Risk management in power systems has become an essential component of ensuring the reliability, stability, and economic efficiency of modern electrical grids. As power systems become increasingly complex and vulnerable to both natural and man-made disruptions, accurate and effective risk measurement techniques are crucial for mitigating potential threats and minimizing system failures. This paper provides a comprehensive review of risk measurement methodologies used in the context of power system risk management. It explores various quantitative techniques, including probabilistic risk assessment, fault tree analysis, and Monte Carlo simulations, and examines their application in evaluating system vulnerabilities, identifying potential hazards, and optimizing risk mitigation strategies. Furthermore, we discuss the integration of these methods with modern power system planning, operation, and control strategies, particularly in light of evolving renewable energy sources and distributed generation technologies. By focusing on both theoretical and practical aspects, this paper offers valuable insights for enhancing the robustness of power systems in the face of growing risks and uncertainties.