Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance
Battery energy storage systems are widely used in energy storage microgrids. As the index of stored energy level of a battery, balancing the State-of-Charge (SoC) can effectively restrain the circulating current between battery cells. Compared with passive balance, active balance, as the most popula...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Batteries |
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| Online Access: | https://www.mdpi.com/2313-0105/9/1/18 |
| _version_ | 1797446084502487040 |
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| author | Yalin Zhang Zhongxin Liu Zengqiang Chen |
| author_facet | Yalin Zhang Zhongxin Liu Zengqiang Chen |
| author_sort | Yalin Zhang |
| collection | DOAJ |
| description | Battery energy storage systems are widely used in energy storage microgrids. As the index of stored energy level of a battery, balancing the State-of-Charge (SoC) can effectively restrain the circulating current between battery cells. Compared with passive balance, active balance, as the most popular SoC balance method, maximizes the capacity of the battery cells and reduces heat generation. However, there is no good solution in the battery management system (BMS) to ensure active balance during distributed charging. In view of this, this paper designs two novel distributed charging strategies based on a kind of smart leader, in which a constant static leader is modified by a dynamic leader. The modified leader is in charge of guiding SoC to converge to the target value and repress SoC imbalance. The maximum and weighed error between the state of the leader and its neighbor cells are used in the two methods, respectively, both in an event triggered manner. When the relevant index exceeds the threshold, the two methods are used to regulate the leader’s state. Under this modification, the eigenvalue of the followers’ error dynamic system is reduced, and SoCs follow the dynamic leader faster, thus repressing SoC imbalance. Compared with a constant leader, the smart leader pays more attention to improving SoC imbalance. Additionally, to facilitate analysis, a reduced method is applied to transform the system with an unified input time delay into a nondelay system. Several cases are designed to verify the effectiveness of the designed strategies and test it under different parameters and different time delays. |
| first_indexed | 2024-03-09T13:36:09Z |
| format | Article |
| id | doaj.art-8dddffe5d6b843ecb267e4a511688bc6 |
| institution | Directory Open Access Journal |
| issn | 2313-0105 |
| language | English |
| last_indexed | 2024-03-09T13:36:09Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Batteries |
| spelling | doaj.art-8dddffe5d6b843ecb267e4a511688bc62023-11-30T21:12:29ZengMDPI AGBatteries2313-01052022-12-01911810.3390/batteries9010018Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC BalanceYalin Zhang0Zhongxin Liu1Zengqiang Chen2The College of Artificial Intelligence, Nankai University, Tianjin 300350, ChinaThe College of Artificial Intelligence, Nankai University, Tianjin 300350, ChinaThe College of Artificial Intelligence, Nankai University, Tianjin 300350, ChinaBattery energy storage systems are widely used in energy storage microgrids. As the index of stored energy level of a battery, balancing the State-of-Charge (SoC) can effectively restrain the circulating current between battery cells. Compared with passive balance, active balance, as the most popular SoC balance method, maximizes the capacity of the battery cells and reduces heat generation. However, there is no good solution in the battery management system (BMS) to ensure active balance during distributed charging. In view of this, this paper designs two novel distributed charging strategies based on a kind of smart leader, in which a constant static leader is modified by a dynamic leader. The modified leader is in charge of guiding SoC to converge to the target value and repress SoC imbalance. The maximum and weighed error between the state of the leader and its neighbor cells are used in the two methods, respectively, both in an event triggered manner. When the relevant index exceeds the threshold, the two methods are used to regulate the leader’s state. Under this modification, the eigenvalue of the followers’ error dynamic system is reduced, and SoCs follow the dynamic leader faster, thus repressing SoC imbalance. Compared with a constant leader, the smart leader pays more attention to improving SoC imbalance. Additionally, to facilitate analysis, a reduced method is applied to transform the system with an unified input time delay into a nondelay system. Several cases are designed to verify the effectiveness of the designed strategies and test it under different parameters and different time delays.https://www.mdpi.com/2313-0105/9/1/18state-of-charge (SoC)battery energy storage systemmultiagent systemsSoC balancesmart leaders |
| spellingShingle | Yalin Zhang Zhongxin Liu Zengqiang Chen Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance Batteries state-of-charge (SoC) battery energy storage system multiagent systems SoC balance smart leaders |
| title | Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance |
| title_full | Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance |
| title_fullStr | Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance |
| title_full_unstemmed | Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance |
| title_short | Smart-Leader-Based Distributed Charging Control of Battery Energy Storage Systems Considering SoC Balance |
| title_sort | smart leader based distributed charging control of battery energy storage systems considering soc balance |
| topic | state-of-charge (SoC) battery energy storage system multiagent systems SoC balance smart leaders |
| url | https://www.mdpi.com/2313-0105/9/1/18 |
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