A Probabilistic Power System Dynamic Security Assessment Model Based On Dynamic Security Region

Stability and security of power systems are important research aspects for a long period of time. Loss of power system security will cause great expense to national economy and people's life, as an example, the direct cost of the America-Canada 8.14 Blackout is about 4-10 billion U.S. Dollars. The rapid increase of power system loads and the power market reformation are both threatening the security of the power systems in our country. Thus, it is of practical significance to make a thorough research on power system security and stability.Lots of computation shows that the DSR boundary hyper-plane coefficients solved through analytic method are correlative highly to that by the least-square approach. Based on this phenomenon, an improved analytic method of DSR is presented, which reduces the error obviously and preserves the speediness feature.A probabilistic power system dynamic security assessment model based on the dynamic security region (DSR) is presented. Probabilistic insecurity indexes are used to express the security states of system elements and the whole power system. The model is composed of a preparing block, a pre-assessment block, a primary assessment block, a secondary assessment block, and an output block. The model has the following features:1) The security information provided by the assessment result is more dependable because of the consideration of some main uncertain factors;2) The improved analytic method of power system DSR and the dynamic equivalent technologies are applied to reduce the computing time and to make the model more practical;3) Step-up assessment strategy is adopted in order to balance the precision and computing time requirements;4) Decompounding of system insecurity indexes to each system component, or to each generator and consumer, and the visualization of assessment results, will help the operators to understand the security status of the power system more clearly;5) The assessment results can be beneficial to the preventive control in traditional power systems and the security pricing in power market environments.