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Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response
As many new devices and factors, such as renewable energy sources, energy storage (ESs), electric vehicles (EVs), and demand response (DR), flood into the distribution network, the characteristics of the distribution network are becoming complicated and diversified. In this study, a two-layer collab...
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Published in: | Energies (Basel) 2022-06, Vol.15 (12), p.4244 |
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description | As many new devices and factors, such as renewable energy sources, energy storage (ESs), electric vehicles (EVs), and demand response (DR), flood into the distribution network, the characteristics of the distribution network are becoming complicated and diversified. In this study, a two-layer collaborative optimized operation model for the multi-character distribution network considering multiple uncertain factors is proposed to achieve optimal dispatching of ES and EV and obtain the optimal grid structure of the distribution network. Based on basic device models of distribution network, the upper layer distribution network reconfiguration (DNR) model is established and solved by the particle swarm optimization (PSO) based on the Pareto optimality and the Prim algorithm. Then, the lower layer optimal dispatching model of ES and EV is established and solved by the binary PSO. The upper layer model and the lower layer model are integrated to form the collaborative optimized operation model for the multi-character distribution network and solved by iterating the upper and lower layers continuously. A case study is conducted on the IEEE 33-bus system. The simulation results show that the total network loss and the voltage deviation are decreased by 15.66% and 15.52%, respectively, after optimal dispatching of ES and EV. The total network loss and the voltage deviation are decreased by 28.39% and 44.46%, respectively, after the DNR with distributed generation (DG) and EV loads with little impact on the average reliability of the power supply. The total network loss and the voltage deviation are decreased by 26.54% and 27.04%, respectively, after the collaborative optimized operation of the multi-character distribution network. The collaborative optimized operation of the distribution network can effectively reduce the total cost by 114.45%, which makes the system change from paying to gaining. |
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In this study, a two-layer collaborative optimized operation model for the multi-character distribution network considering multiple uncertain factors is proposed to achieve optimal dispatching of ES and EV and obtain the optimal grid structure of the distribution network. Based on basic device models of distribution network, the upper layer distribution network reconfiguration (DNR) model is established and solved by the particle swarm optimization (PSO) based on the Pareto optimality and the Prim algorithm. Then, the lower layer optimal dispatching model of ES and EV is established and solved by the binary PSO. The upper layer model and the lower layer model are integrated to form the collaborative optimized operation model for the multi-character distribution network and solved by iterating the upper and lower layers continuously. A case study is conducted on the IEEE 33-bus system. The simulation results show that the total network loss and the voltage deviation are decreased by 15.66% and 15.52%, respectively, after optimal dispatching of ES and EV. The total network loss and the voltage deviation are decreased by 28.39% and 44.46%, respectively, after the DNR with distributed generation (DG) and EV loads with little impact on the average reliability of the power supply. The total network loss and the voltage deviation are decreased by 26.54% and 27.04%, respectively, after the collaborative optimized operation of the multi-character distribution network. The collaborative optimized operation of the distribution network can effectively reduce the total cost by 114.45%, which makes the system change from paying to gaining.</description><identifier>ISSN: 1996-1073</identifier><identifier>EISSN: 1996-1073</identifier><identifier>DOI: 10.3390/en15124244</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Alternative energy sources ; Case studies ; Collaboration ; collaborative operation ; Deviation ; Distributed generation ; distribution network reconfiguration ; Electric potential ; Electric power demand ; electric vehicle ; Electric vehicles ; Electricity ; Energy management ; Energy sources ; Energy storage ; multi-character system ; Network management systems ; Network reliability ; Optimization ; Optimization algorithms ; Reconfiguration ; renewable energy source ; Renewable energy sources ; Renewable resources ; Voltage</subject><ispartof>Energies (Basel), 2022-06, Vol.15 (12), p.4244</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c320t-b53e0560e188b41623f55296f6e0fa0e2e93d76c12bff10c8cb9606c9dc91d1a3</cites><orcidid>0000-0001-9829-3697</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2679720907/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2679720907?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,25730,27900,27901,36988,44565,75095</link.rule.ids></links><search><creatorcontrib>Liu, Zifa</creatorcontrib><creatorcontrib>Li, Jieyu</creatorcontrib><creatorcontrib>Liu, Yunyang</creatorcontrib><creatorcontrib>Yu, Puyang</creatorcontrib><creatorcontrib>Shao, Junteng</creatorcontrib><title>Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response</title><title>Energies (Basel)</title><description>As many new devices and factors, such as renewable energy sources, energy storage (ESs), electric vehicles (EVs), and demand response (DR), flood into the distribution network, the characteristics of the distribution network are becoming complicated and diversified. In this study, a two-layer collaborative optimized operation model for the multi-character distribution network considering multiple uncertain factors is proposed to achieve optimal dispatching of ES and EV and obtain the optimal grid structure of the distribution network. Based on basic device models of distribution network, the upper layer distribution network reconfiguration (DNR) model is established and solved by the particle swarm optimization (PSO) based on the Pareto optimality and the Prim algorithm. Then, the lower layer optimal dispatching model of ES and EV is established and solved by the binary PSO. The upper layer model and the lower layer model are integrated to form the collaborative optimized operation model for the multi-character distribution network and solved by iterating the upper and lower layers continuously. A case study is conducted on the IEEE 33-bus system. The simulation results show that the total network loss and the voltage deviation are decreased by 15.66% and 15.52%, respectively, after optimal dispatching of ES and EV. The total network loss and the voltage deviation are decreased by 28.39% and 44.46%, respectively, after the DNR with distributed generation (DG) and EV loads with little impact on the average reliability of the power supply. The total network loss and the voltage deviation are decreased by 26.54% and 27.04%, respectively, after the collaborative optimized operation of the multi-character distribution network. The collaborative optimized operation of the distribution network can effectively reduce the total cost by 114.45%, which makes the system change from paying to gaining.</description><subject>Alternative energy sources</subject><subject>Case studies</subject><subject>Collaboration</subject><subject>collaborative operation</subject><subject>Deviation</subject><subject>Distributed generation</subject><subject>distribution network reconfiguration</subject><subject>Electric potential</subject><subject>Electric power demand</subject><subject>electric vehicle</subject><subject>Electric vehicles</subject><subject>Electricity</subject><subject>Energy management</subject><subject>Energy sources</subject><subject>Energy storage</subject><subject>multi-character system</subject><subject>Network management systems</subject><subject>Network reliability</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Reconfiguration</subject><subject>renewable energy source</subject><subject>Renewable energy sources</subject><subject>Renewable resources</subject><subject>Voltage</subject><issn>1996-1073</issn><issn>1996-1073</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNUctO5DAQtNCuBBq47BdY4oaUXT8SJz6iAAsSD2m1nK2O0wYPmTjYHtDyCfvVZBgE9KVLrarqVhchPzj7KaVmv3DkFRelKMsdsse1VgVntfz2Be-Sg5SWbC4puZRyj_xvwzBAFyJk_4T0Zsp-5V-wnxFuZmGkV6HHgQZHr9ZD9kV7DxFsxkhPfMrRd-s31jXm5xAfaBvG5HuMfrzbCqYB6e1oMWbwIz2bpSEmCmNPT3C1aX8wTbMI98l3B0PCg_e-ILdnp3_b8-Ly5vdFe3xZWClYLrpKIqsUQ940XcmVkK6qhFZOIXPAUKCWfa0sF51znNnGdloxZXVvNe85yAW52Pr2AZZmin4F8Z8J4M3bIMQ7AzF7O6DhTa1q19SCOygBHDRKi0oJK7htBHOz1-HWa4rhcY0pm2VYx3E-3whV61owPb99QY62LBtDShHdx1bOzCY68xmdfAXUpozX</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Liu, Zifa</creator><creator>Li, Jieyu</creator><creator>Liu, Yunyang</creator><creator>Yu, Puyang</creator><creator>Shao, Junteng</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9829-3697</orcidid></search><sort><creationdate>20220601</creationdate><title>Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response</title><author>Liu, Zifa ; Li, Jieyu ; Liu, Yunyang ; Yu, Puyang ; Shao, Junteng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c320t-b53e0560e188b41623f55296f6e0fa0e2e93d76c12bff10c8cb9606c9dc91d1a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Alternative energy sources</topic><topic>Case studies</topic><topic>Collaboration</topic><topic>collaborative operation</topic><topic>Deviation</topic><topic>Distributed generation</topic><topic>distribution network reconfiguration</topic><topic>Electric potential</topic><topic>Electric power demand</topic><topic>electric vehicle</topic><topic>Electric vehicles</topic><topic>Electricity</topic><topic>Energy management</topic><topic>Energy sources</topic><topic>Energy storage</topic><topic>multi-character system</topic><topic>Network management systems</topic><topic>Network reliability</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Reconfiguration</topic><topic>renewable energy source</topic><topic>Renewable energy sources</topic><topic>Renewable resources</topic><topic>Voltage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Zifa</creatorcontrib><creatorcontrib>Li, Jieyu</creatorcontrib><creatorcontrib>Liu, Yunyang</creatorcontrib><creatorcontrib>Yu, Puyang</creatorcontrib><creatorcontrib>Shao, Junteng</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Directory of Open Access Journals</collection><jtitle>Energies (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Zifa</au><au>Li, Jieyu</au><au>Liu, Yunyang</au><au>Yu, Puyang</au><au>Shao, Junteng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response</atitle><jtitle>Energies (Basel)</jtitle><date>2022-06-01</date><risdate>2022</risdate><volume>15</volume><issue>12</issue><spage>4244</spage><pages>4244-</pages><issn>1996-1073</issn><eissn>1996-1073</eissn><abstract>As many new devices and factors, such as renewable energy sources, energy storage (ESs), electric vehicles (EVs), and demand response (DR), flood into the distribution network, the characteristics of the distribution network are becoming complicated and diversified. In this study, a two-layer collaborative optimized operation model for the multi-character distribution network considering multiple uncertain factors is proposed to achieve optimal dispatching of ES and EV and obtain the optimal grid structure of the distribution network. Based on basic device models of distribution network, the upper layer distribution network reconfiguration (DNR) model is established and solved by the particle swarm optimization (PSO) based on the Pareto optimality and the Prim algorithm. Then, the lower layer optimal dispatching model of ES and EV is established and solved by the binary PSO. The upper layer model and the lower layer model are integrated to form the collaborative optimized operation model for the multi-character distribution network and solved by iterating the upper and lower layers continuously. A case study is conducted on the IEEE 33-bus system. The simulation results show that the total network loss and the voltage deviation are decreased by 15.66% and 15.52%, respectively, after optimal dispatching of ES and EV. The total network loss and the voltage deviation are decreased by 28.39% and 44.46%, respectively, after the DNR with distributed generation (DG) and EV loads with little impact on the average reliability of the power supply. The total network loss and the voltage deviation are decreased by 26.54% and 27.04%, respectively, after the collaborative optimized operation of the multi-character distribution network. The collaborative optimized operation of the distribution network can effectively reduce the total cost by 114.45%, which makes the system change from paying to gaining.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/en15124244</doi><orcidid>https://orcid.org/0000-0001-9829-3697</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alternative energy sources Case studies Collaboration collaborative operation Deviation Distributed generation distribution network reconfiguration Electric potential Electric power demand electric vehicle Electric vehicles Electricity Energy management Energy sources Energy storage multi-character system Network management systems Network reliability Optimization Optimization algorithms Reconfiguration renewable energy source Renewable energy sources Renewable resources Voltage |
title | Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response |
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