Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing
Amidst the escalating challenges of global warming and energy crises, the rapid development of distributed renewable energy resources has emerged as a critical strategy. Regional integrated energy systems (RIESs) have garnered significant attention for their potential to integrate and optimize both...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Industrial Electronics Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10890923/ |
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| author | Kun Cui Ming Chi Yong Zhao Zhi-Wei Liu |
| author_facet | Kun Cui Ming Chi Yong Zhao Zhi-Wei Liu |
| author_sort | Kun Cui |
| collection | DOAJ |
| description | Amidst the escalating challenges of global warming and energy crises, the rapid development of distributed renewable energy resources has emerged as a critical strategy. Regional integrated energy systems (RIESs) have garnered significant attention for their potential to integrate and optimize both distributed renewable energy resources and conventional energy facilities. This article presents a bilevel optimization framework for the electricity-storage coupling market in multi-RIES, considering the integration of 6G network slicing technology and battery energy storage (BES) capacity sharing. The upper-level model maximizes the profit of generation units by optimizing their bidding strategies, while the lower-level model aims to maximize social welfare through market clearing. The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. Numerical case studies validate the effectiveness of the proposed framework, demonstrating enhanced BES utilization, increased renewable energy generation, and improved social welfare. The results also highlight the sensitivity of social welfare to communication costs, underscoring the importance of careful cost calibration. |
| format | Article |
| id | doaj-art-80aa03b0f2d643b185ecf1e2105d98e0 |
| institution | Kabale University |
| issn | 2644-1284 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Industrial Electronics Society |
| spelling | doaj-art-80aa03b0f2d643b185ecf1e2105d98e02025-08-20T03:40:40ZengIEEEIEEE Open Journal of the Industrial Electronics Society2644-12842025-01-01639641410.1109/OJIES.2025.354226210890923Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity SharingKun Cui0https://orcid.org/0009-0004-6751-0221Ming Chi1https://orcid.org/0000-0002-9740-4284Yong Zhao2https://orcid.org/0000-0002-7062-456XZhi-Wei Liu3https://orcid.org/0000-0003-3005-1792School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, ChinaAmidst the escalating challenges of global warming and energy crises, the rapid development of distributed renewable energy resources has emerged as a critical strategy. Regional integrated energy systems (RIESs) have garnered significant attention for their potential to integrate and optimize both distributed renewable energy resources and conventional energy facilities. This article presents a bilevel optimization framework for the electricity-storage coupling market in multi-RIES, considering the integration of 6G network slicing technology and battery energy storage (BES) capacity sharing. The upper-level model maximizes the profit of generation units by optimizing their bidding strategies, while the lower-level model aims to maximize social welfare through market clearing. The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. Numerical case studies validate the effectiveness of the proposed framework, demonstrating enhanced BES utilization, increased renewable energy generation, and improved social welfare. The results also highlight the sensitivity of social welfare to communication costs, underscoring the importance of careful cost calibration.https://ieeexplore.ieee.org/document/10890923/Battery energy storage (BES) capacity sharingbilevel optimizationdevice-to-device (D2D) communication6G network slicingelectricity-storage coupling marketmultiregional integrated energy system (RIES) |
| spellingShingle | Kun Cui Ming Chi Yong Zhao Zhi-Wei Liu Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing IEEE Open Journal of the Industrial Electronics Society Battery energy storage (BES) capacity sharing bilevel optimization device-to-device (D2D) communication 6G network slicing electricity-storage coupling market multiregional integrated energy system (RIES) |
| title | Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing |
| title_full | Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing |
| title_fullStr | Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing |
| title_full_unstemmed | Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing |
| title_short | Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing |
| title_sort | bilevel optimization framework for multiregional integrated energy systems considering 6g network slicing and battery energy storage capacity sharing |
| topic | Battery energy storage (BES) capacity sharing bilevel optimization device-to-device (D2D) communication 6G network slicing electricity-storage coupling market multiregional integrated energy system (RIES) |
| url | https://ieeexplore.ieee.org/document/10890923/ |
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