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The paper presents a supplementary VSC-HVDC Power Oscillation Damping (POD) controller based on wide area measurement signals (WAMS). The controller is designed as Multi Input Single Output (MISO) using a Modal Linear Quadratic Gaussian (MLQG) methodology in order to target critical inter-area electromechanical modes. The approach has been tested on a large (16 machine, 68 bus) test network incorporating parallel HVDC/AC transmission and has shown improved damping compared to a traditional Power System Stabilizer (PSS) based controller structure utilizing local signals. The design process has incorporated the effects of wide area signal transmission delays. Variation in these signal delays and the complete loss of signals has been also investigated to establish the robustness of the WAMS based controller and its sensitivity to loss of signals. Extension of the controller to incorporate reactive power modulation has been investigated, as has variation in available active power modulation capacity. The proposed controller performance has been assessed through small and large disturbance analysis. [ABSTRACT FROM PUBLISHER]

The paper presents a robust probabilistic methodology for assessing the performance of power system controllers. In this study, the proposed probabilistic technique is applied to a novel power oscillation damping (POD) controller structure implemented through active power modulation of multiple voltage source converter based high voltage direct current (VSC-HVDC) links within a large heavily meshed network exhibiting multiple inter-area modes. The modal linear quadratic Gaussian (MLQG) controller, as an example of advanced POD, is implemented in both a centralized and a decentralized form for comparison. Following the development and demonstration of the effectiveness of the controller designs, the robust probabilistic performance evaluation is carried out incorporating outage contingencies for generators, lines, and VSC-HVDC lines. The results obtained demonstrate that both controller structures are largely robust to wide ranging operating conditions. For those conditions where controller performance is unsatisfactory, various mitigation techniques are discussed, including the use of classification tools to guide operational limits. A contingency specific controller design is shown to significantly improve performance when robustness cannot be achieved. [ABSTRACT FROM PUBLISHER]