Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management
The use of energy storage power plants (ESPP) seems necessary to create flexibility in the operation of smart grids and increase economic benefits. The power storage power plants connect directly to the smart distribution substation (DS), saving energy costs and increasing energy efficiency. Also, d...
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description | The use of energy storage power plants (ESPP) seems necessary to create flexibility in the operation of smart grids and increase economic benefits. The power storage power plants connect directly to the smart distribution substation (DS), saving energy costs and increasing energy efficiency. Also, demand response (DR) program management has improved the performance of smart grids by shifting loads. In this regard, the main challenge is the optimal coordination between these two problems by considering control challenges such as limiting the number of charge/discharge times and the number of hours of DR implementation using a linear model that can be solved with powerful commercial solvers. In this paper, we proposed an economic mixed-integer linear programming (MILP) model for optimal coordination of DR and large-scale ESPP considering the practical limitations of charge/discharge times and DR action times with optimal management of distributed generation (DG) resources, which provides more realistic results due to the constraints in operating times in both DR and ESPP. To validate and analyze the proposed model, a standard 33-bus distribution network with a standard Vanadium redox battery power plant and a large 874-bus system with three Vanadium redox battery power plants are considered. Various scenarios have been considered to demonstrate the constraints imposed on the demand side management program and battery charge and discharge, the results of which show that these constraints have a significant impact on the objective function of the problem. Also, by comparing the proposed method with other methods, it was found that the proposed method is more efficient in improving the objective function and limiting options. |
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Motalebi ; Vahedi, M. ; Hoseina, M. ; Moghaddam, M. Samiei</creator><creatorcontrib>Nejad, B. Motalebi ; Vahedi, M. ; Hoseina, M. ; Moghaddam, M. Samiei</creatorcontrib><description>The use of energy storage power plants (ESPP) seems necessary to create flexibility in the operation of smart grids and increase economic benefits. The power storage power plants connect directly to the smart distribution substation (DS), saving energy costs and increasing energy efficiency. Also, demand response (DR) program management has improved the performance of smart grids by shifting loads. In this regard, the main challenge is the optimal coordination between these two problems by considering control challenges such as limiting the number of charge/discharge times and the number of hours of DR implementation using a linear model that can be solved with powerful commercial solvers. In this paper, we proposed an economic mixed-integer linear programming (MILP) model for optimal coordination of DR and large-scale ESPP considering the practical limitations of charge/discharge times and DR action times with optimal management of distributed generation (DG) resources, which provides more realistic results due to the constraints in operating times in both DR and ESPP. To validate and analyze the proposed model, a standard 33-bus distribution network with a standard Vanadium redox battery power plant and a large 874-bus system with three Vanadium redox battery power plants are considered. Various scenarios have been considered to demonstrate the constraints imposed on the demand side management program and battery charge and discharge, the results of which show that these constraints have a significant impact on the objective function of the problem. Also, by comparing the proposed method with other methods, it was found that the proposed method is more efficient in improving the objective function and limiting options.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2022.3184733</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Batteries ; Constraining ; Coordination ; Costs ; Demand response ; demand response program ; Demand side management ; Discharge ; Discharges (electric) ; Distributed generation ; distribution substation ; Economic analysis ; Economic models ; Energy consumption ; Energy costs ; Energy distribution ; Energy management ; Energy storage ; Energy Storage power plant ; Integer programming ; Linear programming ; mathematical model ; Mixed integer ; Power generation ; Power management ; Power plants ; Rechargeable batteries ; Smart grid ; Smart grids ; Substations ; Vanadium</subject><ispartof>IEEE access, 2023, Vol.11, p.16483-16492</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-fc0413f24186c02db43a1df581ef9e31c36ecc978232a18559b7e1e58b7cf9f43</citedby><cites>FETCH-LOGICAL-c408t-fc0413f24186c02db43a1df581ef9e31c36ecc978232a18559b7e1e58b7cf9f43</cites><orcidid>0000-0002-1337-7056 ; 0000-0001-7302-7296</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9801843$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,4010,27610,27900,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Nejad, B. Motalebi</creatorcontrib><creatorcontrib>Vahedi, M.</creatorcontrib><creatorcontrib>Hoseina, M.</creatorcontrib><creatorcontrib>Moghaddam, M. Samiei</creatorcontrib><title>Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management</title><title>IEEE access</title><addtitle>Access</addtitle><description>The use of energy storage power plants (ESPP) seems necessary to create flexibility in the operation of smart grids and increase economic benefits. The power storage power plants connect directly to the smart distribution substation (DS), saving energy costs and increasing energy efficiency. Also, demand response (DR) program management has improved the performance of smart grids by shifting loads. In this regard, the main challenge is the optimal coordination between these two problems by considering control challenges such as limiting the number of charge/discharge times and the number of hours of DR implementation using a linear model that can be solved with powerful commercial solvers. In this paper, we proposed an economic mixed-integer linear programming (MILP) model for optimal coordination of DR and large-scale ESPP considering the practical limitations of charge/discharge times and DR action times with optimal management of distributed generation (DG) resources, which provides more realistic results due to the constraints in operating times in both DR and ESPP. To validate and analyze the proposed model, a standard 33-bus distribution network with a standard Vanadium redox battery power plant and a large 874-bus system with three Vanadium redox battery power plants are considered. Various scenarios have been considered to demonstrate the constraints imposed on the demand side management program and battery charge and discharge, the results of which show that these constraints have a significant impact on the objective function of the problem. Also, by comparing the proposed method with other methods, it was found that the proposed method is more efficient in improving the objective function and limiting options.</description><subject>Batteries</subject><subject>Constraining</subject><subject>Coordination</subject><subject>Costs</subject><subject>Demand response</subject><subject>demand response program</subject><subject>Demand side management</subject><subject>Discharge</subject><subject>Discharges (electric)</subject><subject>Distributed generation</subject><subject>distribution substation</subject><subject>Economic analysis</subject><subject>Economic models</subject><subject>Energy consumption</subject><subject>Energy costs</subject><subject>Energy distribution</subject><subject>Energy management</subject><subject>Energy storage</subject><subject>Energy Storage power plant</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>mathematical model</subject><subject>Mixed integer</subject><subject>Power generation</subject><subject>Power management</subject><subject>Power plants</subject><subject>Rechargeable batteries</subject><subject>Smart grid</subject><subject>Smart grids</subject><subject>Substations</subject><subject>Vanadium</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUc1u1DAYtBBIVEufoBdLnLP4N7GPVVhKpa1aERBHy3E-B6-y9uKkqvoSPDMuKQVfbM03M9_Ig9AFJVtKif5w2ba7rtsywtiWUyUazl-hM0ZrXXHJ69f_vd-i83k-kHJUgWRzhn7tXIrpGBy-SQNM2KeM25TyEKJdQhzx3uYRqs7ZCfAuQh4fcbekbEfAd-kBMr6bbFzw97D8wB_haOOAv8B8SnEGfGNj4R2hzG9PSygYDhF3R5sXfJXD8NfwH-8deuPtNMP5871B3z7tvrafq_3t1XV7ua-cIGqpvCOCcs8EVbUjbOgFt3TwUlHwGjh1vAbndKMYZ5YqKXXfAAWp-sZ57QXfoOvVd0j2YE45lEyPJtlg_gApj6aEDG4C09ta1gqIqokXVtFeCqYkEMEkddS64vV-9Trl9PMe5sUc0n2OJb5hTaNqrXn5-w3iK8vlNM8Z_MtWSsxTj2bt0Tz1aJ57LKqLVRUA4EWhFSlzzn8DT-yZng</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Nejad, B. 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Samiei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-fc0413f24186c02db43a1df581ef9e31c36ecc978232a18559b7e1e58b7cf9f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Batteries</topic><topic>Constraining</topic><topic>Coordination</topic><topic>Costs</topic><topic>Demand response</topic><topic>demand response program</topic><topic>Demand side management</topic><topic>Discharge</topic><topic>Discharges (electric)</topic><topic>Distributed generation</topic><topic>distribution substation</topic><topic>Economic analysis</topic><topic>Economic models</topic><topic>Energy consumption</topic><topic>Energy costs</topic><topic>Energy distribution</topic><topic>Energy management</topic><topic>Energy storage</topic><topic>Energy Storage power plant</topic><topic>Integer programming</topic><topic>Linear programming</topic><topic>mathematical model</topic><topic>Mixed integer</topic><topic>Power generation</topic><topic>Power management</topic><topic>Power plants</topic><topic>Rechargeable batteries</topic><topic>Smart grid</topic><topic>Smart grids</topic><topic>Substations</topic><topic>Vanadium</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nejad, B. 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Motalebi</au><au>Vahedi, M.</au><au>Hoseina, M.</au><au>Moghaddam, M. Samiei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2023</date><risdate>2023</risdate><volume>11</volume><spage>16483</spage><epage>16492</epage><pages>16483-16492</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>The use of energy storage power plants (ESPP) seems necessary to create flexibility in the operation of smart grids and increase economic benefits. The power storage power plants connect directly to the smart distribution substation (DS), saving energy costs and increasing energy efficiency. Also, demand response (DR) program management has improved the performance of smart grids by shifting loads. In this regard, the main challenge is the optimal coordination between these two problems by considering control challenges such as limiting the number of charge/discharge times and the number of hours of DR implementation using a linear model that can be solved with powerful commercial solvers. In this paper, we proposed an economic mixed-integer linear programming (MILP) model for optimal coordination of DR and large-scale ESPP considering the practical limitations of charge/discharge times and DR action times with optimal management of distributed generation (DG) resources, which provides more realistic results due to the constraints in operating times in both DR and ESPP. To validate and analyze the proposed model, a standard 33-bus distribution network with a standard Vanadium redox battery power plant and a large 874-bus system with three Vanadium redox battery power plants are considered. Various scenarios have been considered to demonstrate the constraints imposed on the demand side management program and battery charge and discharge, the results of which show that these constraints have a significant impact on the objective function of the problem. Also, by comparing the proposed method with other methods, it was found that the proposed method is more efficient in improving the objective function and limiting options.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2022.3184733</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-1337-7056</orcidid><orcidid>https://orcid.org/0000-0001-7302-7296</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Batteries Constraining Coordination Costs Demand response demand response program Demand side management Discharge Discharges (electric) Distributed generation distribution substation Economic analysis Economic models Energy consumption Energy costs Energy distribution Energy management Energy storage Energy Storage power plant Integer programming Linear programming mathematical model Mixed integer Power generation Power management Power plants Rechargeable batteries Smart grid Smart grids Substations Vanadium |
title | Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management |
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