Fiaz Ahmad

A robust cascaded controller for DC-DC Boost and Cuk converters

Purpose This paper aims to propose a robust cascaded controller based on proportional-integral (PI) and continuous sliding mode control. Design/methodology/approach Cascaded control structure is an attractive control scheme for DC-DC power converters. It has a two-loop structure where the outer loop contains PI controller and the inner loop uses sliding mode control (SMC). This structure thus combines the merits of both the control schemes. However, there are some issues that have prohibited its adoption in industry, the discontinuous nature of SMC which leads to variable switching frequency operation and is hard to realize practically. This paper attempts to overcome this issue by changing the discontinuous functionality of SMC to continuous by utilizing the concept of equivalent control. Findings The robustness of the controller designed is verified by considering various cases, namely, ideal case with no uncertainties, sudden variation of input supply voltage, load resistance, reference voltage, circuit-parameters and for noise disturbance. The controller effectiveness is validated by simulating the DC-DC boost and Cuk converters in SimPowerSystems toolbox of MATLAB/Simulink. It is shown that the performance of the proposed controller is satisfactory, and both reference output voltage and inductor current are tracked with little or no sensitivity to disturbances. Originality/value The results for various scenarios are interesting and show that the controller works quite satisfactorily for all the simulated uncertainties.

Disturbance-observer based control of voltage-source-converter under unbalanced voltage conditions

Purpose This paper aims to propose a novel grid current control strategy for grid-connected voltage source converters (VSCs) under unbalanced grid voltage conditions. Design/methodology/approach A grid voltage dynamic model is represented in symmetrical positive and negative sequence reference frames. A proportional controller structure with a first-order low-pass filter disturbance observer (DOB) is designed for power control in unbalanced voltage conditions. This controller is capable of meeting the positive sequence power requirements, and it also eliminates negative sequence power components which cause double-frequency oscillations on power. The symmetrical components are calculated by using the second-order generalized integrator-based observer, which accurately estimates the symmetrical components. Findings Proportional current controllers are sufficient in this study in a wide range of operating conditions, as DOB accurately estimates and feed-forwards nonlinear terms which may be deteriorated by physical and operating conditions. This is the first reported scheme which estimates the VSC disturbances in terms of symmetrical component decomposition and the DOB concept. Originality/value The proposed method does not require any grid parameter to be known, as it estimates nonlinear terms with a first-order low-pass filter DOB. The proposed control system is implemented on a dSPACE ds1103 digital controller by using a three-phase, three-wire VSC.

Successive-over-relaxation based recursive Bayesian approach for power system configuration identification

Purpose The purpose of this paper is to propose successive-over-relaxation (SOR) based recursive Bayesian approach (RBA) for the configuration identification of a Power System. Moreover, to present a comparison between the proposed method and existing RBA approaches regarding convergence speed and robustness. Design/methodology/approach Swift power network configuration identification is important for adopting the smart grid features like power system automation. In this work, a new SOR-based numerical approach is adopted to increase the convergence speed of the existing RBA algorithm and at the same time maintaining robustness against noise. Existing RBA and SOR-RBA are tested on IEEE 6 bus, IEEE 14 bus networks and 48 bus Danish Medium Voltage distribution network in the MATLAB R2014b environment and a comparative analysis is presented. Findings The comparison of existing RBA and proposed SOR-RBA is performed, which reveals that the latter has good convergence speed compared to the former RBA algorithms. Moreover, it is robust against bad data and noise. Originality value Existing RBA techniques have slow convergence and are also prone to measurement noise. Their convergence speed is effected by noisy measurements. In this paper, an attempt has been made to enhance convergence speed of the new identification algorithm while keeping its numerical stability and robustness during noisy measurement conditions. This work is novel and has drastic improvement in the convergence speed and robustness of the former RBA algorithms.

Design of a robust cascaded controller for Cuk converter

In this paper, design of a robust cascade controller for a Cuk converter is investigated. The controller contains two loop cascaded structure. The external voltage loop, which is the slow loop, contains the continuous proportionalintegral( PI) voltage controller whereas the internal current loop, which is the fast loop, contains the continuous sliding mode controller(CSMC). The controller effectiveness is validated by simulating the Cuk converter in SimPowerSystems ® toolbox of MATLAB/Simulink ®. The simulation is done for six different cases including ideal case, sudden variation of input supply voltage, load resistance, reference voltage, for noise disturbance and parametric variation. It is shown that the performance of the proposed controller is satisfactory and the ultimate goal of tracking the reference by the converter output voltage and the inductor current is achieved with little or no sensitivity to the uncertainties simulated.

Performance comparison of static and dynamic state estimators for electric distribution systems

Abstract State estimation is an integral component of energy management systems used for the monitoring and control of operation of transmission networks worldwide. However, it has so far not yet been widely adopted in the distribution networks due to their passive nature with no active generation. But this scenario is challenged by the integration of distributed generators (DGs) at this level. Various static and dynamic state estimators have been researched for the transmission systems. These cannot be directly applied to the distribution systems due to their different philosophy of operation. Thus the performance of these estimators need to be re-evaluated for the distribution systems. This paper presents a computational and statistical performance of famous static estimator such as weighted least squares (WLS) and dynamic state estimators such as extended Kalman filter (EKF) and unscented Kalman filter (UKF) for electric distribution system. Additionally, an improved-UKF (IUKF) is also proposed which enhances the robustness and numerical stability of the existing UKF algorithm. All the estimators are tested for load variation and bad data for IEEE-30, 33 and 69 bus radial distribution networks using statistical performance metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Percent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance index (J). Based on these metrics, IUKF outperforms other estimators under the simulated noisy measurement conditions.

An improved unscented Kalman filter based dynamic state estimation algorithm for electric distribution systems

Purpose To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman filter (UKF) and newly developed algorithm, termed Inproved unscented Kalman Filter (IUKF) for IEEE-30, 33 and 69-bus radial distribution networks for load variations and bad data for two measurement noise scenarios, i.e. 30% and 50% are shown. Design/methodology/approach State estimation (SE) plays an instrumental role in realizing smart grid features like distribution automation (DA), enhanced distribution generation (DG) penetration and demand response (DR). Implementation of DA requires robust, accurate and computationally efficient dynamic SE techniques that can capture the fast changing dynamics of distribution systems more effectively. In this paper, the UKF is improved by changing the way the state covariance matrix is calculated, to enhance its robustness and accuracy under noisy measurement conditions. UKF and propo...