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Irradiance-Driven Natural Watermarking for Detection of False Data Injection in PV Inverters.

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Title: Irradiance-Driven Natural Watermarking for Detection of False Data Injection in PV Inverters.
Authors: Bjorndal, Lars1 (AUTHOR), Balahewa, Imasha1 (AUTHOR), Vosoughi Kurdkandi, Naser1 (AUTHOR), Huang, Tong1 (AUTHOR) thuang7@sdsu.edu, Mi, Chris1 (AUTHOR)
Source: Energies (19961073). Jun2026, Vol. 19 Issue 12, p2851. 22p.
Subject Terms: *Falsification of data, *Photovoltaic power systems, *Internet security, *Hardware-in-the-loop simulation, *Anomaly detection (Computer security), *Smart power grids
Abstract: The widespread deployment of photovoltaic (PV) inverters with digital control and communication systems has increased the power grid's attack surface, making it more vulnerable to cyberattacks. This creates a need for locally implementable attack-detection methods that do not disrupt inverter operation. This paper therefore proposes an irradiance-driven natural watermarking approach for decentralized detection of false data injection (FDI) attacks on inverter terminal measurements. The approach leverages irradiance-driven DC-link voltage variations to watermark the inverter outputs, generating a non-removable signature in the true measurements. The proposed method is evaluated using a real-time hardware-in-the-loop model of a three-phase grid-following PV inverter that captures PV-array and grid-connection dynamics. Implementation robustness is further assessed on a separate hardware grid-forming inverter testbed with non-idealized components. In the tested cases, the detection model identifies noise-injection and replay attacks within 15 ms , while otherwise undetectable model-based attacks are revealed when DC-link voltage variations between 5% and 10% occur. These experimental results demonstrate that irradiance-driven natural watermarking can reveal FDI attacks without affecting normal inverter operation. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194909300
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Irradiance-Driven Natural Watermarking for Detection of False Data Injection in PV Inverters.
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  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Bjorndal%2C+Lars%22">Bjorndal, Lars</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Balahewa%2C+Imasha%22">Balahewa, Imasha</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vosoughi+Kurdkandi%2C+Naser%22">Vosoughi Kurdkandi, Naser</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Tong%22">Huang, Tong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> thuang7@sdsu.edu</i><br /><searchLink fieldCode="AR" term="%22Mi%2C+Chris%22">Mi, Chris</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jun2026, Vol. 19 Issue 12, p2851. 22p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Falsification+of+data%22">Falsification of data</searchLink><br />*<searchLink fieldCode="DE" term="%22Photovoltaic+power+systems%22">Photovoltaic power systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br />*<searchLink fieldCode="DE" term="%22Hardware-in-the-loop+simulation%22">Hardware-in-the-loop simulation</searchLink><br />*<searchLink fieldCode="DE" term="%22Anomaly+detection+%28Computer+security%29%22">Anomaly detection (Computer security)</searchLink><br />*<searchLink fieldCode="DE" term="%22Smart+power+grids%22">Smart power grids</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The widespread deployment of photovoltaic (PV) inverters with digital control and communication systems has increased the power grid's attack surface, making it more vulnerable to cyberattacks. This creates a need for locally implementable attack-detection methods that do not disrupt inverter operation. This paper therefore proposes an irradiance-driven natural watermarking approach for decentralized detection of false data injection (FDI) attacks on inverter terminal measurements. The approach leverages irradiance-driven DC-link voltage variations to watermark the inverter outputs, generating a non-removable signature in the true measurements. The proposed method is evaluated using a real-time hardware-in-the-loop model of a three-phase grid-following PV inverter that captures PV-array and grid-connection dynamics. Implementation robustness is further assessed on a separate hardware grid-forming inverter testbed with non-idealized components. In the tested cases, the detection model identifies noise-injection and replay attacks within 15 ms , while otherwise undetectable model-based attacks are revealed when DC-link voltage variations between 5% and 10% occur. These experimental results demonstrate that irradiance-driven natural watermarking can reveal FDI attacks without affecting normal inverter operation. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/en19122851
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 2851
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      – SubjectFull: Falsification of data
        Type: general
      – SubjectFull: Photovoltaic power systems
        Type: general
      – SubjectFull: Internet security
        Type: general
      – SubjectFull: Hardware-in-the-loop simulation
        Type: general
      – SubjectFull: Anomaly detection (Computer security)
        Type: general
      – SubjectFull: Smart power grids
        Type: general
    Titles:
      – TitleFull: Irradiance-Driven Natural Watermarking for Detection of False Data Injection in PV Inverters.
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            NameFull: Bjorndal, Lars
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            NameFull: Vosoughi Kurdkandi, Naser
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            NameFull: Huang, Tong
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            NameFull: Mi, Chris
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            – D: 15
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
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              Value: 19961073
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              Value: 19
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              Value: 12
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            – TitleFull: Energies (19961073)
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