有源电力滤波器谐波电流检测与跟踪控制研究
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摘要
随着世界经济的快速发展,大量非线性负荷的应用使得电力系统谐波污染现象日益严重。同时,随着新能源并网发电、分布式发电技术的运用和智能电网的建设,给传统电力系统提出了新的挑战,产生了谐波和其它新的电能质量问题,促使电能质量治理产品需求快速增长。
抑制电力系统谐波是电能质量治理的一项重要措施,采用主动补偿方式的有源电力滤波器(Active Power Filter, APF)能对频率和幅值都变化的谐波进行实时跟踪补偿,补偿特性不受电网阻抗的影响,且装置无需能量储存器件,因而受到广泛重视,研究成果不断涌现。为提高APF产品性能和对工程实际情况的适应性,相关研究仍在不断深入进行。本文针对以上研究背景,以应用广泛的三相三线并联型有源电力滤波器(Shunt Active Power Filter, SAPF)为对象,围绕提高SAPF的谐波电流检测性能、增强补偿电流跟踪技术的鲁棒性和提高谐波抑制效果等方面展开了一些有益的研究。
为提高基于瞬时无功功率理论的谐波电流检测法在检测精度和收敛速度方面的性能,提出了一种新颖的最小均方(Least mean square, LMS)与最小四阶矩(Least mean fourth, LMF)相结合的LMS/LMF自适应滤波器算法。根据误差信号的变化自适应地调整LMS和LMF算法在权值更新中的占比,当滤波器原始输入信号突变时,系统主要采用LMF检测算法,而当滤波器原始输入信号稳定时,系统主要采用LMS检测算法,以同时发挥LMF算法收敛速度快和LMS算法稳态精度高的优点。推导了该算法的收敛条件、时间常数和失调公式。仿真和试验结果表明,该算法使低通滤波器动态过程收敛更快,稳态误差更小,提高了瞬时无功功率理论谐波检测法的性能。
为了提高电压空间矢量双滞环电流控制方法在SAPF的补偿电流跟踪性能,提出了一种新颖的4段滞环比较器。直接在复平面上实施控制,4段滞环比较器输入误差电流矢量,输出4种状态值,可以确定误差电流矢量的空间分布；通过求取指令电流微分的近似值,快速确定参考电压矢量所在区域。根据两个4段滞环比较器的输出状态值与参考电压矢量的空间分布选择最佳的输出开关矢量,使补偿电流误差控制在滞环宽度以内。该控制方法提高了直流电压利用率,降低了开关次数,系统动态响应快。
将神经网络引入SAPF的补偿电流跟踪控制中,提出了一种SAPF的神经网络逆系统线性化解耦控制方法,以提高SAPF的补偿电流跟踪性能。首先推出SAPF的数学模型,证明其可逆性,接着设计SAPF的神经网络逆系统,和原系统一起构建伪线性系统,并采用比例积分控制器控制伪线性系统。将BP、RBF神经网络应用于SAPF的逆系统线性化解耦控制方法,实现了SAPF补偿电流跟踪控制的线性化和解耦,其控制效果优于反馈线性化控制方法。同时,在系统参数变化较大时,BP神经网络构成的逆系统控制方法具有很强的鲁棒性。
提出了一种SAPF滑模变结构统一控制方法,将SAPF中补偿电流控制和直流侧电压控制统一实现,同时利用滑模变结构控制来提高鲁棒性。首先,根据SAPF在dq坐标系下的数学模型,确定状态变量id、iq和Udc,然后以这三个状态变量误差的线性组合定义了补偿电流和直流侧电压的统一控制滑模面,设计了控制律,并采用饱和函数代替符号函数,以削弱抖振。接着推导出滑模稳定条件和等效控制的存在性。通过滑模面的合理设计可以实现SAPF补偿电流和直流侧电压的统一控制,选择滑模函数中的K值要兼顾滑模控制的稳定性和动态品质,当负载和元件参数在一定范围内发生变化时,SAPF能正常工作,具有较好的鲁棒性。
With the rapid development of world economy, harmonic pollution problems in the power system has been increasing severe by the use of a large scale of nonlinear loads. Meanwhile, utilization of new technologies such as smart grid, distribution generation and renewable energy integration causes various types of power quality issues. These increasing complexities of power quality problems pose new challenges to solutions of harmonic suppression and other power quality issues, and require development of new power quality management products that can-provide considerable and equivalent functions.
Harmonic suppression of power system is one of important measures for power quality management. Active power filter (APF) which adopts active compensation way can compensate harmonics components in real-time when frequency and amplitude vary with time. It doesn't need energy storage devices and its compensation performance would not be affected by power grid impedance. Therefore the APF technology has received much attention recently and numerous related research results have been reported. Further research on the performance improvement of APF and its adaptability to the engineering actual situation is required. A three-phase and three-wire shunt active power filter (SAPF) prototype is studied and analyzed in the dissertation to improve the capabilities of harmonic current detection, robustness of compensatory current tracking and performance of harmonic suppression.
In order to improve the detection accuracy and convergence speed of harmonic current detection method based on instantaneous reactive power theory, a novel algorithm of LMS/LMF adaptive filter is proposed, which combines a LMS algorithm with a LMF algorithm. The new algorithm can adjust self-adaptively the proportions of LMS and LMF in weight update. When the input sign of the adaptive filter change suddenly, the algorithm is mainly adopted by LMF algorithm. As the input sign of the adaptive filter is in steady state, the algorithm is mainly adopted by LMS algorithm. So, the LMS/LMF algorithm integrates the merits of both fast convergence speed of LMF algorithm and high stability precision of LMS algorithm. The convergence condition, time constant and misadjustment formula of the proposed algorithm are derived. The simulation and experiment results show that the proposed method can make the dynamic response of the low pass filter faster and its stability accuracy better, thus improve dynamic and steady performances of the harmonic current detection method based on instantaneous reactive power theory.
To improve compensatory current tracking performance of SAPF based on double hysteresis current control strategy of voltage space vector, a novel4-level α-β hysteresis comparator is proposed. The control strategy is directly implemented on α-β coordinates. The4-level α-β hysteresis comparators are input by current error vectors and output4state values to determine the location region of current error vectors. The location region of the reference voltage vector can be determined rapidly by the approximate value of the differential reference currents. The optimum output switching vector at each instant is selected according to state values output of two4-level α-β hysteresis comparators and reference voltage vector. The compensatory current error is limited within the hysteresis width. The proposed control method can efficiently increase the utilization of DC voltage, decrease IGBTs switching number and achieve fast response in SAPF.
To improve compensatory current tracking performance of SAPF, a linearized and decoupling control method is proposed based on neural network inverse (NNI). Firstly, the mathematical model of SAPF is derived and its reversibility is proved. Then the NNI of SAPF is designed, which combines with original system of SAPF to construct a pseudolinear system, the pseudolinear system can be simply controlled by a proportional plus integral controller. The Back Propagation (BP) neural network and Radial Basis Function (RBF) neural network are adopted in the proposed control method, which makes compensatory current tracking control linearized and decoupled, and it outperforms feedback linearization method. Meanwhile, it is proved that the inverse system control method which is adopted by BP neural network exhibits strong robustness when the system parameters change dramatically.
In order to combine the control of the compensatory currents and the DC voltage of SAPF, and make SAPF more robust, a unified control strategy based on sliding mode variable structure control is proposed. At first, according to the mathematical model of SAPF in dq reference frame, the state variables id, iq, Udc is determined, and the linear combinations of the three state variables errors are used to define the sliding surface function of the unified control strategy. The control law is designed, and saturation function substitutes for sign function to eliminate chattering. Then the stabilization conditions of sliding mode and existence of equivalent control are derived. It is proved that the unified control strategy of SAPF can be achieved through suitable sliding surface function, and the K values selection of sliding surface function has to find a compromise between the stabilization and dynamic performance of sliding mode variable structure control. SAPF can work properly and be more robust when the load and device parameters change within a certain range.
抑制电力系统谐波是电能质量治理的一项重要措施,采用主动补偿方式的有源电力滤波器(Active Power Filter, APF)能对频率和幅值都变化的谐波进行实时跟踪补偿,补偿特性不受电网阻抗的影响,且装置无需能量储存器件,因而受到广泛重视,研究成果不断涌现。为提高APF产品性能和对工程实际情况的适应性,相关研究仍在不断深入进行。本文针对以上研究背景,以应用广泛的三相三线并联型有源电力滤波器(Shunt Active Power Filter, SAPF)为对象,围绕提高SAPF的谐波电流检测性能、增强补偿电流跟踪技术的鲁棒性和提高谐波抑制效果等方面展开了一些有益的研究。
为提高基于瞬时无功功率理论的谐波电流检测法在检测精度和收敛速度方面的性能,提出了一种新颖的最小均方(Least mean square, LMS)与最小四阶矩(Least mean fourth, LMF)相结合的LMS/LMF自适应滤波器算法。根据误差信号的变化自适应地调整LMS和LMF算法在权值更新中的占比,当滤波器原始输入信号突变时,系统主要采用LMF检测算法,而当滤波器原始输入信号稳定时,系统主要采用LMS检测算法,以同时发挥LMF算法收敛速度快和LMS算法稳态精度高的优点。推导了该算法的收敛条件、时间常数和失调公式。仿真和试验结果表明,该算法使低通滤波器动态过程收敛更快,稳态误差更小,提高了瞬时无功功率理论谐波检测法的性能。
为了提高电压空间矢量双滞环电流控制方法在SAPF的补偿电流跟踪性能,提出了一种新颖的4段滞环比较器。直接在复平面上实施控制,4段滞环比较器输入误差电流矢量,输出4种状态值,可以确定误差电流矢量的空间分布；通过求取指令电流微分的近似值,快速确定参考电压矢量所在区域。根据两个4段滞环比较器的输出状态值与参考电压矢量的空间分布选择最佳的输出开关矢量,使补偿电流误差控制在滞环宽度以内。该控制方法提高了直流电压利用率,降低了开关次数,系统动态响应快。
将神经网络引入SAPF的补偿电流跟踪控制中,提出了一种SAPF的神经网络逆系统线性化解耦控制方法,以提高SAPF的补偿电流跟踪性能。首先推出SAPF的数学模型,证明其可逆性,接着设计SAPF的神经网络逆系统,和原系统一起构建伪线性系统,并采用比例积分控制器控制伪线性系统。将BP、RBF神经网络应用于SAPF的逆系统线性化解耦控制方法,实现了SAPF补偿电流跟踪控制的线性化和解耦,其控制效果优于反馈线性化控制方法。同时,在系统参数变化较大时,BP神经网络构成的逆系统控制方法具有很强的鲁棒性。
提出了一种SAPF滑模变结构统一控制方法,将SAPF中补偿电流控制和直流侧电压控制统一实现,同时利用滑模变结构控制来提高鲁棒性。首先,根据SAPF在dq坐标系下的数学模型,确定状态变量id、iq和Udc,然后以这三个状态变量误差的线性组合定义了补偿电流和直流侧电压的统一控制滑模面,设计了控制律,并采用饱和函数代替符号函数,以削弱抖振。接着推导出滑模稳定条件和等效控制的存在性。通过滑模面的合理设计可以实现SAPF补偿电流和直流侧电压的统一控制,选择滑模函数中的K值要兼顾滑模控制的稳定性和动态品质,当负载和元件参数在一定范围内发生变化时,SAPF能正常工作,具有较好的鲁棒性。
With the rapid development of world economy, harmonic pollution problems in the power system has been increasing severe by the use of a large scale of nonlinear loads. Meanwhile, utilization of new technologies such as smart grid, distribution generation and renewable energy integration causes various types of power quality issues. These increasing complexities of power quality problems pose new challenges to solutions of harmonic suppression and other power quality issues, and require development of new power quality management products that can-provide considerable and equivalent functions.
Harmonic suppression of power system is one of important measures for power quality management. Active power filter (APF) which adopts active compensation way can compensate harmonics components in real-time when frequency and amplitude vary with time. It doesn't need energy storage devices and its compensation performance would not be affected by power grid impedance. Therefore the APF technology has received much attention recently and numerous related research results have been reported. Further research on the performance improvement of APF and its adaptability to the engineering actual situation is required. A three-phase and three-wire shunt active power filter (SAPF) prototype is studied and analyzed in the dissertation to improve the capabilities of harmonic current detection, robustness of compensatory current tracking and performance of harmonic suppression.
In order to improve the detection accuracy and convergence speed of harmonic current detection method based on instantaneous reactive power theory, a novel algorithm of LMS/LMF adaptive filter is proposed, which combines a LMS algorithm with a LMF algorithm. The new algorithm can adjust self-adaptively the proportions of LMS and LMF in weight update. When the input sign of the adaptive filter change suddenly, the algorithm is mainly adopted by LMF algorithm. As the input sign of the adaptive filter is in steady state, the algorithm is mainly adopted by LMS algorithm. So, the LMS/LMF algorithm integrates the merits of both fast convergence speed of LMF algorithm and high stability precision of LMS algorithm. The convergence condition, time constant and misadjustment formula of the proposed algorithm are derived. The simulation and experiment results show that the proposed method can make the dynamic response of the low pass filter faster and its stability accuracy better, thus improve dynamic and steady performances of the harmonic current detection method based on instantaneous reactive power theory.
To improve compensatory current tracking performance of SAPF based on double hysteresis current control strategy of voltage space vector, a novel4-level α-β hysteresis comparator is proposed. The control strategy is directly implemented on α-β coordinates. The4-level α-β hysteresis comparators are input by current error vectors and output4state values to determine the location region of current error vectors. The location region of the reference voltage vector can be determined rapidly by the approximate value of the differential reference currents. The optimum output switching vector at each instant is selected according to state values output of two4-level α-β hysteresis comparators and reference voltage vector. The compensatory current error is limited within the hysteresis width. The proposed control method can efficiently increase the utilization of DC voltage, decrease IGBTs switching number and achieve fast response in SAPF.
To improve compensatory current tracking performance of SAPF, a linearized and decoupling control method is proposed based on neural network inverse (NNI). Firstly, the mathematical model of SAPF is derived and its reversibility is proved. Then the NNI of SAPF is designed, which combines with original system of SAPF to construct a pseudolinear system, the pseudolinear system can be simply controlled by a proportional plus integral controller. The Back Propagation (BP) neural network and Radial Basis Function (RBF) neural network are adopted in the proposed control method, which makes compensatory current tracking control linearized and decoupled, and it outperforms feedback linearization method. Meanwhile, it is proved that the inverse system control method which is adopted by BP neural network exhibits strong robustness when the system parameters change dramatically.
In order to combine the control of the compensatory currents and the DC voltage of SAPF, and make SAPF more robust, a unified control strategy based on sliding mode variable structure control is proposed. At first, according to the mathematical model of SAPF in dq reference frame, the state variables id, iq, Udc is determined, and the linear combinations of the three state variables errors are used to define the sliding surface function of the unified control strategy. The control law is designed, and saturation function substitutes for sign function to eliminate chattering. Then the stabilization conditions of sliding mode and existence of equivalent control are derived. It is proved that the unified control strategy of SAPF can be achieved through suitable sliding surface function, and the K values selection of sliding surface function has to find a compromise between the stabilization and dynamic performance of sliding mode variable structure control. SAPF can work properly and be more robust when the load and device parameters change within a certain range.
引文
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