1. Introduction
With the increasing penetration of renewable energy in power systems, the risk of grid outages and voltage/frequency disturbances has grown significantly. In this context, the battery energy storage system (BESS) has emerged as a critical component for enhancing grid resilience and enabling black start capability. The battery energy storage system can balance the intermittent output of photovoltaic systems and assist in restoring power supply after a major blackout. This paper investigates the contribution of the battery energy storage system to improving the black start capability of a distribution network. We evaluate the role of the battery energy storage system in smoothing fluctuations and disturbances related to voltage and frequency variations after unexpected disturbances. Simulation studies are conducted on the IEEE 33-bus test network to assess the dynamic performance of the battery energy storage system in restoring power and reducing disturbances during black start. The results demonstrate that by employing the battery energy storage system in the black start process, the normal power supply for all loads in the network is guaranteed.
2. Model of Battery Energy Storage System Supporting Grid Black Start
2.1 Equivalent Circuit Model of the Battery Energy Storage System
To accurately model the battery energy storage system, we adopt a controlled voltage source and a fixed internal resistance to simulate the charging and discharging behavior of the battery energy storage system. The simplified equivalent circuit model is shown in Figure 1 (conceptual description). The charging and discharging voltage of the controlled voltage source is given by Equation (1).
\[
E = E_0 – K \frac{Q}{Q – \int i(t) dt} \cdot i(t) + A\exp\left(-B \int i(t) dt\right) + U_{RC}
\]
where \(E\) is the battery terminal voltage, \(E_0\) is the constant voltage, \(K\) is the polarization coefficient, \(Q\) is the battery capacity, \(i(t)\) is the dynamic current, \(\int i(t)dt\) is the accumulated charge, \(A\) and \(B\) are exponential voltage and capacity constants respectively, and \(U_{RC}\) represents the RC network voltage. The internal resistance of the battery energy storage system is assumed constant in this study.
2.2 Calculation of Equivalent Parameters of the Battery Energy Storage System
The charging/discharging efficiency of the battery energy storage system and its internal resistance can be expressed as Equation (2).
\[
\eta = \frac{V_{\text{nom}} I_{\text{nom}}}{V_{\text{nom}} I_{\text{nom}} \pm I_{\text{nom}}^2 R_0}, \quad R_0 = V_{\text{nom}} \frac{1 – \eta}{0.2 I_{\text{nom}}}
\]
where \(V_{\text{nom}}\) and \(I_{\text{nom}}\) are nominal voltage and current, and \(\eta\) is the efficiency. During the black start process, the battery energy storage system compensates for power deficits when the system generation cannot meet the load demand, or absorbs excess power to smooth fluctuations when generation exceeds demand. The state-of-charge (SOC) of the battery energy storage system is calculated using Equation (3).
\[
\text{SOC}(t) = \text{SOC}_0 + \frac{\int P_{\text{BESS}}(t) dt}{E_{\text{rated}}}
\]
where \(\text{SOC}_0\) is the initial SOC, \(P_{\text{BESS}}(t)\) is the instantaneous power (positive for discharge, negative for charge), and \(E_{\text{rated}}\) is the rated energy capacity.
3. Simulation Model Description
We select the IEEE 33-bus test network for our study. The network includes photovoltaic (PV) systems and two 1 MVA diesel generators connected at buses 3 and 13. The transformer tap is automatically regulated by an on-load tap changer (OLTC). The load active and reactive power curves are shown in Figure 3 (conceptual). The PV active and reactive power output curves are shown in Figure 4 and Figure 5 (conceptual). The control block diagram of the battery energy storage system is depicted in Figure 6 (conceptual), consisting of PQ control, frequency control, and charging control. The charging control maintains the SOC within allowable limits. Considering the PV output profile, the charging/discharging schedule of the battery energy storage system is given in Figure 7 (conceptual). Table 1 summarizes the key parameters of the simulation system.
| Parameter | Value |
|---|---|
| Rated apparent power of BESS | 5 MVA |
| Rated active power of BESS | 2.5 MW |
| Rated energy capacity of BESS | 10 MWh |
| Diesel generator rating (each) | 1 MVA |
| PV system rating | 2 MW |
| Load peak (total) | ~3.7 MW |
| Base voltage (LV side) | 0.4 kV |
| Base voltage (MV side) | 12.66 kV |
4. Simulation Results and Analysis
4.1 Black Start Study
In the black start scenario, we assume the IEEE 33-bus system is disconnected from the main grid, and all loads and generators are tripped. Two diesel generators (DG1 and DG2) are used to restore the network in island mode. To evaluate the impact of the battery energy storage system, we compare two cases:
- Case 1 (Without BESS): Two generators restore the network without the battery energy storage system.
- Case 2 (With BESS): One generator (DG1) and the battery energy storage system restore the network.
In Case 1, the system restores power without the battery energy storage system. Figure 8 (conceptual) shows the system frequency and voltage magnitudes. The simulation starts with DG1 connected, all other generators and loads disconnected. Then nine loads are restored in six stages, keeping frequency above 47 Hz. At t=130 s, DG2 is connected. Finally, the remaining four loads are restored. The total black start time is 180 s, and the two DGs can only restore 53% of the total load demand.
In Case 2, DG1 and the battery energy storage system are initially operated. By leveraging the battery energy storage system’s capability in voltage and frequency control, 53% of the total load is restored in 120 s. Figure 10 (conceptual) shows the system frequency and voltage magnitudes, and Figure 11 (conceptual) shows the active power outputs of DG1, DG2, and the battery energy storage system. Compared to the case without the battery energy storage system, the battery energy storage system enables faster network restoration. The total load in the network with the battery energy storage system can be 100% supplied. Table 2 summarizes the comparison.
| Indicator | Case 1 (Without BESS) | Case 2 (With BESS) |
|---|---|---|
| Time to restore 53% load | 180 s | 120 s |
| Final load restoration level | 53% | 100% |
| Maximum frequency deviation | > 3 Hz below nominal | < 0.5 Hz below nominal |
4.2 Frequency Control Study
To investigate the ability of the battery energy storage system to regulate active power during frequency steps, we set two scenarios:
- Case 1 (Without BESS): DG connected to bus 03, battery energy storage system inactive.
- Case 2 (With BESS): DG connected to bus 03, battery energy storage system connected to bus 18.
At the start, the PV system and DG2 are disconnected, and the loads consume maximum power. Figure 12 (conceptual) shows the system frequency dropping from 50 Hz to 49.5 Hz instantly. Figure 13 (conceptual) shows the active power changes of DG1 and the battery energy storage system. With the battery energy storage system, the active power output from the medium-voltage grid is reduced by about 0.75 MW, as shown in Figure 14 (conceptual). This demonstrates that the battery energy storage system provides fast frequency response and reduces the dependence on upstream grid power.
4.3 Voltage Control Study
To study the battery energy storage system’s performance in supporting voltage during dips, we set similar scenarios. The battery energy storage system is configured to regulate its reactive power when the voltage drops by 12%. At the start, PV and DG2 are disconnected, and loads consume maximum power. The voltage at the transformer low-voltage side initially drops by 4% (Figure 15, conceptual). Figures 16 and 17 (conceptual) show the reactive power outputs of the battery energy storage system, DG1, and the medium-voltage grid, as well as the voltage at the battery energy storage system’s transformer. The battery energy storage system increases its reactive power output by 33% to support voltage, limiting the voltage drop at bus 18 to about 2%, compared to a 3% drop without the battery energy storage system (Figure 18, conceptual).
4.4 Fault Ride-Through Study
We analyze the battery energy storage system’s support during a three-phase short-circuit fault at the 66 kV terminal (high-voltage side of the feeder transformer) with a duration of 0.82 s. Figure 19 (conceptual) compares the total reactive power of the battery energy storage system with and without connection. When the battery energy storage system is disconnected, reactive power is zero; when connected, it initially operates in under-excitation mode (consuming reactive power) and then switches to over-excitation mode to inject reactive power into the grid. Figure 20 (conceptual) compares the voltage magnitudes at three critical buses (bus 18, bus 25, bus 33) for both cases. Table 3 lists the voltage magnitudes during and after the fault.
| Bus | Voltage during fault (p.u.) – With BESS | Voltage during fault (p.u.) – Without BESS | Voltage after fault (p.u.) – With BESS | Voltage after fault (p.u.) – Without BESS |
|---|---|---|---|---|
| 25 | 0.20 | 0.18 | 0.974 | 0.969 |
| 18 | 0.31 | 0.18 | 1.01 | 0.95 |
| 33 | 0.21 | 0.17 | 0.95 | 0.93 |
The results show that the battery energy storage system significantly improves the voltage profile during and after the fault, reducing voltage dips and enhancing recovery speed.
5. Conclusion
This study evaluates the effectiveness of the battery energy storage system in grid black start and its performance during frequency and voltage disturbances. Through comparative analysis under various scenarios, we verify that adding a battery energy storage system aids the black start process and improves system stability under disturbances. The simulation results indicate that using the battery energy storage system during black start facilitates faster network restoration compared to without the battery energy storage system. Moreover, during the black start process, the battery energy storage system can satisfy the full load demand, whereas without the battery energy storage system, the load cannot be completely supplied. In the case of voltage sags, the battery energy storage system can quickly provide reactive power support to maintain voltage stability. Additionally, the frequency response of the battery energy storage system helps reduce the system frequency deviation, thereby decreasing the required power support from the upstream grid. These findings underscore the critical role of the battery energy storage system in modern power systems for enhancing black start capability and overall grid resilience.