Optimal design of model predictive control with superconducting magnetic energy storage for load frequency control of nonlinear hydrothermal power system using bat inspired algorithm

- Bat inspired algorithm (BIA) based design of model predictive controllers (MPCs) is proposed for LFC.
- Two-area hydro-thermal system, equipped with MPC and SMES, is considered to accomplish this study.
- BIA is devoted to search for optimistic controller parameters.
- Simulation results confirm the effectiveness of MPC and SMES.

This paper proposes bat inspired algorithm (BIA) as a new optimization approach of a model predictive control (MPC) and superconducting magnetic energy storage (SMES) for load frequency control (LFC) of a two-area interconnected hydrothermal system. The proposed power system model includes generation rate constraint (GRC), governor dead band, and time delay. Conventionally, the parameters of MPC controller and SMES are obtained by trial and error method or experiences of designers. To overcome this problem, the BIA is applied to simultaneously tune the parameters of MPC controller and SMES to minimize deviations of frequency and tie-line power flow of the interconnected power system against load disturbances. Simulation results show that the performance of the proposed BIA based MPC controller with SMES is superior to the conventional proportional-integral (PI) controller based integral square error technique and BIA based MPC controller without SMES in terms of the overshoot settling time and robustness.