A Hybrid Model Reference Controller Integrated with an Optimization Technique for Generator Speed Control of a Hydropower Plant

Abstract

Designing an effective speed control strategy to stabilize the rotational speed of a synchronous generator is highly important for the operation and stability of a hydropower plant. Traditionally, PID regulators are employed to eliminate the speed deviations due to load changes in such a power system. With the fast development of modern control techniques together with poor control performances of the PID regulators, intelligent speed controllers i.e. fuzzy logic and artificial neural network – based controllers should be considered to find a more feasible speed control scheme. This paper proposes a newly hybrid control strategy applying a model reference adaptive control (MRC) integrated with an efficient optimization mechanism to solve the generator speed control problem. The novel controller is completely able to deal with the speed control problem against the random load changes in a hydroelectric power system with better control performances when compared to several counterparts such as the conventional PID regulator. This claim will be demonstrated through a number of numerical simulations implemented in MATLAB/Simulink platform for a typical hydropower plant model which also be established in this study.