A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response
Conventionally, community energy management system (CEMS) is provided with the information of surplus and shortage amounts only at each time interval. This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS...
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Veröffentlicht in: | IEEE transactions on smart grid 2018-03, Vol.9 (2), p.1323-1333 |
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creator | Bui, Van-Hai Hussain, Akhtar Kim, Hak-Man |
description | Conventionally, community energy management system (CEMS) is provided with the information of surplus and shortage amounts only at each time interval. This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. Easy to implement and computationally inexpensive mixed integer linear programming models are developed for each step. |
doi_str_mv | 10.1109/TSG.2016.2585671 |
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This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. 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This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. Easy to implement and computationally inexpensive mixed integer linear programming models are developed for each step.</description><subject>Adjustable power</subject><subject>demand response</subject><subject>energy management system</subject><subject>Energy storage</subject><subject>Load management</subject><subject>Microgrids</subject><subject>mixed integer linear programming</subject><subject>multi-microgrids</subject><subject>multiagent system</subject><subject>Optimization</subject><subject>State of charge</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1rAjEQhkNpoWK9F3rJH1ibr_3I0VqrBaWl2vMSk8k2su5KslK89ac3suJcZhiedxgehB4pGVNK5PNmPR8zQrMxS4s0y-kNGlApZMJJRm-vc8rv0SiEHYnFOc-YHKC_CV4d686pCpoueVEBDF448MrrH6dVjWcN-OqEV6qJyD5CeN151UHc2db34WTltG8r70zA07YJzoB3TYUnZncMndrWgD_bX_BYNQa_wv7cviAcIgoP6M6qOsDo0ofo-222mS6S5cf8fTpZJppT0iVZnlLgnFmxJaIwopCWGEkZ4ZpYIwzPjd0aqXKhgGuhMl2YgjGjNBjJoOBDRPq78dMQPNjy4N1e-VNJSXmWWEaJ5VlieZEYI099xAHAFc9TQlMq-D_BbnAO</recordid><startdate>20180301</startdate><enddate>20180301</enddate><creator>Bui, Van-Hai</creator><creator>Hussain, Akhtar</creator><creator>Kim, Hak-Man</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-4910-4172</orcidid></search><sort><creationdate>20180301</creationdate><title>A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response</title><author>Bui, Van-Hai ; Hussain, Akhtar ; Kim, Hak-Man</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c310t-6751e332f4b048d489f0d91203c0fd4d37dfbd9a74ae3c4a6c8d822daced92e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adjustable power</topic><topic>demand response</topic><topic>energy management system</topic><topic>Energy storage</topic><topic>Load management</topic><topic>Microgrids</topic><topic>mixed integer linear programming</topic><topic>multi-microgrids</topic><topic>multiagent system</topic><topic>Optimization</topic><topic>State of charge</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bui, Van-Hai</creatorcontrib><creatorcontrib>Hussain, Akhtar</creatorcontrib><creatorcontrib>Kim, Hak-Man</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE transactions on smart grid</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bui, Van-Hai</au><au>Hussain, Akhtar</au><au>Kim, Hak-Man</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response</atitle><jtitle>IEEE transactions on smart grid</jtitle><stitle>TSG</stitle><date>2018-03-01</date><risdate>2018</risdate><volume>9</volume><issue>2</issue><spage>1323</spage><epage>1333</epage><pages>1323-1333</pages><issn>1949-3053</issn><eissn>1949-3061</eissn><coden>ITSGBQ</coden><abstract>Conventionally, community energy management system (CEMS) is provided with the information of surplus and shortage amounts only at each time interval. This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. Easy to implement and computationally inexpensive mixed integer linear programming models are developed for each step.</abstract><pub>IEEE</pub><doi>10.1109/TSG.2016.2585671</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-4910-4172</orcidid></addata></record> |
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subjects | Adjustable power demand response energy management system Energy storage Load management Microgrids mixed integer linear programming multi-microgrids multiagent system Optimization State of charge |
title | A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response |
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