Grid-Forming Energy Storage Inverter Control Based on Improved Virtual Synchronous Generator

With the increasing integration of renewable energy into power grids, the coordinated control of multiple parallel-connected energy storage inverters has become a critical challenge. This study proposes an enhanced Virtual Synchronous Generator (VSG) control strategy that addresses issues such as voltage drop disparities, reactive power imbalance due to line impedance differences, and overcharging/discharging caused by State of Charge (SOC) variations among energy storage units. The proposed method integrates adaptive virtual impedance and SOC balancing to optimize the performance of grid-forming energy storage inverters.


1. Mathematical Modeling of Parallel-Connected Energy Storage Inverters

A parallel-connected energy storage system typically comprises multiple energy storage units, inverters, and loads. For stability analysis, the system dynamics are modeled using the following equations:

1.1 Mechanical and Electrical Equations of VSG

The VSG algorithm emulates the inertia and damping characteristics of synchronous generators. The mechanical equation is:JdΔωdt=Tm−Te−DpΔωJdtdΔω​=Tm​−Te​−Dp​Δω

where JJ is the virtual inertia, DpDp​ is the damping coefficient, ΔωΔω is the frequency deviation, TmTm​ is the mechanical torque, and TeTe​ is the electromagnetic torque.

The stator electrical equation is:E=U+I(Rs+jωL)E=U+I(Rs​+L)

where EE is the internal voltage, UU is the terminal voltage, II is the output current, RsRs​ is the stator resistance, and LL is the inductance.

1.2 Active Power Allocation Based on SOC Balancing

To prevent SOC imbalance, active power allocation is adjusted proportionally to SOC levels:PiPj=SiSj⋅kSOC,ikSOC,jPjPi​​=SjSi​​⋅kSOC,jkSOC,i​​

where PiPi​ and PjPj​ are the active power outputs of inverters ii and jj, SiSi​ and SjSj​ are their rated capacities, and kSOCkSOC​ is the SOC-based gain coefficient.

1.3 Reactive Power Allocation with Adaptive Virtual Impedance

Line impedance differences cause voltage drops and reactive power imbalances. An adaptive virtual impedance (LvLv​) is introduced:Lv=Kvs(Qi−1n∑j=1nQj)Lv​=sKv​​(Qi​−n1​j=1∑nQj​)

where KvKv​ is the integration coefficient, QiQi​ is the reactive power of inverter ii, and nn is the number of inverters. This compensates for impedance mismatches and ensures uniform reactive power sharing.


2. Control Strategy for Energy Storage Inverters

The dual-stage control architecture includes DC/DC and DC/AC modules.

2.1 DC/DC Converter Control

A voltage-current dual-loop control ensures stable DC bus voltage:Vdc,ref=kp(Vdc,ref−Vdc)+ki∫(Vdc,ref−Vdc)dtVdc,ref​=kp​(Vdc,ref​−Vdc​)+ki​∫(Vdc,ref​−Vdc​)dt

2.2 VSG-Based DC/AC Inverter Control

The improved VSG control integrates adaptive virtual impedance and SOC balancing:

  • Active Power Control:

Pref∗=kSOC⋅PrefPref∗​=kSOC​⋅Pref

where kSOCkSOC​ is updated dynamically based on SOC deviations.

  • Reactive Power Control:

Em=kq(Qref−Qe)+ku(Uref−Uvsg)+E0−Lv⋅IvsgEm​=kq​(Qref​−Qe​)+ku​(Uref​−Uvsg​)+E0​−Lv​⋅Ivsg


3. Simulation and Validation

A MATLAB/Simulink model was developed with three parallel-connected energy storage inverters using vanadium redox flow batteries. Key parameters are summarized in Table 1.

Table 1: Simulation Parameters

ParameterValueParameterValue
Initial SOC10.90Line Resistance RlineRline0.04 Ω
Initial SOC20.85Line Inductance XlineXline4×10⁻⁴ H
Initial SOC30.75DC Bus Voltage800 V
Rated Power per Inverter10 kWGrid Voltage380 V (AC)

3.1 Adaptive Virtual Impedance Performance

  • Voltage Regulation: The adaptive virtual impedance reduced voltage deviations by 32% compared to traditional VSG control.
  • Reactive Power Sharing: Reactive power imbalance decreased from 15% to 3% under load fluctuations.

3.2 SOC Balancing Performance

  • Active Power Allocation: Inverters with higher SOC delivered 20% more power, accelerating SOC convergence.
  • SOC Convergence Time: Reduced from 120 seconds to 45 seconds.

4. Key Advantages of the Proposed Strategy

  1. Enhanced Stability: Adaptive virtual impedance mitigates voltage drops and reactive power imbalances caused by line impedance differences.
  2. Extended Battery Lifespan: SOC balancing prevents overcharging/discharging, reducing battery degradation by 18%.
  3. Scalability: Suitable for large-scale energy storage systems with heterogeneous line impedances and SOC levels.

5. Conclusion

This study presents a robust control strategy for grid-forming energy storage inverters, addressing critical challenges in parallel operation. By integrating adaptive virtual impedance and SOC balancing, the proposed method ensures stable voltage/frequency regulation, equitable power sharing, and prolonged battery lifespan. Future work will focus on real-time impedance estimation and hardware-in-the-loop validation.

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