1. Introduction
With the rapid growth of distributed renewable energy systems, solar inverters have become critical components in modern power grids. This study focuses on optimizing the parallel operation of 10 kW single-phase photovoltaic (PV) energy storage inverters using a virtual synchronous generator (VSG) strategy. By emulating the inertia and damping characteristics of traditional synchronous generators, the proposed approach addresses challenges such as unstable dynamic responses, power imbalance, and harmonic distortion in multi-inverter systems.
2. Hardware Design of Solar Inverter
2.1 Topology Selection and Efficiency Analysis
The solar inverter comprises a bidirectional DC/DC converter and a DC/AC inverter. For the DC/DC stage, four non-isolated topologies were analyzed: Boost/Buck, Half-Bridge, Cuk, and SEPIC/Zeta. Key metrics included voltage stress, inductor current, and switching losses.
Table 1: Comparison of DC/DC Topologies
| Parameter | Boost/Buck | Half-Bridge | Cuk | SEPIC/Zeta |
|---|---|---|---|---|
| Voltage Stress | High | Low | Moderate | High |
| Inductor Current | 138 A | 102 A | 151 A | 120 A |
| Switching Losses | 18% | 12% | 22% | 25% |
The half-bridge topology was selected due to its low voltage stress (460 V), minimal inductor current ripple (20%), and 98% efficiency.
For the DC/AC stage, the Heric topology was chosen for its low leakage current (<30 mA) and high efficiency (98.5%). Key components include:
- IGBTs: IXYS IXYK120N120C3 (1200 V/240 A)
- Filter Inductors: 0.2 mH
- Capacitors: 10 μF
2.2 Simulation and Validation
A Simulink model verified the design:
- DC/DC Boost Mode: Input = 240 V, Output = 450 V, efficiency = 97.8%.
- DC/AC Inversion: Output = 220 V/50 Hz, THD < 2%.
3. VSG-Based Power Sharing Control
3.1 Emulation of Synchronous Generator Dynamics
The VSG algorithm replicates the swing equation of synchronous generators:Pref−P=JdtdΔω+DΔω+kp(ωref−ω)Qref−Q=kq(Uref−U)
where J (inertia), D (damping), kp, and kq are optimized parameters.
Table 2: Impact of VSG Parameters on Dynamic Response
| Parameter | Range | Overshoot | Settling Time (s) |
|---|---|---|---|
| J | 1–35 kg·m² | 5%–25% | 0.1–0.5 |
| D | 500–2000 | 3%–15% | 0.08–0.3 |
| kp | 500–4000 | 4%–20% | 0.07–0.4 |
3.2 Decoupling and Virtual Impedance
To achieve accurate power sharing, the output impedance must be inductive. A virtual impedance loop and second-order generalized integrator (SOGI) were integrated:Zv=Rv+jωLvUref=E−Zv⋅Io
where Lv=3.5 mH minimized harmonic coupling.
4. Dynamic Performance Optimization
4.1 Voltage Sag Compensation
Uncompensated voltage sag reached 20% under 10 kW load. A feedforward compensation term reduced this to 1%:ΔU=UgridP(Rv+Rl)+Q(Xv+Xl)
4.2 Frequency-Adaptive VSG with QABC Algorithm
A quantum-enhanced artificial bee colony (QABC) algorithm optimized J and D dynamically. The fitness function combined THD and ITAE:Fitness=A⋅THD+B⋅ITAE+C⋅∣ΔP∣+D⋅∣ΔQ∣
Key improvements:
- Convergence speed: 30% faster than standard ABC.
- THD reduction: 15.6% (current), 16.3% (voltage).
Table 3: QABC-Optimized Parameters
| Scenario | J (kg·m²) | D (N·s/m) | ξ (Damping Ratio) |
|---|---|---|---|
| Light Load (5 kW) | 14 | 1220 | 0.65 |
| Heavy Load (15 kW) | 18 | 1750 | 0.72 |
5. Experimental Validation
A 10 kW prototype was tested under grid-connected, islanded, and parallel modes.
5.1 Power Sharing Accuracy
Two inverters (2:1 capacity ratio) shared 15 kW + 15 kVar loads:P1:P2=2:1,Q1:Q2=2:1
Table 4: Power Sharing Deviation
| Metric | Traditional VSG | Proposed VSG + QABC |
|---|---|---|
| Active Power Error | 8.2% | 2.9% |
| Reactive Power Error | 6.7% | 3.5% |
5.2 Transient Response
The optimized system reduced settling time by 50% (0.37 s vs. 0.73 s) and overshoot by 64% during load steps.
6. Conclusion
This work demonstrates a comprehensive VSG-based control strategy for single-phase solar inverters, enhancing grid stability and power quality. Key innovations include virtual impedance decoupling, frequency-adaptive parameter tuning, and a quantum-inspired optimization algorithm. Experimental results validate superior dynamic performance (THD < 1.5%, power sharing error < 3.5%), making the system viable for high-penetration renewable grids.