Crow search algorithm based optimal dynamic performance control of SVC assisted SMIB system

A study on improvement of dynamic as well as steady state performance of power system model using static VAR compensator (SVC) is carried out in this paper. SVC refers to a shunt device within the family of flexible alternating current transmission system and is widely used for enhancing voltage profile and power transmission capability. SVC along with power system stabilizer (PSS) is employed to damp out the oscillation and take back the system to a stable state following disturbance. Crow search algorithm (CSA) is implemented to optimize conventional parameters of PSS and SVC. Simulation results found by it are compared with others optimization algorithms such as particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO). Also, power system model under the effect of CSA based tuned PSS and SVC is verified using eigenvalue analysis under steady state condition for investigating steady state stability. A comparative time domain simulation under MATLAB/SIMULINK platform employing CSA, PSO and TLBO tuned PSS and SVC with studied single machine infinite bus system is carried for dynamic stability assessment. Results obtained confirm the efficacy of the CSA in better tuning of PSS and SVC than other counterparts.