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REVIEW 3 major objections 5 minor 18 references

Damping LFOs: Grid Following with Power Oscillation Damping vs. Grid Forming vs. PSS

T0 review · 3 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read A grid-forming inverter with virtual synchronous machine control damps low-frequency oscillations almost as well as a traditional power system stabilizer in a standard two-area test system.

desk verdict A useful PSS/E implementation study whose central PSS comparison is confounded by a different test system, so the 'rivals PSS' claim is not supported as presented. read the letter →

arxiv 2505.24204 v1 pith:AANUXFZY submitted 2025-05-30 eess.SY cs.SY

Tamojit Chakraborty , Anamitra Pal , Sam Maleki This is my paper
classification eess.SYcs.SY
keywords low-frequencyoscillationsgrid-forminginvertersgrid-followingpoweroscillationdampingvirtualsynchronousmachinesystemstabilizersmall-signalstabilitytwo-areatest
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper sets out to show that, in a renewable-rich two-area grid, a grid-forming inverter whose controller emulates a synchronous machine's swing dynamics can damp low-frequency oscillations about as well as the traditional power system stabilizer that synchronous generators have long used. The authors build two custom controller models—a grid-following power plant controller with auxiliary power oscillation damping in active-power and reactive-power modes, and a grid-forming controller with virtual synchronous machine or droop variants—and compare them against a standard droop-based grid-forming benchmark and a PSS2B stabilizer. In eigenvalue analysis, the proposed GFM-VSM attains a damping ratio of 12.5%, close to the PSS at 13.3% and above the grid-following POD controllers at 10.6–11.6%. If the claim holds, converter-based assets could partly substitute for the damping that retires synchronous generators take away.

What carries the argument

The load-bearing mechanism is the swing-dynamics emulation in the outer active-power-frequency loop of the proposed GFM controller. That loop uses an integrator with a first-order time constant to replicate the swing equation of a synchronous machine, producing a frequency reference with adjustable inertia and damping; a virtual excitation PI controller generates the voltage reference, and an inner current controller with voltage and frequency droop forms a voltage source behind an internal impedance. A phase-locked loop converts the machine frame to the network frame. This combination supplies the damping torque that a PSS would otherwise inject through the excitation system, which is why the VSM variant approaches PSS-level damping while the droop-only and grid-following variants do not.

What would settle it

Repeat the experiment with the same configuration for every strategy: keep the 75 MW inverter at Bus 2 and SG1 at 925 MW while applying the PSS2B to SG1, then extract the tie-line mode by Prony analysis. If the PSS damping ratio drops to or below the GFM-VSM's 12.5% under identical operating conditions, the ranking that underlies the paper's main claim would be overturned.

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Extended reading notes

Core claim

The central claim of the paper is that a grid-forming inverter with a virtual synchronous machine (VSM) control layer damps low-frequency inter-area oscillations to a similar extent as a traditional PSS: in the two-area test system the VSM case gives a damping ratio of 12.5% versus 13.3% for the PSS2B, and it outperforms both grid-following POD variants (10.6% and 11.6%), the proposed droop-only GFM (11.8%), and the standard droop-based GFM benchmark (11.8%). The discovery is established by time-domain simulation followed by Prony-based eigenvalue extraction: the strategy's most oscillatory mode has real part $-0.6765$ and imaginary part $5.35$, compared with $-0.7812$ and $5.84$ for the PSS. In the load-change response, the VSM controller counteracts tie-line oscillations almost immediately, mimicking the behavior of a synchronous machine. The paper's own summary is that GFM control, particularly the GFM-VSM, dampens LFOs to a similar extent as a traditional PSS.

Load-bearing premise

The paper assumes the PSS result is comparable to the other results even though the PSS case uses a different system configuration: the 75 MW inverter is disconnected and SG1 is raised from 925 MW to 1000 MW.

Editorial extensions

If this is right

  • A single 75 MW grid-forming unit can take over much of the LFO damping duty in a two-area system, so damping need not disappear as synchronous generators are retired.
  • Grid-following inverters with auxiliary POD remain a second-best option: their damping ratios (10.6–11.6%) trail the GFM-VSM (12.5%), so GFM control is the stronger choice where converters must stabilize the grid.
  • Because the GFM-VSM's damping is close to the PSS's, adding a PSS to remaining synchronous generators is still useful but may not be required solely for LFO damping in converter-dominated areas.
  • The proposed controller has adjustable inertia and damping constants, so the same model can be retuned across different grids; the paper demonstrates this in one benchmark rather than as a general rule.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Beyond the paper, the swing-dynamics argument implies that the GFM-VSM should also add damping to inter-area modes in much larger networks; the paper only demonstrates a single-machine case, so the scaling to multi-VSM grids is an untested extension.
  • The fairness of the PSS comparison is the main open question: because the PSS case disconnects the 75 MW inverter and raises SG1's output to 1000 MW, a head-to-head test on identical operating points is needed before accepting the 13.3% versus 12.5% ordering.
  • A testable next step is to tune the VSM inertia and damping constants across a range of tie-line impedances and load steps to see whether the 12.5% damping ratio is robust or specific to the one operating point studied.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper develops two user-defined PSS/E controller models for damping low-frequency oscillations (LFOs): a grid-following power plant controller with an auxiliary power oscillation damping (POD) function (with P and Q modes), and a grid-forming (GFM) controller with a virtual synchronous machine (VSM) or droop variant. These are compared against a WECC REGFM benchmark and a conventional PSS2B power system stabilizer on a modified Kundur two-area system. The comparison is based on a time-domain three-phase fault simulation followed by Prony analysis (PSSPLT) to estimate eigenvalues; Table I reports damping ratios ranging from 13.3% for the PSS to 4.9% for the no-PSS case. The paper's central claim is that the proposed GFM-VSM, with a 12.5% damping ratio, damps LFOs 'to a similar extent as a traditional PSS' (Section IV).

Significance. If the comparison were clean, the result would be practically valuable: a grid-forming inverter with swing-dynamics emulation could provide PSS-level damping in a renewable-rich power system, and the paper would offer two new user-defined models implementable in a commercial tool. Credit is due for implementing both a GFL-POD and a GFM-VSM/droop controller in PSS/E, benchmarking against a generic REGFM model and a PSS2B stabilizer, and presenting a ranked comparison in Table I. However, the significance is currently conditional: the headline PSS comparison is confounded by a different test system, the 'eigenvalues' are Prony estimates without validation, and no controller parameters are reported. These are not presentation details but load-bearing gaps for the paper's main conclusion.

major comments (3)
  1. [Section III.A, Table I] The PSS case is run on a different test system from all other cases. Section III.A states: 'To evaluate the system performance with PSS, the CIG device is disconnected and the SG1 generates 1000 MW,' whereas the GFL and GFM cases keep the 75 MW CIG at Bus 2 and SG1 at 925 MW. Table I's comparison of PSS (13.3%) with GFM-VSM (12.5%) therefore changes both the device under test and the system operating point in one step. The inter-area mode frequency also differs (5.84032 rad/s for PSS vs. 5.34967 rad/s for GFM-VSM), indicating different modal content and participation. The conclusion that GFM-VSM 'rivals' the PSS is unsupported without rerunning the PSS case on the identical system (CIG connected, SG1 at 925 MW) or otherwise demonstrating that the configuration change is benign.
  2. [Section III.C] The manuscript labels the values in Table I as 'eigenvalues,' but they are obtained by Prony analysis using PSS/E's PSSPLT program, not by linearizing the system state matrix. Prony-based estimates depend on the time window, model order, and signal selection, and no such details are provided. The entire ranking, and the quantitative damping ratios (13.3%, 12.5%, 11.8%, etc.), rest on this unvalidated estimation procedure. The authors should either report the Prony settings and validate the estimates against an exact linearization (e.g., PSS/E eigenvalue analysis or state-matrix computation), or rephrase the claims as time-domain decay observations rather than eigenvalue-based damping ratios.
  3. [Section II, Section III.B] No controller parameter values are reported for the POD controller (Eqs. 1-2), the GFM UDM (Eqs. 3-6), the PSS2B stabilizer, or the REGFM model. The central result is a ranking of damping performance across controllers, and without the parameter values the reader cannot assess whether the ranking reflects controller architecture or tuning effort. This is a reproducibility issue that should be fixed by providing a parameter table and the tuning criteria for each controller before the comparison can be evaluated.
minor comments (5)
  1. [Section II.A, Eq. (2)] The washout block equation ds1/dt = (1/Tw)*(Kw*s0/Tw - s1) does not have the standard washout form with zero steady-state output; please clarify the output equation and the intended transfer function, since a washout should reject the DC component.
  2. [Section II.B, Eqs. (5)-(6)] The text states that the outer P controller 'has an integrator and a first-order time constant,' but Eq. (5) is a first-order lag without an explicit integrator term; please clarify how the integrator is represented in the model.
  3. [Table I] The row labeled 'NO PSS' is not explicitly described as a distinct configuration in Section III.B; please state what this case includes (e.g., CIG connected with no POD/GFM/PSS) so that the baseline is unambiguous.
  4. [Section III.C] The text says 'the proposed GFM-VSM outperforms the others in terms of damping effectiveness,' but Table I lists PSS with a higher damping ratio than GFM-VSM; please reconcile this wording with the 'rivals' conclusion.
  5. [Figures 6 and 8] The time axes and units are not visible in the manuscript text; please ensure the figures are self-contained so that the oscillation decay behavior can be independently assessed.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the damping comparison is a simulation outcome, not a derived prediction fitted to its own inputs.

full rationale

The paper's central claims rest on time-domain simulations and Prony-based modal estimates (Table I), not on a derivation in which an output is defined as an input. The GFM-VSM and GFL-POD controllers are implemented as user-defined models with stated control blocks; no parameter is stated to be fitted to the reported damping ratios. The comparison against PSS is weakened by a configuration mismatch: Section III.A states that 'To evaluate the system performance with PSS, the CIG device is disconnected and the SG1 generates 1000 MW,' while the GFM/GFL cases retain the 75 MW CIG and SG1 at 925 MW. This is a controlled-comparison validity concern, not circular reasoning. The paper also labels Prony estimates as eigenvalues in Section III.C ('The eigenvalues are obtained by performing Prony Analysis using PSS/E built-in program PSSPLT'), which is a methodological labeling issue rather than circularity. The self-citations (e.g., [5], [9], [15], [18]) are technical references for prior POD/PPC/GFM work and REECA model settings; they are not invoked as an authority that forces the damping ranking. No equation in the paper reduces by construction to a fitted target, and no 'prediction' is statistically forced by prior fitting. Therefore no significant circularity is present.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central claim rests on standard power system models, unreported controller parameters, and a comparison design that changes the test system across control strategies. No new physical entities are introduced, but the free parameters are numerous and unspecified, and the PSS-comparison axiom is ad hoc.

free parameters (4)
  • POD controller gains and time constants = not reported
    Kw, Tf, Tw, lead-lag time constants, and limits shape the damping ratio of the GFL-POD cases; the paper gives equations (1) and (2) but no numerical values.
  • GFM VSM/droop control parameters = not reported
    Kin, Kiv, Kvd, Kvq, Kfd, Kfq, Tvdrp, Tfdrp, and inertia/damping coefficients determine the GFM-VSM and GFM-Droop eigenvalues; without values the ranking cannot be audited.
  • PSS2B stabilizer parameters = not reported
    The PSS baseline's 13.3% damping ratio depends on its tuning, which is not specified in the paper.
  • Tie-line impedance adjustment to marginal stability = not reported
    The authors vary tie-line impedance until the system becomes marginally stable to excite LFOs; the chosen value is a scenario-setting free choice that affects all cases.
assumptions (4)
  • domain assumption The PSS/E two-area model with GENROU generators, ESST4B exciters, TGOV1 governors, and ZI loads adequately represents the real system's small-signal behavior.
    Section III.A describes the model but provides no validation against field data or a more detailed EMT model.
  • domain assumption Prony analysis of a single time-domain simulation yields an accurate estimate of the dominant inter-area mode.
    Section III.C uses PSS/E PSSPLT; Prony estimates depend on simulation window, signal selection, and noise, and no comparison with full linearization is given.
  • domain assumption The WECC REGFM model with 'typical parameters' from [14] is a representative grid-forming benchmark.
    Section II.C relies on an external model parameterization without sensitivity analysis.
  • ad hoc to paper Comparing the PSS case with the CIG disconnected and SG1 at 1000 MW to the GFM/GFL cases with the CIG in service is a valid basis for ranking damping performance.
    Section III.A changes topology and dispatch across comparator arms; this is a load-bearing assumption for the 'rivals PSS' claim.

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Cite this review

Pith. "Pith review of Damping LFOs: Grid Following with Power Oscillation Damping vs. Grid Forming vs. PSS." pith.science (2026). https://pith.science/paper/AANUXFZY

@misc{pith2026250524204,
  author       = {Pith},
  title        = {Pith review of: Damping LFOs: Grid Following with Power Oscillation Damping vs. Grid Forming vs. PSS},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AANUXFZY}},
  note         = {Machine review of arXiv:2505.24204}
}
read the original abstract

Low-frequency oscillations (LFOs) present a significant challenge to the stability and reliability of power systems, especially in grids with a high penetration of renewable energy sources. Traditional grid-following (GFL) inverters have proven less effective in damping such oscillations. This paper presents a GFL-power plant controller with an auxiliary power oscillation damping control for damping LFOs. This approach is compared with a traditional power system stabilizer (PSS) for a two-area power system. Next, the research is extended by deploying grid forming (GFM) controls, which by actively controlling the voltage and frequency dynamics emulate the behavior of traditional synchronous generators. The paper analyzes two GFM control strategies: virtual synchronous machine (VSM) and droop control, and demonstrates their effectiveness in damping LFOs in the test system. The simulation results reveal that the performance of the proposed GFM-VSM rivals that of the PSS and is better than the GFL-power oscillation damper.

Figures

Figures reproduced from arXiv: 2505.24204 by the authors.

Figure 1
Figure 1. Proposed GFL-POD Controller [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Droop Controller [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Current Controller device is disconnected and the SG1 generates 1000 MW. The PSS model used in this study is the PSS2B. The electrical model of the CIG with the POD used in this study consists of the generator converter model REGCA and electrical control model REECA and a user-defined PPC model in PSS/E. The variables VFlag and QFlag in the REECA model [18] are set to 1. The end-user has a choice through a flag to a… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: VSC Interface for the Proposed GFM [PITH_FULL_IMAGE:figures/full_fig_p004_4.png]
Figure 5
Figure 5. Figure 5: Two-area System with CIG Device [PITH_FULL_IMAGE:figures/full_fig_p004_5.png]
Figure 6
Figure 6. Figure 6: Active Power Flow from Bus 2 to 3 when Tie Line Impedance Changes [PITH_FULL_IMAGE:figures/full_fig_p004_6.png]
Figure 8
Figure 8. Figure 8: Active Power Flow from Bus 2 to 3 when Load changes [PITH_FULL_IMAGE:figures/full_fig_p005_8.png]

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Reference graph

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