Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matri...Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.展开更多
This paper introduces a robust sparse recovery model for compressing bad data and state estimation(SE),based on a revised multi-stage convex relaxation(R-Capped-L1)model.To improve the calculation efficiency,a fast de...This paper introduces a robust sparse recovery model for compressing bad data and state estimation(SE),based on a revised multi-stage convex relaxation(R-Capped-L1)model.To improve the calculation efficiency,a fast decoupled solution is adopted.The proposed method can be used for three-phase unbalanced distribution networks with both phasor measurement unit and remote terminal unit measurements.The robustness and the computational efficiency of the R-Capped-Ll model with fast decoupled solution are compared with some popular SE methods by numerical tests on several three-phase distribution networks.展开更多
针对传统静态状态估计方法的缺点,提出了一种改进的电力系统状态估计方法,即将部分节点相量测量单元(phasor measurement unit,PMU)量测数据与监控数据采集(supervisory control and data acquisition,SCADA)量测数据融合进行电力系统...针对传统静态状态估计方法的缺点,提出了一种改进的电力系统状态估计方法,即将部分节点相量测量单元(phasor measurement unit,PMU)量测数据与监控数据采集(supervisory control and data acquisition,SCADA)量测数据融合进行电力系统的全网状态估计。该方法简化了系统的雅可比矩阵,缩短了计算时间。文章研究了PMU和SCADA系统融合改进后的快速分解法,针对SCADA量测数据的缺点,通过历史数据库对潮流数据进行预测,并依据PMU量测量对系统进行分析,继而进行系统全网状态的动态监测。通过算例证明,与传统的估计方法相比,该方法改善了状态估计的精确性,减少了迭代次数,细致地描绘了电网状态的变化过程,为调度中心下一步的决策提供了依据。展开更多
状态估计作为能量管理系统(EMS)和实时电力市场的基础和核心,正在变得日益重要。该文从信息科学的新视角,对电力系统状态估计的数学基础进行了研究。根据最小信息损失(MIL)决策原理,提出了能够适用于各种概率分布的通用的 MIL 状态估计...状态估计作为能量管理系统(EMS)和实时电力市场的基础和核心,正在变得日益重要。该文从信息科学的新视角,对电力系统状态估计的数学基础进行了研究。根据最小信息损失(MIL)决策原理,提出了能够适用于各种概率分布的通用的 MIL 状态估计新原理。并在理论上证明了加权最加权最小二乘(WLAV)估计法都是MIL 状态估计的特例,将传统状态估计方法在信息学的意义上统一起来,赋予了传统状态估计方法全新的信息学内涵。在 MIL 意义上,针对次输电系统和配电系统状态估计中普遍采用的电流幅值量测,得到了大电流是 WLS 估计法的近似条件。用算例比较了 MIL 和 WLS 状态估计的估计结果,进一步验证了 WLS 法在非正态分布时的近似条件。展开更多
谐波状态估计技术是在GPS技术(Global Position System)和PMU技术(Phasor Measurement Unit)基础发展起来的一项新型技术,它通过状态估计手段实现对监测的电网谐波进行分析。系统地介绍了电力系统谐波状态估计技术的概念、谐波测量系统...谐波状态估计技术是在GPS技术(Global Position System)和PMU技术(Phasor Measurement Unit)基础发展起来的一项新型技术,它通过状态估计手段实现对监测的电网谐波进行分析。系统地介绍了电力系统谐波状态估计技术的概念、谐波测量系统、估计算法和工程应用情况。在介绍状态估计算法时,通过将其分为静态状态估计算法和动态状态估计算法,分别对其进行评述;最后对谐波状态估计技术以后的研究进行了展望。展开更多
基金This work is supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0467)Jiangsu Province,China.During the revision of this paper,the author is supported by China Scholarship Council(No.201906840021)China to continue some research related to data processing.
文摘Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.
基金supported in part by the National Key Research and Development Plan of China(No.2018YFB0904200)in part by the National Natural Science Foundation of China(No.51725703).
文摘This paper introduces a robust sparse recovery model for compressing bad data and state estimation(SE),based on a revised multi-stage convex relaxation(R-Capped-L1)model.To improve the calculation efficiency,a fast decoupled solution is adopted.The proposed method can be used for three-phase unbalanced distribution networks with both phasor measurement unit and remote terminal unit measurements.The robustness and the computational efficiency of the R-Capped-Ll model with fast decoupled solution are compared with some popular SE methods by numerical tests on several three-phase distribution networks.
文摘针对传统静态状态估计方法的缺点,提出了一种改进的电力系统状态估计方法,即将部分节点相量测量单元(phasor measurement unit,PMU)量测数据与监控数据采集(supervisory control and data acquisition,SCADA)量测数据融合进行电力系统的全网状态估计。该方法简化了系统的雅可比矩阵,缩短了计算时间。文章研究了PMU和SCADA系统融合改进后的快速分解法,针对SCADA量测数据的缺点,通过历史数据库对潮流数据进行预测,并依据PMU量测量对系统进行分析,继而进行系统全网状态的动态监测。通过算例证明,与传统的估计方法相比,该方法改善了状态估计的精确性,减少了迭代次数,细致地描绘了电网状态的变化过程,为调度中心下一步的决策提供了依据。
文摘状态估计作为能量管理系统(EMS)和实时电力市场的基础和核心,正在变得日益重要。该文从信息科学的新视角,对电力系统状态估计的数学基础进行了研究。根据最小信息损失(MIL)决策原理,提出了能够适用于各种概率分布的通用的 MIL 状态估计新原理。并在理论上证明了加权最加权最小二乘(WLAV)估计法都是MIL 状态估计的特例,将传统状态估计方法在信息学的意义上统一起来,赋予了传统状态估计方法全新的信息学内涵。在 MIL 意义上,针对次输电系统和配电系统状态估计中普遍采用的电流幅值量测,得到了大电流是 WLS 估计法的近似条件。用算例比较了 MIL 和 WLS 状态估计的估计结果,进一步验证了 WLS 法在非正态分布时的近似条件。
文摘谐波状态估计技术是在GPS技术(Global Position System)和PMU技术(Phasor Measurement Unit)基础发展起来的一项新型技术,它通过状态估计手段实现对监测的电网谐波进行分析。系统地介绍了电力系统谐波状态估计技术的概念、谐波测量系统、估计算法和工程应用情况。在介绍状态估计算法时,通过将其分为静态状态估计算法和动态状态估计算法,分别对其进行评述;最后对谐波状态估计技术以后的研究进行了展望。
