Handling communication loss in automatic generation control using MPC

The paper presents a distributed Model Predictive Control (MPC) scheme for Automatic Generation Control (AGC) to handle the communication failure in a large interconnected power system. The developed methodology does so by accurately quantifying the impact of the signals, which are lost due to a communication link failure. We first develop a decentralized dynamic system model for AGC in such a way that the communication signals impact only the locally measurable states. Under normal operating conditions the error between the measured and the predicted values of the local states contain information of unknown feed forward disturbances but during communication failure it also has the information of the lost signal. We embed the decentralized model with an integrator to get rid of the unknown feed forward disturbances from the error, which allows to accurately estimate the lost communication signals during communication failure. Finally a reference tracking problem is formed using MPC strategy to derive a closed form control law for AGC. These claims of the effectiveness of the designed model and controller are validated using the simulation studies on a two-area power system model.