Fast Frequency Regulation From a Wind Farm-BESS Unit by Model Predictive Control: Method and Hardware-in-the-Loop Validation

The integration of Renewable Energy Sources (RES) into the power system requires an upgrade of the adopted management and control solutions. Focusing on frequency regulation, the same RES, as well as loads, both possibly coupled with energy storage systems, are called to provide a contribution through suitable regulation services. In this context, this paper proposes a control strategy for enabling a unit composed by a Wind Farm and Battery Energy Storage Systems (BESSs) to provide a fast frequency regulation service. The control is based on Model Predictive Control technique, whereas the regulation service is defined according to the technical requirements of the Italian Transmission System Operator (TSO). The approach is also tested via Hardware-In-the-Loop simulations. More specifically, tests are carried out by implementing the control algorithm on a Raspberry Pi board that communicates with a real BESS and with a real-time simulator implementing a benchmark power system. The validation results prove the practical effectiveness of the proposed control method since they demonstrate that the designed algorithms can be implemented on a low-cost hardware and applied, without computational and communication issues, in a real-field framework.

Automated summary

This paper proposes a control strategy based on Model Predictive Control technique for a unit composed of a Wind Farm and Battery Energy Storage Systems (BESSs) to provide a fast frequency regulation service. The approach is tested via Hardware-In-the-Loop simulations and proves to be effective.