Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP
Abstract Hydrogen‐based energy systems (HESs) have shown great potential to promote the process of decarbonization. Conventional studies mainly focus on the sizing and operation of HESs in a determined static situation, and the dynamic planning model of HESs considering large‐scale uncertain scenari...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-07-01
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| Series: | IET Generation, Transmission & Distribution |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/gtd2.12863 |
| _version_ | 1827909406307647488 |
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| author | Binrui Cao Xiong Wu Bingwen Liu Xiuli Wang Penglei Wang Yunyi Wu |
| author_facet | Binrui Cao Xiong Wu Bingwen Liu Xiuli Wang Penglei Wang Yunyi Wu |
| author_sort | Binrui Cao |
| collection | DOAJ |
| description | Abstract Hydrogen‐based energy systems (HESs) have shown great potential to promote the process of decarbonization. Conventional studies mainly focus on the sizing and operation of HESs in a determined static situation, and the dynamic planning model of HESs considering large‐scale uncertain scenarios of future developments should be considered. This paper proposes a multi‐stage stochastic programming (MSP) long‐term planning model to find the optimal sequential planning results of the grid‐connected HES. The planning model considers the long‐term uncertainties of the investment cost decrease and the load increase. Additionally, the short‐term uncertainties of renewable energies are also considered to obtain robust results in each stage. The improved stochastic dual dynamic integer programming (SDDIP) is then employed to solve the MSP long‐term planning model with consideration of the realized uncertainties. Specifically, the sequential planning order is developed to improve the efficiency of the SDDIP. Numerical case studies are constructed to show the convergence process of the improved SDDIP and the planning results of the HES. Moreover, the improved SDDIP shows greater efficiency compared with the traditional SDDIP and the method which solves the model directly. |
| first_indexed | 2024-03-13T01:36:36Z |
| format | Article |
| id | doaj.art-29a61b2236754751b12b39aa5640d970 |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-03-13T01:36:36Z |
| publishDate | 2023-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-29a61b2236754751b12b39aa5640d9702023-07-04T04:39:15ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952023-07-0117133016302910.1049/gtd2.12863Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIPBinrui Cao0Xiong Wu1Bingwen Liu2Xiuli Wang3Penglei Wang4Yunyi Wu5School of Electrical Engineering Xi'an Jiaotong University Xi'an ChinaSchool of Electrical Engineering Xi'an Jiaotong University Xi'an ChinaSchool of Electrical Engineering Xi'an Jiaotong University Xi'an ChinaSchool of Electrical Engineering Xi'an Jiaotong University Xi'an ChinaChina Three Gorges Corporation Beijing ChinaChina Three Gorges Corporation Beijing ChinaAbstract Hydrogen‐based energy systems (HESs) have shown great potential to promote the process of decarbonization. Conventional studies mainly focus on the sizing and operation of HESs in a determined static situation, and the dynamic planning model of HESs considering large‐scale uncertain scenarios of future developments should be considered. This paper proposes a multi‐stage stochastic programming (MSP) long‐term planning model to find the optimal sequential planning results of the grid‐connected HES. The planning model considers the long‐term uncertainties of the investment cost decrease and the load increase. Additionally, the short‐term uncertainties of renewable energies are also considered to obtain robust results in each stage. The improved stochastic dual dynamic integer programming (SDDIP) is then employed to solve the MSP long‐term planning model with consideration of the realized uncertainties. Specifically, the sequential planning order is developed to improve the efficiency of the SDDIP. Numerical case studies are constructed to show the convergence process of the improved SDDIP and the planning results of the HES. Moreover, the improved SDDIP shows greater efficiency compared with the traditional SDDIP and the method which solves the model directly.https://doi.org/10.1049/gtd2.12863distribution planning and operationhydrogen storagemulti‐stage planning model |
| spellingShingle | Binrui Cao Xiong Wu Bingwen Liu Xiuli Wang Penglei Wang Yunyi Wu Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP IET Generation, Transmission & Distribution distribution planning and operation hydrogen storage multi‐stage planning model |
| title | Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP |
| title_full | Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP |
| title_fullStr | Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP |
| title_full_unstemmed | Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP |
| title_short | Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP |
| title_sort | multi stage stochastic long term planning of grid connected hydrogen based energy system based on improved sddip |
| topic | distribution planning and operation hydrogen storage multi‐stage planning model |
| url | https://doi.org/10.1049/gtd2.12863 |
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