Probabilistic operational planning using dynamic programming with time-domain simulations

Abstract

A dynamic programming model with time-domain simulations of contingencies is created to find the least-costly operational strategies according to a probabilistic operational criterion with selected preventive and corrective actions. The results show that the operational model can identify strategies which appear to be satisfactory according to a static analysis, but where the system response in the time-domain is violating the systems operational requirements. The model calculates the costs related to many possible operating strategies compared to models which only search parts of the solution space. This can be useful for TSOs that want to use the model for decision support. However, computational times are very limiting due to the time-domain simulations. Consequently, approaches for limiting the number of scenarios or speeding up the time-domain simulations should be investigated.