Cyber-attack detection and electrical system stability for electric vehicle charging infrastructure
Some embodiments provide a system to protect an electric vehicle charging infrastructure. An electric vehicle charging site may receive Alternating Current (“AC”) power from a power grid and provides Direct Current (“DC”) power to electric vehicles. A sensor spoof observer and controller may receive information from at least two AC current sensors, wherein the observer calculates a grid voltage disturbance using a structure based on an AC filter dynamic model. A system stability assurance platform may: (i) monitor current and voltage to detect resonance, (ii) identify impedance associated with a detected resonance, and (iii) apply a result of an analysis of the identified impedance to an adaptive damping control algorithm. A user interface platform may then provide information about a component of the charging infrastructure being cyber-attacked to a distribution system operator via a graphical user interface display.
1. A system to protect an electric vehicle charging infrastructure, comprising:
an electric vehicle charging site to receive Alternating Current (“AC”) power from a power grid and provides Direct Current (“DC”) power to electric vehicles, including:
a sensor spoof observer and controller to receive information from at least two AC current sensors, wherein the observer calculates a grid voltage disturbance using a structure based on an AC filter dynamic model;
a system stability assurance platform to: (i) monitor current and voltage to detect resonance, (ii) identify impedance associated with a detected resonance, and (iii) apply a result of an analysis of the identified impedance to an adaptive damping control algorithm; and
a user interface platform to provide information about a component of the charging infrastructure being cyber-attacked to a distribution system operator via a graphical user interface display.
2. The system of claim 1 , wherein the sensor spoof observer and controller and the system stability assurance platform are implemented in a hierarchical manner such that the sensor spoof observer and controller is deployed in an individual converter control layer and the system stability assurance platform is deployed in a charging station layer and a substation layer.
3. The system of claim 1 , wherein the sensor spoof observer and controller utilizes information from a second AC current sensor when it is determined that a first AC current sensor is being cyber-attacked.
4. The system of claim 1 , wherein the AC filter dynamic model is continuously corrected using a difference between a measured output and an observed output to minimize state-variable divergence.
5. The system of claim 1 , wherein the grid voltage disturbance is associated with AC unbalance.
6. The system of claim 1 , wherein the system stability assurance platform detects resonance associated with at least one of: (i) altered control parameters, and (ii) cycling setpoints.
7. The system of claim 1 , wherein the system stability assurance platform includes an AC system-level stability assurance algorithm and a DC system-level stability assurance algorithm.
8. The system of claim 1 , wherein the resonance is detected via at least one of: (i) a sliding Discrete Fourier Transform (“DFT”), and (ii) a wavelet analysis.
9. The system of claim 1 , wherein the impedance associated with the detected resonance is identified using analytical model predictions and a small-signal injection to improve signal-to-noise ratio.
10. The system of claim 1 , wherein the graphical user interface display includes at least one of: (i) static information regarding the charging site, (ii) a physical location of the charging site, (iii) a topology of the charging site, (iv) a number of charging ports, (v) indications of occupied charging ports, (vi) details regarding a nature of a cyber-attack, (vii) an indication regarding resonance, (viii) a frequency or magnitude of resonance, and (ix) a cyber-attack remediation recommendation.
11. The system of claim 1 , wherein the electric vehicle charging site is associated with extreme fast charging.
12. A computerized method to protect an electric vehicle charging infrastructure that receives Alternating Current (“AC”) power from a power grid and provides Direct Current (“DC”) power to electric vehicles, comprising:
receiving, at a sensor spoof observer and controller, information from at least two AC current sensors;
calculating, by the sensor spoof observer and controller, a grid voltage disturbance using a structure based on an AC filter dynamic model;
monitoring, by a system stability assurance platform, current and voltage to detect resonance;
identifying, by the system stability assurance platform, impedance associated with a detected resonance;
applying, by the system stability assurance platform, a result of an analysis of the identified impedance to an adaptive damping control algorithm; and
providing, by a user interface platform, information about a component of the charging infrastructure being cyber-attacked to a distribution system operator via a graphical user interface display.
13. The method of claim 12 , wherein the sensor spoof observer and controller utilizes information from a second AC current sensor when it is determined that a first AC current sensor is being cyber-attacked.
14. The method of claim 12 , wherein the AC filter dynamic model is continuously corrected using a difference between a measured output and an observed output to minimize state-variable divergence.
15. The method of claim 12 , wherein the grid voltage disturbance is associated with AC unbalance.
16. The method of claim 12 , wherein the system stability assurance platform detects resonance associated with at least one of: (i) altered control parameters, and (ii) cycling setpoints.
17. The method of claim 12 , wherein the system stability assurance platform includes an AC system-level stability assurance algorithm and a DC system-level stability assurance algorithm.
18. A non-transitory, computer-readable medium storing program code, the program code executable by a computer processor to cause the processor to perform a method to protect an electric vehicle charging infrastructure that receives Alternating Current (“AC”) power from a power grid and provides Direct Current (“DC”) power to electric vehicles, the method comprising:
receiving, at a sensor spoof observer and controller, information from at least two AC current sensors;
calculating, by the sensor spoof observer and controller, a grid voltage disturbance using a structure based on an AC filter dynamic model;
monitoring, by a system stability assurance platform, current and voltage to detect resonance;
identifying, by the system stability assurance platform, impedance associated with a detected resonance;
applying, by the system stability assurance platform, a result of an analysis of the identified impedance to an adaptive damping control algorithm; and
providing, by a user interface platform, information about a component of the charging infrastructure being cyber-attacked to a distribution system operator via a graphical user interface display.
19. The medium of claim 18 , wherein the resonance is detected via at least one of: (i) a sliding Discrete Fourier Transform (“DFT”), and (ii) a wavelet analysis.
20. The medium of claim 18 , wherein the impedance associated with the detected resonance is identified using analytical model predictions and a small-signal injection to improve signal-to-noise ratio.
21. The medium of claim 18 , wherein the graphical user interface display includes at least one of: (i) static information regarding the charging site, (ii) a physical location of the charging site, (iii) a topology of the charging site, (iv) a number of charging ports, (v) indications of occupied charging ports, (vi) details regarding a nature of a cyber-attack, (vii) an indication regarding resonance, (viii) a frequency or magnitude of resonance, and (ix) a cyber-attack remediation recommendation.
22. The medium of claim 18 , wherein the electric vehicle charging site is associated with extreme fast charging.