In the context of global efforts toward carbon peaking and carbon neutrality, the large-scale integration of renewable energy sources such as wind and photovoltaic power poses challenges to grid stability. Energy storage technology has emerged as a critical solution to enhance grid reliability, improve power quality, and support the widespread adoption of renewables. Among various storage methods, electrochemical energy storage, particularly battery energy storage systems, has gained significant attention due to its high energy density, reliability, safety, and flexible installation. However, the large-scale deployment of battery energy storage systems intensifies the demand for effective thermal management. Heat accumulation within battery packs, if not efficiently dissipated, can accelerate aging, reduce lifespan, and in severe cases, lead to thermal runaway, posing safety risks. Thus, designing cooling systems that ensure optimal heat dissipation, energy efficiency, and safe operation is paramount for the advancement of battery energy storage systems.
Current mainstream cooling methods for battery energy storage systems include air cooling and liquid cooling. Air cooling systems are simple and low-cost but offer inferior heat dissipation efficiency, cooling uniformity, and reliability compared to liquid cooling systems. Liquid cooling, with its excellent thermal performance and temperature homogeneity, is increasingly favored for large-scale battery energy storage system integration. Liquid cooling primarily encompasses indirect cold plate cooling and direct immersion cooling. Indirect cold plate cooling, though mature and applied in electric vehicles and small-scale energy storage stations, often requires complex coolant channel designs, substantial coolant volumes, and additional air-conditioning refrigeration units, increasing system complexity and cost. Direct immersion cooling, while effective for temperature uniformity, typically uses expensive electronic fluorinated fluids, large quantities of coolant, and imposes strict pressure control, limiting its scalability in battery energy storage systems.
Energy consumption is another critical aspect. In practice, cooling for battery energy storage systems often relies on air-conditioning refrigeration units, which can be energy-intensive. While existing research focuses on heat dissipation capabilities, less attention has been paid to energy efficiency and reduction. Therefore, designing rational cooling system processes is essential for improving energy efficiency and achieving sustainable, high-performance thermal management for battery energy storage systems. This paper proposes a novel indirect liquid cooling system based on Mechanical Vapor Recompression (MVR) falling film evaporation, utilizing water as the cooling medium. The system aims to leverage the high heat transfer efficiency of phase-change evaporation while minimizing energy consumption through MVR technology. We detail the system design, simulate its performance using Aspen Plus, conduct comparative energy and economic analyses with conventional refrigeration systems, and explore the effects of key thermodynamic parameters.
The proposed MVR falling film indirect liquid cooling system integrates a closed-loop design for battery modules. It consists of two main modules: the falling film indirect cooling module and the MVR module. The falling film module includes battery modules, liquid distributors, and vacuum falling film chambers formed by falling film plates attached to the battery sides. The MVR module comprises a compressor, a vapor-liquid separator, a condenser, a pressure-reducing valve, valves, and a circulation pump. The working process begins with system evacuation and water filling. Under vacuum, water from the separator and condenser is pumped to the distributors, forming a thin liquid film on the falling film plates. This film absorbs heat from the battery modules, evaporating into steam. Due to pressure differences, steam is drawn into the vapor-liquid separator, where liquid water is recirculated, and vapor is compressed by the compressor. The compressed vapor, at elevated temperature and pressure, is condensed in the condenser by exchanging heat with a cooling medium. The condensate then passes through a pressure-reducing valve to match the saturation pressure in the falling film chamber before returning to the cooling cycle.
The falling film indirect cooling structure eliminates complex internal channels found in traditional cold plates, reducing thermal resistance. Compared to immersion cooling, it significantly cuts coolant usage and cost, allowing battery modules to operate at atmospheric pressure, enhancing safety. The MVR principle enhances the heat exchange temperature difference with the environment, enabling efficient heat dissipation. For simulation, Aspen Plus software is employed with water as the component and the IAPWS-95 standard for thermodynamic properties. Key assumptions include neglecting pipeline energy losses, non-condensable gas effects, and steady-state operation. The compressor power is modeled as:
$$ W = \frac{m_v \Delta H_{id,v}}{\eta_c} $$
where \( W \) is the compressor power consumption in kW, \( m_v \) is the vapor mass flow rate in kg/s, \( \Delta H_{id,v} \) is the theoretical isentropic enthalpy change of vapor in kJ/kg, and \( \eta_c \) is the compressor efficiency. The evaporator heat transfer is modeled as:
$$ Q = m_w \Delta H_{w,e} $$
where \( Q \) is the cooling load in kW, \( m_w \) is the water mass flow rate in kg/s, and \( \Delta H_{w,e} \) is the enthalpy change of water during evaporation in kJ/kg. Assuming complete evaporation, \( m_w = m_v \). Initial design parameters are set as shown in Table 1.
| Design Parameter | Value |
|---|---|
| Cooling Load (kW) | 210 |
| Cooling Temperature (K) | 303 |
| Operating Pressure (Pa) | 4247 |
| Falling Film Water Flow Rate (kg/h) | 311 |
| Compression Temperature Rise (K) | 15 |
Simulation results indicate that with a cooling temperature of 303 K, the net cooling load for complete evaporation of 311 kg/h water is 204.492 kW, and the MVR compressor power consumption is only 14.227 kW. For comparison, a conventional first-level energy efficiency air-conditioning refrigeration system with a cooling capacity of 210 kW is considered. The performance comparison is summarized in Table 2.
| Cooling Temperature (K) | Latent Heat (kJ/kg) | Cooling Load (kW) | MVR Compressor Power (kW) | First-Level Refrigeration Power (kW) | Energy Saving of MVR vs. First-Level Refrigeration (%) |
|---|---|---|---|---|---|
| 303 | 2429.67 | 204.492 | 14.227 | 61.967 | 77.04 |
The MVR system achieves significant energy savings of 77.04% compared to the conventional system. This is attributed to the MVR system’s internal vapor compression cycle, which eliminates the need for an additional refrigerant loop, reducing compression work. The fundamental principle contrast is illustrated in the context of battery energy storage system cooling: MVR utilizes a single compression step to elevate vapor temperature for heat rejection, whereas conventional systems rely on multi-stage refrigeration cycles.
Key thermodynamic parameters influencing the MVR system performance are cooling temperature and compression temperature rise. The impact of these parameters on compressor power and energy saving effect is analyzed. The compressor power decreases with higher cooling temperature and lower compression temperature rise. For instance, with a compression temperature rise of 12 K, increasing the cooling temperature from 283 K to 313 K reduces compressor power by 1.311 kW (10.7%), as shown in the relation:
$$ \frac{\partial W}{\partial T_{cool}} < 0 $$
where \( T_{cool} \) is the cooling temperature. This reduction occurs because higher cooling temperatures result in higher vapor temperatures at compressor inlet, lowering the compression ratio and volume flow rate. The vapor density \( \rho_v \) increases with temperature, affecting compressor suction volume \( V_s \):
$$ V_s = \frac{m_v}{\rho_v} $$
Similarly, compressor power increases with compression temperature rise \( \Delta T_{comp} \). At 303 K cooling temperature, increasing \( \Delta T_{comp} \) from 10 K to 15 K raises compressor power by 4.883 kW (52.3%), due to higher pressure ratios. The energy saving effect relative to conventional systems improves with higher cooling temperature and lower compression temperature rise. For example, at 12 K compression rise, energy saving rises from 80.4% to 82.5% as cooling temperature increases from 283 K to 313 K. This trend underscores the importance of optimizing these parameters for battery energy storage system cooling to maximize efficiency.
An economic analysis is conducted using annualized cost (AC) and payback period (PBP) methods. The annualized cost includes capital, maintenance, and electricity costs over the system lifespan. The capital recovery factor is applied:
$$ C_{acc} = C_{ccm} \times \frac{i(1+i)^n}{(1+i)^n – 1} $$
where \( C_{ccm} \) is the initial investment cost, \( i \) is the interest rate (10%), and \( n \) is the lifespan (15 years). Maintenance cost \( C_{mc} \) is 10% of \( C_{acc} \). The annual electricity cost is:
$$ C_{rec} = C_{ee} \times W \times t $$
with electricity price \( C_{ee} = 0.8 \) RMB/kWh, system power consumption \( W \) in kW, and annual operating hours \( t = 3000 \) h. The salvage value \( S_a \) is calculated as:
$$ S_a = S \times \frac{i}{(1+i)^n – 1} $$
where \( S \) is the salvage value (20% of \( C_{ccm} \)). The payback period is given by:
$$ PBP = \frac{\ln\left(1 – \frac{C_{ccm}}{B_j}(i – r)\right)}{\ln\left(\frac{1+r}{1+i}\right)} $$
where \( B_j \) is the first-year savings and \( r \) is the discount rate (6%). Initial investment costs for the MVR system are detailed in Table 3, compared to a conventional system.
| Component | Quantity | Cost (RMB) |
|---|---|---|
| Steam Compressor | 1 | 12,000 |
| Condenser | 1 | 3,000 |
| Vapor-Liquid Separator | 1 | 1,000 |
| Pressure-Reducing Valve | 1 | 400 |
| Circulation Pump | 1 | 500 |
| Valves | 1 | 300 |
| Total Investment Cost | – | 17,200 |
For the conventional system, the initial investment cost is approximately 24,200 RMB. The economic comparison is presented in Table 4.
| Item | MVR System | Conventional System |
|---|---|---|
| Initial Investment Cost \( C_{ccm} \) (RMB) | 17,200 | 24,200 |
| Annualized Capital \( C_{acc} \) (RMB) | 2,262 | 3,182 |
| Annual Maintenance Cost \( C_{mc} \) (RMB) | 227 | 319 |
| Annual Electricity Cost \( C_{rec} \) (RMB) | 34,145 | 148,721 |
| Total Annualized Cost AC (RMB) | 36,525 | 152,069 |
| Payback Period PBP (years) | 0.163 | – |
The MVR system reduces initial investment by 7,000 RMB, primarily due to the elimination of an extra heat exchanger. Annual electricity savings amount to 114,576 RMB, leading to total annual cost savings of 115,544 RMB. The payback period for the MVR system is 0.163 years, or about 2 months, indicating rapid return on investment when replacing conventional refrigeration in battery energy storage system cooling applications.
In summary, the MVR falling film indirect liquid cooling system demonstrates substantial energy and economic benefits for battery energy storage systems. At a cooling temperature of 303 K and load of 210 kW, it reduces compressor power by 77.04% compared to first-level efficiency refrigeration. Optimizing cooling temperature and compression temperature rise can further enhance performance. Economic analysis reveals a short payback period of 2 months, making it a viable and efficient cooling solution. Future work should focus on experimental validation of temperature uniformity in falling film modules and detailed investigation of flow and heat-mass transfer mechanisms to fully exploit this technology’s potential for advancing thermal management in battery energy storage systems.
To further elaborate on the design principles, the falling film evaporation process offers high heat transfer coefficients due to thin film formation and phase change. The heat transfer rate \( q \) for falling film evaporation can be expressed as:
$$ q = h_{fg} \cdot \dot{m}_{evap} $$
where \( h_{fg} \) is the latent heat of vaporization and \( \dot{m}_{evap} \) is the evaporation rate. The overall heat transfer coefficient \( U \) for the falling film plate considering conduction through the plate and convective evaporation is:
$$ \frac{1}{U} = \frac{1}{h_{evap}} + \frac{\delta}{k_{plate}} + \frac{1}{h_{batt}} $$
with \( h_{evap} \) as the evaporation heat transfer coefficient, \( \delta \) as plate thickness, \( k_{plate} \) as thermal conductivity, and \( h_{batt} \) as the battery-paste interface coefficient. For battery energy storage system applications, maintaining temperature uniformity is critical to prevent localized hot spots. The temperature distribution \( T(x,y,z) \) in the battery module can be modeled using the heat conduction equation:
$$ \rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T) + \dot{q}_{gen} $$
where \( \rho \) is density, \( c_p \) is specific heat, \( k \) is thermal conductivity, and \( \dot{q}_{gen} \) is heat generation rate per volume from battery reactions. Integrating the cooling system, the boundary condition at the battery-cooling plate interface is:
$$ -k \frac{\partial T}{\partial n} = h_{evap} (T_{surface} – T_{sat}) $$
where \( T_{sat} \) is the saturation temperature corresponding to the vacuum chamber pressure. The MVR cycle efficiency is often evaluated by the coefficient of performance (COP), defined as:
$$ COP_{MVR} = \frac{Q_{cooling}}{W_{comp}} $$
For the simulated case, \( COP_{MVR} = 204.492 / 14.227 \approx 14.37 \), significantly higher than conventional refrigeration COP values (typically 3-4). This highlights the energy efficiency potential for battery energy storage system cooling.
Regarding scalability, the system can be adapted for larger battery energy storage system installations by modular design. The cooling load \( Q_{total} \) for a battery pack with \( N \) cells can be estimated as:
$$ Q_{total} = N \cdot I^2 R_{int} + N \cdot \Delta H_{rxn} $$
where \( I \) is current, \( R_{int} \) is internal resistance, and \( \Delta H_{rxn} \) is reaction enthalpy. The falling film water flow rate requirement scales linearly with load:
$$ \dot{m}_w = \frac{Q_{total}}{h_{fg}} $$
Compressor sizing would then follow based on vapor flow rate and desired compression ratio. System control strategies, such as variable speed drives for the compressor and pump, can optimize performance under partial loads, common in battery energy storage system operations due to fluctuating charge-discharge cycles.
In terms of environmental impact, using water as the coolant eliminates issues associated with synthetic refrigerants, such as high global warming potential. Water is non-toxic, abundant, and has excellent thermodynamic properties. The closed-loop design minimizes water consumption, aligning with sustainability goals for battery energy storage system deployments.
Potential challenges include fouling on falling film plates, which could reduce heat transfer over time. Regular maintenance or anti-fouling coatings may be required. Additionally, ensuring uniform liquid distribution across large falling film surfaces is crucial for consistent cooling. Advanced distributor designs, such as perforated plates or spray nozzles, can be explored. The vacuum maintenance in the falling film chamber also requires reliable sealing and monitoring to prevent air ingress, which could degrade evaporation performance.
Comparative studies with other advanced cooling technologies, such as heat pipe-based systems or phase change material (PCM) integration, could further contextualize the MVR system’s advantages. For instance, PCMs offer passive cooling but may have limited heat dissipation rates during high loads. Hybrid approaches combining MVR falling film with PCMs might be investigated for enhanced thermal buffering in battery energy storage systems.
In conclusion, the MVR falling film indirect liquid cooling system presents a promising avenue for efficient thermal management in battery energy storage systems. Its design leverages phase-change heat transfer and vapor recompression to achieve high energy savings and economic viability. Future research should focus on prototype development, experimental testing under real-world cycling conditions, and lifecycle assessment to validate long-term reliability and environmental benefits. As battery energy storage systems continue to expand globally, innovative cooling solutions like this will play a vital role in ensuring their safe, efficient, and sustainable operation.