Experimental Validation of Cyberattack Detector for Battery Energy Storage-based Virtual Power Plant

The fluctuating availability of renewable energy sources might necessitate a greater incorporation of battery energy storage systems (BESSs) within the electrical grid. These BESSs serve multiple purposes, including frequency regulation and backup support. In tandem, the utilization of internet-of-things (IoT) enabled technologies is progressively expanding in the realm of BESS. Nonetheless, the absence of specific regulations on the integration of IoT in BESS design and operation may escalate the vulnerability of utility-scale batteries to potential cyberattacks. Combining Adaptive Boosting and Hidden Moving Target Defense (MTD) techniques originating in the smart grid domain, the cyberattack detection and mitigation algorithm was developed. To validate its performance in the case study, a set of experiments was conducted. Leveraging an experimental dataset comprising a group of independently controlled BESSs, the study evaluates the functionality and effectiveness of the proposed methodology. Operating within the context of a Virtual Power Plant (VPP), the algorithm adeptly manages the VPP setpoints and dynamically regulates the power injection of each BESS into the grid. This comprehensive investigation provides crucial insights into bolstering the resilience of BESSs against the evolving landscape of cyber threats, thereby ensuring the secure and uninterrupted operation of these vital energy infrastructure components.