Application Of Automatic Generation Control Based On State Space Model Predictive Control

The frequency of power system is an important index of power quality. It reflects the balance between active power and load power, and it has close relationship with the safety and efficiency of power equipment of broad users. Therefore, one of the most important tasks during power system operation is to supervise and control the frequency and to keep the frequency deviation in allowable range. With the development of electric power industry, the power systems gradually realize interconnected operation. The task of interconnected operation is to maintain and improve the quality of frequency, realize the power transmission between different power grids through tie lines, guarantee the tie line exchange power according to plan, improve the regulation performance in control area, so as to play superiority of large power grid operation. As an important means to implement load frequency control (LFC), the control effect of automatic generation control (AGC) will directly influence the quality of the power grids. In the actual automatic generation control system, the existence of the generation rate constraints (GRC) and the governor valve position limited present great challenge to the control schemes, since it would influence the dynamic responses of the system significantly and lead to larger overshoot and longer settling time. Model predictive control (MPC) is a popular control strategy which takes systematic account of process input, state and output constraints, thereby is employed to automatic generation control based on the state space model of AGC. This paper adopts quadratic programming MPC to cope with the generation rate constraint (GRC) and fuzzy T-S model to cope with the governor valve position limited. The proposed methodology is tested with a two-area interconnected power system. Simulation results demonstrate the effectiveness of the proposed model predictive control algorithm.