Abstract
This article presents an in-depth analysis and approach for the optimal allocation of vanadium redox flow battery (VRB) energy storage systems (ESS) in active distribution networks (ADNs). The objective is to enhance wind power integration and optimize the economic performance of ADNs. By considering the dynamic efficiency and lifetime of VRBs, this study aims to maximize the benefits of wind power consumption, reduce load interruptions, minimize greenhouse gas emissions, and minimize network losses. An optimization model is developed, validated, and tested using a modified IEEE 33-bus system. The results demonstrate the effectiveness of the proposed approach in determining the optimal size and location of vanadium redox flow battery energy storage system for ADN applications.
Introduction
Active distribution networks (ADNs) are evolving to accommodate increasing amounts of renewable energy sources, such as wind and solar. However, the intermittent nature of renewable energy poses challenges for grid stability and reliability. Battery energy storage system (ESS) have emerged as a promising solution to mitigate these challenges by providing ancillary services and enhancing grid flexibility. Among various battery technologies, vanadium redox flow batteries (VRBs) are particularly suitable for large-scale energy storage applications due to their high energy density, long cycle life, and modular scalability.
This article proposes an optimal allocation method for vanadium redox flow battery energy storage system in ADNs, focusing on the dynamic efficiency and lifetime of VRBs. By integrating these factors into the optimization framework, the approach ensures that the designed VRB ESSs can maximize the economic benefits for ADNs while ensuring reliable and efficient operation.
Vanadium Redox Flow Battery (VRB) Characteristics
Dynamic Efficiency and Power Output
VRBs exhibit dynamic efficiency, which varies with the state of charge (SOC) and power output. The charging and discharging efficiencies are typically modeled as functions of SOC and power level. These efficiencies significantly impact the energy storage and retrieval processes, thereby influencing the overall performance of vanadium redox flow battery energy storage system.
Table 1 summarizes the key characteristics of VRBs in terms of their power and energy capacities, efficiencies, and cycle life.
| Characteristic | Value |
|---|---|
| Power Capacity | 1 MW |
| Energy Capacity | 5 MWh |
| Charging Efficiency | 85% – 95% |
| Discharging Efficiency | 85% – 95% |
| Cycle Life | 10,000+ cycles |
Cycle Life and Degradation
The cycle life of VRBs is influenced by several factors, including the depth of discharge (DoD), temperature, and charging/discharging rates. the cycle life decreases with increasing DoD. This degradation can significantly impact the long-term economic viability of vanadium redox flow battery energy storage system.
Optimization Model for VRB ESS Allocation
The optimal allocation of vanadium redox flow battery energy storage system in ADNs involves identifying the best size and location to maximize the overall benefits. This section outlines the proposed optimization model, considering various technical and economic factors.
Objective Function
The objective function aims to minimize the net cost associated with vanadium redox flow battery energy storage system deployment, which includes investment costs, maintenance costs, energy savings, and penalties for load interruptions and wind curtailment.
textMinimizef=C+TBd−KENScdotEENS−KACcdotEAC+TC+PC
where:
- C represents the total costs excluding VRB investment and replacement costs.
- TBd is the daily energy savings due to reduced energy purchases.
- KENS and KAC are the unit costs of load interruption and wind curtailment, respectively.
- EENS and EAC are the expected energy not served and abandoned wind energy, respectively.
- TC and PC are the total capital and replacement costs of vanadium redox flow battery energy storage system.
Constraints
Several constraints must be considered to ensure the feasibility and reliability of the ADN with vanadium redox flow battery energy storage system integration. These include:
- VRB Capacity Constraints:Ptextrated,min<Ptextrated<Ptextrated,maxquadtextandquadEtextrated,min<Etextrated<Etextrated,max
- Node Voltage Constraints:VtextminleqVleqVtextmax
- Grid Power Constraints:Ptextgrid,minleqPtextgridleqPtextgrid,max
- VRB Power Output Constraints:∣PtextVRB∣leq∣Pc(p.u.)∣cdotPtextVRB,rated
- SOC Constraints:textSOCtextminleqtextSOCleq1
Energy Management Strategy
The energy management strategy determines the charging and discharging behavior of vanadium redox flow battery energy storage system based on the wind power output, load demand, and grid power availability. The strategy ensures that the SOC is maintained within acceptable limits to optimize the use of stored energy and minimize load interruptions and wind curtailment.
Case Study: Modified IEEE 33-Bus System
To validate the proposed optimization model, a modified IEEE 33-bus system with integrated wind power generation is used. The system parameters are summarized in Table 2.
| Parameter | Value |
|---|---|
| Total Wind Capacity | 1 MW (600 kW + 400 kW) |
| Load Range | 2.25 – 2.75 MW |
| Grid Power Limits | 1.775 – 2.05 MW |
| Node Voltage Limits | 0.94 – 1.06 p.u. |
| Electricity Price | 0.078 $/kWh |
| VRB Lifetime | 10 years |
| Discount Rate | 10% |
Results and Analysis
The optimization results indicate that the optimal location for a vanadium redox flow battery energy storage system with a capacity of 176 kW and 1345 kWh is node 15. Figure 2 shows the total cost function as a function of VRB capacity at the optimal location.
With the optimal vanadium redox flow battery energy storage system deployment, the ADN experiences significant improvements in various performance metrics:
- Reduced Grid Power Dependence: The grid power requirement decreases from 43.6973 MWh to 42.8908 MWh, reducing the need for grid energy purchases.
- Reduced Load Interruptions and Wind Curtailment: The expected energy not served (EENS) decreases from 263.956 kWh to 205.46 kWh, and the abandoned wind energy (EAC) reduces from 11.37% to 5.29%.
- Improved Economic Performance: The total cost savings, including reduced energy costs and penalties, outweigh the additional investment and replacement costs of the vanadium redox flow battery energy storage system.
Table 3 summarizes the key cost components with and without vanadium redox flow battery energy storage system deployment.
| Cost Component | Without VRB | With Optimal VRB |
|---|---|---|
| Total Cost ($) | 104.17 | 61.48 |
| Investment Cost ($) | 0 | 98.395 |
| Replacement Cost ($) | 0 | 10.27 |
| Energy Savings ($) | 0 | 57.53 + 32.73 |
| Penalties ($) | 63.03 + 41.14 | 25.83 + 19.27 |
Table 3: Cost breakdown with and without VRB deployment.
SOC and Dynamic Efficiency Trends
The SOC and dynamic efficiency trends over a typical day with the optimal vanadium redox flow battery energy storage system deployment. The SOC is managed to ensure sufficient energy availability during peak demand periods, while minimizing unnecessary charging and discharging cycles.
Conclusion
This article proposes an optimal allocation method for vanadium redox flow battery energy storage system in ADNs to enhance wind power integration and optimize economic performance. By considering the dynamic efficiency and lifetime of VRBs, the approach ensures that the designed vanadium redox flow battery energy storage system maximize the benefits of wind power consumption while minimizing load interruptions, greenhouse gas emissions, and network losses. The results from the modified IEEE 33-bus system demonstrate the effectiveness of the proposed optimization framework in determining the optimal size and location of vanadium redox flow battery energy storage system for ADN applications.
Future work could explore more detailed modeling of VRB degradation mechanisms and the integration of advanced control strategies to further improve the performance of vanadium redox flow battery energy storage system in ADNs. Additionally, the impact of uncertainties in wind power and load forecasts on the optimal allocation of vanadium redox flow battery energy storage system warrants further investigation.