Methodology for assessing the impact of unplanned outage of thermal power units on power supply security

With the increasing complexity of the grid structure, there is a trend towards diversification of the role played by thermal power units in the grid. In this context, the reliability assessment of the power generation system needs to consider the differentiated electrical location and tidal characteristics of thermal power units in the system to identify the weak links in the power supply more accurately. Therefore, a new methodology for assessing the impact of unplanned outage on power supply security is proposed. The method uses a Bayesian network to calculate the probability of an unplanned outage of a unit, which entirely considers multiple uncertainties, such as the unit’s operating status and environmental factors. A Monte Carlo simulation model is constructed based on the obtained probability parameters to calculate the reliability indicators of the system and each node. In order to further consider the electrical position of the units in the system and their tidal current influence characteristics, reliability sensitivity indexes are defined to quantitatively rank the influence of different units on the power supply guarantee, which helps to identify the fundamental units and weak links, and provides a more scientific and accurate reference basis for the formulation of targeted operation strategies and contingency measures.