Neural-net based megawatt-frequency control

The design of a new adaptive control system is presented, and its performance in a computer simulation of the single-area megawatt-frequency control problem is demonstrated. The new design utilizes self-organization and predictive estimation capabilities of neural-net computing. Real-time adaptation is facilitated by the error-based online learning scheme implemented on a clusterwise segmented associative memory system. The use of the pattern recognition approach in power systems control is demonstrated. The role of feedback is emphasized in order to compensate for uncertainties and lack of information