Improved risk-based TTC evaluation with system case partitioning

Managing the security of a system has always been one of the challenging tasks for a system operator, especially within a competitive environment where a system is commonly operated close to its limits. Therefore, the Total Transfer Capability (TTC) index was introduced by NERC in 1996 mainly to provide the system operator with information necessary for the system security management. In addition, the presence of variable generation from renewable energy further complicates the system operation and planning. When evaluating the TTC, it is important to consider the uncertainty associated with the system parameters and the system security related to the transient stability. This paper presents a risk-based TTC evaluation by means of Monte Carlo simulation together with transient stability consideration. However, this method requires excessive computing time in view of a large sample size; as a result, the TTC may not be available to the system operators in time. Since the heavy computational burden is a major impediment to the widespread use of this method; hence, a system case partitioning using two filters, i.e. performance indices and decision tree, is proposed as a means to reduce the sample size and enhance the computational speed. The validation of the proposed method is conducted through a numerical simulation on the 90-bus system integrated with wind power and photovoltaic (PV).

► A novel efficient total transfer capability evaluation method is proposed.
► The system case partitioning is proposed to help improve the computational speed.
► The proposed system case partitioning can screen out the risk-related cases.
► The accuracy and run time depend on the number of cases in the partitioned set.
► The proposed method can reduce the run time while obtaining acceptable accuracy.