A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data an...A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.展开更多
作为电力系统中的基本量测设备,电子式电压互感器(electronic voltage transformers,EVTs)的测量精度对系统的监控、控制与安全运行至关重要。为此,提出了一种基于混合深度模型和自适应窗宽概率密度估计的互感器测量误差区间预测模型。...作为电力系统中的基本量测设备,电子式电压互感器(electronic voltage transformers,EVTs)的测量精度对系统的监控、控制与安全运行至关重要。为此,提出了一种基于混合深度模型和自适应窗宽概率密度估计的互感器测量误差区间预测模型。首先,通过改进的集合经验模态分解对历史比差特征进行数据前处理。其次,提出了基于数据驱动的双向时序卷积网络、双向门控循环单元和多头注意力机制混合深度学习模型,对分解后的不同模态分量进行预测。此外,引入自适应选择最优窗宽的核密度概率估计方法,拟合预测结果构建不同置信度下的预测区间,并比较不同核函数对于预测区间的影响。通过算例分析,验证了所提模型在提高确定性预测和概率区间预测准确度方面的有效性。展开更多
随着国家“双碳”目标的持续推进,风力发电装机占比持续增高,强随机波动的大规模风电出力给电力系统的“保消纳、保供电”带来严峻挑战,高精度的风电功率预测是解决上述挑战的重要基础手段,风电场和电网调度中心均将持续提升风电功率预...随着国家“双碳”目标的持续推进,风力发电装机占比持续增高,强随机波动的大规模风电出力给电力系统的“保消纳、保供电”带来严峻挑战,高精度的风电功率预测是解决上述挑战的重要基础手段,风电场和电网调度中心均将持续提升风电功率预测精度视为长期重点工作。为此,提出一种基于短期风电功率预测误差分布特性统计与波动特性分析的风电功率预测修正方法。首先,考虑误差时序-条件特点对误差进行基于改进非参数核密度估计法(kernel density estimation,KDE)的误差概率密度分布特性分析,得出不同置信水平下的风电功率预测置信区间,以实现预测误差的分层划分。其次,采用变分模态分解算法(variational mode decomposition,VMD)将风电功率预测误差序列分解为趋势分量和随机分量,针对2类误差分量特点展开分类预测,并对最终所得误差结果进行波动性分析。最后,结合误差分层划分结果与误差波动特性分析进行综合判断,提出针对各类情况的误差补偿方案,从而获得修正后的短期风电功率预测值。实际算例表明,所提误差补偿方法可将风电功率月均方根误差较补偿前减少2.6个百分点,平均绝对误差较补偿前减少2.4个百分点,该方法能够有效减小风电功率预测误差,提升短期风电功率预测精度。展开更多
In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way A...In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.展开更多
Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and...Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.展开更多
针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于...针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于FSO链路和RF链路的信道模型,采用有限状态马尔科夫链(Finite State Markov Chain,FSMC)分别对单双站FSO/RF混合链路的切换选择进行建模,推导得出不同参数和天气情况下系统稳态的中断概率表达式.数值计算结果表明,当中断概率达到10^(-6),雨雾天气链路距离为1~7 km时,双站FSO/RF混合链路相比单站可获得4~25 dB的增益.展开更多
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education(20114307120032)the National Natural Science Foundation of China(71201167)
文摘A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.
文摘作为电力系统中的基本量测设备,电子式电压互感器(electronic voltage transformers,EVTs)的测量精度对系统的监控、控制与安全运行至关重要。为此,提出了一种基于混合深度模型和自适应窗宽概率密度估计的互感器测量误差区间预测模型。首先,通过改进的集合经验模态分解对历史比差特征进行数据前处理。其次,提出了基于数据驱动的双向时序卷积网络、双向门控循环单元和多头注意力机制混合深度学习模型,对分解后的不同模态分量进行预测。此外,引入自适应选择最优窗宽的核密度概率估计方法,拟合预测结果构建不同置信度下的预测区间,并比较不同核函数对于预测区间的影响。通过算例分析,验证了所提模型在提高确定性预测和概率区间预测准确度方面的有效性。
文摘随着国家“双碳”目标的持续推进,风力发电装机占比持续增高,强随机波动的大规模风电出力给电力系统的“保消纳、保供电”带来严峻挑战,高精度的风电功率预测是解决上述挑战的重要基础手段,风电场和电网调度中心均将持续提升风电功率预测精度视为长期重点工作。为此,提出一种基于短期风电功率预测误差分布特性统计与波动特性分析的风电功率预测修正方法。首先,考虑误差时序-条件特点对误差进行基于改进非参数核密度估计法(kernel density estimation,KDE)的误差概率密度分布特性分析,得出不同置信水平下的风电功率预测置信区间,以实现预测误差的分层划分。其次,采用变分模态分解算法(variational mode decomposition,VMD)将风电功率预测误差序列分解为趋势分量和随机分量,针对2类误差分量特点展开分类预测,并对最终所得误差结果进行波动性分析。最后,结合误差分层划分结果与误差波动特性分析进行综合判断,提出针对各类情况的误差补偿方案,从而获得修正后的短期风电功率预测值。实际算例表明,所提误差补偿方法可将风电功率月均方根误差较补偿前减少2.6个百分点,平均绝对误差较补偿前减少2.4个百分点,该方法能够有效减小风电功率预测误差,提升短期风电功率预测精度。
基金Project(IRT0852) supported by the Program for Changjiang Scholars and Innovative Research Team in University,ChinaProject(2012CB316100) supported by the National Basic Research Program of China+2 种基金Projects(61101144,61101145) supported by the National Natural Science Foundation of ChinaProject(B08038) supported by the "111" Project,ChinaProject(K50510010017) supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.
基金Project(61201381)supported by the National Nature Science Foundation of ChinaProject(YP12JJ202057)supported by the Future Development Foundation of Zhengzhou Information Science and Technology College,China
文摘Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.
文摘针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于FSO链路和RF链路的信道模型,采用有限状态马尔科夫链(Finite State Markov Chain,FSMC)分别对单双站FSO/RF混合链路的切换选择进行建模,推导得出不同参数和天气情况下系统稳态的中断概率表达式.数值计算结果表明,当中断概率达到10^(-6),雨雾天气链路距离为1~7 km时,双站FSO/RF混合链路相比单站可获得4~25 dB的增益.
