A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations.

New Coordinated Tuning of SVC and PSSs in Multimachine Power System Using Coyote Optimization Algorithm

This paper presents a new approach for coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controller. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are mostly preferable. In this regard, a nonlinear time domain based objective function is used. Then, the coyote optimization algorithm (COA) is employed for solving this optimization problem. In order to ensure the robustness and performance of the proposed controller (COA-PSS&SVC), the objective function is evaluated for various extreme loading conditions and system configurations. To show the contribution of the coordinated controllers on the improvement of the system stability, PSSs and SVC are optimally designed in individual and coordinated manners. Moreover, the effectiveness of the COA-PSS&SVC is assessed through comparison with other controllers. Nonlinear time domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations.