This study focuses on a 10kW single-phase energy storage inverter, proposing an optimized virtual synchronous generator (VSG) control strategy to address challenges in dynamic response stability and power distribution during parallel operation. Key innovations include circuit topology selection, adaptive parameter tuning, and harmonic suppression.
1. Circuit Topology Optimization
The energy storage inverter employs a bidirectional DC/DC converter and HERIC-based DC/AC module. The converter efficiency reaches 98.2% through topology optimization:
$$L = \frac{V_{in} \cdot D(1-D)}{2\Delta I \cdot f_{sw}}$$
$$C = \frac{I_{out} \cdot D}{\Delta V \cdot f_{sw}}$$
| Topology | Efficiency (%) | Component Count | Voltage Stress (V) |
|---|---|---|---|
| Half-Bridge | 98.2 | 6 | 460 |
| Full-Bridge | 96.8 | 8 | 920 |
| HERIC | 97.5 | 10 | 460 |
2. VSG Control Algorithm
The VSG control strategy emulates synchronous generator characteristics through inertial and damping simulation:
$$J\frac{d\Delta\omega}{dt} + D\Delta\omega = P_{ref} – P_{out}$$
$$V_{ref} = V_0 – k_q(Q_{ref} – Q_{out})$$
| Parameter | Range | Optimal Value |
|---|---|---|
| J (kg·m²) | 4.8-16.6 | 14 |
| D (N·s/m) | 1204-1752 | 1220 |
| k_p | 3000-6000 | 5000 |
3. Quantum-Enhanced Adaptive Control
The proposed quantum artificial bee colony (QABC) algorithm improves parameter optimization:
$$x_i^{t+1} = round\left[\alpha \cdot \ln\left(\frac{1}{u}\right) \cdot (p_{best} – x_i^t)\right]$$
$$fit = \int_0^T t|e(t)|dt + THD_u + THD_i$$
Comparative tests demonstrate superior performance:
| Algorithm | Settling Time (ms) | THDi (%) | Power Deviation (%) |
|---|---|---|---|
| Traditional VSG | 455 | 3.90 | 8.2 |
| QABC-VSG | 373 | 3.29 | 2.9 |
4. Experimental Validation
The 10kW energy storage inverter prototype achieves:
- Voltage regulation accuracy: ±1.2%
- Frequency stability: 50±0.1Hz
- Peak efficiency: 97.8%
$$P_{dist} = \frac{S_i}{\sum S_j}P_{total}$$
$$Q_{dist} = \frac{X_i^{-1}}{\sum X_j^{-1}}Q_{total}$$
Field tests with parallel systems show:
| Load Condition | Voltage Dip (%) | Recovery Time (ms) |
|---|---|---|
| No-load → 10kW | 1.2 | 120 |
| 10kW → 20kW | 2.8 | 180 |
This research significantly enhances the grid-forming capability of energy storage inverters, providing technical support for high-penetration renewable energy systems. The proposed control strategy demonstrates 64.6% improvement in power distribution accuracy and 15.6% reduction in harmonic distortion compared with conventional methods.