Smart Inverter Twin Model for Anomaly Detection
Conference
·
· 2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL)
- Kansas State University
Smart inverters connected to a communication network are vulnerable to various anomalies in the form of cyberattacks. In this paper, a self-security approach is implemented using the digital twin concept for smart inverters. The digital twin is formed using the inverter’s dynamic model. Then, the incoming setpoints are autonomously examined using the digital twin, and only the safe setpoints are engaged to the inverter’s local controller. This paper demonstrates the details of the self-security algorithm and how the inverter’s digital twin is formed. In particular, the stable and unstable operation region is experimentally verified by changing the power setpoints engaged to the local controller, using a laboratory setup including a three-phase 1.5-kVA SiC-MOSFET inverter and a 12-kW NHR 9410 regenerative power grid emulator. The results demonstrate that the digital twin model can potentially protect inverters from abnormal operation by examining the incoming commands (new setpoints) using the inverter’s digital twin before engaging the setpoints to the local controller.
- Research Organization:
- Kansas State University
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- DOE Contract Number:
- EE0008767
- OSTI ID:
- 1905745
- Report Number(s):
- DOE-KSU-8767
- Conference Information:
- Journal Name: 2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL)
- Country of Publication:
- United States
- Language:
- English
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