Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation
Since renewable energy generation has strong uncertainties and pure conventional unit dispatch schemes are limited by the unit-operating capacities, such scheduling is inapplicable for power systems with high proportions of renewable energy sources (RESs). We propose an optimal scheduling model for...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2025.1588704/full |
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| author | Zhi Li Dawei Xie Haifeng Ye Yujun Li Jinzhong Li Yichi Chen Yue Yang |
| author_facet | Zhi Li Dawei Xie Haifeng Ye Yujun Li Jinzhong Li Yichi Chen Yue Yang |
| author_sort | Zhi Li |
| collection | DOAJ |
| description | Since renewable energy generation has strong uncertainties and pure conventional unit dispatch schemes are limited by the unit-operating capacities, such scheduling is inapplicable for power systems with high proportions of renewable energy sources (RESs). We propose an optimal scheduling model for battery energy storage systems (BESSs) by considering the uncertainties of RESs. The probability distribution of renewable energy generation is characterized using a Gaussian mixture model that effectively captures its stochastic nature. Chance constraints are incorporated into the dispatch model to enhance system security while ensuring sufficient reserve capacity to mitigate fluctuations in the RES outputs. Furthermore, these constraints are transformed into their deterministic equivalents using quantile-based methods. Case studies were then conducted on two systems to demonstrate the ability of the proposed model to improve system security and economic efficiency. The results indicate that incorporating BESSs can significantly reduce the system risk probability and operational costs, particularly under scenarios with high RES penetration. The model also highlights the tradeoffs between BESS capacity and system risk levels as well as constraint settings and economic benefits to provide valuable insights for practical applications. It is expected that future efforts in this field will be focused on extending the model to include the impacts of BESSs on branch power transmission risks. |
| format | Article |
| id | doaj-art-567260e1e48b4d3cac84ef64a48134dc |
| institution | OA Journals |
| issn | 2296-598X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj-art-567260e1e48b4d3cac84ef64a48134dc2025-08-20T02:24:25ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2025-06-011310.3389/fenrg.2025.15887041588704Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generationZhi Li0Dawei Xie1Haifeng Ye2Yujun Li3Jinzhong Li4Yichi Chen5Yue Yang6State Grid Anhui Electric Power Co., Ltd., Hefei, ChinaState Grid Anhui Electric Power Co., Ltd., Hefei, ChinaState Grid Anhui Electric Power Co., Ltd., Hefei, ChinaState Grid Anhui Electric Power Co., Ltd., Hefei, ChinaState Grid Anhui Electric Power Co., Ltd., Hefei, ChinaSchool of Electrical Engineering and Automation, Hefei University of Technology, Hefei, ChinaSchool of Electrical Engineering and Automation, Hefei University of Technology, Hefei, ChinaSince renewable energy generation has strong uncertainties and pure conventional unit dispatch schemes are limited by the unit-operating capacities, such scheduling is inapplicable for power systems with high proportions of renewable energy sources (RESs). We propose an optimal scheduling model for battery energy storage systems (BESSs) by considering the uncertainties of RESs. The probability distribution of renewable energy generation is characterized using a Gaussian mixture model that effectively captures its stochastic nature. Chance constraints are incorporated into the dispatch model to enhance system security while ensuring sufficient reserve capacity to mitigate fluctuations in the RES outputs. Furthermore, these constraints are transformed into their deterministic equivalents using quantile-based methods. Case studies were then conducted on two systems to demonstrate the ability of the proposed model to improve system security and economic efficiency. The results indicate that incorporating BESSs can significantly reduce the system risk probability and operational costs, particularly under scenarios with high RES penetration. The model also highlights the tradeoffs between BESS capacity and system risk levels as well as constraint settings and economic benefits to provide valuable insights for practical applications. It is expected that future efforts in this field will be focused on extending the model to include the impacts of BESSs on branch power transmission risks.https://www.frontiersin.org/articles/10.3389/fenrg.2025.1588704/fullbattery energy storage systemrenewable energyGaussian mixture modelchance constraintoptimal dispatchsystem risk |
| spellingShingle | Zhi Li Dawei Xie Haifeng Ye Yujun Li Jinzhong Li Yichi Chen Yue Yang Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation Frontiers in Energy Research battery energy storage system renewable energy Gaussian mixture model chance constraint optimal dispatch system risk |
| title | Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| title_full | Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| title_fullStr | Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| title_full_unstemmed | Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| title_short | Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| title_sort | chance constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation |
| topic | battery energy storage system renewable energy Gaussian mixture model chance constraint optimal dispatch system risk |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2025.1588704/full |
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