1. Introduction
As a core device in the energy internet, energy routers play a pivotal role in integrating distributed energy resources, energy storage systems, and electric vehicles (EVs) into smart grids. This study focuses on an energy router with multiple EV charging ports, photovoltaic (PV) generation, energy storage, and DC/AC load interfaces. The primary objective is to develop a coordinated control strategy that ensures stable DC bus voltage and achieves state-of-charge (SOC) balancing among multiple EVs, thereby prolonging battery life and enhancing grid stability.
EVs, when connected to the energy router, can act as mobile energy storage units. However, initial SOC discrepancies among EVs can lead to overcharging or over-discharging, damaging batteries and threatening grid stability. To address this, a hierarchical control strategy based on DC bus voltage signaling (DBS) is proposed, combined with an SOC balancing control method using improved droop control and consistency algorithms.
2. Energy Router Structure and Topology
The energy router investigated in this study comprises multiple ports: a power grid port, PV port, energy storage port, multiple EV ports, and DC/AC load ports. The grid port enables bidirectional energy exchange with the utility grid, while the PV port integrates renewable energy. The energy storage port stabilizes DC bus voltage fluctuations caused by intermittent PV generation, and the EV ports facilitate both charging and discharging of EVs as mobile storage.
2.1 Topology Description
The topology of the energy router is illustrated in Figure 1 (textual description). Key components include:
- PV Port: Outputs voltage \(U_{pv}\) and current \(I_{pv}\).
- Energy Storage Port: Features voltage \(U_{bat}\) and current \(I_{batt}\).
- EV Ports: Each port has voltage \(U_{ev}\) and current \(I_{ev}\).
- Grid Port: Uses a cascade H-bridge (CHB) structure for AC/DC conversion and a dual active bridge for electrical isolation.
3. Hierarchical Control Strategy of Energy Router
The control strategy is divided into three layers: power scheduling, DC bus voltage control, and converter control.
3.1 Power Scheduling Layer (Layer 1)
- Function: Receives grid dispatch commands and coordinates energy flow among PV, energy storage, and EVs to meet energy interconnection requirements.
- Key Objective: Maximize PV utilization while maintaining system stability.
3.2 DC Bus Voltage Control Layer (Layer 2)
- Function: Manages EV charging/discharging and energy storage operations based on DC bus voltage (\(U_{DC}\)) to ensure voltage stability within ±5% of the nominal value (700 V).
- Four Working Modes:ModeVoltage RangePV ControlEnergy Storage & EVsGrid Interaction1720–735 VDroop control (limited power)Absorb surplus PV powerIslanded or grid-connected2700–720 VMPPT controlAbsorb surplus PV powerGrid-connected (droop control)3680–700 VMPPT controlSupply power deficitGrid-connected (power compensation)4665–680 VMPPT controlSupply power deficit with gridGrid-connected (max power output)
3.3 Converter Control Layer (Layer 3)
- PV Converter: Switches between droop control (Mode 1) and MPPT control (Modes 2–4).
- Grid Converter: Uses voltage 外环 (outer loop) and current 内环 (inner loop) control for bus voltage stability.
- Energy Storage Converter: Employs voltage and current dual-loop control with SOC and current limits (Figure 2, textual description).
4. SOC Balancing Control for Electric Vehicles
4.1 Challenges in EV SOC Balancing
When multiple EVs are connected, traditional droop control may fail to balance SOC due to mismatched battery capacities and line impedances. The SOC of the g-th EV is defined as:\(SOC_g = SOC_{g0} – \frac{\int i_g dt}{C_{eg}}\) where \(SOC_{g0}\) is the initial SOC, \(i_g\) is the output current, and \(C_{eg}\) is the battery capacity. The derivative of SOC is:\(\dot{SOC}_g = -\frac{i_g}{C_{eg}}\) For SOC balancing, the ratio of output currents to capacities must be equal for all EVs: \(\frac{i_g}{C_{eg}} = \frac{i_j}{C_{ej}}\).
4.2 Improved Droop Control with Consistency Algorithm
To address impedance and capacity mismatches, a virtual current-based consistency algorithm is introduced. The droop control equation is modified as:\(U_{ref,g} = U^* – k \cdot i_g + \rho_{vEV,g}\) where \(\rho_{vEV,g}\) is the voltage correction term derived from the virtual current consistency control:\(\rho_{vEV,g} = k_{pb} \left( \bar{i}_{vEV} – i_{vEV,g} \right) + k_{ib} \int \left( \bar{i}_{vEV} – i_{vEV,g} \right) dt\) Here, \(\bar{i}_{vEV}\) is the average virtual current of all EVs, and \(k_{pb}, k_{ib}\) are PI control gains.
4.3 EV Working Modes
EVs switch between charging and discharging based on PV and load power:
- Charging Mode: Activated when \(P_{pv} > P_{load}\). EVs charge until reaching \(SOC_{max}\), then disconnect.
- Discharging Mode: Activated when \(P_{pv} < P_{load}\). EVs discharge until reaching \(SOC_{min}\), then disconnect.
5. Simulation Results and Analysis
Simulations were conducted in Matlab/Simulink to validate the control strategy. Key parameters are listed in Table 1.
Table 1: Simulation Parameters
| Parameter | Value |
|---|---|
| DC Bus Voltage | 700 V |
| PV Voltage | Variable |
| Energy Storage Capacity | 10 kWh |
| EV Battery Capacity | 20 kWh (each) |
| Switching Frequency | 15 kHz |
5.1 Case 1: Islanded Operation with PV Power Increase
- Initial Conditions: PV power < load power, bus voltage < 700 V. Energy storage discharges to stabilize voltage.
- EVs Added at 1.5 s: Two EVs with initial SOC of 46% and 49% start charging.
- Results: EV SOCs converge to 55% by 120 s, with bus voltage stable at 700 V (Figure 3, textual description).
5.2 Case 2: Grid-Connected Operation with PV Power Deficit
- Initial Conditions: PV power < load power, bus voltage 665 V. EVs (SOC 81% and 77%) discharge to support the grid.
- Energy Storage Stops at 2 s: Grid takes over power compensation.
- Results: EV SOCs balance at 79% by 600 s, bus voltage stabilizes at 700 V (Figure 4, textual description).
5.3 Case 3: High PV Power and Grid Interaction
- Initial Conditions: PV power > load power, bus voltage 735 V. Energy storage charges until \(SOC = 90\%\).
- PV Power Drops at 2 s: EVs and grid maintain voltage stability.
- Results: Bus voltage remains within ±3% of nominal value, demonstrating robust voltage control (Figure 5, textual description).
6. Conclusion
This study presents a coordinated control strategy for energy routers with multiple EV ports, achieving both DC bus voltage stability and EV SOC balancing. Key findings include:
- The hierarchical control strategy based on DC bus voltage effectively manages energy flow and maximizes PV utilization.
- The improved droop control with a consistency algorithm ensures rapid SOC balancing among EVs, preventing overcharging/over-discharging.
- Simulations validate the strategy’s effectiveness under various operating conditions, highlighting its potential for practical energy internet applications.