Research Article  Open Access
Guanglin Sha, Qing Duan, Wanxing Sheng, Aiqiang Pan, Zhe Liu, Chunyan Ma, Caihong Zhao, Jiaxun Teng, Lumin Fu, Yi Zheng, "A Multiport Electric Energy Routing Scheme Applied to Battery Energy Storage System", Journal of Engineering, vol. 2021, Article ID 6637926, 15 pages, 2021. https://doi.org/10.1155/2021/6637926
A Multiport Electric Energy Routing Scheme Applied to Battery Energy Storage System
Abstract
In this paper, the research status of topology and control strategy of energy storage gridconnected system is analyzed, and aiming at the working characteristics of the repurposed battery, a cascade power electronic transformer (CPET) with independent DC output is proposed. The working principle of current fed isolated bidirectional DCDC converter (CFIBDC) and cascaded Hbridge (CHB) is analyzed, and the decoupling control strategy is designed. In this paper, a hierarchical control strategy is designed for the repurposed battery energy storage (RBES) gridconnected system based on CPET, which consists of three layers: energy layer, power layer, and state of charge (SOC) layer. The energy layer responds to active and reactive power scheduling instructions, the power layer controls the gridconnected current and tracks the grid voltage, and the SOC layer equates the charged state of repurposed batteries. A 3 MVA/12 kV threephase gridconnected simulation system was established, and a 1 kW singlephase system experiment platform was designed. The simulation and experimental results can verify the correctness of the theoretical analysis and the feasibility of the control strategy.
1. Introduction
In recent years, the proportion of renewable energy in the power system has gradually increased, but its output power is characterized by volatility and intermittency, which limits the capacity of renewable energy generation to connect to the grid on a large scale [1, 2]. Supporting battery energy storage system can effectively improve the ability of power grid to accept renewable energy [3–6]. The cost factors of largecapacity converters and energy storage batteries limit the promotion and application of the battery energy storage system, while repurposed lithium batteries and link topology provide a new idea to solve the cost problem [7].
The echelon utilization of the retired power battery of electric vehicles is to design the repurposed battery cells into a battery pack after screening. Due to the limitation of the production process of the battery itself, the actual capacity, internal resistance, voltage, and other performance parameters of the battery are different to some extent, which is collectively referred to as the inconsistency of the battery [8–10]. After longterm use of repurposed battery packs, the battery performance degrades, and the single battery parameters will show obvious dispersion, which is manifested as obvious capacity difference, internal resistance difference, and voltage difference between batteries [11–13]. The existence of inconsistencies in battery cells leads to uneven charging and discharging within the battery pack. If not controlled, longterm operation will greatly reduce the reliability and security of the battery energy storage system [14]. In the design of largecapacity energy storage system, the battery pack needs to be continuously charged and discharged, and the inconsistency of discreteness will lead to a large difference in the decay speed of battery parameters, thus accelerating and amplifying the inconsistency of the battery pack [15, 16]. In the echelon utilization of repurposed batteries, the inconsistency problem will be solved from two aspects. First, we select batteries with small differences to form the battery pack and build the battery management system to reduce the inconsistency of batteries within the same group. Second, we select the appropriate electrical topology structure and design the balanced control, which can slow down the rate of battery performance decline.
PET integrates voltage transformation, highfrequency electrical isolation, and flexible power flow control, making it a research direction of topological structure of battery energy storage system. For the PET used in distributed energy storage methods, the control targets are mostly DC link voltage equalizing control and isolation level parallel submodule power equalizing control. Reference [17] presented cell and phase balance for power and energy of a 10cell multilevel inverter cascaded Hbridge. The CHB inverter control for each stage leg used the type of phaseshifted carrier. The control strategy based on the idea of a virtual synchronous generator is used on the way to balance the power and energy distributed among cells in the same phase and between phases. Reference [18] described a 14.14 kV, 2 MW, and 1000 Ah system with fortyfive Li (lithium) ion battery units. The system is based on a cascaded Hbridge multilevel PWM converter with star configuration focusing on the active power balancing of individual converter cells and a control system is proposed which consists of active power control and SOC balancing control (interphase SOC balancing control and phasephase SOC balancing control). In [19], two SOC balancing techniques are proposed for an electrical vehicle charging station which is based on a gridtied cascaded CHB multilevel converter. The first proposed technique uses the redundant states of the CHB converter to generate different AC voltages to balance the SOCs of the CHB cells. In the second proposed technique, the information of AC input current is employed to design the switching states at each quarter of the period. Hu et al. [20] proposed a novel hybrid power converter topology based on CHB and matrix converter. The CHB, as the energy control unit, can be used to balance the voltage/SOC of battery packages individually and significantly improve the modularity, stability, and safety of EV system. Kandasamy et al. [21] investigated a module level SOC balancing control in cascaded CHB based BESS using multidimensional modulation technique. SOC can be equalized between the battery modules in a phase leg of CHB with the proposed control strategy.
Aiming at the inconsistency problem of repurposed batteries, this paper presents a cascade power electronic transformer with independent DC outputs. The RBES combines the control target and topology structure to design the threelayer control architecture including energy layer, power layer, and SOC layer. The energy layer is used to respond to scheduling instructions and suppress power fluctuations, peak load clipping, and reactive power compensation. The power layer distributes active power based on SOC and divides reactive power equally to make full use of system capacity. SOC layer equalizes the charged state of decommissioned lithium battery to avoid short plate effect and stabilize the voltage of high voltage bus. The security and reliability of the RBES are enhanced.
2. System Composition and Power Flow Analysis
2.1. System Composition
The echelon RBES gridconnected system of the CPET proposed in this paper is shown in Figure 1. The system adopts a twostage structure, with an independent DC output terminal to access the repurposed battery, and the topology is divided into the DC cell group consisting of cascade CFIBDC module and the DCAC consisting of CHB module. Based on a 3 MVA/12 kV medium voltage grid system, considering the tradeoff among system cost, life, passive components, switching devices, frequency, and power quality during design progress, the number of each phase containing Hbridge cell is N = 4, and the number of CFIBDC cell modules contained in the DC group corresponding to each Hbridge is M = 4. Within the DCDC unit, the highvoltage side of the CFIBDC adopts series structure to obtain the highvoltage bus voltage, V_{dcia} = 3000 V, and the lowvoltage side of the converter is connected to the repurposed battery module, respectively, to realize independent energy balance control. The Hbridge module constitutes a multilevel cascade system, realizing the gridconnected control.
2.2. Cascade HBridge Analysis
The CHB topology is shown in Figure 1. All modules are in series structure; that is, the output current of the modules is the same, and the power distribution between the modules will be determined by their output voltage. In order to realize the independent control of active and reactive power, a discrete Fourier transform phaselocked loops (PLL) method is adopted. This method is only based on singlephase grid voltage signal and can extract basic phase, frequency, and amplitude information from any signal. The active power and reactive power can be decoupled by coordinate transformation, and then they can be controlled independently. The distribution of active power and reactive power of phase A among N Hbridge modules is illustrated in Figure 2. The same analysis is also carried out for phase B and phase C, which will not be repeated in this paper.
(a)
(b)
In the coordinate analysis, considering the relative stability of the grid voltage, the synchronous signal is V_{ga}. The αaxis in the αβ coordinate system is in phase with the grid voltage, and the βaxis lags the αaxis by 90°. The daxis in the dq coordinate system is aligned with the grid voltage through PLL control technology, and qaxis lags d axis by 90°, as shown in Figure 2(a). The grid voltage components in the αβ coordinate system and the dq coordinate system are given by the following equations, respectively:where ω is the grid voltage frequency, V_{ga} is the amplitude of phaseA grid voltage, and = V_{ga}; V_{ga_q} = 0.
A vector diagram of the AC voltage is given in Figure 2(a) to illustrate the power distribution principle between the CHB modules of phase A. The same analytical method can be applied to phase B and phase C. The d′q′ coordinate system is constructed in the vector diagram, where the d′ axis is in phase with the grid current, and the q′ axis lags the d′ axis by 90°. Obviously, the d′ axis component of the inverter output voltage determines the active power, while the q′ axis component determines the reactive power. In Figure 2(b), the power distribution of CHB topology in different gridconnected power situations is described. The gridconnected voltage V_{sa} output by CHB is synthesized from the output voltage V_{ia} (i = 1, …, N) of Hbridge modules with different amplitude and angle and and can be decoupled to realize independent control of active power and reactive power of each Hbridge module. In the coordinate transformation of dq coordinate system and d′q′ coordinate system, the grid voltage and current reference angle θ_{ga} are the key to the transformation. The grid current i_{ga} can be measured and projected onto the coordinate system to obtain i_{ga_α} and i_{ga_β}. The grid current flowing through αβdq coordinate system is transformed into the dq coordinate system as follows:
Therefore, the reference angle of θ_{ga} of grid voltage and current can be obtained:
We substitute the result obtained from (4) into dqd′q′:
The voltage component based on d′q′ coordinate system can be obtained by (5), the voltage signals and of active power and reactive power output are distributed to each Hbridge module through the energy balance control algorithm, and then the d′ axis voltage reference value of each Hbridge module can be obtained, so as to control the active power component of corresponding module, and the obtained q′ axis voltage reference value controls the reactive power component. In order to convert the voltage component of the d′q′ coordinate system into the modulation ratio control quantity of each module of the CHB topology, we transform the output voltage reference signal of the active power and reactive power of the d′q′ coordinate system obtained by the equalization control to the αβ coordinate system through the d′q′αβ coordinate system:
As shown in Figure 2(a), the output reference signals of each module are = , the modulation ratio of each Hbridge module can be calculated: = /V_{dcia}. Then, the decoupling control of active power and reactive power can be completed, and the power balance control of each Hbridge module can be realized easily. In the control, the modulation ratio should not exceed the modulation ratio control limit to avoid output instability. This paper does not analyze the overmodulation control.
2.3. Cascading CFIBDC Analysis
The structure of CFIBDC is shown in Figure 3. The lowvoltage side of the converter is a multiplexed halfbridge structure. The lowvoltage halfbridge and the input inductor L_{b} constitute the front Buck/Boost circuit to obtain the capability of wide input voltage range. The input inductance makes the converter have current source characteristics to reduce the input current ripple. At the same time, the halfbridges and capacitorbridges in both primary and secondary sides constitute the dual active bridge. The capacitor arm clamping the voltage of switching tube can solve the problem of high voltage spike. The center tap on the high voltage side of the transformer yields two high voltage halfbridge structures, and interbridge circulation can solve the soft switch problem under light load and improve the efficiency in the full power range.
3. Analysis of Hierarchical Control Strategy
The CPET based RBES gridconnected system designed in this paper mainly realizes the control target of smooth power fluctuation and peak cut of renewable energy. The system is divided into 2layer structure, composed of DCDC part and DCAC part, which can realize the independent control of the two parts. Combined with the gridconnected RBES topology, the control requirements and objectives of the energy storage system are decomposed, and the threelayer control structure of the RBES system with CPET structure is designed to achieve their respective control objectives, namely, the energy layer, the power layer, and the SOC layer.
In the RBES gridconnected system, the DCDC stage is divided into charging state and discharging state, and the DCAC stage is divided into inverting state and rectifying state. When the RBES gridconnected system works in the inverter state, the repurposed battery discharges and the energy is transmitted forward. The whole system is powered by the repurposed battery to the grid. When the RBES gridconnected system works in the rectifier state, the repurposed battery is charged and the energy is transmitted in reverse, and the whole system absorbs the excess energy from the grid side to the repurposed battery.
Whether the energy is transmitted forward or backward, the control objectives of the DCAC stage are gridconnected current tracking of the grid voltage and the completion of active and reactive power scheduling instructions, while the control objectives of the DCDC stage are to stabilize the voltage of the HVDC bus and balance the charged state of repurposed batteries.
The DCDC stage and the DCAC stage are connected by the HVDC bus. The voltage of the HVDC bus V_{dcik} will be affected by the two stages of the circuit. In the case of rectifier, the DCAC stage raises the voltage of the DC bus, while in the case of inverter, the DCAC stage pulls down the voltage of the DC bus. In this paper, the HVDC bus voltage is controlled by the DC/DC stage. Based on the above analysis, it can be known that the automatic switching between forward flow and reverse flow of energy can also be realized in the stable voltage control implementation of CFIBDC converter; twostage circuit control can also be completely decoupled which only focus on their respective control objectives. Hierarchical control strategy diagram is shown in Figure 4.
3.1. Energy Layer Control Strategy
According to the power output of renewable energy and the expected design value of system power at the current time of the power grid, the power dispatching center obtains the active power dispatching instruction P_{g} and reactive power dispatching instruction Q_{g} and sends the dispatching instructions to the RBES gridconnected system. The RBES gridconnected system achieves the control target of energy layer according to the control strategy shown in Figure 5.
(a)
(b)
In the energy layer control, the RBES system detects the reactive power QRBES and active power PRBES of PCC nodes and takes them as a feedback value. The reactive power dispatch instruction Q_{g} and the active power dispatch instruction P_{g} are, respectively, differentiated from the feedback value, getting the next cycle adjustment of power value ΔP. Then, the power closedloop control is completed to obtain the reference value of active power and the reference value of reactive power. By transferring the reference value to the power layer, the RBES gridconnected system based on CPET is controlled to realize the tracking control of scheduling instructions.
The energy layer regulates the dynamic response speed of the RBES gridconnected system, controls the startstop and power switching of the system, which realizes the nonimpact and flexible switching of operating conditions, and controls the active power and reactive power output of the RBES system to reach the grid dispatching value.
3.2. Power Layer Control Strategy
The control objective of CHB topology is to track the active power of the energy layer by referring to the given value P^{∗}_{ref} and the reactive power by referring to the given value Q^{∗}_{ref}, which realizes the dispatching instruction of the grid dispatching center. The gridconnected current tracks the voltage on the side of the grid which is the standard sine wave. The control strategy of the power layer is shown in Figure 5.
The above energy layer control strategy calculates the given values of active power and reactive power and transfers the reference values to the power layer. Firstly, according to (7), the power layer control obtains the given reference quantity of d axis current and the given reference quantity of q axis current. The active and reactive power value of the RBES gridconnected system is evenly divided into the threephase system. According to singlephase PLL dq vector transformation technology, the voltage current detection signal of the system is obtained by abc/dq vector transformation in the dq static coordinate system, and the active power and reactive power are decoupledcontrolled in the static coordinate system. The system error signal is obtained by the difference between the given reference value of dq axis current and the actual current flow, which is calculated by PI controller to obtain the voltage signals of d axis and q axis:
The voltage signal of dq axis and the charged state SOC_{ik} value of each DC unit group are input into the power distribution module, respectively. According to the active power and reactive power distribution (8), the voltage given signal of dq axis of each module can be obtained. Although the active power according to SOC_{ik} value distribution can inhibit DC unit charged state significantly difference between groups and avoid the short board effect, it actually cannot completely eliminate the differences of DC units charged state between groups. Considering the capacity and control complexity of system, the small difference of charged state in engineering application is acceptable, so the control strategy of allocating active power according to the charged state of each DC unit group is feasible. The reactive power is an equilibrium control, and each Hbridge module has the same parameters and reactive power capacity, which makes the reactive power divided equally among all Hbridge units:
The modulation ratio of each module is different, which makes the RMS value of output AC voltage inconsistent, while the link structure makes the RMS value of each module the same, so each module has different power output value, which indirectly realizes the SOC value equalization control, and controls the total power of the cascade module and the change of the scheduling value of the system.
3.3. SOC Layer Control Strategy
In the SOC layer, the charging and discharging power of each module is evenly controlled according to the SOC status of the repurposed battery, which enables the balanced control of the SOC value of the repurposed battery to ensure the safe and stable operation of the battery pack. Combined with the working principle of the CFIBDC converter, it can be seen that the power transmission direction is controlled by the phase shift angle between bridges, while the energy flow direction is automatically switched under the voltage stabilization control of the HVDC bus. Since the cascaded structure of each module makes the module have the same current, it is necessary to control different output voltage to regulate the output power of each module, so SOC equalization is to control the output voltage value of each module.
In Figure 6, voltage loop is used in CFIBDC to realize the output voltage control, the control parameter is the phase shift angle ϕ between bridges, and voltage matching is achieved by controlling duty cycle D, which can reduce converter loss. SOC equalization control strategy requires that different voltage values of each module be given, respectively, and output power be adjusted to realize SOC equalization. The voltage error signal can be obtained by making the difference between the voltage given value and voltage sampling V_{H}. The phase shift angle can be obtained by PI regulator. The PWM driving signal can be generated by the phase shift square wave controller, and then the voltage stabilizing control can be completed by adjusting the CFIBDC.
The voltage distribution controller is shown in Figure 7, the difference between the average SOC_{ik} value of the DC unit group and the state of charge value of each module to obtain the error signal of the SOC value, which is corrected by the PI controller for the corresponding module voltage. In the SOC equalization control, a correction coefficient calculator is designed to distinguish the different equilibrium objectives of different SOC based on charge and discharge, which is actually a hysteresis control strategy. We multiply the obtained voltage correction value and correction coefficient to obtain the SOC equalization correction voltage increment and then add the given value of the mean voltage and the SOC equalization correction voltage increment to obtain the given value of the voltage of each module. The corresponding last module compensates the voltage regulator value of the whole DC unit group; that is, it satisfies equation (9) and controls the whole DC unit group by the voltage given value of the moduleM, which realizes the voltage regulator control of the HVDC bus:
The correction factor calculator is shown in Figure 8. In the process of voltage rise, when the voltage of HVDC bus reaches 3050 V, the system enters the charging control area and the correction coefficient gradually increases to 1. When it is higher than 3100 V, the correction coefficient remains at 1. In the process of voltage reduction, when the voltage is reduced to 2950 V, the correction factor gradually decreases to −1 and maintains −1 after 2900 V. The voltage of the HVDC bus ranges from 2950 V to 3050 V, which is the hysteresis area controlled by the system. In other words, the voltage of the HVDC bus will fluctuate in the voltage hysteresis area and stabilize at a certain voltage value.
4. Simulation Results
In order to verify the effectiveness of the CPET topology and its control strategy involved in this paper, a simulation model of the RBES system was built by Matlab software. The parameters used in the simulation are shown in Table 1.

In the power layer simulation, the variation of power scheduling value is shown in Figure 9. The whole schedule consists of six steadystate operating points and dynamic processes between them, which can reflect different operating conditions of the system, respectively. As can be seen in this figure, the grid voltage V_{ga} of phase A is taken as the reference signal, the threephase grid current can ensure tracking the grid voltage as a standard sine wave after the change of active and reactive power, and the RBES system can output the dispatching power value with no difference. In the startup and power switching state of the RBES system, the impact of the power grid is small, and the scheduling instructions can be quickly tracked and adjusted in a short time to meet the engineering requirements of the largecapacity system. In reactive or active scheduling instruction switching, the two can reach a stable state without mutual influence.
Figure 10 shows the modulation waveforms and the output voltage waveforms of each module when the DC unit group has different SOC values. In the simulation setting, the power of the energy storage system is 1.5 MW/1.5 MVar, and the SOC values of the DC unit group are 0.7, 0.7, 0.8, and 0.75 in turn.
It can be seen that each modulated wave has the same phase but different amplitude. In the detail figure, SOC values of H_{1a} module and H_{2a} module are the same, and the modulation wave is the same; the SOC value of H_{3a} module and H_{4a} module are both larger than that of H_{1a} module, so it can be seen that the amplitude of modulation is greater than that of H_{1a} module, and the difference of amplitude of modulation is equal. The corresponding output waveforms of each module are ±3 kV and 0 V level, while within a cycle, the phase shift between the drive signals of adjacent modules is 45°, and different modulation amplitude corresponds to the conduction time of different switching tube.
In the SOC layer simulation of the RBES system, the parameters of capacity and SOC value of repurposed lithium batteries within the DC unit group are shown in Table 2. The entire charging and discharging processes are simulated to verify the correctness of the SOC balancing strategy.

From the comparison and analysis of the SOC value in the charging and discharging simulation waveform diagrams in Figure 11, it can be seen that for repurposed lithium batteries with the same initial SOC value and actual capacity, the output voltage setting values of the corresponding modules are always the same (e.g., Ei_{k_1} and Ei_{k_2}). For repurposed lithium batteries with equal initial SOC but different actual capacity, with the increase of discharge time, the difference of output voltage setting values of modules gradually increases, but the SOC values remain the same (e.g., Ei_{k_1} and Ei_{k_3}). For repurposed lithium batteries with different initial SOC values and the same actual capacity, with the increase of discharge time, the output voltage setting values corresponding to the modules gradually tend to be consistent and finally equal, and the difference in SOC values also gradually decreases, tending to be consistent and finally equal (e.g., Ei_{k_1} and Ei_{k_4}). Under different working conditions of the RBES system, the voltage of highvoltage bus can always maintain a steady state of 3 kV, which verifies the effectiveness of the control.
5. Experimental Results
In order to test the control algorithm, a singlephase RBES gridconnected experimental system with rated power of 1 kW was designed by referring to the parameter design and device selection method of the aforementioned 3 MVA/12 kV system, so as to verify the correctness of the conclusions obtained from the above analysis. The experimental platform is designed as a singlephase AC 220 V gridconnected system, in which the number of cascaded Hbridges is N = 2, and the number of cascaded CFIBDC is set as M = 2. The design of the experimental platform is shown in Figure 12.
The rated power of the single CFIBDC converter is 250 W, the rated input voltage is 50 V, the output voltage is controlled at 100 V, and the two modules cascade to obtain 200 V. The rated power of a single Hbridge module is 500 W, the rated input voltage is 200 V, and the detailed parameters of the CFIBDC converter and CHB topology are shown in Table 3.

Figure 13 shows the experimental platform diagram of the DC unit group. In the experiment, two DC stabilized power supplies are connected to the CFIBDC converter cascaded to form a DC unit group, and the 200 V voltage obtained by cascading is connected to H_{1a} module. The other Hbridge module, H_{2a}, is directly connected to 200 V DC power supply. The experiment is mainly divided into two parts: one is the soft switching and voltage equalization analysis of the cascaded CFIBDC unit and the second is the fivelevel gridconnected output waveform under the carrier phase shift of the cascaded Hbridge unit, which mainly includes the cascaded Hbridge output voltage and current waveforms, active power, and reactive power compensation state waveforms.
Figure 14 shows the soft switching waveforms of the CFIBDC converter under the noload condition. In the noload state, the phase shift angle ϕ between the bridges is close to 0°, and the converter generates a circulating current through the phase shift angle ϕ_{s} inside the bridge to achieve ZVS. Figure 15 shows the soft switching waveforms at half load. When the load reaches a certain condition, the output current can realize the soft switching of the highvoltage side switching tubes. In order to improve the overall efficiency of the converter, the SPS phase shift method is adopted. The phase angle ϕ_{s} is always 0, and the converter can realize ZVS depending on the operating current.
(a)
(b)
Figure 16(a) shows the steadystate output waveforms at half load, the output voltage of each module has slight fluctuations, and the peaktopeak output voltage is less than 5 V, which meets the system requirements. The input voltage of the module D_{1a_1} is 45 V and the output voltage obtained by the equalization calculation is 95 V. The input voltage of the module D_{1a_2} is 50 V, and the output voltage obtained by the equalization calculation is 105 V. The measured output voltage can be seen that the steadystate output voltage of module D_{1a_1} is 95.1 V, the steadystate output voltage of module D_{1a_2} is 104 V, the cascaded output voltage is 200 V, and the output power is 250 W.
(a)
(b)
Figure 16(b) shows the dynamic waveforms switching from half load to 3/4 load. The steadystate output voltage of module D_{1a_1} is 95.1 V, the steadystate output voltage of module D_{1a_2} is 104 V, and the steadystate cascaded output voltage is 200 V. When the load is switched, the output voltage of the module D_{1a_2} fluctuates, which further affects the cascade output voltage, but the output gets the stability soon. It can be seen that the output voltage stabilizes before and after load switching of each module, which can realize different power output of each module under the premise of stable output voltage on the cascaded side.
Figure 17 shows the experimental waveforms when the output power of the CHB is 1.1 kW, and the current waveform is in phase with the voltage waveform. The effective value of the voltage is 220 V, the effective value of the current is 5 A, the frequency of voltage and current is 50 Hz, and the voltage and current waveforms are present. It is a standard sine wave with no phase difference.
Figure 18 shows the waveforms of the power switching. The CHB output voltage is not affected by power switching. The AC current i_{ga} has almost no distortion, and the voltage and current waveforms have no phase difference.
Figure 19 shows the waveforms of the offgrid operation with load and the gridconnected operation with resistive load. After gridconnected, the CHB converter delivers energy to both the offgrid load and the grid.
By comparing the experimental waveforms and simulation waveforms, the correctness and effectiveness of the theory can be verified. The whole system can realize active and reactive power grid connection in the cascade state of modules.
6. Conclusions
Based on the research background of cascade utilization of repurposed batteries in power energy storage system, a series of analysis and research on RBES system based on CPET were carried out in this paper. The topological structure and control strategy of DCAC stage and DCDC stage in this system were analyzed.
CPET is composed of current fed dual active bridge modules and Hbridge module. AC side can be directly connected to the medium and high voltage power grid, and lowvoltage side has an independent DC output end. The hierarchical control strategy of the RBES system based on CPET is composed of the energy layer, the power layer, and the SOC layer. The energy layer responds to the active and reactive scheduling instructions, the power layer controls the gridconnected current and tracks the grid voltage, and the SOC layer equates the charged state of repurposed batteries.
Data Availability
The data used to support the findings of this study were supplied by Jiaxun Teng under license and so cannot be made freely available. Requests for access to these data should be made to Jiaxun Teng (tengjiaxun@qq.com).
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this study.
Acknowledgments
This work was funded by the Science and Technology Project of State Grid Corporation of China “Research funding of energy Internet multienergy flow integration and routing technology based on multiport energy router.”
References
 O. O. Mengi and I. H. Altas, “A new energy management technique for PV/wind/grid renewable energy system,” International Journal of Photoenergy, vol. 2015, Article ID 356930, 19 pages, 2015. View at: Publisher Site  Google Scholar
 T. Cheng, M. Chen, Y. Wang et al., “Adaptive robust method for dynamic economic emission dispatch incorporating renewable energy and energy storage,” Complexity, vol. 2018, Article ID 2517987, 13 pages, 2018. View at: Publisher Site  Google Scholar
 R. Zhu, A. L. Zhao, G. C. Wang, X. Xia, and Y. Yang, “An energy storage performance improvement model for gridconnected windsolar hybrid energy storage system,” Computational Intelligence and Neuroscience, vol. 2020, Article ID 8887227, 10 pages, 2020. View at: Publisher Site  Google Scholar
 L. Chen, Li Ren, L. Zhu, T. Wang, and Y. Li, “Wind generation systems including energy storage,” International Journal of Rotating Machinery, vol. 2017, Article ID 7424812, 9 pages, 2017. View at: Publisher Site  Google Scholar
 A. Cavallo, G. Canciello, and B. Guida, “Energy storage system control for energy management in advanced aeronautic applications,” Mathematical Problems in Engineering, vol. 2017, Article ID 4083132, 9 pages, 2017. View at: Publisher Site  Google Scholar
 R. Singh, S. Taghizadeh, N. M. L. Tan, and J. Pasupuleti, “Battery energy storage system for PV output power leveling,” Advances in Power Electronics, vol. 2014, Article ID 796708, 11 pages, 2014. View at: Publisher Site  Google Scholar
 S. Jin, Z. Mao, H. Li, and W. Qi, “Dynamic operation management of a renewable microgrid including battery energy storage,” Mathematical Problems in Engineering, vol. 2018, Article ID 5852309, 19 pages, 2018. View at: Publisher Site  Google Scholar
 W.Y. Chang, “The state of charge estimating methods for battery: a review,” International Scholarly Research Notices, vol. 2013, Article ID 953792, 12 pages, 2013. View at: Publisher Site  Google Scholar
 J. Gonçalves de Oliveira and H. Bernhoff, “Battery recharging issue for a twopowerlevel flywheel system,” Journal of Electrical and Computer Engineering, vol. 2010, Article ID 470525, 5 pages, 2010. View at: Publisher Site  Google Scholar
 B. Yu, “Design and experimental results of battery charging system for microgrid system,” International Journal of Photoenergy, vol. 2016, Article ID 7134904, 6 pages, 2016. View at: Publisher Site  Google Scholar
 Y. Han, J. Wang, Q. Zhao, and P. Han, “An optimal operating strategy for battery life cycle costs in electric vehicles,” Journal of Applied Mathematics, vol. 2014, Article ID 305905, 6 pages, 2014. View at: Publisher Site  Google Scholar
 S. Y. Kim and G.I. Kwon, “Interruptbased stepcounting to extend battery life in an activity monitor,” Journal of Sensors, vol. 2016, Article ID 5824523, 6 pages, 2016. View at: Publisher Site  Google Scholar
 E. Yao, M. Wang, Y. Song, and Y. Yang, “State of charge estimation based on microscopic driving parameters for electric vehicle’s battery,” Mathematical Problems in Engineering, vol. 2013, Article ID 946747, 6 pages, 2013. View at: Publisher Site  Google Scholar
 L. Chen, K. Qian., M. Qin., X. Xu., and Y. Xia., “A configurationcontrol integrated strategy for electric bus charging station with echelon battery system,” IEEE Transactions on Industry Applications, vol. 56, no. 5, pp. 6019–6028, 2020. View at: Publisher Site  Google Scholar
 T. Zhao, J. Jiang, C. Zhang, K. Bai, and N. Li, “Robust online state of charge estimation of lithiumion battery pack based on error sensitivity analysis,” Mathematical Problems in Engineering, vol. 2015, Article ID 573184, 11 pages, 2015. View at: Publisher Site  Google Scholar
 Y. Wei, S. Dai, J. Wang, Z. Shan, and J. Min, “Switch matrix algorithm for series lithium battery pack equilibrium based on derived acceleration information gaussseidel,” Mathematical Problems in Engineering, vol. 2019, Article ID 8075453, 9 pages, 2019. View at: Publisher Site  Google Scholar
 H. Hasabelrasul, X. Yan, and A. S. Gadalla, “Cascaded Hbridge multilevel inverter balancing for energypower based on VSG,” in Proceedings of the 2019 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE), pp. 1–5, Khartoum, Sudan, 2019. View at: Google Scholar
 X. Yan. and H. Hasabelrasul, “Active power analysis for the battery energy storage systems based on a modern cascaded multilevel converter,” in Proceedings of the 2018 IEEE International Conference on Energy Internet (ICEI), pp. 111–116, Beijing, China, 2018. View at: Google Scholar
 A. Moeini. and S. Wang, “The State of charge balancing techniques for electrical vehicle charging stations with cascaded Hbridge multilevel converters,” in Proceedings of the 2018 IEEE Applied Power Electronics Conference and Exposition (APEC), pp. 637–644, San Antonio, TX, USA, 2018. View at: Google Scholar
 T. Hu., L. Xu., L. Qiu., Y. Li, and X. Han, “A hybrid converter for energy management of EV drives,” in Proceedings of the 2015 IEEE Applied Power Electronics Conference and Exposition (APEC), pp. 3132–3137, Charlotte, North Carolina, 2015. View at: Google Scholar
 K. Kandasamy, D. M. Vilathgamuwa, and G. Foo, “Intermodule SoC balancing control for CHB based BESS using multidimensional modulation,” in Proceedings of the 2013 IEEE International Conference on Industrial Technology (ICIT), pp. 1630–1635, Cape Town, South Africa, 2013. View at: Publisher Site  Google Scholar
Copyright
Copyright © 2021 Guanglin Sha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.