The Stability Paradox: Why Grid-Forming Inverters Fail the Forensic Audit

As the stability of low-inertia grids becomes a cornerstone of global decarbonization, Grid-Forming Inverter (GFMI) technology has ascended to the pinnacle of power electronics. Between 2024 and 2025, control strategies such as Droop, VSM (Virtual Synchronous Mechanism), and dVOC (dynamic Virtual Oscillator Control) have undergone rigorous comparative analysis, accelerating the deployment of autonomous operation and black-start capabilities.

However, while technical stabilization is within our grasp, a critical void remains in real-world operations and incident response: "Forensic Stability." While high-resolution waveforms and event logs can capture what occurred, the evidentiary basis for why a specific control logic dictated a decision at a precise microsecond remains unanchored.

This article identifies the structural vulnerabilities in GFMI audits caused by implementation disparities and dynamic mode switching, presenting the ADIC (Accountable Deterministic Information Closure) approach—a framework to seal the evidentiary basis of control without disrupting the underlying system logic.

▼ADIC DEMO https://ghostdrifttheory.github.io/ghostdrift-adic-audit/

1. The Frontier of Grid Stabilization: The Promise of GFMI

For engineers at the forefront of GFMI implementation, the selection of a control law is an elite design process that dictates the resilience of the entire power system.

• The Classical Foundation of Droop Control: A robust decentralized coordination mechanism that achieves autonomous power sharing through frequency and voltage cues.

• The Mimicry of VSM (Virtual Synchronous Mechanism): By emulating rotational inertia and damping, VSM provides a behavior that "synchronizes" with the grid, ensuring seamless compatibility with legacy synchronous machinery.

• The Structural Rigor of dVOC (dynamic Virtual Oscillator Control): By mathematically defining stability and convergence during the design phase, dVOC provides a theoretical guarantee for the next generation of grid formation.

In practice, these strategies are integrated with localized protection, current limiting, and auxiliary functions, operating as a dynamic, state-dependent control suite.

2. Three Structural Barriers to Audit Integrity: The "Ghost Drift" of Intent

The higher the performance of GFMI, the more likely "interpretative branching" occurs during post-incident investigations. Three specific "blind spots" allow the basis of decision-making to drift:

2.1 The Opacity of State-Dependent Mode Switching

GFMI systems transition instantaneously between grid-following, grid-forming, and current-limiting modes based on transient grid conditions. While the crux of an audit is "which mode was active under what specific criteria," the absence of pre-fixed and sealed transition rules allows for the retrospective reconstruction of justifications.

2.2 "Homonymous but Heterogeneous" Implementation Gaps

Even when control strategies share a common label—such as "VSM" or "dVOC"—their specific "implementation profiles" (discretization methods, limiter priorities, or PLL integration) vary significantly across manufacturers. When two nominally identical VSM systems behave differently during an incident, accountability remains inaccessible unless the specific logic is fixed and verifiable.

2.3 The Limits of Waveform Analysis: Evidence without Context

Current forensics rely on Sequence of Events (SOE) and high-speed waveforms. While these are excellent for recording physical "facts," they do not capture the "design intent" or "parameter set" active at the moment of execution. Without this context, evidence remains fragmentary, permitting post-hoc rationalization of system failures.

3. The Core Issue: The Absence of "Determination of Design Selection"

Discussions regarding GFMI typically focus on transient stability and protection coordination. However, for a rigorous audit, the industry requires proof that "the specific control logic, parameters, and switching conditions were structurally fixed at the moment of execution, and any post-hoc substitution is detected through verification."

Without this "fixation of design selection," explanations will continue to drift indefinitely after an incident, leaving the final decision authority in a state of indeterminacy—a phenomenon we define as "Ghost Drift."

4. The ADIC Solution: Sealing the Basis of Control

ADIC (Accountable Deterministic Information Closure) provides a "verification-ready sealing" for the operational boundaries of GFMI without interfering with its sophisticated control algorithms.

4.1 S_core: Pre-Fixation and Structural Registration

Before operations begin, the following elements are registered and fixed as immutable IDs:

• Control Logic ID: The specific control law and its unique implementation profile.

• Parameter Set ID: The specific bundle of gains, limiter thresholds, and priorities.

• Mode-Switch Condition ID: The rules triggering mode transitions and the permissible thresholds for exceptions.

This ensures that the operational state remains verifiable based on the S_core.

4.2 Ledger: Verifiability via Evidentiary Chaining

At each event, the active Logic ID, Parameter ID, and Transition Mode ID are recorded in a tamper-evident chain structure. Any attempt to substitute an after-the-fact explanation will result in a mismatch during the verification process, ensuring that discrepancies are detected.

4.3 Two-Layer Verification: Integrating "Facts" and "Logic"

By combining the "facts" provided by SOE/waveforms with the "fixed basis" proved by the Ledger, audits can finally reach a definitive conclusion regarding the determination of design selection.

5. Case Study: Mode Transition During Grid Current Limiting

Consider a scenario in a weak grid where an inverter’s output drops sharply due to current limiter activation. Waveforms track the physical event, but the debate shifts to: "Who determined these specific limiter settings and priorities, and were they active at the time?"

• Conventional Operation: Disparities in implementation allow for diverging post-hoc explanations, causing responsibility to evaporate.

• ADIC-Augmented Operation: The specific IDs active at the moment of the incident are indelibly fixed in the Ledger. Verification determines if the behavior was within the pre-fixed S_core. Deviations or substitutions are flagged, while operations within the agreed range are processed as a valid exercise of decision authority (Decision Authority Closure).

6. Conclusion: Audit Stabilization as a Catalyst for Infrastructure Trust

The ultimate challenge of GFMI is not performance; it is the structural vulnerability that allows the "basis of decision-making" to drift during an audit.

ADIC provides the consistency of verification by fixing logic, parameters, and switching conditions as IDs without altering the control logic. This "closure" elevates GFMI from a sophisticated device to a truly reliable social infrastructure—transforming the "Ghost Drift" of accountability into a singular, verifiable point of truth.

▶AI Accountability Project