Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration
Against the dual background of frequent occurrence of typhoon disaster and increasing penetration of new energy generation, a rolling optimal scheduling strategy of multiple flexibility resources including scaled electric vehicle (EV) is proposed to enhance the resilience of the distribution network...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Power Engineering Technology
2025-01-01
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| Series: | 电力工程技术 |
| Subjects: | |
| Online Access: | https://www.epet-info.com/dlgcjsen/article/abstract/240328288 |
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| author | MA Canhao CHEN Lijuan WU Zhi |
| author_facet | MA Canhao CHEN Lijuan WU Zhi |
| author_sort | MA Canhao |
| collection | DOAJ |
| description | Against the dual background of frequent occurrence of typhoon disaster and increasing penetration of new energy generation, a rolling optimal scheduling strategy of multiple flexibility resources including scaled electric vehicle (EV) is proposed to enhance the resilience of the distribution networks under typhoon disaster. Firstly, the fault scenarios of lines and photovoltaic (PV) in the region are simulated by Monte Carlo method based on typical meteorological characteristics, and the typical scenarios are screened by using system information entropy to get the temporal fault states of lines and PV. Secondly, a multiple flexibility resources optimization regulated model is established with the objective of minimizing the weighted load loss rate. Based on the spatio-temporal characteristics of EVs, they are expropriated and regulated, and the network is reconfigured and coordinated with mobile emergency generators (MEG) to maximize the use of resources in the network. Finally, in order to adapt to the evolution of the system fault state and adjust the regulated scheme in real time, a two-stage rolling solution method is proposed to reduce the problem solving complexity. A simulation analysis is conducted on an improved actual power supply unit network in a certain area of Jiangsu province, and the results show that the proposed strategy can effectively reduce load losses and enhance the resilience of the distribution networks in extreme scenarios. |
| format | Article |
| id | doaj-art-67c7c9fb737a457eab4e9477589eeebe |
| institution | Kabale University |
| issn | 2096-3203 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Editorial Department of Electric Power Engineering Technology |
| record_format | Article |
| series | 电力工程技术 |
| spelling | doaj-art-67c7c9fb737a457eab4e9477589eeebe2025-02-08T08:40:18ZzhoEditorial Department of Electric Power Engineering Technology电力工程技术2096-32032025-01-0144111512510.12158/j.2096-3203.2025.01.012240328288Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaborationMA Canhao0CHEN Lijuan1WU Zhi2School of Electrical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210096, ChinaAgainst the dual background of frequent occurrence of typhoon disaster and increasing penetration of new energy generation, a rolling optimal scheduling strategy of multiple flexibility resources including scaled electric vehicle (EV) is proposed to enhance the resilience of the distribution networks under typhoon disaster. Firstly, the fault scenarios of lines and photovoltaic (PV) in the region are simulated by Monte Carlo method based on typical meteorological characteristics, and the typical scenarios are screened by using system information entropy to get the temporal fault states of lines and PV. Secondly, a multiple flexibility resources optimization regulated model is established with the objective of minimizing the weighted load loss rate. Based on the spatio-temporal characteristics of EVs, they are expropriated and regulated, and the network is reconfigured and coordinated with mobile emergency generators (MEG) to maximize the use of resources in the network. Finally, in order to adapt to the evolution of the system fault state and adjust the regulated scheme in real time, a two-stage rolling solution method is proposed to reduce the problem solving complexity. A simulation analysis is conducted on an improved actual power supply unit network in a certain area of Jiangsu province, and the results show that the proposed strategy can effectively reduce load losses and enhance the resilience of the distribution networks in extreme scenarios.https://www.epet-info.com/dlgcjsen/article/abstract/240328288resilience of distribution networktyphoon disastersystem information entropyflexibility resourceselectric vehicle (ev)rolling optimal |
| spellingShingle | MA Canhao CHEN Lijuan WU Zhi Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration 电力工程技术 resilience of distribution network typhoon disaster system information entropy flexibility resources electric vehicle (ev) rolling optimal |
| title | Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| title_full | Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| title_fullStr | Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| title_full_unstemmed | Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| title_short | Resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| title_sort | resilience enhancement strategy for distribution networks considering multiple flexibility resources collaboration |
| topic | resilience of distribution network typhoon disaster system information entropy flexibility resources electric vehicle (ev) rolling optimal |
| url | https://www.epet-info.com/dlgcjsen/article/abstract/240328288 |
| work_keys_str_mv | AT macanhao resilienceenhancementstrategyfordistributionnetworksconsideringmultipleflexibilityresourcescollaboration AT chenlijuan resilienceenhancementstrategyfordistributionnetworksconsideringmultipleflexibilityresourcescollaboration AT wuzhi resilienceenhancementstrategyfordistributionnetworksconsideringmultipleflexibilityresourcescollaboration |