Tuning of damping controller for UPFC using quantum particle swarm optimizer

On the basis of the linearized Phillips–Herffron model of a single machine power system, we design optimally the unified power flow controller (UPFC) based damping controller in order to enhance power system low frequency oscillations. The problem of robustly UPFC based damping controller is formulated as an optimization problem according to the time domain-based objective function which is solved using quantum-behaved particle swarm optimization (QPSO) technique that has fewer parameters and stronger search capability than the particle swarm optimization (PSO), as well as is easy to implement. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The effectiveness of the proposed controller is demonstrated through non-linear time-domain simulation and some performance indices studies under various disturbance conditions of over a wide range of loading conditions. The results analysis reveals that the designed QPSO based UPFC controller has an excellent capability in damping power system low frequency oscillations in comparison with the designed classical PSO (CPSO) based UPFC controller and enhance greatly the dynamic stability of the power systems. Moreover, the system performance analysis under different operating conditions show that the δE based damping controller is superior to the mB based damping controller.