Grid-Forming Inverters: Control Architecture and Application in High-DER Power Systems

Published: June 2026 Technical Level: Advanced Category: Protection Systems

Abstract

Grid-following inverters — the dominant inverter control architecture in current solar PV and battery storage installations — require a pre-existing voltage and frequency reference provided by synchronous generators or the utility grid to operate. As synchronous generation is displaced by inverter-based resources and the inertia of the bulk power system declines, the stability properties that grid-following inverters depend on become less reliable, creating a potential feedback instability where the loss of synchronous inertia degrades the grid conditions that inverter-based resources need to operate stably. Grid-forming inverter control architectures address this problem by enabling inverter-based resources to establish and maintain voltage and frequency references autonomously, without requiring an external reference — a capability that is essential for stable operation of microgrids and isolated islands, and that is increasingly recognized as a necessary attribute of bulk power system inverter-based resources at high penetration levels. This paper develops the control engineering basis of the principal grid-forming architectures — virtual synchronous machine (VSM), droop control, and matching control — their dynamic performance characteristics, and the stability analysis framework that determines when grid-forming capability is necessary versus the conventional grid-following architecture.

1. Introduction

The distinction between grid-following and grid-forming inverter behavior is rooted in the control loop architecture. A grid-following inverter uses a phase-locked loop (PLL) to synchronize its output current with the grid voltage phasor, then injects a current whose magnitude and phase angle are determined by the active and reactive power setpoints. The grid voltage — its magnitude, frequency, and phase — is an external input to the grid-following inverter's control system; the inverter is a current source that follows the grid. A grid-forming inverter, by contrast, internally generates a voltage phasor reference and uses that reference to produce a controlled voltage output. The inverter is a voltage source that can establish grid conditions rather than merely following them.

The practical significance of this distinction becomes apparent during grid disturbances. When a large generator trips and system frequency begins to decline, synchronous generators that remain online provide an immediate inertial response — their rotational kinetic energy flows into the grid as the rotational speed decreases, partially arresting the frequency decline before governor controls respond. Grid-following inverters provide no inertial response: their PLL tracks the declining frequency without injecting additional power, and their active power output remains at its setpoint. Grid-forming inverters with virtual inertia control — specifically, the virtual synchronous machine architecture — emulate the inertial response of a synchronous machine by momentarily increasing active power output when frequency declines, providing synthetic inertia that partially compensates for the loss of synchronous inertia.

2. Grid-Forming Control Architectures

2.1 Virtual Synchronous Machine

The virtual synchronous machine (VSM) architecture models the rotor dynamics of a synchronous machine in software and uses the resulting synthetic rotor state variables as the reference for the inverter's voltage controller. The VSM swing equation governs the synthetic rotor dynamics:

Jdωdt=Tmech−Telec−D(ω−ω0)J \frac{d\omega}{dt} = T_{mech} - T_{elec} - D(\omega - \omega_0)

Where: JJ is the virtual moment of inertia in kg·m², a tunable parameter that determines the synthetic inertia constant.

ω\omega is the virtual rotor angular velocity in rad/s.

TmechT_{mech} is the virtual mechanical torque setpoint (corresponding to the active power setpoint).

TelecT_{elec} is the virtual electromagnetic torque (corresponding to the inverter's actual active power output).

DD is the virtual damping coefficient in N·m·s/rad.

ω0\omega_0 is the nominal angular velocity, 2π×602\pi \times 60 rad/s.

When the grid frequency drops (meaning the external grid is below ω0\omega_0), the VSM's virtual rotor — which has a virtual inertia and is governed by the swing equation — decelerates more slowly than the frequency drop, creating a difference between the virtual rotor speed and the grid frequency that the controller translates into an increase in active power output. This power injection partially supports the grid frequency, emulating the inertial response of a physical synchronous machine. The magnitude of the inertial response is proportional to JJ and can be tuned to provide the synthetic inertia constant H=Jω02/(2Srated)H = J\omega_0^2 / (2 S_{rated}) that the grid operator requires.

2.2 Droop Control

The droop control architecture is a simpler grid-forming implementation that directly implements the frequency-active power and voltage-reactive power droop characteristics of synchronous generators without modeling rotor dynamics. The active power droop relationship is:

Pref=P0+1mp(ω0−ωmeas)P_{ref} = P_0 + \frac{1}{m_p}(\omega_0 - \omega_{meas})

Where: PrefP_{ref} is the active power reference command in per-unit.

P0P_0 is the nominal active power setpoint.

mpm_p is the active power droop coefficient (the frequency change per unit of active power change).

ωmeas\omega_{meas} is the measured grid frequency.

This droop characteristic causes the inverter to increase active power output when frequency falls below nominal — the same qualitative response as a synchronous generator's governor — without emulating the rotor inertia dynamics. The droop control response is immediate and does not require a grid voltage reference (the frequency measurement is derived from the inverter's own output voltage), making it suitable for islanded microgrid operation where no utility reference is available.

As a worked example, consider a 2 MW grid-forming inverter configured with a 5 percent droop, so its active-power gain is 1/mp=Prated/(droop⋅f0)=2/(0.05×60)=0.6671/m_p = P_{rated}/(\text{droop} \cdot f_0) = 2/(0.05 \times 60) = 0.667 MW/Hz. If the measured frequency dips by 0.2 Hz below nominal (from 60.0 to 59.8 Hz), the droop law commands an active-power increase of:

ΔP=1mp(ω0−ωmeas)=0.667×0.2=0.133 MW=133 kW\Delta P = \frac{1}{m_p}(\omega_0 - \omega_{meas}) = 0.667 \times 0.2 = 0.133 \ \text{MW} = 133 \ \text{kW}

Where the symbols are as defined above. The inverter therefore raises its output by 133 kW — about 6.7 percent of its rating — in immediate response to the 0.2 Hz dip, mirroring the governor action of a synchronous machine. The example also shows how the droop setting trades response stiffness against frequency range: a tighter 3 percent droop would command 2/(0.03×60)×0.2=2222/(0.03 \times 60) \times 0.2 = 222 kW for the same dip, giving a stronger response at the cost of a narrower frequency band before the inverter saturates at its rating.

3. Stability in High-DER Systems

The stability analysis framework for power systems with high penetration of grid-forming inverter-based resources differs fundamentally from the classical synchronous machine stability analysis because: the inverter's response time constants are in the millisecond range rather than the second range of synchronous machine electromagnetic transients; the inverter's control bandwidth interacts with the grid's LC resonance modes in ways that classical stability analysis does not capture; and the behavior of multiple parallel grid-forming inverters is more sensitive to their relative control parameters than the behavior of multiple parallel synchronous machines, which are physically coupled through their mutual electromagnetic torques.

The small-signal stability analysis for a microgrid with NN parallel grid-forming inverters requires linearizing the combined inverter control equations and network equations around the operating point, computing the eigenvalues of the resulting state-space matrix, and verifying that all eigenvalues have negative real parts. The critical eigenvalues — the ones whose real parts are closest to zero — determine the stability margins and guide the selection of the virtual inertia and droop coefficients. For practical microgrid designs, these parameters are tuned iteratively using time-domain simulation with detailed inverter models to verify that the transient response to load steps and generation disturbances meets the specified frequency and voltage nadir requirements.

Related Work

The analysis in this paper connects to several companion studies in this library. Readers concerned with the upstream and downstream engineering will find Renewable Energy Grid Integration develops a closely related aspect of the same problem, while Microgrid Design and Control extends the treatment into an adjacent domain. For the broader methodological context, Renewable Integration and Grid Stability Under IEEE 1547-2018 provides complementary depth.

Conclusion

Grid-forming inverter control addresses the feedback instability that emerges as synchronous generation is displaced by inverter-based resources: grid-following inverters require the voltage and frequency reference that synchronous machines provide, so their displacement erodes the very grid conditions they depend on, and the analysis developed in this paper shows that grid-forming control breaks this dependence by establishing the inverter as a voltage source that forms, rather than follows, the grid reference. The central engineering conclusion is that the virtual-synchronous-machine and droop control architectures synthesize the inertial and frequency-regulation behavior that the bulk system loses as synchronous inertia declines, enabling stable operation at high inverter penetration and in islanded microgrids. For the practicing engineer, the operative takeaway is that grid-forming capability is becoming a system-level necessity rather than a niche feature, because stability in high-DER systems depends on a sufficient share of grid-forming resources to anchor voltage and frequency, and the control architecture selected must be matched to the inertia and fault-current characteristics the application requires.

References

[1] IEEE Standard 1547-2018, Standard for Interconnection and Interoperability of Distributed Energy Resources, IEEE, 2018.

[2] Q.-C. Zhong and G. Weiss, "Synchronverters: Inverters That Mimic Synchronous Generators," IEEE Transactions on Industrial Electronics, vol. 58, no. 4, 2011.

[3] R. Lasseter et al., "CERTS Microgrid Laboratory Test Bed," IEEE Transactions on Power Delivery, vol. 26, no. 1, 2011.

[4] B. Johnson et al., "Synchronization of Parallel Single-Phase Inverters with Virtual Oscillator Control," IEEE Transactions on Power Electronics, vol. 29, no. 11, 2014.

[5] NERC, Reliability Guideline: BPS-Connected Inverter-Based Resource Performance, NERC, 2022.

[6] D. Gross et al., "On the Stability of Island-Forming Microgrids," IEEE Transactions on Power Systems, vol. 34, no. 3, 2019.

[7] EPRI, Grid-Forming Inverter Control: Status and Outlook, EPRI Technical Report 3002025987, 2023.

[8] P. Kundur, Power System Stability and Control, McGraw-Hill, 1994. (Classical stability analysis methodology.)