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

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 15ms, 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.

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Publication Details

Journal
Energies
Published
2026-06-16
DOI
https://doi.org/10.3390/en19122851
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
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article

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

Imasha Balahewa, Lars Bjorndal, Tong Huang, Naser Vosoughi Kurdkandi et al.
Energies
Smart Grid Security and Resilience
article

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

Imasha Balahewa, Lars Bjorndal, Tong Huang, Naser Vosoughi Kurdkandi, Chris Mı
article en

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 15ms, 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.

EnergiesVol. 19(12)
San Diego State University (US)
Affordable and clean energy
Openalex Percentile: Top 7%
Smart Grid Security and Resilience
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