In this thesis a sliding mode based control algorithm is applied in load frequency control of a power system. Firstly, an operation of load frequency control within a power system is described. Drawbacks of presently widely used load frequency control algorithm, PI algorithm, are specified. Based on the goals of load frequency control and PI algorithm drawbacks, requirements of a new control algorithm are defined. For the purposes of testing the proposed algorithm, linear and nonlinear power system models are designed. Each model is consisted of four control areas. Components of both models are explained in detail.
Sliding mode control algorithm is proposed as the new load frequency control algorithm. Sliding mode control algorithm is chosen due to its robustness to particular uncertainties and system parameter variations. In this thesis a discrete time sliding mode control algorithm is used. Parameters of the proposed control algorithm are computed using genetic algorithms. To compute a control signal in sliding mode controller, a full system knowledge is required. Not all system state and disturbance components are measurable, therefore they are estimated using fast output sampling technique.
Simulation research is firstly conducted on linear power system model. On that model a comparison of the proposed load frequency control algorithm and commonly used PI control algorithm is obtained. Simulation results show that the proposed algorithm outperforms PI algorithm. Moreover, simulation results show robustness of the proposed algorithm to presence of parameters identification error, measurement noise and variations of all system parameters. The proposed control algorithm is also tested on nonlinear power system model and its good performance is thereby confirmed.