Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties
With the development of integrated energy systems, the system energy demands become more complicated and the renewable energy proportion becomes higher. Under this background, integrated energy systems gradually present a state of high randomness and strong uncertainty, which affects the system coll...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723009496 |
| _version_ | 1797388813958381568 |
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| author | Biao Feng Yu Fu Qingxi Huang Cuiping Ma Qie Sun Ronald Wennersten |
| author_facet | Biao Feng Yu Fu Qingxi Huang Cuiping Ma Qie Sun Ronald Wennersten |
| author_sort | Biao Feng |
| collection | DOAJ |
| description | With the development of integrated energy systems, the system energy demands become more complicated and the renewable energy proportion becomes higher. Under this background, integrated energy systems gradually present a state of high randomness and strong uncertainty, which affects the system collaborative optimization. In order to handle the multiple uncertainties’ effects effectively, multi-objective optimization considering uncertainties of energy demand and renewable energy using information gap decision theory (IGDT) method was carried out. By analyzing the optimization results and comparing the results of different weight coefficient of multiple uncertainties, the renewable energy uncertainty has a strong effect, while the energy demand uncertainty’s effect is more complex. |
| first_indexed | 2024-03-08T22:46:16Z |
| format | Article |
| id | doaj.art-6adbb811ecf1440f89657541fa7d025e |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-08T22:46:16Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-6adbb811ecf1440f89657541fa7d025e2023-12-17T06:39:25ZengElsevierEnergy Reports2352-48472023-10-019695701Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertaintiesBiao Feng0Yu Fu1Qingxi Huang2Cuiping Ma3Qie Sun4Ronald Wennersten5PowerChina HuaDong Engineering Corporation Limited, 201 Gaojiao Road, Hangzhou 311122, ChinaInstitute of Thermal Science and Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, ChinaInstitute for Advanced Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, ChinaInstitute for Advanced Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, ChinaInstitute of Thermal Science and Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, China; Institute for Advanced Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, China; Corresponding author at: Institute of Thermal Science and Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, China.Institute for Advanced Technology, Shandong University, 17923 Jingshi Road, Jinan 250061, ChinaWith the development of integrated energy systems, the system energy demands become more complicated and the renewable energy proportion becomes higher. Under this background, integrated energy systems gradually present a state of high randomness and strong uncertainty, which affects the system collaborative optimization. In order to handle the multiple uncertainties’ effects effectively, multi-objective optimization considering uncertainties of energy demand and renewable energy using information gap decision theory (IGDT) method was carried out. By analyzing the optimization results and comparing the results of different weight coefficient of multiple uncertainties, the renewable energy uncertainty has a strong effect, while the energy demand uncertainty’s effect is more complex.http://www.sciencedirect.com/science/article/pii/S2352484723009496Integrated energy systemUncertaintyHigh proportion of renewable energyIGDT method |
| spellingShingle | Biao Feng Yu Fu Qingxi Huang Cuiping Ma Qie Sun Ronald Wennersten Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties Energy Reports Integrated energy system Uncertainty High proportion of renewable energy IGDT method |
| title | Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| title_full | Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| title_fullStr | Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| title_full_unstemmed | Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| title_short | Multi-objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| title_sort | multi objective optimization of an integrated energy system with high proportion of renewable energy under multiple uncertainties |
| topic | Integrated energy system Uncertainty High proportion of renewable energy IGDT method |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723009496 |
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