The Journal of Engineering (Oct 2018)
Power system stochastic transient stability assessment based on Monte Carlo simulation
Abstract
Electrical power system is a complicated dynamic system with plenty of random disturbances while this character has been aggravated attributed to the rapid development of renewable energy technology. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. Thus, stochastic transient stability analysis has been established by introducing stochastic differential equations to traditional transient stability analysis. Previous studies on stochastic transient stability assessment just provided a preliminary result but failed to assess its accuracy and reliability, which are essential mathematical properties. Based on the theory of probability and statistics, the Monte Carlo simulation is utilised to further improve the numerical simulation method for transient stability evaluation. Two stability assessment indices are proposed: instability probability and expectation of critical clearing time (ECCT). Then, a corresponding method to calculate the indices and their confidence level is proposed. A two-stage adaptive method is introduced to pre-estimate the sample capacity under a given confidence coefficient, so that the corresponding confidence intervals of the indices can be calculated. The effectiveness of the proposed method is validated on the three-machine, nine-bus system, which demonstrates that it would be suitable for future hybrid AC/DC power systems with fluctuating renewable energy generations.
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