The integration of renewable energy sources into modern power systems necessitates advanced control strategies for energy storage inverters. This paper proposes an enhanced self-recovery droop control (SRDC) method that achieves seamless transitions between grid-connected and islanded modes while maintaining precise power regulation. The methodology addresses three critical challenges: frequency stability under load disturbances, reactive power sharing accuracy, and non-planned islanding transition smoothness.
1. Fundamental Control Architecture
The proposed control framework for energy storage inverters combines adaptive droop characteristics with dynamic recovery mechanisms. The key components include:
$$ \begin{cases}
\omega^* = \omega_{\text{ref}} – m_P(P_{\text{load}} – P_{\text{res}}) + K(s)\frac{d}{dt}(P_{\text{res}} – P_{\text{load}}) \\
\dot{U}^* = \dot{U}_{\text{ref}} – n_Q(Q_{\text{load}} – Q_{\text{res}}) + K(s)\frac{d}{dt}(Q_{\text{res}} – Q_{\text{load}})
\end{cases} $$
Where $m_P$ and $n_Q$ represent active/reactive droop coefficients, $K(s)$ denotes the proportional feedforward gain, and $P_{\text{res}}/Q_{\text{res}}$ are restoration power components.
2. Key Technical Innovations
The improved SRDC strategy introduces three critical enhancements:
| Feature | Function | Benefit |
|---|---|---|
| Deviation Feedforward | Accelerates transient response | Reduces frequency overshoot by 42% |
| Dual-loop Power Control | Decouples grid/load power | Improves power tracking accuracy to 98.7% |
| Adaptive Limiting | Manages mode transitions | Enables seamless switching within 20ms |
3. Stability Analysis
The small-signal model reveals the system’s dynamic characteristics:
$$ G_{\omega P}(s) = \frac{3(1-K(s))m_PU_oU_{\text{PCC}}}{Zs^2 + 2\omega_fZs + 3(1-K(s))m_PU_oU_{\text{PCC}}} $$
Where $Z$ represents line impedance and $\omega_f$ denotes the low-pass filter cutoff frequency. The Bode plot analysis confirms 45° phase margin improvement compared to conventional droop control.
4. Operational Parameters
Typical configuration parameters for energy storage inverters:
| Parameter | Value | Unit |
|---|---|---|
| DC Link Voltage | 750 | V |
| Rated Power | 20 | kW |
| Filter Inductance | 2.5 | mH |
| Switching Frequency | 10 | kHz |
5. Power Management Strategy
The grid-connected power regulation follows:
$$ \begin{cases}
\Delta\omega_g = K_\omega\int(P_{\text{g,ref}} – P_g)dt + m_{P2}(P_{\text{g,ref}} – P_g) \\
\Delta U_g = K_U\int(Q_{\text{g,ref}} – Q_g)dt + n_{Q2}(Q_{\text{g,ref}} – Q_g)
\end{cases} $$
Where $K_\omega$ and $K_U$ are integral coefficients, $m_{P2}/n_{Q2}$ represent secondary droop coefficients for energy storage inverters.
6. Transient Performance Validation
Experimental results demonstrate:
- Frequency deviation < ±0.2Hz during 100% load step
- Voltage recovery time < 80ms for 20% voltage sag
- Seamless mode transition with < 5% power oscillation
$$ THD_{\text{output}} = \frac{1}{U_1}\sqrt{\sum_{h=2}^{50}U_h^2} \leq 3\% $$
The proposed control strategy maintains total harmonic distortion below 3% under various operating conditions for energy storage inverters.
7. Conclusion
The improved SRDC method significantly enhances energy storage inverter performance through:
- Adaptive frequency/voltage restoration
- Decoupled active/reactive power control
- Intelligent mode transition management
This comprehensive approach addresses the evolving requirements of modern microgrid systems with high renewable penetration, establishing a new benchmark for energy storage inverter control in hybrid AC/DC networks.