This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two...This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two main objectives of the controller design, damping low frequencies oscillations and enhancing power system stability. This method relies on shaping the closed-loop sensitivity functions in the Nyquist plot under the constraints of these functions. These constraints can be linearized by choosing a desired open-loop transfer function. The robust controller is designed to minimize the error between the open-loop of the original plant model and the desired transfer functions. These outcomes can be achieved by using convex optimization methods. Convexity of the problem formulation ensures global optimality. One of the advantages of the proposed approach is that the approach accounts for multi-model uncertainty. In contrast to the methods available in the literature, the proposed approach deals with full-order model (i.e., model reduction is not required) with lower controller order. The issue of time delay of feedback signals has been addressed in this paper for different values of time delay by applying a multi-model optimization technique. The proposed approach is compared to other existing techniques to design a robust controller which is based on H2 under pole placement. Both techniques are applied to the 68-bus system to evaluate and validate the robust controller performance under different load scenarios and different wind generations.展开更多
文摘This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two main objectives of the controller design, damping low frequencies oscillations and enhancing power system stability. This method relies on shaping the closed-loop sensitivity functions in the Nyquist plot under the constraints of these functions. These constraints can be linearized by choosing a desired open-loop transfer function. The robust controller is designed to minimize the error between the open-loop of the original plant model and the desired transfer functions. These outcomes can be achieved by using convex optimization methods. Convexity of the problem formulation ensures global optimality. One of the advantages of the proposed approach is that the approach accounts for multi-model uncertainty. In contrast to the methods available in the literature, the proposed approach deals with full-order model (i.e., model reduction is not required) with lower controller order. The issue of time delay of feedback signals has been addressed in this paper for different values of time delay by applying a multi-model optimization technique. The proposed approach is compared to other existing techniques to design a robust controller which is based on H2 under pole placement. Both techniques are applied to the 68-bus system to evaluate and validate the robust controller performance under different load scenarios and different wind generations.
