行准确的短期负荷预测是电力部门合理制定每日调度计划的重要依据。提出了一种基于BIRCH(balanced iterative reducing and clustering using hierarchies)聚类算法-卷积神经网络(convolutional neural network, CNN)-门控循环单元(gated recurrent unit, GRU)的短期电力负荷预测方法。根据智能电表采集的历史负荷数据,该方法首先采用BIRCH聚类算法分析不同用户的用电习惯,将用户聚类为多个用户群;然后构建由负荷数据和时间以及气候信息组成的多特征时间序列数据集,并采用训练集进行CNN-GRU预测模型构建。训练集首先输入到基于一维卷积层设计的CNN网络,以提取不同特征变量之间的非线性关系;之后将数据输入GRU网络,以提取数据在时间维度上的时序特性,最后由全连接层输出短期负荷预测结果。以爱尔兰能源管理委员会提供的公开数据集作为实际算例,以ANN网络、CNN网络及CNN-GRU网络为对比模型,实验结果表明,所提出方法的平均绝对百分比误差达到了2.932 1%,有较高的预测精度和较快的模型训练速度。
基金supported in part by the National Natural Science Foundation of China (No.51777093)
文摘This paper presents a cascode configuration synchronous rectifier device based on silicon MOSFET and Schottky diode,which can replace traditional power diode directly.This structure has self-driven ability with simple external circuit,and the conduction characteristic is preferable to a power diode.Static characterization and switching behavior analysis of proposed structure are conducted in this paper.The switching process is illustrated in detail using real model which considers the parasitic inductances and the nonlinearity of junction capacitors.The real time internal voltage and current value during switching transition are deduced with the equivalent circuit.To validate the analysis,two voltage specification rectifiers are built.Finally,double-pulse test results and the practical design example verify the performance advantages of proposed structure.
