Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs
The vigorous development of clean energy is an important way to achieve “Carbon peak, Carbon neutral”, but the inherent intermittent and uncontrollable power generation characteristics of clean energy such as scenery and other comprehensive factors make the energy consumption problem more prominent,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/53/e3sconf_ogegs2023_01031.pdf |
| _version_ | 1828716285542793216 |
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| author | Chen Jinhong Chen Chongle Lin Kai Li Hua Xie Chuansheng |
| author_facet | Chen Jinhong Chen Chongle Lin Kai Li Hua Xie Chuansheng |
| author_sort | Chen Jinhong |
| collection | DOAJ |
| description | The vigorous development of clean energy is an important way to achieve “Carbon peak, Carbon neutral”, but the inherent intermittent and uncontrollable power generation characteristics of clean energy such as scenery and other comprehensive factors make the energy consumption problem more prominent, and the multi-energy complementary can solve the energy consumption problem more effectively. However, the current study of multi-energy complementary operation only considers the fuel cost, load shedding and wind and solar abandonment cost, and does not consider enough the peaking cost of thermal power units and the life loss of batteries. To address these problems, a multi-energy complementary energy system operation optimization model considering multiple types of peaking costs is established, and the peaking costs of regulating units are modeled more finely and solved by a dynamic inertia weighted particle swarm algorithm. The results demonstrate that the addition of energy storage system can effectively reduce the total operating cost of the system under the condition of large-scale clean energy grid connection, and the addition of creeping cost and low load operating cost can reflect the cost of conventional units more realistically, which can better provide the dispatching strategy for the decision of multi-energy complementary operation of power system. |
| first_indexed | 2024-03-12T14:10:13Z |
| format | Article |
| id | doaj.art-f775db6754c7421e860d9b25b6ea07ec |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-12T14:10:13Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-f775db6754c7421e860d9b25b6ea07ec2023-08-21T09:02:44ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014160103110.1051/e3sconf/202341601031e3sconf_ogegs2023_01031Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costsChen Jinhong0Chen Chongle1Lin Kai2Li Hua3Xie Chuansheng4Fujian Shuikou Power Generation Group Co., LtdFujian Shuikou Power Generation Group Co., LtdFujian Shuikou Power Generation Group Co., LtdNorth China Electric Power University, School of Economics and ManagementNorth China Electric Power University, School of Economics and ManagementThe vigorous development of clean energy is an important way to achieve “Carbon peak, Carbon neutral”, but the inherent intermittent and uncontrollable power generation characteristics of clean energy such as scenery and other comprehensive factors make the energy consumption problem more prominent, and the multi-energy complementary can solve the energy consumption problem more effectively. However, the current study of multi-energy complementary operation only considers the fuel cost, load shedding and wind and solar abandonment cost, and does not consider enough the peaking cost of thermal power units and the life loss of batteries. To address these problems, a multi-energy complementary energy system operation optimization model considering multiple types of peaking costs is established, and the peaking costs of regulating units are modeled more finely and solved by a dynamic inertia weighted particle swarm algorithm. The results demonstrate that the addition of energy storage system can effectively reduce the total operating cost of the system under the condition of large-scale clean energy grid connection, and the addition of creeping cost and low load operating cost can reflect the cost of conventional units more realistically, which can better provide the dispatching strategy for the decision of multi-energy complementary operation of power system.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/53/e3sconf_ogegs2023_01031.pdfmulti-energy complementaryintegrated energy systempeaking costoptimal operationparticle swarm algorithm |
| spellingShingle | Chen Jinhong Chen Chongle Lin Kai Li Hua Xie Chuansheng Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs E3S Web of Conferences multi-energy complementary integrated energy system peaking cost optimal operation particle swarm algorithm |
| title | Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs |
| title_full | Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs |
| title_fullStr | Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs |
| title_full_unstemmed | Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs |
| title_short | Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs |
| title_sort | research on optimal operation model of multi energy complementary energy system considering multi type peak shaving costs |
| topic | multi-energy complementary integrated energy system peaking cost optimal operation particle swarm algorithm |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/53/e3sconf_ogegs2023_01031.pdf |
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