Salp Swarm Algorithm Based Integral LQG Control of Two Area Nonlinear Power System with Renewable Energy Penetration

In this article a salp swarm algorithm (SSA)-based integral linear quadratic Gaussian (ILQG) controller is presented for compensating load-frequency disruptions in a two-area power system due to load/generation mismatches from renewable energy penetration. Nonlinearities such as a governor dead band (GDB), generation rate constraint (GRC), and communication time delay in phasor measurement units are considered to mimic the system’s actual behavior. The control- and state-weighting matrices for the design of the integral linear quadratic regulator (ILQR) and disturbance- and noise-covariance ones for that of the Kalman filter were optimized by the SSA optimizer. The optimization was performed using a nonlinear Simulink model of the system containing all the uncertainties. Therefore, the SSA-ILQG is the result of a two-stage optimization problem whereby the outer optimization loop determines the optimal weighting and covariance matrices of the LQR and Kalman filter cost function, respectively. The inner optimization loop solves the linear quadratic problem of the LQR and Kalman filter. The proposed SSA-ILQG controller offers 7.41 and 36.11 times fewer integral time absolute errors than the SSA-ILQR and conventional LQR-PI ones, respectively.