With the accelerating transformation of the energy structure, battery energy storage systems have become increasingly critical in modern power grids. Traditional centralized battery energy storage systems suffer from parallel mismatch between battery clusters, low charging/discharging efficiency, and high operation and maintenance costs. To address these challenges, we propose a novel string-type battery energy storage system that employs a dual-stage architecture combining single-cluster management with modularized power conversion systems (PCS). By integrating optimizers at the battery pack level and controllers at the battery cluster level, this system significantly enhances the overall performance, improves the electrical balance among battery packs, and provides a new pathway for the development of battery energy storage systems.
1. Energy Storage Technology Research
Centralized battery energy storage systems represent a traditional technical route, while string-type battery energy storage systems offer a more advanced approach. String-type systems outperform centralized systems in discharge performance, investment cost, operation and maintenance, safety, system design, wiring, and management.
1.1 Advantages of String-Type Battery Energy Storage Systems
Discharge Performance: String-type battery energy storage systems utilize battery pack optimization technology to effectively eliminate capacity loss caused by series mismatch within battery clusters (typically, a battery pack consists of 18 cells in series, and a battery cluster consists of 21 battery packs in series). The intelligent single-cluster controller further prevents capacity loss due to circulating currents. As a result, the total discharge energy over the entire lifecycle of a string-type battery energy storage system is increased by 6% compared to a centralized system. Without battery pack equalization design, centralized systems cannot manage the imbalance between packs within a cluster, leading to incomplete charge/discharge cycles and reduced usable capacity.
Investment Cost: String-type battery energy storage systems adopt high-density factory pre-installation solutions, reducing on-site delivery costs to 0.01–0.03 CNY/Wh. Moreover, these systems support mixing new and old batteries and flexible battery replenishment, allowing an initial capacity reduction of 30% compared to centralized systems. Centralized systems require an initial overcapacity of more than 30% to compensate for the lack of replenishment capability, thereby increasing upfront capital expenditure.
Operation and Maintenance: String-type battery energy storage systems simplify maintenance by eliminating the need for manual state-of-charge (SOC) adjustment of replacement batteries or regular SOC calibration. Battery packs can be replaced directly on site, reducing operation and maintenance costs by over 90%. In contrast, centralized systems require labor-intensive SOC adjustment and periodic calibration.
Safety: String-type battery energy storage systems incorporate an advanced internal short-circuit detection algorithm based on artificial intelligence (AI) outlier detection. This algorithm detects sudden and derivative internal short circuits, achieving early warning and protection, thereby improving system safety by more than 90%. Centralized systems struggle to identify internal short circuits, posing a higher fire risk.
System Design: String-type battery energy storage systems feature modular design covering temperature control, battery systems, and PCS, achieving a system availability of over 99.9%. A single PCS failure in a centralized system can affect the entire container, reducing availability to 97%–98%.
Wiring and Management: String-type battery energy storage systems automatically generate AC/DC wiring topology diagrams without manual configuration. The system displays wiring status and abnormal alerts intuitively, eliminating physical inspection. In contrast, centralized systems require manual wiring configuration. For management, string-type systems use 3D visualization to present cluster-level and battery-pack-level data, including real-time SOC and charging/discharging power for every pack, along with monitoring of cell state-of-health (SOH), SOC, temperature, and voltage. Centralized systems only show the highest and lowest module SOC values, lacking comprehensive module status visibility and making fault location difficult.
1.2 Optimizer Testing
To verify the performance enhancement provided by the battery pack optimizer, we conducted a comparative test on two battery clusters from a string-type battery energy storage system. Each battery pack includes a housing, cells, a battery management unit (BMU), and an optimizer. The battery pack parameters are listed in Table 1.
| Parameter | Value |
|---|---|
| Cell configuration | 1P18S |
| Rated voltage (V) | 57.6 |
| Rated capacity (Ah) | 280 |
| Rated energy (kWh) | 16.13 |
| Dimensions (L×W×H) (mm) | 442×307×660 |
The battery cluster consists of a battery rack and 21 battery modules (including BMS and optimizer). Key parameters are shown in Table 2.
| Parameter | Value |
|---|---|
| Rated voltage (V) | 1075.2 |
| Rated capacity (Ah) | 280 |
| Rated energy (kWh) | 338.7 |
| Dimensions (H×L×W) (mm) | 1565.0×2475.0×787.5 |
| Optimal operating temperature (°C) | 10–40 |
We collected charge/discharge energy data over six months for both clusters. Table 3 compares the average charge/discharge energy with the optimizer turned off and on.
| Optimizer Status | Rated Energy (kWh) | Charge-Discharge Energy (kWh) |
|---|---|---|
| Off | 338.7 | 320.1 |
| On | 338.7 | 327.7 |
Additionally, we measured the total grid-exported energy and grid-imported energy (including auxiliary power) over one month and calculated the overall efficiency. The results are shown in Table 4.
| Optimizer Status | Exported Energy (kWh) | Imported Energy (kWh) | Overall Efficiency (%) |
|---|---|---|---|
| Off | 46236.6 | 58527.4 | 79.00 |
| On | 48224.8 | 59346.7 | 81.26 |
From Tables 3 and 4, we observe that with the optimizer enabled, the average charge-discharge energy increases by 2.37%, from 320.1 kWh to 327.7 kWh, and the overall efficiency improves by 2.26%, from 79.00% to 81.26%. These improvements demonstrate the effectiveness of the optimizer in enhancing the performance of the battery energy storage system.
1.3 Mainstream PCS Architectures
The large-scale PCS architectures currently in use include: centralized PCS architecture, single-cluster management + modularized PCS dual-stage architecture, and single-cluster management + modularized PCS single-stage architecture. Since the dual-stage architecture encompasses all functions of the single-stage version, we focus on the first two. The schematic diagrams of these two architectures are illustrated below.
In the centralized architecture (see the conceptual representation above), battery modules are connected in series to form battery clusters. Each cluster is equipped with a high-voltage box, and multiple clusters are connected in parallel before being fed into a single large-capacity centralized PCS. The AC output is then stepped up to 35 kV. In the dual-stage architecture, a cluster controller (DC/DC converter) is added to each cluster. After parallel connection, the combined output is fed into a modularized PCS, enabling independent cluster management before the final AC voltage step-up to 35 kV.
2. Experimental Results and Analysis
We now analyze the performance of the proposed string-type battery energy storage system from the perspectives of PCS architecture comparison, BMS advantages, PCS advantages, and system-level configuration.
2.1 PCS Architecture Comparison
Table 5 provides a comprehensive comparison of the centralized PCS architecture and the dual-stage single-cluster management + modularized PCS architecture across multiple dimensions relevant to battery energy storage systems.
| Evaluation Criterion | Centralized PCS Architecture | Single-Cluster Management + Modularized PCS Dual-Stage Architecture |
|---|---|---|
| Discharge energy | Low – parallel mismatch between clusters causes loss of usable capacity and power. | High – eliminates parallel mismatch, achieving >6% more discharge energy than centralized. |
| System configuration flexibility | Poor – cannot mix old and new batteries; expansion requires simultaneous battery and PCS upgrades, affecting AC capacity. | Good – allows mixing of different battery clusters and configurations, supports old/new battery sharing; expansion does not affect AC capacity. |
| Grid connection performance | Meets GB 51048-2014 standard. | Meets GB 51048-2014; additionally, the power variation during high-voltage ride-through is limited to ≤10%. |
| Maintainability | Poor – large PCS requires professional on-site maintenance. | Good – modular DC/DC converters and PCS are easy to maintain. |
| Availability | Low – centralized PCS module failure cannot be isolated individually. | High – modular design allows fault isolation and replacement of individual modules. |
| Safety | Low – no individual module isolation; risk of circulating currents between clusters. | High – eliminates circulating currents between clusters. |
2.2 Advantages of the Battery Management System (BMS)
2.2.1 BMS Architecture
The BMS is the core of the string-type battery energy storage system. It comprises four hierarchical levels: the Battery Management Unit (BMU), the Battery Cluster Unit (BCU), the Central Management Unit (CMU), and the Smart Array Control Unit (SACU). This hierarchical structure enables precise measurement, control, and protection of the battery system. Each battery pack is equipped with one BMU (Level 1), which performs real-time monitoring of physical parameters, SOC estimation, online diagnostics, charge/discharge control, equalization, and thermal management. Each battery cluster is controlled by one BCU (Level 2), which independently manages the cluster to avoid bias currents and the “short-plank effect,” ensuring stable output power. The BCU also performs SOC/SOH estimation, thermal runaway management, and communicates via CAN bus with the upper layers. The CMU (Level 3) manages all BCUs, provides data analysis, anomaly alarming, and safety control. Finally, the SACU (Level 4) acts as the advanced control layer, coordinating the CMU, PCS, and the energy management system (EMS) to execute dispatch commands and manage energy flow.
2.2.2 Key BMS Functions
The BMS of the proposed battery energy storage system offers several advanced functions:
- High-precision real-time acquisition of cell temperature, voltage, pack voltage, cluster voltage, and current to optimize battery operation.
- Accurate SOC and SOH estimation with automatic calibration, including calculation of cycle count, depth of discharge (DOD), and other critical parameters.
- Precise charge/discharge control based on SOC planning and fault diagnostics with appropriate responses.
- Distributed thermal management: each cluster is independently cooled by a door-mounted air conditioner, and each pack contains a speed-adjustable fan. The temperature difference between packs within a container is kept below 3°C at 0.5C charge rate. Thermal protection thresholds trigger fan speed adjustment or system shutdown if dangerous temperatures are reached.
- Interoperability with PCS via SACU for information exchange using Ethernet, fiber, or RS485 interfaces.
- Multi-level equalization: cell-level, pack-level, and cluster-level equalization to mitigate capacity loss and circulating current risks caused by inconsistency.
- Local and remote operation, displaying system status, alarms, and event logs.
- Local storage of at least 5000 events and 30 days of historical data, complying with GB/T 34131-2023.
2.3 PCS Advantages
The PCS in the string-type battery energy storage system features single-cluster management capability, enabling independent SOC calibration for each cluster and eliminating circulating currents that could compromise safety and battery life. It also supports flexible DC-side battery replenishment, allowing the safe mixing of old and new battery clusters without direct parallel connection. The PCS adopts a modular design with a rated power per unit not exceeding 250 kW, which improves maintainability and system availability of the entire battery energy storage system.
2.4 Proposed String-Type Battery Energy Storage System Configuration
2.4.1 Diverse Application Scenarios
The proposed string-type battery energy storage system has been successfully deployed in extreme environments including high-temperature regions (Hainan Province), extremely cold regions (Jilin Province), and high-altitude areas (Qinghai Province). It has also been applied in various scenarios such as spinning reserve and grid frequency regulation in Singapore, shared energy storage in Hubei Province, grid ancillary services (peak shaving) in China, and enterprise power reliability (behind-the-meter) in Jiangsu Province.
2.4.2 Typical Containerized Energy Storage Solution
We designed a containerized battery energy storage system with a total capacity of 2.032 MWh, integrated into a standard 0.3048 m height container. The system composition is listed in Table 6, and a schematic layout is shown below (note: the figure is representative).
| Equipment | Model and Specification |
|---|---|
| Container energy storage system | LUNA2000-2.0 MWh |
| Battery | 3.2V/280Ah cells, 1P18S module, 21 modules per cluster, 6 clusters total |
| BMS | Includes BMU, BCU, CMU, and communication harness |
| Cluster controller | DC/DC converter (2 independent inputs per unit) |
| HVAC system | Distributed air conditioners |
| Fire protection system | Smoke detectors, temperature sensors, fire alarm panel, FK-5-1-12 gas, alarm bell, etc. |
The configuration ensures safe and efficient operation of the battery energy storage system in various conditions.
3. Conclusion
We have proposed a novel string-type battery energy storage system that effectively addresses the key limitations of traditional centralized systems. Through comparative testing and analysis, we demonstrated significant improvements in performance, safety, and economics. The dual-stage architecture combining single-cluster management with modularized PCS, along with battery pack optimizers, increases the average charge-discharge energy by 2.37% and overall efficiency by 2.26%. The system has been verified in extreme environments and diverse application scenarios, proving its wide adaptability and high efficiency. Future work will focus on further optimizing the system design, expanding its application range, and promoting the widespread adoption of advanced battery energy storage systems.