Model Predictive Control for Load Frequency Regulation with PEVs

With the participation of a significant number of PEVs, it is really challenging to achieve economic-effective in load frequency control while sustaining satisfiable system performance. To tackle this challenge, this chapter proposes a new model predictive control strategy for the load frequency control with the large-scale PEV participation. In the light of the vulnerability of load frequency control to false data injection attacks, a model-based \(\chi ^{2}\) intrusion detection unit is integrated with the proposed DEMPC. This model-based intrusion detection unit can not only monitor the false data injection attacks, but also generate a model-based state prediction for the DEMPC once the data is identified as compromised. Then, an event-triggering mechanism is presented to reduce the computation and communication burdens of each area controller. Simulation studies of a four-area power system are conducted and the results validate the effectiveness of the proposed intrusion detection unit and event-triggering conditions for the DEMPC.