This thesis investigates the effects of High Voltage Direct Current (HVDC) lines andmulti-terminal grids on power system small-disturbance stability in the presence ofoperational uncertainties. The main outcome of this research is the comprehensiveprobabilistic assessment of the stability improvements that can be achieved through theuse of supplementary damping control applied to HVDC systems.Power systems are increasingly operated closer to stability boundaries in order toimprove their efficiency and economic value whilst a growing number of conventionalcontrolled power plants are being replaced by stochastic renewable generation sources.The resulting uncertainty in conditions can increase the risk of operational stabilityconcerns and should be thoroughly evaluated. There is also a growing necessity toexplore the potential improvements and challenges created by the introduction of newequipment, such as HVDC systems. In recent years, HVDC systems have become moreeconomically competitive and increasingly flexible, resulting in a proliferation ofprojects. Although primarily installed for power transmission purposes, their flexibilityand controllability can provide further benefits, such as the damping of persistentoscillations in the interconnected networks.This work contributes to a number of areas of power systems research, specificallysurrounding the effects of HVDC systems on the small-disturbance stability oftransmission networks. The application and comprehensive assessment of a Wide AreaMeasurement System (WAMS) based damping controller with various HVDC systemsis completed. The studies performed on a variety of HVDC technology types andconfigurations - as well as differing AC test networks - demonstrate the potential forHVDC-based Power Oscillation Damping (POD). These studies include examinationsof previously unexplored topics such as the effects of available modulation capacity andthe use of voltage source converter multi-terminal HVDC grids for POD. Followingthese investigations, a methodology to probabilistically test the robustness of HVDC based damping controllers is developed. This methodology makes use of classificationtechniques to identify possible mitigation options for power system operators whenperformance is sub-optimal. To reduce the high computational burden associated withthis methodology, the Probabilistic Collocation Method (PCM) is developed in order toefficiently identify the statistical distributions of critical system modes in the presenceof uncertainties. Methods of uncertain parameter reduction based on eigenvaluesensitivity are developed and demonstrated to ensure accurate results when the PCM isused with large test systems. Finally, the concepts and techniques introduced within thethesis are combined to probabilistically design a WAMS-based POD controller morerobust to operational uncertainties. The use of the PCM during the probabilistic designresults in rapid and robust synthesis of HVDC-based POD controllers.