Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services
Abstract This paper addresses the limitations of existing research that focuses on single-sided resources and two-timescale optimization, overlooking the coordinated response of various energy storage resources across different timescales in comprehensive energy systems. To tackle these shortcomings...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92601-9 |
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| author | Yunshou Mao Zhihong Cai Xianan Jiao Dafeng Long |
| author_facet | Yunshou Mao Zhihong Cai Xianan Jiao Dafeng Long |
| author_sort | Yunshou Mao |
| collection | DOAJ |
| description | Abstract This paper addresses the limitations of existing research that focuses on single-sided resources and two-timescale optimization, overlooking the coordinated response of various energy storage resources across different timescales in comprehensive energy systems. To tackle these shortcomings, the study integrates flexible demand-side resources, such as electric vehicles (EVs), hydrogen storage, and air conditioning clusters, as generalized energy storage. It explores their impact on the operation cost of the comprehensive energy system across three stages: day-ahead, intraday, and real-time. The paper establishes an optimization scheduling model for mobile energy storage, hydrogen storage, and virtual energy storage of air conditioning clusters, considering the physical and temporal constraints of different storage devices, aiming to minimize the operational cost. The day-ahead stage employs C&CG to address the uncertainty of wind and photovoltaic power generations, while the intraday stage synergizes hydrogen storage, gas turbines, and demand-side substitutable and transferable loads to mitigate renewable energy fluctuations. The real-time stage leverages the virtual energy storage model of air conditioning clusters for rapid response to renewable energy deviations. Case studies validate the effectiveness of the model, demonstrating that multi-timescale optimization of generalized energy storage in comprehensive energy systems can significantly reduce operational costs and enhance system reliability. |
| format | Article |
| id | doaj-art-840e464a1b854ba790a67daad75f201d |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-840e464a1b854ba790a67daad75f201d2025-08-20T03:01:34ZengNature PortfolioScientific Reports2045-23222025-03-0115112010.1038/s41598-025-92601-9Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage servicesYunshou Mao0Zhihong Cai1Xianan Jiao2Dafeng Long3School of Electronic Information and Electrical Engineering, Huizhou UniversityElectric Power Research Institute of EHV Power Transmission Company, CSGSchool of automation, Guangdong university of technologySchool of Electronic Information and Electrical Engineering, Huizhou UniversityAbstract This paper addresses the limitations of existing research that focuses on single-sided resources and two-timescale optimization, overlooking the coordinated response of various energy storage resources across different timescales in comprehensive energy systems. To tackle these shortcomings, the study integrates flexible demand-side resources, such as electric vehicles (EVs), hydrogen storage, and air conditioning clusters, as generalized energy storage. It explores their impact on the operation cost of the comprehensive energy system across three stages: day-ahead, intraday, and real-time. The paper establishes an optimization scheduling model for mobile energy storage, hydrogen storage, and virtual energy storage of air conditioning clusters, considering the physical and temporal constraints of different storage devices, aiming to minimize the operational cost. The day-ahead stage employs C&CG to address the uncertainty of wind and photovoltaic power generations, while the intraday stage synergizes hydrogen storage, gas turbines, and demand-side substitutable and transferable loads to mitigate renewable energy fluctuations. The real-time stage leverages the virtual energy storage model of air conditioning clusters for rapid response to renewable energy deviations. Case studies validate the effectiveness of the model, demonstrating that multi-timescale optimization of generalized energy storage in comprehensive energy systems can significantly reduce operational costs and enhance system reliability.https://doi.org/10.1038/s41598-025-92601-9Generalized energy storageTwo-stage robust optimizationColumn-and-constraint generationIntegrated energy systemAir conditioning virtual energy storage |
| spellingShingle | Yunshou Mao Zhihong Cai Xianan Jiao Dafeng Long Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services Scientific Reports Generalized energy storage Two-stage robust optimization Column-and-constraint generation Integrated energy system Air conditioning virtual energy storage |
| title | Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| title_full | Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| title_fullStr | Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| title_full_unstemmed | Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| title_short | Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| title_sort | multi timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services |
| topic | Generalized energy storage Two-stage robust optimization Column-and-constraint generation Integrated energy system Air conditioning virtual energy storage |
| url | https://doi.org/10.1038/s41598-025-92601-9 |
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