Post Optimal Analysis application on the reliability evaluation of the Iran power grid

Access to a computational tractable method for representing the system more realistically has always been an important issue in power system reliability assessment. The Post Optimal Analysis (POA), as a well recognized technique to attack a set of similar optimization problems, has been successfully used to assess the reliability of composite systems. This method exploits the similarity of the system states to speed up the contingency evaluation procedure without sacrificing the accuracy of the results. In this paper, the performance and practical feasibility of the POA technique for power system reliability evaluation is tested using the Iran power grid. The POA based approach is applicable in both sorts of state sampling methods namely analytical enumeration (AE) and Monte Carlo simulation (MCS). Considering the dimension of the Iran power grid, in this paper system states are sampled using the MCS approach. In the simulations, a diverse range of reliability indices at both overall system and individual load point levels are computed with/without POA accommodation. The accuracy and execution time associated with the POA based method are compared with those obtained using the conventional method. Although considerable efforts have been devoted to collect and compile equipments performance data in the Iran grid data collection system, the uncertainty in the availability data of components is inevitable. Accordingly, a sensitivity analysis is carried out to investigate the effects of possible errors in equipments forced outage rates (FORs). The impacts on system risk of different peak load levels are also investigated.