Optimization study of wind, solar, hydro and hydrogen storage based on improved multi-objective particle swarm optimization
Accelerating the construction of a new energy system, vigorously advancing the development of renewable energy, and establishing a new complementary electricity system is one of the important measures for green transformation, playing a crucial role in the future energy development. Consequently, th...
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| Veröffentlicht in: | Journal of energy storage Jg. 93; S. 112298 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Ltd
15.07.2024
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| ISSN: | 2352-152X, 2352-1538 |
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| Abstract | Accelerating the construction of a new energy system, vigorously advancing the development of renewable energy, and establishing a new complementary electricity system is one of the important measures for green transformation, playing a crucial role in the future energy development. Consequently, this article, targeting the current status of multi-energy complementarity, establishes a complementary system of pumped hydro storage, battery storage, and hydrogen storage, and formulates an optimization model for a wind-solar‑hydrogen storage system to facilitate the integration of wind and solar power. The article improves the multi-objective particle swarm optimization by incorporating learning factors with asynchronous changes and an exponential nonlinear decreasing inertia weight. It aims to minimize the system's total cost and environmental protection cost, using the IMOPSO algorithm to optimize the model. The results indicate that the total cost is 8262 CNY/(kW·h), and the environmental protection cost is 541.9 CNY/(kW·h). The integration rates of wind and solar power are 64.37 % and 77.25 %, respectively, which represent an increase of 30.71 % and 25.98 % over the MOPSO algorithm. The system's total clean energy supply reaches 94.1 %, offering a novel approach for the storage and utilization of clean energy.
•Improved multi-objective particle swarm algorithm with varying learning factors and nonlinear decreasing inertia weight;•An optimization model for a wind-solar-hydrogen storage system is constructed;•The model is refined using the IMOPSO algorithm to minimize both the overall system costs and the costs associated with environmental protection. |
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| AbstractList | Accelerating the construction of a new energy system, vigorously advancing the development of renewable energy, and establishing a new complementary electricity system is one of the important measures for green transformation, playing a crucial role in the future energy development. Consequently, this article, targeting the current status of multi-energy complementarity, establishes a complementary system of pumped hydro storage, battery storage, and hydrogen storage, and formulates an optimization model for a wind-solar‑hydrogen storage system to facilitate the integration of wind and solar power. The article improves the multi-objective particle swarm optimization by incorporating learning factors with asynchronous changes and an exponential nonlinear decreasing inertia weight. It aims to minimize the system's total cost and environmental protection cost, using the IMOPSO algorithm to optimize the model. The results indicate that the total cost is 8262 CNY/(kW·h), and the environmental protection cost is 541.9 CNY/(kW·h). The integration rates of wind and solar power are 64.37 % and 77.25 %, respectively, which represent an increase of 30.71 % and 25.98 % over the MOPSO algorithm. The system's total clean energy supply reaches 94.1 %, offering a novel approach for the storage and utilization of clean energy.
•Improved multi-objective particle swarm algorithm with varying learning factors and nonlinear decreasing inertia weight;•An optimization model for a wind-solar-hydrogen storage system is constructed;•The model is refined using the IMOPSO algorithm to minimize both the overall system costs and the costs associated with environmental protection. |
| ArticleNumber | 112298 |
| Author | Zhang, Yunxin Cao, Qingjiao Wang, Liying Wu, Kegui Zhang, Jihua Ding, Shuai Liu, Yang Tian, Hao Wang, Jixuan Wen, Yujing |
| Author_xml | – sequence: 1 givenname: Jixuan surname: Wang fullname: Wang, Jixuan email: wangjixuan113@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 2 givenname: Yujing surname: Wen fullname: Wen, Yujing email: wenyujing0228@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 3 givenname: Kegui surname: Wu fullname: Wu, Kegui email: w609756178@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 4 givenname: Shuai surname: Ding fullname: Ding, Shuai email: ding_0413@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 5 givenname: Yang surname: Liu fullname: Liu, Yang email: lyy20010705xxx@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 6 givenname: Hao surname: Tian fullname: Tian, Hao email: th990501683123@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 7 givenname: Jihua surname: Zhang fullname: Zhang, Jihua email: tullpe@hhu.edu.cn organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 8 givenname: Liying surname: Wang fullname: Wang, Liying email: wangliying@hebeu.edu.cn organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 9 givenname: Qingjiao surname: Cao fullname: Cao, Qingjiao email: caoqingjiao@hebeu.edu.cn organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China – sequence: 10 givenname: Yunxin surname: Zhang fullname: Zhang, Yunxin email: zhangyunxin2024@163.com organization: Hebei University of Engineering School of Water Conservancy and Hydroelectric Power, Handan, Hebei, 056038, China |
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| Cites_doi | 10.1016/j.seta.2023.103534 10.1016/j.est.2023.108086 10.1016/j.segan.2024.101299 10.1016/j.enconman.2018.06.001 10.1016/j.apenergy.2018.08.034 10.1016/j.energy.2020.117908 10.1016/j.segan.2019.100268 10.1016/j.energy.2023.128756 10.35833/MPCE.2022.000424 |
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| Keywords | Wind-solar-hydrogen storage IMOPSO algorithm Optimization study Carbon footprint |
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