Improving Transient Stability Assessment Using Supercapacitor Energy Storage based on Critical Trajectory Method

The development of industrial companies leads to the massive growth of electricity consumption and the instability between the existing supply and load. Moreover, the high penetration of renewable energy will be vulnerable when a fault occurs due to the reduction of the total inertia system. Thus, the stability of the system becomes one of the primary concerns in the electrical power system due to the necessity of reliability and good quality in energy supply. When interference occurs, it can lead to system blackouts because the imbalance between the value of total generation and supplied load. In this condition, the mechanical torque is mismatched with the electrical torque and lead to losing synchronism of the generator. The rotation becomes faster when the mechanical torque is greater than the electrical torque, but the rotation becomes slower when the mechanical torque is smaller than the electrical torque. As a result, the transient stability will be affected. Therefore, research in transient stability is needed to minimize the occurrence of blackouts. The reliability and quality of an electric power system must be observed when blackouts occur. In addition, huge losses can be sensed from both sides, such as consumers and suppliers. This research proposed a method in improving transient stability through the extended value of Critical Clearing Time (CCT). The critical trajectory method is used to obtain the CCT rather than the time domain simulation method because it has faster calculation. Moreover, in enhancing the transient stability, the Supercapacitor Energy Storage (SCES) is installed in the system. The primary objectives of this research are the sizing and the allocation of SCES. The result from modified IEEE plants shows that SCES can extend the transient stability analysis through the CCT value. The critical generator is chosen as the location of SCES because it is the most vulnerable generator when a fault occurs to the system. Furthermore, it is done using the energy index method and validated using the ranking method. To obtain the optimal sizing of SCES, artificial intelligence such as the firefly algorithm is used to calculate the optimal value of the SCES through the CCT value. Moreover, the SCES sizing is compared to the manual viii calculation. The result shows that the value of SCES is well calculated, has faster calculation, and has better precision by using the firefly algorithm. Thus, the value of CCT can be used as one of the parameters in the stability assessment and fundamental knowledge for setting the protection system. The proposed method is expected to espouse the development of the electrical system in Indonesia