Abstract

AbstractThis paper suggests an inter‐area oscillation suppressor based on second‐order sliding mode controller (SOSMC) for doubly fed induction generator (DFIG) to suppress the inter‐area power system oscillations. SOSMC‐based suppressor targets at improving the reactive power control capability of DFIG to retrieve the stability of affected power system caused by fault occurrence into the stable condition. This controller has been initially designed for two‐area power system, after that it has been extended for multi‐area power systems. SOSMC‐based suppressor has no sensitivity to the uncertainty and variation of the parameter in all system operation conditions as compared with the conventional suppressors. Due to exploration and exploitation capability of chaotic whale optimization algorithm (CWOA), it is applied as main optimizer to optimally tune the suppressor's parameters and merge with the dynamic stability scheme. This optimization algorithm is beneficial for complex dynamic stability problem, because during the iterative procedure, it can enhance the exploration capability to find the best solution. The optimization scheme based on CWOA has been compared with the conventional whale optimization algorithm (WOA) and particle swarm optimization (PSO). The suppressor damping capability has been evaluated with consideration of some possible disturbance scenarios. Furthermore, the objective function has been carried out based on the prominent dynamic performance criteria such as integral of time multiplied absolute error (ITAE), integral of absolute error (IAE), integral of squared error (ISE), and integral of time multiplied squared error (ITSE). Considering the various operating points, the SOSMC‐based suppressor ameliorates the system robustness as compared to the conventional suppressor. At last, the simulation results extracted from both interconnected power systems confirm the enhancement of power system operability and performance in suppression of the inter‐area oscillations, and also validate the robustness of the suggested control strategy against the model uncertainties and unmodeled dynamics.

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