Optimal configuration of 5G base station energy storage considering sleep mechanism
The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries. To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operatio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2022-02-01
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| Series: | Global Energy Interconnection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096511722000263 |
| _version_ | 1828554585907658752 |
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| author | Xiufan Ma Qiuping Zhu Ying Duan Xiangyu Meng Zhi Wang |
| author_facet | Xiufan Ma Qiuping Zhu Ying Duan Xiangyu Meng Zhi Wang |
| author_sort | Xiufan Ma |
| collection | DOAJ |
| description | The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries. To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operation of the energy storage, and the planning of 5G base stations considering the sleep mechanism. A multi-base station cooperative system composed of 5G acer stations was considered as the research object, and the outer goal was to maximize the net profit over the complete life cycle of the energy storage. Furthermore, the power and capacity of the energy storage configuration were optimized. The inner goal included the sleep mechanism of the base station, and the optimization of the energy storage charging and discharging strategy, for minimizing the daily electricity expenditure of the 5G base station system. Additionally, genetic algorithm and mixed integer programming were used to solve the bi-level optimization model, analyze the numerical example test comparison of the three types of batteries and the net income of the configuration, and finally verify the validity of the model. Furthermore, the sleep mechanism, the charging and discharging strategy for energy consumption, and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration. |
| first_indexed | 2024-12-12T05:38:26Z |
| format | Article |
| id | doaj.art-a98b66b2f37a41678757930b45bcc280 |
| institution | Directory Open Access Journal |
| issn | 2096-5117 |
| language | English |
| last_indexed | 2024-12-12T05:38:26Z |
| publishDate | 2022-02-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Global Energy Interconnection |
| spelling | doaj.art-a98b66b2f37a41678757930b45bcc2802022-12-22T00:36:01ZengKeAi Communications Co., Ltd.Global Energy Interconnection2096-51172022-02-01516676Optimal configuration of 5G base station energy storage considering sleep mechanismXiufan Ma0Qiuping Zhu1Ying Duan2Xiangyu Meng3Zhi Wang4School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, PR ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, PR ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, PR ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, PR ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, PR ChinaThe high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries. To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operation of the energy storage, and the planning of 5G base stations considering the sleep mechanism. A multi-base station cooperative system composed of 5G acer stations was considered as the research object, and the outer goal was to maximize the net profit over the complete life cycle of the energy storage. Furthermore, the power and capacity of the energy storage configuration were optimized. The inner goal included the sleep mechanism of the base station, and the optimization of the energy storage charging and discharging strategy, for minimizing the daily electricity expenditure of the 5G base station system. Additionally, genetic algorithm and mixed integer programming were used to solve the bi-level optimization model, analyze the numerical example test comparison of the three types of batteries and the net income of the configuration, and finally verify the validity of the model. Furthermore, the sleep mechanism, the charging and discharging strategy for energy consumption, and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.http://www.sciencedirect.com/science/article/pii/S20965117220002635G base stationSleep mechanismEnergy storage configurationFull life cycleBi-level optimization |
| spellingShingle | Xiufan Ma Qiuping Zhu Ying Duan Xiangyu Meng Zhi Wang Optimal configuration of 5G base station energy storage considering sleep mechanism Global Energy Interconnection 5G base station Sleep mechanism Energy storage configuration Full life cycle Bi-level optimization |
| title | Optimal configuration of 5G base station energy storage considering sleep mechanism |
| title_full | Optimal configuration of 5G base station energy storage considering sleep mechanism |
| title_fullStr | Optimal configuration of 5G base station energy storage considering sleep mechanism |
| title_full_unstemmed | Optimal configuration of 5G base station energy storage considering sleep mechanism |
| title_short | Optimal configuration of 5G base station energy storage considering sleep mechanism |
| title_sort | optimal configuration of 5g base station energy storage considering sleep mechanism |
| topic | 5G base station Sleep mechanism Energy storage configuration Full life cycle Bi-level optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2096511722000263 |
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