Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend
For the optimal power distribution problem of battery energy storage power stations containing multiple energy storage units, a grouping control strategy considering the wind and solar power generation trend is proposed. Firstly, a state of charge (SOC) consistency algorithm based on multi-agent is...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/4/1857 |
| _version_ | 1797621233854971904 |
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| author | Wei Guo Wenyi Fan Yang Zhao Jiakun An Chunguang He Xiaomei Guo Yanan Qian Libo Ma Hongshan Zhao |
| author_facet | Wei Guo Wenyi Fan Yang Zhao Jiakun An Chunguang He Xiaomei Guo Yanan Qian Libo Ma Hongshan Zhao |
| author_sort | Wei Guo |
| collection | DOAJ |
| description | For the optimal power distribution problem of battery energy storage power stations containing multiple energy storage units, a grouping control strategy considering the wind and solar power generation trend is proposed. Firstly, a state of charge (SOC) consistency algorithm based on multi-agent is proposed. The adaptive power distribution among the units started can be realized using this algorithm. Then, considering the trend of wind and solar power generation, a reasonable grouping control strategy is formulated. The grouping situation of the units is determined by using the probability distribution characteristics of energy storage charging and discharging, which reduces the number of charging and discharging conversions and extends the power station life. Finally, the actual data of a wind–solar energy storage microgrid is used to verify the method. The simulation results demonstrate that the proposed method has certain advantages in terms of control effect, SOC consistency, and extending the power station life. |
| first_indexed | 2024-03-11T08:52:55Z |
| format | Article |
| id | doaj.art-7b88ec8ef6114b09aa35e04159448718 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T08:52:55Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7b88ec8ef6114b09aa35e041594487182023-11-16T20:18:46ZengMDPI AGEnergies1996-10732023-02-01164185710.3390/en16041857Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation TrendWei Guo0Wenyi Fan1Yang Zhao2Jiakun An3Chunguang He4Xiaomei Guo5Yanan Qian6Libo Ma7Hongshan Zhao8State Grid Hebei Economic Research Institute, Shijiazhuang 050023, ChinaState Grid Hebei Economic Research Institute, Shijiazhuang 050023, ChinaState Grid Hebei Economic Research Institute, Shijiazhuang 050023, ChinaState Grid Hebei Economic Research Institute, Shijiazhuang 050023, ChinaState Grid Hebei Economic Research Institute, Shijiazhuang 050023, ChinaSchool of Electrical Engineering, North China Electric Power University, Baoding 071000, ChinaSchool of Electrical Engineering, North China Electric Power University, Baoding 071000, ChinaSchool of Electrical Engineering, North China Electric Power University, Baoding 071000, ChinaSchool of Electrical Engineering, North China Electric Power University, Baoding 071000, ChinaFor the optimal power distribution problem of battery energy storage power stations containing multiple energy storage units, a grouping control strategy considering the wind and solar power generation trend is proposed. Firstly, a state of charge (SOC) consistency algorithm based on multi-agent is proposed. The adaptive power distribution among the units started can be realized using this algorithm. Then, considering the trend of wind and solar power generation, a reasonable grouping control strategy is formulated. The grouping situation of the units is determined by using the probability distribution characteristics of energy storage charging and discharging, which reduces the number of charging and discharging conversions and extends the power station life. Finally, the actual data of a wind–solar energy storage microgrid is used to verify the method. The simulation results demonstrate that the proposed method has certain advantages in terms of control effect, SOC consistency, and extending the power station life.https://www.mdpi.com/1996-1073/16/4/1857energy storage unitpower distributionmulti-agentgrouping battery unitswind and solar power generation trend |
| spellingShingle | Wei Guo Wenyi Fan Yang Zhao Jiakun An Chunguang He Xiaomei Guo Yanan Qian Libo Ma Hongshan Zhao Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend Energies energy storage unit power distribution multi-agent grouping battery units wind and solar power generation trend |
| title | Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend |
| title_full | Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend |
| title_fullStr | Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend |
| title_full_unstemmed | Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend |
| title_short | Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend |
| title_sort | grouping control strategy for battery energy storage power stations considering the wind and solar power generation trend |
| topic | energy storage unit power distribution multi-agent grouping battery units wind and solar power generation trend |
| url | https://www.mdpi.com/1996-1073/16/4/1857 |
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