Evaluation of thermal behaviors for the multi-stack vanadium flow battery module

Journal of Energy Storage 27 (2020) 101081

Contents lists available at ScienceDirect

Journal of Energy Storage journal homepage: www.elsevier.com/locate/est

Evaluation of thermal behaviors for the multi-stack vanadium flow battery module

T

⁎

Fuyu Chena, Hai Gaob, Hui Chena, , Chuanwei Yanb a b

School of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng, China Institute of Metal Research, Chinese Academy of Sciences, Shenyang, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Vanadium flow battery Thermal behavior Thermal modeling Multi-stack module Module optimization Module temperature

The multi-stack module containing several stacks is commonly used to form a flow battery system for large-scale energy storage applications. The performance and safety of such modules can be highly affected by the module thermal behavior. To fully investigate the thermal behavior of all-vanadium flow battery module, an in-depth analysis is for the first time conducted for an eight-stack 250 kW module. To begin with, both the experimental and simulated results confirm the existence of a fast temperature rising in operation. After that, simulation results further demonstrate that the module temperature variations during charge-discharge cycling can be divided into three phases of fast rising, slowly rising and keeping. In addition, the temperatures of the stacks in the module are very close, with a certain extent higher than those of the tanks. Besides, the temperature rising can be notably moderated by lowering the applied current, extending the storage time, reducing the surrounding air temperature, enlarging the tank surface area and rising up the flow rate. The in-depth study not only provides a cost-effective method to predict and control the temperature variations of multi-stack modules, but also offers a mechanistic insight into the module thermal behavior.

Abbreviations VFB ODE PDE SOC BMS ASR

Vanadium Flow Battery Ordinary Differential Equation Partial Differential Equation State of Charge Battery Management System Area Specific Resistance

1. Introduction Due to the fast development of global economy, the large amount of fossil fuel consumption has resulted in serious environmental and social problems, which drives human beings to explore the use of new energies created from renewable sources, for instance, the wind and solar [1]. The natural characteristics of intermittence, variability and uncertainty however, have restricted the wide application of renewable energies in power systems through the years. Thus, the power energy storage technologies are essential to fit the renewable energy sources [2,3] by means of peak shaving, power prediction, output smoothing and so on [4]. To date, various energy storage technologies including electrochemical and physical forms have been able to be used in

⁎

practical. While the flow batteries, with the features of long cycling life, good scalability, being independent of energy and power, high energy efficiency [5–7], are supposed to have the greatest potential for gridscale energy storage applications on account that they can offer large storage stations being safe, stable and cost acceptable, such that the efficiency of the present grid infrastructure can be largely improved [8]. Of all the flow batteries, the all-vanadium redox flow battery (VFB) has to date exhibited the greatest potential for large-scale electrical energy storage applications with the merit of the use of same element in both half-cells that fully prevents the cross-contamination and enables a theoretically indefinite electrolyte life [9–12]. As an energy storage technology for large-scale use, the hundreds kilowatts VFB module with multiple stacks is commonly used as a basic unit to form a VFB system, with each module comprising of two electrolyte tanks and a certain number of series or parallel connected stacks, as shown in Fig. 1(a). To facilitate applications of the VFB system in large-scale energy storage field, considerable effort has been conducted for the multi-stack VFB module focusing on the improvement of its performance, especially the efficiency and capacity. For instance, the main reason for the loss in module efficiency and capacity in operation compare to a single stack is the shunt current which can happen once the voltage across the module is established. To avoid the

Corresponding author. E-mail address: [email protected] (H. Chen).

https://doi.org/10.1016/j.est.2019.101081 Received 21 October 2019; Received in revised form 15 November 2019; Accepted 15 November 2019 2352-152X/ © 2019 Elsevier Ltd. All rights reserved.

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

Nomenclature A C Cp d h H F i I k N Q r

R T V z ρ θ

area, m2 mole concentration, mol L−1 vanadium electrolyte specific heat, J g−1K−1 polypropylene thickness, m convection heat transfer coefficient tank height, m faraday constant, C mol−1 current density, A m−2 applied current, A polypropylene conductivity, W m−1K−1 cell/stack number, electrolyte flow rate, m3 s−1 radius, m

stack resistance, Ω temperature, K volume, m3 Number of electrons transferred, electrolyte density, kg m−3 transport delay, s

Subscripts and Superscripts r t s c + -

reactant tank stack cell positive negative

Fig. 1. (a) Schematic of the VFB module with multiple stacks; (b) the practical 250 kW module with eight stacks.

of highly potential to be deposited which, if not controlled, could block electrolyte channels, increase the piping pressure, and subsequently decline the module performance and reliability [19]. In addition, ion diffusions across the membrane, material conductivity and side reactions can also be affected by the temperature variation. From this prospective, the thermal analysis and temperature management are of great significance for performance and reliability of the VFB module with multiple stacks. Although electrolyte temperatures can be readily measured on the stack inlet and outlet, a comprehensive analysis or a thorough evaluation of the stack temperature variations in a multi-stack VFB module under different operating conditions proves cumbersome by experiments since large amounts of energy are needed that appears to be uneconomical. Alternatively, thermal modelling as an effective tool can address this limitation for investigation of thermal behavior in largescale multi-stack VFB modules. Some previous studies have successfully developed thermal models for the VFB, these typically including ordinary differential equation (ODE) based dynamic models for temperature prediction in long-term operation [20–26], partial differential equation (PDE) based transient thermal models to analyze temperature distribution in the cell/stack [27,28], as well as equivalent circuit models to investigate the heat dissipation and generation [29]. While these studies have offered deep insights in understanding the thermal behavior in a VFB cell or stack, they have neither extended to a multistack module level nor covered any thermal analysis for a real VFB module. As a matter of fact, the heat generated in a real module during long-term charge-discharge cycling can be huge compared to a single stack due to its operation in large power. As a consequence, the module temperature can run excessively high without proper module design and optimization as well as temperature control. Accordingly, conducting a comprehensive investigation to optimize the module thermal behavior and understand the temperature variation is of great value for the operation and design for multi-stack VFB modules in practical.

negative impacts of the shunt current and understand its mechanism in the module, several studies have been carried out, such as analysis of its impacts for a VFB module with three stacks [13], investigation of the effects module connection and pipe design on VFB module efficiency [14] and studies on the multi-stack VFB piping design taking into account of the trade-offs of space requirement, energy loss and shunt current [15]. Besides of the shunt currents, the ring current occurred in parallel stacks can also potentially decline the module capacity. Tomazic et al. provided a method to minimize the detrimental impacts of ring current by cutting off the electrical circuit of the parallel stacks under open-circuit conditions [16]. Other than that, our previous works have also attempted to promote the module performance by a fully investigation of the module layout and transport delay based on dynamic modellings for VFB multi-stack module [17,18]. All above studies with respect to the flow battery multi-stack module are greatly significant for module design, optimization and fabrication so as to obtain a superior module performance of both the energy efficiency and module capacity. Apart from the efficiency and capacity, the safety and reliability play an equally important role for the wide application of the VFB technology. While safety concerns can be properly addressed in the VFB owing to the use of non-flammable aqueous supporting electrolytes, the reliability issues associated with piping/stack blockage and leakage are still seen from practical operation of multi-stack VFB modules in some demonstrate projects, which, to a great extent, limits the long-term stability and life cycle of the multi-stack VFB module and introduces additional maintenance costs. Fundamentally, both blockage and leakage issues are closely associated with the temperature variation and thermal behavior of the VFB module. On one hand, different component materials in the stack possess different thermal expansion coefficients, so any undesirable temperature variation can become a potential threat to the reliability of sealing. On the other hand, if the vanadium electrolyte temperature stays over 40 °C for a long time running, the V5+ is 2

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

R denotes the stack internal resistance, Ω; I denotes the current for each stack, A; U+ denotes the overall heat transfer coefficient for positive tank, W m−2K−1; A+ denotes the surface area for positive tank, m−2; U− denotes the overall heat transfer coefficient for negative tank, W m−2K−1; A− denotes the surface area for negative tank, m−2.

In this paper, a comprehensive analysis in the thermal behavior of the multi-stack VFB module is for the first time conducted. To start with, a dynamic thermal model for the multi-stack VFB module is developed based on the energy conservation. Afterwards, the variations of module temperature during operation for a real 250 kW VFB module are investigated. Both the experimental and simulated results prove the existence of a significant temperature rising for the VFB module during charge-discharge cycling. After that, to simulate the thermal behavior and temperature variation of the grid-scale flow battery module with multiple stacks, an eight-stack 250 kW VFB module is engaged for analysis. The simulation results indicate that the temperature variations of the VFB module in operation consist of three phases, with the properties of fast rising, slowly rising and keeping, respectively. In addition, the temperatures of the stacks in the module are very close, with a certain extent higher than those of the tanks. Besides, the thermal behavior can be effectively optimized by lowering the applied current, extending the storage time, reducing the temperature of surrounding air, enlarging the tank surface area and increasing the flow rate. The above in-depth analysis of the thermal behavior and temperature variation of VFB modules with multiple stacks is of great significance for the module engineering that the module performance, safety and reliability can be largely improved.

A flow battery module commonly consists of multiple stacks and two tanks. As a result, the time derivative of temperature can be derived from Eq. (2) for multi-stack system dT (t )

⎧ Cp ρVc s,i = Q+Cp ρ (T+ (t ) − Ts,i (t )) + Q−Cp ρ (T− (t ) − Ts,i (t )) + I 2R dt ⎪ ⎪ dT+ (t ) N 1 Cp ρV+ dt = Ns Q+Cp ρ N ∑i =s 1 Ts,i (t ) − T+ (t ) + U+A+ (Tair (t ) − T+ (t )) s ⎨ dT− (t ) ⎪ Ns 1 ⎪Cp ρV− dt = Ns Q−Cp ρ Ns ∑i = 1 Ts,i (t ) − T− (t ) + U−A− (Tair (t ) − T− (t )) ⎩ (2)

( (

) )

where Ns is the number of stack in the module and Ts, i denotes the electrolyte temperature of stack i. The flow rate Q+ and Q− are expressed as

2. Model development A dynamic model that can fully meet the underlying physics as well as be adequately simplified is commonly needed to simulate the thermal behavior of a multi-stack VFB module. To develop such VFB module dynamic models, several assumptions are made as follows:

⎧Q+ = f

Nc I Fcr+

⎨Q− = f ⎩

Nc I Fcr−

(3)

where f is the flow factor, F is the Faraday constant (equals to 96,485 C mol−1), Nc is the number of cell in each stack, cr+ and cr− denote the reactant concentrations in the positive side and the negative side at the end of charge/discharge. Two polypropylene cylindrical tanks are imposed in this work for simulation, with each tank possessing an overall heat transfer coefficient determined by [13]: For tank cylinder wall:

(1) The temperatures and ion concentrations of electrolyte in each tank and stack are uniform; (2) The heat transfer occurred through the stacks and pipes can be minimized; (3) The only heat source in the module during charging-discharging cycling is stack resistances; (4) The resistance of each stack is constant in operation; (5) The volumes of electrolyte in stacks and tanks are assumed to be constant.

U1 =

1

( ) + ( ) ln ( ) + ( ) ( ) 1 h11

r k

r+d r

r r+d

1 h21

(4)

where r denotes the tank radius, m; k denotes polypropylene conductivity, Wm−1K−1; d denotes polypropylene thickness, m; h11 /h21 denote the convection heat transfer coefficients for the inner/outer cylinder surfaces (set to be 207.1 Wm−2K−1 and 5.3 Wm−2K−1 respectively [20]).

2.1. Thermal model According to the above assumptions and the energy conservation, the time derivatives of temperatures in the stack and tank are described in forms of the ordinary differential equations as bellow For single stack system:

For bottom or top circular wall:

dT (t )

⎧Cp ρVs dts = Q+Cp ρ (T+ (t ) − Ts (t )) + Q−Cp ρ (T− (t ) − Ts (t )) + I 2R ⎪ dT+ (t ) = Q+Cp ρ (Ts (t ) − T+ (t )) + U+A+ (Tair (t ) − T+ (t )) Cp ρV+ dt ⎨ ⎪ C ρV dT− (t ) = Q C ρ (T (t ) − T (t )) + U A (T (t ) − T (t )) − dt − p − − − air − p s ⎩

U2 =

1

( ) ( )+( ) 1 h12

+

d k

1 h22

(5)

where h12 /h22 denote the convection heat transfer coefficients for the inner/outer bottom or top surfaces (set to be 405.2 Wm−2K−1 and 3.5 Wm−2K−1 respectively [20]). The surface area for the cylindrical wall A1 can be determined in the form of Eq. (6)

(1) where CP denotes the vanadium electrolyte specific heat, J g−1K−1; Ts denotes the temperature of the stack, K; Tair denotes the temperature of surrounding air, K; T+ denotes the positive tank temperature, K; T− denotes the negative tank temperature, K; ρ denotes the electrolyte density, kg m3; Vs denotes the electrolyte volume for each half-stack, m3; V+ denotes the electrolyte volume in the positive tank, m3; Q+ denotes the positive flow rate for each stack, m3 s−1; V− denotes the electrolyte volume in the negative tank, m3; Q− denotes the negative flow rate for each stack, m3 s−1;

A1 = 2 × π × r × H

(6)

where H is the tank height. The surface area for the circular wall of the bottom or top A2 can be determined in the form of Eq. (7)

A2 = π × r 2

(7)

The total heat transferred between the surrounding air and the electrolyte tank, as a result, can be expressed as

Q heat = UA (Tair − Tt ) 3

(8)

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

from stack ith to the tank, s. Vi, j denotes the volume of section jth in the m sections piping from stack ith to the tank, m3. Qi, j denotes the flow rate of section jth in the m sections piping from stack ith to the tank, m3 s−1.

Table 1 Parameters for the eight-stack 250 VBF module. Parameters

Value/mode

Power of the module Power of each stack Electrical connection Cell number in each stack, Nc Storage time

250 kW 32 kW 8 stacks in series 60 0.5 h for real module, 1 h for simulation 450 A 90 cm x 50 cm x 0.35 cm 2 mol L−1 3.2 J g−1 K−1 3.4 m3 1.35 g cm−3 1.01 Ω cm2 1.14 Ω cm2 1.18 Ω cm2 1.19 Ω cm2 1.20 Ω cm2 1.23 Ω cm2 1.24 Ω cm2 1.47 Ω cm2 19 m 0.05 m 0.5 m 0.02 m 0.7 L s−1 0.01 m 3.5 m 0.16 Wm−1K−1

Electric current, I Electrode size Vanadium concentration, c Specific heat, Cp Electrolyte volume for each half-cell, V Electrolyte density, ρ ASR of Stack 1, R1 ASR of Stack 2, R2 ASR of Stack 3, R3 ASR of Stack 4, R4 ASR of Stack 5, R5 ASR of Stack 6, R6 ASR of Stack 7, R7 ASR of Stack 8, R8 Primary pipe length in total Primary pipe radius Branch pipe length for each stack Branch pipe radius Flow rate for each stack, Q Polypropylene thickness, θ’ Tank height, H Polypropylene conductivity, k

Taking into accounting of the transport delay calculated above, the thermal models of the flow battery module with multiple stacks need to be derived as:

⎧ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪

Cp ρVc

dTs,i (t ) dt

⎛ m = Q+Cp ρ ⎜T+ ⎛⎜t − ⎛∑ j = 1 ⎝ ⎝ ⎝ ⎜

m + Q−Cp ρ ⎛⎜T− ⎛⎜t − ⎛∑ j = 1 ⎝ ⎝ ⎝

m T+ ⎛⎜t − ⎛∑ j = 1 ⎝ ⎝

Note: if t < θi ,

⎜

⎜

where (9)

m Ts,i ⎜⎛t − ⎛∑ j = 1 ⎝ ⎝ ⎜

2.2. Transport delay

length of pipe fluid velocity

=

Vp Q

= =

πrp2 Lp

(10)

θ denotes the transport time between tank and stack, s; Vp denotes the electrolyte volume in the pipe from stack to tank, m3; Lp denotes the length of pipe, m. rp denotes the radius of pipe, m; For multi-stack VFB modules, various types of pipes employing different diameter and length are commonly used to form the whole piping system. Thus, the transport delay from the tank to the stack should be calculated as a sum of the delays in each of the pipe sections the electrolyte flows through, as given in Eq. (11). m

m

Vi,j

∑ θi,j = ∑ Q j=1

j=1

i,j

m

=

∑ j=1

Q I,j 2L πr i,j i,j

Qi,j

Q I,j

⎟

⎜

⎟

⎞ ⎞⎟ = T+ (0) ⎠+⎠

⎟

⎞ ⎞⎟ = Ts,i (0) ⎠+⎠

⎟

⎞ ⎟⎞ = Ts,i (0) ⎠−⎠

⎟

3.1. Temperature rise of the practical VFB module For a large-scale VFB module, the heat generated from the inner stacks is commonly great, thus the temperature rising is inevitable during operation. In order to investigate the temperature rising characteristic, a 250 kW real VFB module is conducted in the study by a real-time test on the electrolyte temperature of the returning pipe where the temperature can be approximately equal to the average temperature of all the stacks during charge-discharge cycling. The test carries out at two surrounding air temperatures of 20 °C and 25 °C for 60 min (charging in the first 30 min and discharging in the second 30 min) at the nominal current of 450 A. The results are

πri,j2 L i,j Qi,j

2L πr I,j I,j

2L πr I,j I,j

⎜

To begin with, a real eight-stack all-vanadium flow battery module illustrated Fig. 1(b) is engaged in this work for module temperature measurement. The parameters of the applied multi-stack module are presented in Table 1, where the module power is 250 kW by employing eight stacks with a power of 32 kW. The area specific resistances (ASR) of stacks have been proposed in our previous study [11]. Additionally, the electric current is set to be 450 A at a SOC range of 20% - 80%. About 3.4 m3 electrolytes with 2 M vanadium ions are filled into each tank and cycled between tank and stacks at a flow rate of 0.7 L s−1 for each stack. After that, in order to give a deep insight into the thermal behavior and temperature characteristics of the flow battery module with multiple stacks, a VFB module of 250 kW with the same geometry and specifications as the above real module is employed in the further simulation.

where

θi =

⎞ ⎟⎞ − Ts,i (t ) ⎟⎞ + I 2R ⎠−⎠ ⎠

⎟

3. Results and discussion

volume of pipe volumetric flowrate

Q

⎞ ⎞⎟ − Ts,i (t ) ⎞ ⎟ ⎠+⎠ ⎠

⎟

Considering that there are two tanks and Ns stacks in a VFB module, the whole multi-stack VFB module model will consist of 2 + Ns ordinary differential equations in total.

Employing multi-stack that shares a common piping, the transport delay can be easily taken place in the flow battery module as a result of the movement of the electrolyte, and subsequently affect the ion concentration and temperature of each stack during operation. The fluid movement in VFB piping can be commonly supposed to be plug flow. Therefore, for single stack VFB systems, the transportation delay from tank to stack can be calculated as [30]:

θ=

Qi,j

Qi,j

2 ⎛1 N ⎞ dT (t ) m πr i,j Li,j C ρV + = NQ+Cp ρ ⎜ N ∑i =s 1 Ts,i ⎜⎛t − ⎛∑ j = 1 Q ⎞ ⎟⎞ − T+ (t ) ⎟ + U+ s i,j ⎨ p + dt ⎝ ⎠ + ⎝ ⎠ ⎝ ⎠ ⎪ ⎪ A+ (Tair (t ) − T+ (t )) ⎪ 2 ⎪ dT− (t ) m πr i,j Li,j ⎞ ⎛ 1 Ns ⎪ Cp ρV− dt = NQ−Cp ρ ⎜ Ns ∑i = 1 Ts,i ⎜⎛t − ⎛∑ j = 1 Qi,j ⎞ ⎟⎞ − T− (t ) ⎟ + U− ⎝ ⎠ ⎪ −⎠ ⎝ ⎠ ⎝ ⎪ ( ( ) ( )) A T t T t − air − − ⎩ (12)

m Ts,i ⎛⎜t − ⎛∑ j = 1 ⎝ ⎝

UA = U1 A1 + 2U2 A2

2L πr i,j i,j

⎜

2L πr i,j i,j

(11)

where θi denotes the transport time between tank and stack ith, s; θi, j denotes the transport time of section jth in the m sections piping 4

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

temperature of around 65–66 °C, enabling the module temperature keeps stable. Besides, Fig. 3(c) and (d) also indicate that there are temperature differences among the stacks and tanks in the module during operation. In order to observe the differences more specifically, the temperatures of the eight stacks and two tanks of the 250 kW VFB module at two typical times of 2 h and 200 h are demonstrated in Fig. 3(e)−(h). First of all, it is confirmed that the feeding modes can hardly affect the module thermal behavior. In addition, of all the stacks in the module, being consistent with Eq. (2), the stack with the higher resistance exhibits the higher temperature. However, the temperature differences among the eight stacks are not notable as a result of the small resistance difference. Moreover, the positive and negative electrolyte tanks possess the same temperature, with about 0.5 °C lower than those in stacks. Accordingly, if the temperature monitoring point is in or close to the tanks, a correction of about 0.5 °C should be conducted for the battery management system (BMS). For the reason that the feeding modes for the multi-stack module can significantly influence the transport time of electrolyte flowed from the tank to the stack according to our previous work [10], and the thermal behaviors of the module are similar for the two feeding modes, the author speculates that the transport delay can hardly affect the thermal behavior of the module as well. To verify it, the stack 8 and positive tank are selected to be investigated with the opposite side feeding mode (same as below), and the temperature variations with and without the transport delay are given in Figs. (i) and (j). As indicated, the temperature curves with and without transport delay are basically coincident for both the stack and tank. This is principally because the transport delay is generally a short time of several minutes, while an obvious temperature rising being taken place in a multi-stack VFB module needs several hours. Thus, on one hand, for the practical largescale VFB module, the piping design and optimization can be more flexible due to the impacts of the piping parameters such as diameter and length associated with the transport delay can be minimized, on the other hand, for the VFB thermal model of VFB module, the transport delay can be ignored, thus the model and calculation can be greatly simplified.

presented in Fig. 2(a) and (b), where the temperatures show an approximately linear increase over time. Specifically, the temperatures increase by about 1 °C per 15 min at both the two ambient temperatures. As a result, after the 1 h testing, the final temperatures reach up to 24 °C and 29 °C respectively. So, the rising of temperature for the VFB module in operation does exist. If not effectively controlled, it can lower the module performance, accelerate the material aging and threaten the system security. The monitoring and controlling of the heat and temperature therefore are essential for the VFB module. However, It is difficult to interpret the temperature characteristic and its influence by experimental methods, for the reason that on one hand the large amount of energy is required for the heat transfer and temperature variation testing that appears to be uneconomical, and on the other hand, the cooling system in real module generally has the priority to start getting involved if the electrolyte temperature in pipe reaches up to about 35 °C for safety. Hence, the thermal dynamic models can be of great value for analyzing the characteristic and effects on the multistack module and helpful to the module design and optimization. By using the dynamic model, the temperature variations of the module are simulated, and the results are demonstrated in Fig. 2(a) and (b), where the simulated and experimental curves are in good agreement. Thus the thermal model is proven to be effective and capable to be applied into the following studies on the module thermal behavior and temperature characteristic for VFB technology. 3.2. Simulated results of module temperature variations To fully investigate the temperature variations and thermal behaviors for the flow battery module, an eight-stack 250 kW VFB module with the parameters depicted in Table 1 are conducted into the study by developing a VFB module thermal model. In practical, the electrolytes for the two half sides can be commonly cycled between the tank and stacks as two modes. One is the same side mode as illustrated in Fig. 3(a); the other is the opposite side mode as illustrated in Fig. 3(b). The temperature variations of the module during operation for both the two modes are presented in Fig. 3(c) and (d). It can be seen that for both the two feeding modes, the module temperature variations are similar with the process consisting of three phases: in the first phase, the temperature increases rapidly by about 35 °C in 25 h, reaching up to 55 °C from 20 °C; in the second phase, the temperature increases slowly by about 10 °C in 50 h, reaching up to 65 °C from 55 °C; in the third phase, the temperature keeps stable at around 65–66 °C. This can be explained according to Eq. (2), where the module temperature can rise up more and more slowly with the increasing of the temperature difference between the surrounding air and the module as a result of the energy balance and the fixed heat generated from the module during constant current charging-discharging cycling. In particular, such a temperature difference can be large enough to dissipate all the heat generated from the module to the surroundings at the module

3.3. Optimization of module thermal behavior According to Section 3.2, the temperature of the VFB module will be finally stable during charge-discharge cycling. Unfortunately however, at the nominal current of 450 A, the final temperature can be over 65 °C. Such a high temperature can not only accelerate material aging and reduce module cycle life, but give rise to a great potential of the precipitation of V-ion from the solution as well. To avoid this risk, five key factors of current, energy storage time, surrounding air temperature, tank shape and flow rate that potentially affect the module thermal behavior are further analyzed. Such a work can be helpful for optimizing the module design and operation, in addition of great

Fig. 2. Temperature rise of practical VFB module during charge-discharge cycling at surrounding temperatures of (a) 20 °C and (b) 25 °C. 5

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

Fig. 3. Module temperature variations during operation: (a)-(b) Schematics for the feeding mode of same side and opposite side; (c)-(d) Temperature curves of stacks and tanks; (e)-(h) Temperatures of stacks and tanks at time of 2 h and 200 h; (i) – (j) Temperatures of stacks and tank with and without transport delay.

80% of the nominal current and 60% of the nominal current are illustrated in Fig. 4(a)−(c). It can be observed that the shapes of the temperature curves for different applied currents are similar, with the three phases of fast rising, slowly rising and keeping, but the final steady temperatures are quite different. Taking the temperature of stack 8 as an example (same as below), the final temperatures for each current are depicted in Fig. 4(d), where the final temperatures are

significance in practical.

3.3.1. Effects of current According to Eq. (2), reducing the applied current is the most immediate way to minimize the heat production. In this regard, the temperature variations of the module for different applied currents of 450 A, 360 A and 270 A which are respectively the nominal current, 6

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

Fig. 4. Effect of current: (a)-(c) Temperature curves for currents of 450 A, 360 A and 270 A; (d) Final steady temperature.

the storage time of 1–4 h are further illustrated in Fig. 5(f). As can be depicted, the final steady temperatures are lowered with the extending of storage time. In particular, for the storage time of 4 h, the final temperature is about 39 °C, enabling the temperature of the electrolyte being in a relatively safe range. Thus the VFB module with a long storage time is capable of slowing down the temperature rising as well as maintaining the temperature within a low level. This further confirms that the VFB technology is of great technical superiority for the applications requiring for high capacity and long storage time.

effectively lowered with the decreasing of the current. Especially for 60% of the nominal current of 270 A, the steady temperature can be finally kept below 40 °C, such that the potential of the V-ion precipitation can be minimized without additional temperature control such as thermal management system. Hence, for the large-scale VFB module, especially the module without thermal management system, a lower charge-discharge current is highly beneficial to the module temperature control. Despite that, the negative effects of lowering the applied current can still be seen, such as lowering the module power and adding the unit power cost. As a result, an appropriate limitation of applied current is welcomed in practical, such that a better comprehensive performance can be finally achieved.

3.3.3. Effect of surrounding air temperature At the surrounding air temperature of 20 °C as discussed above, for the 250 kW/4 h VFB module, the final steady temperature can be lower than 40 °C. However, as an extensively used storage technology, the application environment of VFBs is often complex and harsh. Among all the environmental considerations, the surrounding air temperature is definitely the most influential factor on the thermal behavior of VFB module. As a result, the temperature characteristic and overall performance of the VFB module can be significantly distinguished if installed in the places with different latitudes. Accordingly, three typical areas with different latitudes are selected for investigation as shown in Fig. 6(a), which are Dalian (China), Xiamen (China) and Tamil (India), with the average annual temperatures of 10 °C, 20 °C and 30 °C respectively. Assuming that the surrounding air temperature is constant and equal to the average annual temperature, the temperature characteristics for the multi-stack module are evaluated and the simulation results are demonstrated in Fig. 6(b). As observed, with the variation of the surrounding air temperature, the temperature curves shift upward or downward in parallel with the constant shape, meaning that although the initial and final temperatures differ for different surrounding air temperature, the variation trends and rising speed of the module temperature stay the same. The final steady temperatures, as

3.3.2. Effects of storage time Apart from the current, the volume of electrolyte is another key factor affecting the module thermal behavior because the electrolyte is the medium of heat transfer between the stacks and tanks. For the electrolytes with the same concentration, the volume is highly associated with the energy storage time. The effects of energy storage time therefore, are vital to be fully evaluated. Accordingly, Fig. 5(a)−(d) demonstrate the temperature variations as the storage time extends from 1 h to 4 h at the nominal current, where the shapes of the curves are significantly different for different storage time. With the increasing of storage time, the heating rate is effectively decelerated especially at the beginning of the operation. In addition, the final steady temperature is lowered as well. Specifically, the heating rates in the first 25 h are further depicted in Fig. 5(e). As observed, the temperature rises by 1.7 °C per hour for the storage time of 1 h. By comparison, for the storage time of 4 h, the temperature rises by only 0.5 °C per hour. This can be explained from Eq. (2), where mathematically, the time derivative of temperature becomes smaller as the electrolyte volume increases. Apart from the heating rates, the final steady temperatures for 7

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

Fig. 5. Effect of storage time: (a)-(d) Temperature curves for the storage time of 1–4 h; (e) Heating rate in the first 25 h; (f) Final steady temperature.

the most direct factor affecting the heat dissipation. Accordingly, three types of electrolyte tank with different bottom shapes of circle, square and rectangle (length: width=2:1) are engaged for investigation in this study. Besides, in order to facilitate the comparison, all the tanks are assumed to be of the same height of 3.5 m. Thus, the surface areas of the tanks with different shapes are 48.8 m2, 53.1 m2 and 55.5 m2 for circle, square and rectangle respectively as calculated. Fig. 7(a)–(c) demonstrate the temperature variations versus time for the 250 kW/4 h VFB module with the above tanks as the electrolyte reservoirs, where the curve shapes is similar, but the difference of final steady temperatures is relatively obvious. The final temperatures are specifically 39.1 °C for circle, 37.7 °C for square and 37.0 °C for rectangle as further depicted in Fig. 7(d). As a result, by optimizing the shapes of the electrolyte tanks, a lower final temperature of more than 2 °C can be yielded. In addition, the order of precedence for the heat dissipation is the first for rectangle, the second for square and the third for circle, which is right the order of the tank surface area. Hence, the optimization of the tank shape is an effective way to lower the final steady temperature. For a real largescale VFB module, therefore, cuboid tanks should be used for a better thermal behavior instead of cylinder tanks. Moreover, to obtain a more advanced temperature characteristic of the VFB module, if possible,

further demonstrated in Fig. 6(c), are 29 °C, 39 °C and 49 °C respectively if used in Dalian, Xiamen and Tamil. More specifically, the difference of the VFB final steady temperatures is exactly the difference of the surrounding air temperatures. This can be significantly valuable for the large-scale flow battery module application. Firstly, the surrounding air temperature of the VFB module needs to be tightly controlled in practical. For instance, the air conditioning system can be used to cool the surrounding air for most of the fixed-type and container-type VFB energy storage station. Secondly, for some special circumstances the ambient temperature is excessive high or unmanageable, the electrolyte cooling system has to be configured on the VFB module, despite it can introduce an additional energy loss and cause a subsequent efficiency loss. The last but not the least, for the VFBs, if the thermal behavior and temperature variation are once analyzed in a laboratory or factory, the results can be applied equally to any other place with a modification of the initial temperature. 3.3.4. Effect of tank shape Increasing the heat dissipation is another way to cool the module and optimize its thermal behavior. The surface area of the electrolyte tanks, as a major medium exchanging the heat with the surroundings, is 8

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

Fig. 6. Effect of surrounding air temperature: (a) Selection of typical areas; (b) Temperature curves for different surrounding air temperatures; (c) Final steady temperature.

Fig. 7. Effect of tank shape: (a-c) Temperature curves for tanks with the different bottom shapes of (a) circle, (b) square and (c) rectangle; (d) Final steady temperature. 9

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

production from the interior is inevitable during operation. The design, optimization and operation management for a better thermal behavior therefore, to a great extent, are essential in practical. For the VFBs, in particular, cycling the electrolyte between the tanks and stacks makes the system possess a natural superiority of transform the heat from the inner stacks to the outside, thus various and flexible methods can be provided for the optimization of module thermal behavior, such that the controlling the module temperature within a reasonable interval can be finally achieved. By investigating an eight-stack 250 kW VFB module, this study not only reveals the rules of temperature variations of VFB module during charge-discharge cycling, but also provide the effective ways to optimize the thermal behavior of the module. Despite that the current work only focuses on an all-vanadium flow battery module of 250 kW with eight stacks, the investigation can be applied into the modules with other power level or stack number as well. Ultimately, the thermal behavior optimization is a procedure of reducing the heat production and/or increasing the heat dissipation at a certain initial condition. Accordingly, any other methods that can help the module to reduce the heat production and/or increase the heat dissipation are welcomed in practical as well. Beyond the above discussion, at least two other considerations are worthwhile for the follow-up study as well. Firstly, for specific applications with high temperature environments or short energy storage time that the module temperature can not be reliably controlled under 40 °C only by design, optimization and operation management, a cooling system seems to be indispensable for large-scale modules. However, how to design and optimize the cooling system for different application requirements, as well as how the cooling system can affect the module performance are not considered in the present work. Secondly, the effects of the thermal behavior on the module electrochemical performance are also not conducted in this paper. In practical, the variations of module temperature can cause different conductivity of module materials and diffusivity of vanadium ions in electrolyte, thus subsequently affect the energy efficiency and module capacity. Hence, a comprehensive dynamic model of more complexity to capture

further increasing the aspect ratio of the bottom rectangle or some other methods which are beneficial to enlarging the tank surface area are also welcomed. 3.3.5. Effect of flow rate The flow rate, inferred from Eq. (2), whose optimization can effectively promote the heat exchanging between the stacks and the tanks, is also influential in the module thermal behavior. Hence, based on the above optimization, the 250 kW/4 h VFB module with the rectangle (length: width=2:1) tanks as the electrolyte reservoirs is applied into the study for analyzing the effects of the flow rate. Fig. 8(a)−(c) illustrate the temperature curves of the module for the different flow factors of 1, 3 and 5. It can be observed that with the increasing of the flow rate, the temperatures of the tank and stacks in the module become closer and closer. Especially at the flow factor of 5, the curves are almost coincident as shown in Fig. 8(c), where the maximum temperature difference among the tank and stacks is only about 0.1 °C. This is of great significance because for the temperature detection of a real module, the realistic monitoring point is not the stack, but the tank or piping. Thus, the closer the temperatures of the monitoring point and the inner stacks are, the easier the parameter corrections are, such that a higher accuracy of BMS can be achieved and a superior performance and safety of the VFB module can be finally obtained. Moreover, the final temperatures of the module with different flow factors are further demonstrated in Fig. 8(d). It can be depicted that as the flow rate increases, the final steady temperature can be lowered gradually. Specifically, the final temperature lowers by 0.6 °C with the flow factor increasing from 1 to 5. Even so, adopting a very high flow rate is not preferred in practice, considering the considerable pumping losses. Therefore, an appropriate flow rate is commonly of advantages and favorable for the practice of multi-stack VFB module. 3.4. Discussions For all the electrochemical energy storage technologies, the heat

Fig. 8. Effect of flow rate: (a-c) Temperature curves for different flow factor of 1, 3 and 5; (d) Final steady temperature. 10

Journal of Energy Storage 27 (2020) 101081

F. Chen, et al.

vanadium flow battery, J. Electrochimica Acta 215 (2016) 57–65. [4] G. Hua, M. Jing, D. Wang, Z. Sun, C. Xu, W. Ren, H. Cheng, C. Yan, X. Fan, F. Li, A gradient bi-functional graphene-based modified electrode for vanadium redox flow batteries, J. Energy Storage Mater. 13 (2018) 66–71. [5] X. Wei, W. Pan, W. Duan, A. Hollas, Z. Yang, B. Li, Z. Nie, J. Liu, D. Reed, W. Wang, Materials and systems for organic redox flow batteries: status and challenges, J. ACS Energy Lett. 2 (2017) 2187–2204. [6] Y. Shi, C. Eze, B. Xiong, W. He, H. Zhang, T.M. Lim, A. Ukil, J. Zhao, Recent development of membrane for vanadium redox flow battery applications: a review, J. Appl. Energy 238 (2019) 202–224. [7] J. Ye, L. Xia, C. Wu, M. Ding, C. Jia, Q. Wang, Redox targeting-based flow batteries, J. Phys. D. Appl. Phys. 52 (2019) 443001. [8] J. Sheng, A. Mukhopadhyay, W. Wang, H. Zhu, Recent advances in the selective membrane for aqueous redox flow batteries, J. Mater. Today Nano 7 (2019) 110044. [9] G. Wei, W. Su, Z. Wei, M. Jing, X. Fan, J. Liu, C. Yan, Effect of the graphitization degree for electrospun carbon nanofibers on their electrochemical activity towards VO2+/VO2+redox couple. [10] J. Ye, Y. Cheng, L. Sun, M. Ding, C. Wu, D. Yuan, X. Zhao, C. Xiang, C. Jia, A green SPEEK/lignin composite membrane with high ion selectivity for vanadium redox flow battery, J. Membr. Sci. 572 (2019) 110–118 J. Electrochimica Acta, 199(2016) 143-153. [11] J. Xiong, S. Wang, X. Li, Z. Yang, J. Zhang, C. Yan, A. Tang, Mechanical behavior and Weibull statistics based failure analysis of vanadium flow battery stacks, J. Power Sourc. 412 (2019) 272–281. [12] L. Xia, Q. Zhang, C. Wu, Y. Liu, M. Ding, J. Ye, Y. Cheng, C. Jia, Graphene coated carbon felt as a high-performance electrode for all vanadium redox flow batteries, Surf. Coat. Technol. 358 (2019) 153–158. [13] F. Wandschneider, S. Röhm, P. Fischer, K. Pinkwart, J. Tübke, H. Nirschl, A multistack simulation of shunt currents in vanadium redox flow batteries, J. Power Sourc. 261 (2014) 64–74. [14] S. Konig, M. Suriyah, T. Leibfried, Model based examination on influence of stack series connection and pipe diameters on efficiency of vanadium redox flow batteries under consideration of shunt currents, J. Power Sourc. 281 (2015) 272–284. [15] Q. Ye, J. Hu, P. Cheng, Z. Ma, Design trade-offs among shunt current, pumping loss and compactness in the piping system of a multi-stack vanadium flow battery, J. Power Sourc. 296 (2015) 352–364. [16] G. Tomazic, M. Skyllas-Kazacos, Redox flow batteries, in: P. Moseley, J. Garche (Eds.), Electrochemical Energy Storage for Renewable Sources and Grid Balancing, Elsevier, 2015, pp. 309–336. [17] H. Chen, X. Li, H. Gao, J. Liu, C. Yan, A. Tang, Numerical modelling and in-depth analysis of multi-stacks vanadium flow battery module incorporating transport delay, J. Appl. Energy 247 (2019) 13–23. [18] H. Chen, S. Wang, H. Gao, X. Feng, C. Yan, A. Tang, Analysis and optimization of module layout for multi-stack vanadium flow battery module, J. Power Sourc. 427 (2019) 154–164. [19] M. Kazacos, M. Cheng, M. Skyllas-Kazacos, Vanadium redox cell electrolyte optimization studies, J. Appl. Electrochem. 20 (1990) 463–467. [20] A. Tang, S. Ting, J. Bao, M. Skyllas-Kazacos, Thermal modelling and simulation of the all-vanadium redox flow battery, J. Power Sourc. 203 (2012) 165–176. [21] A. Tang, J. Bao, M. Skyllas-Kazacos, Thermal modelling of battery configuration and self-discharge reactions in vanadium redox flow battery, J. Power Sourc. 216 (2012) 489–501. [22] B. Xiong, J. Zhao, K. Tseng, M. Skyllas-Kazacos, T. Lim, Y. Zhang, Thermal hydraulic behavior and efficiency analysis of an all-vanadium redox flow battery, J. Power Sourc. 242 (2014) 314–324. [23] Y. Yan, Y. Li, M. Skyllas-Kazacos, J. Bao, Modelling and simulation of thermal behaviour of vanadium redox flow battery, J. Power Sourc. 322 (2016) 116–128. [24] Y. Yan, M. Skyllas-Kazacos, J. Bao, Effects of battery design, environmental temperature and electrolyte flowrate on thermal behaviour of a vanadium redox flow battery in different applications, J. Power Sourc. 11 (2017) 104–118. [25] A.S. A.Trovò, M. Giomo, M. Guarnieri, Thermal modeling of industrial-scale vanadium redox flow batteries in high-current operations, J. Power Sourc. 421 (2019) 204–214. [26] A. Trovò, G. Marini, A. Sutto, P. Alotto, M. Giomo, F. Moro, M. Guarnieri, Standby thermal model of a vanadium redox flow battery stack with crossover and shuntcurrent effects, J. Appl. Energy 240 (2019) 893–906. [27] Q. Zheng, H. Zhang, F. Xing, X. Ma, X. Li, G. Ning, A three-dimensional model for thermal analysis in a vanadium flow battery, J. Appl. Energy 113 (2014) 1675–1685. [28] W. Wang, G. Shu, H. Tian, X. Zhu, A numerical model for a thermally-regenerative ammonia-based flow battery using for low grade waste heat recovery, J. Power Sourc. 388 (2018) 32–44. [29] Z. Wei, J. Zhao, B. Xiong, Dynamic electro-thermal modeling of all-vanadium redox flow battery with forced cooling strategies, J. Appl. Energy 135 (2014) 1–10. [30] Seborg D.E., Edger T.F., Mellichamp D.A.M process dynamics and control 2004.

both thermal and electrochemical behaviors is required for the further study on multi-stack VFB module, that an exacter prediction of the module performance can be achieved. 4. Conclusion The present work fully investigates the thermal behavior and temperature variation of the VFB module consisting of multiple stacks by developing a dynamic VFB thermal model on the basis of energy conservation. The experimental testing and modeling simulation on a real eight-stack 250 kW vanadium flow battery module have both proven the existence of the temperature increasing during operation and the subsequent potential of threat to the module safety and reliability. To comprehensively analyze the module thermal behavior and temperature variation, a 250 kW VFB module with eight stacks is conducted for simulation by the proposed thermal model. The Simulation analysis indicates that the temperature variations of the module during chargedischarge cycling can be divided into three phases of fast rising, slowly rising and keeping. In addition, the temperatures of the stacks in the module are very close, with a certain extent higher than those of the tanks. In addition, the simulation investigation further demonstrates that lowering the applied current, extending the storage time, reducing the surrounding air temperature, enlarging the surface area of the tanks and increasing the flow rate are capable of optimizing the module thermal behavior and can help to moderate the module temperature rising. Such an in-depth analysis focusing on the thermal behavior of VFB module with multi-stack not only offers an effective method to predict and control the temperature variations of multi-stack modules, but also gives a mechanistic insight into the module thermal behavior. Moreover, the dynamic thermal model proposed in this paper successfully extends the existing single stack VFB thermal model to multi-stack level, which provides a method with high cost-effectiveness for investigation of the MW-level VFB systems by simulation, thus the large amount of testing time and research cost can be significantly saved. Declaration of Competing Interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “Evaluation of thermal behaviors for the multistack vanadium flow battery module”. Acknowledgement C. Yan acknowledge the support from Shenyang Key R & D and Technology Transfer Program (No. Z17-7–026). References [1] L. Zeng, T. Zhao, L. Wei, H. Jiang, M. Wu, Anion exchange membranes for aqueous acid-based redox flow batteries: current status and challenges, J. Appl. Energy 33–234 (2019) 622–643. [2] M. Ding, G. Chen, W. Xu, C. Jia, H. Luo, Bio-inspired synthesis of nanomaterials and smart structures for electrochemical energy storage and conversion, Nano Mater. Sci. (2019), https://doi.org/10.1016/j.nanoms.2019.09.011. [3] Mi. Jing, X. Zhang, X. Fan, L. Zhao, J. Liu, C. Yan, CeO2 embedded electrospun carbon nanofibers as the advanced electrode with high effective surface area for

11