Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality
In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the di...
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| Veröffentlicht in: | IET renewable power generation 2020-12, Vol.14 (18), p.3888-3896 |
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| container_title | IET renewable power generation |
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| creator | Wang, Jun Zheng, Xiaodong Tai, Nengling Liu, Yu Yang, Zengli Wang, Jing Tu, Qi |
| description | In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model. |
| doi_str_mv | 10.1049/iet-rpg.2020.0528 |
| format | Article |
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The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.</description><identifier>ISSN: 1752-1416</identifier><identifier>EISSN: 1752-1424</identifier><identifier>DOI: 10.1049/iet-rpg.2020.0528</identifier><language>eng</language><publisher>The Institution of Engineering and Technology</publisher><subject>DER integrated distribution network ; distributed energy resources scheduling ; distributed power generation ; distribution networks ; genetic algorithms ; load shedding ; multiobjective optimal recovery solution ; nondominated sorting genetic algorithm‐II ; optimal recovery strategy ; optimal scheduling model ; power outage ; power shortage ; recovery ability ; recovery process ; Research Article ; scheduling ; scheduling coefficient ; scheduling rationality ; scheduling resource</subject><ispartof>IET renewable power generation, 2020-12, Vol.14 (18), p.3888-3896</ispartof><rights>The Institution of Engineering and Technology</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3343-ff47c1b66cbe8775559012860f16eeaa7031f8e8e46bf921f4addc779ebac25e3</citedby><cites>FETCH-LOGICAL-c3343-ff47c1b66cbe8775559012860f16eeaa7031f8e8e46bf921f4addc779ebac25e3</cites><orcidid>0000-0001-8042-1363 ; 0000-0001-9021-734X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1049%2Fiet-rpg.2020.0528$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1049%2Fiet-rpg.2020.0528$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,11562,27924,27925,45574,45575,46052,46476</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1049%2Fiet-rpg.2020.0528$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc></links><search><creatorcontrib>Wang, Jun</creatorcontrib><creatorcontrib>Zheng, Xiaodong</creatorcontrib><creatorcontrib>Tai, Nengling</creatorcontrib><creatorcontrib>Liu, Yu</creatorcontrib><creatorcontrib>Yang, Zengli</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Tu, Qi</creatorcontrib><title>Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality</title><title>IET renewable power generation</title><description>In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.</description><subject>DER integrated distribution network</subject><subject>distributed energy resources scheduling</subject><subject>distributed power generation</subject><subject>distribution networks</subject><subject>genetic algorithms</subject><subject>load shedding</subject><subject>multiobjective optimal recovery solution</subject><subject>nondominated sorting genetic algorithm‐II</subject><subject>optimal recovery strategy</subject><subject>optimal scheduling model</subject><subject>power outage</subject><subject>power shortage</subject><subject>recovery ability</subject><subject>recovery process</subject><subject>Research Article</subject><subject>scheduling</subject><subject>scheduling coefficient</subject><subject>scheduling rationality</subject><subject>scheduling resource</subject><issn>1752-1416</issn><issn>1752-1424</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkNFOwyAUhonRxDl9AO94gU6gFFrvdG7TZMnMoteE0sNk1naBzqVvP5oZL_UKOOf_gPMhdEvJhBJe3DnoEr_bTBhhZEIylp-hEZUZSyhn_Px3T8UlugphS0hWkFyMkF7tOvela-zBtN_gexw6rzvY9Li1-Gm2Dtg18TjUKly52HXlvnNtgxvoDq3_xKUOsRULwXxAta9ds8ExHiO6dl1_jS6srgPc_Kxj9D6fvU2fk-Vq8TJ9WCYmTXmaWMuloaUQpoRcyiyLH6QsF8RSAaC1JCm1OeTARWkLRi3XVWWkLKDUhmWQjhE93Wt8G4IHq3Y-TuZ7RYkaHKnoSEVHanCkBkeRuT8xB1dD_z-g1q8L9jgnVMg0wskJHmLbdu_jvOGPx44Gwn-P</recordid><startdate>20201221</startdate><enddate>20201221</enddate><creator>Wang, Jun</creator><creator>Zheng, Xiaodong</creator><creator>Tai, Nengling</creator><creator>Liu, Yu</creator><creator>Yang, Zengli</creator><creator>Wang, Jing</creator><creator>Tu, Qi</creator><general>The Institution of Engineering and Technology</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-8042-1363</orcidid><orcidid>https://orcid.org/0000-0001-9021-734X</orcidid></search><sort><creationdate>20201221</creationdate><title>Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality</title><author>Wang, Jun ; Zheng, Xiaodong ; Tai, Nengling ; Liu, Yu ; Yang, Zengli ; Wang, Jing ; Tu, Qi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3343-ff47c1b66cbe8775559012860f16eeaa7031f8e8e46bf921f4addc779ebac25e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>DER integrated distribution network</topic><topic>distributed energy resources scheduling</topic><topic>distributed power generation</topic><topic>distribution networks</topic><topic>genetic algorithms</topic><topic>load shedding</topic><topic>multiobjective optimal recovery solution</topic><topic>nondominated sorting genetic algorithm‐II</topic><topic>optimal recovery strategy</topic><topic>optimal scheduling model</topic><topic>power outage</topic><topic>power shortage</topic><topic>recovery ability</topic><topic>recovery process</topic><topic>Research Article</topic><topic>scheduling</topic><topic>scheduling coefficient</topic><topic>scheduling rationality</topic><topic>scheduling resource</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Jun</creatorcontrib><creatorcontrib>Zheng, Xiaodong</creatorcontrib><creatorcontrib>Tai, Nengling</creatorcontrib><creatorcontrib>Liu, Yu</creatorcontrib><creatorcontrib>Yang, Zengli</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Tu, Qi</creatorcontrib><collection>CrossRef</collection><jtitle>IET renewable power generation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wang, Jun</au><au>Zheng, Xiaodong</au><au>Tai, Nengling</au><au>Liu, Yu</au><au>Yang, Zengli</au><au>Wang, Jing</au><au>Tu, Qi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality</atitle><jtitle>IET renewable power generation</jtitle><date>2020-12-21</date><risdate>2020</risdate><volume>14</volume><issue>18</issue><spage>3888</spage><epage>3896</epage><pages>3888-3896</pages><issn>1752-1416</issn><eissn>1752-1424</eissn><abstract>In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.</abstract><pub>The Institution of Engineering and Technology</pub><doi>10.1049/iet-rpg.2020.0528</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-8042-1363</orcidid><orcidid>https://orcid.org/0000-0001-9021-734X</orcidid></addata></record> |
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| source | Wiley-Blackwell Open Access Titles |
| subjects | DER integrated distribution network distributed energy resources scheduling distributed power generation distribution networks genetic algorithms load shedding multiobjective optimal recovery solution nondominated sorting genetic algorithm‐II optimal recovery strategy optimal scheduling model power outage power shortage recovery ability recovery process Research Article scheduling scheduling coefficient scheduling rationality scheduling resource |
| title | Optimal recovery strategy of DERs integrated distribution network based on scheduling rationality |
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