The deterministic method has been the primary means of performing power system security assessment for a long time. This is partly because it is easy to understand and implement, and partly because it is usually quite conservative. In the past where monopoly was prevalent, the conservativeness resulted in a high degree of reliability in most power systems, while the investment and operational costs rose without the pressure of competition. However, now because of the deregulation and practical difficulties to obtain authorizations from regulatory bodies to build power plants and transmission lines, people are more and more willing to operate power systems with lower security margins. This demands more accurate and comprehensive risk assessment tools. On the other hand, because of the fast development of the computer and of computational mathematics, probabilistic risk assessment becomes more and more practical. This kind of risk assessment can deal with both operational and planning problems. Although planning and operations are normally regarded as different categories, this paper is aimed at building a framework for power system risk assessment in the planning stage such that it is developed naturally from the operational stage. The framework is modular so that it is relatively easy to implement, and each module can be improved individually without influencing other parts of the framework. Compared with Monte Carlo simulation where possible system trajectories are sampled, our framework employs the expected trajectory, while accounting for the load uncertainty. One of the most prominent advantages of our proposed technique is that it can provide us decomposable and assignable risk among system components. The IEEE RTS' 96 is used as the test power system for our proposed framework. Various calculation results are listed and analyzed. Some facility planning decisions are suggested based on our calculations. Our proposed framework is shown to be valid and efficient by these calculations.
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