Study of a Self-Tuning Predictive Voltage and Frequency Controller on a Cyber-Physical Model of a Distributed Generation Plant

The development of digital technology for monitoring and controlling physical processes of individual distributed generation plants in the electric power systems and its integration are driving the need to consider cyber-physical systems. Changes in operating conditions of distributed generation plants and in topology of electrical network require tuning the controllers to ensure stability of parallel operation of synchronous generators used. Controllers with a predictive device can be implemented to improve the efficiency of the tuning procedures due to their significant complexity. The paper provides a structure and a description of a digital model of a self-tuning predictive voltage and frequency controller for a synchronous generator. The studies were carried out on a cyber-physical model of a turbine generator set based on the MATLAB/Simulink Real Time Windows Target software. The purpose of the presented studies is to determine the effectiveness of the proposed self-tuning predictive controller in various transient conditions of the cyber-physical model of a turbine generator set in comparison with typical proportional- integral-derivative (PID) controllers. The experimental results demonstrated the advantages and effectiveness of the proposed predictive controller. In both normal and emergency conditions, it improved the quality indicators of the voltage and frequency control process.