A bottom-up approach for demand response aggregators’ participation in electricity markets
•This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness...
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Veröffentlicht in: | Electric power systems research 2017-02, Vol.143, p.121-129 |
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creator | Mahmoudi, Nadali Heydarian-Forushani, Ehsan Shafie-khah, Miadreza Saha, Tapan K. Golshan, M.E.H. Siano, Pierluigi |
description | •This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness and significance of the proposed bottom-up DR.
This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market. |
doi_str_mv | 10.1016/j.epsr.2016.08.038 |
format | Article |
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This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.</description><identifier>ISSN: 0378-7796</identifier><identifier>EISSN: 1873-2046</identifier><identifier>DOI: 10.1016/j.epsr.2016.08.038</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Bottom-up DR model ; Constraint modelling ; Consumer behavior ; Customer-driven DR ; Customers ; Customers’ behaviour ; DR aggregator ; Economic conditions ; Electrical loads ; Electricity ; Electricity consumption ; Electricity markets ; Feasibility studies ; Markets ; Mathematical models ; Optimization ; Power supply ; Pricing ; Stochastic models ; Stochastic programming</subject><ispartof>Electric power systems research, 2017-02, Vol.143, p.121-129</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Feb 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-ffd59f6bd623078fc3d1df92613d0a6fcd247e47ffc0911802816cc10353a2263</citedby><cites>FETCH-LOGICAL-c446t-ffd59f6bd623078fc3d1df92613d0a6fcd247e47ffc0911802816cc10353a2263</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.epsr.2016.08.038$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Mahmoudi, Nadali</creatorcontrib><creatorcontrib>Heydarian-Forushani, Ehsan</creatorcontrib><creatorcontrib>Shafie-khah, Miadreza</creatorcontrib><creatorcontrib>Saha, Tapan K.</creatorcontrib><creatorcontrib>Golshan, M.E.H.</creatorcontrib><creatorcontrib>Siano, Pierluigi</creatorcontrib><title>A bottom-up approach for demand response aggregators’ participation in electricity markets</title><title>Electric power systems research</title><description>•This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness and significance of the proposed bottom-up DR.
This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.</description><subject>Bottom-up DR model</subject><subject>Constraint modelling</subject><subject>Consumer behavior</subject><subject>Customer-driven DR</subject><subject>Customers</subject><subject>Customers’ behaviour</subject><subject>DR aggregator</subject><subject>Economic conditions</subject><subject>Electrical loads</subject><subject>Electricity</subject><subject>Electricity consumption</subject><subject>Electricity markets</subject><subject>Feasibility studies</subject><subject>Markets</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Power supply</subject><subject>Pricing</subject><subject>Stochastic models</subject><subject>Stochastic programming</subject><issn>0378-7796</issn><issn>1873-2046</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kM9KAzEQxoMoWKsv4CngeddJsk12wUsp_oOCF70JIc2fmtpu1iQVevM1fD2fxJR69jTD8H0z3_wQuiRQEyD8elXbIcWalr6GtgbWHqERaQWrKDT8GI2AibYSouOn6CylFQDwTkxG6HWKFyHnsKm2A1bDEIPSb9iFiI3dqN7gaNMQ-mSxWi6jXaocYvr5-saDitlrP6jsQ499j-3a6hzLKO_wRsV3m9M5OnFqnezFXx2jl7vb59lDNX-6f5xN55VuGp4r58ykc3xhOGUgWqeZIcZ1lBNmQHGnDW2EbYRzGjpCWqAt4VoTYBOmKOVsjK4Oe0v8j61NWa7CNvblpKQwAU4aIvYqelDpGFKK1skh-pJ0JwnIPUW5knuKck9RQisLxWK6OZhsyf_pbZRJe9tra3ws_0oT_H_2X38mfV4</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Mahmoudi, Nadali</creator><creator>Heydarian-Forushani, Ehsan</creator><creator>Shafie-khah, Miadreza</creator><creator>Saha, Tapan K.</creator><creator>Golshan, M.E.H.</creator><creator>Siano, Pierluigi</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20170201</creationdate><title>A bottom-up approach for demand response aggregators’ participation in electricity markets</title><author>Mahmoudi, Nadali ; Heydarian-Forushani, Ehsan ; Shafie-khah, Miadreza ; Saha, Tapan K. ; Golshan, M.E.H. ; Siano, Pierluigi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-ffd59f6bd623078fc3d1df92613d0a6fcd247e47ffc0911802816cc10353a2263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Bottom-up DR model</topic><topic>Constraint modelling</topic><topic>Consumer behavior</topic><topic>Customer-driven DR</topic><topic>Customers</topic><topic>Customers’ behaviour</topic><topic>DR aggregator</topic><topic>Economic conditions</topic><topic>Electrical loads</topic><topic>Electricity</topic><topic>Electricity consumption</topic><topic>Electricity markets</topic><topic>Feasibility studies</topic><topic>Markets</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Power supply</topic><topic>Pricing</topic><topic>Stochastic models</topic><topic>Stochastic programming</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mahmoudi, Nadali</creatorcontrib><creatorcontrib>Heydarian-Forushani, Ehsan</creatorcontrib><creatorcontrib>Shafie-khah, Miadreza</creatorcontrib><creatorcontrib>Saha, Tapan K.</creatorcontrib><creatorcontrib>Golshan, M.E.H.</creatorcontrib><creatorcontrib>Siano, Pierluigi</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Electric power systems research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mahmoudi, Nadali</au><au>Heydarian-Forushani, Ehsan</au><au>Shafie-khah, Miadreza</au><au>Saha, Tapan K.</au><au>Golshan, M.E.H.</au><au>Siano, Pierluigi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A bottom-up approach for demand response aggregators’ participation in electricity markets</atitle><jtitle>Electric power systems research</jtitle><date>2017-02-01</date><risdate>2017</risdate><volume>143</volume><spage>121</spage><epage>129</epage><pages>121-129</pages><issn>0378-7796</issn><eissn>1873-2046</eissn><abstract>•This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness and significance of the proposed bottom-up DR.
This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.epsr.2016.08.038</doi><tpages>9</tpages></addata></record> |
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subjects | Bottom-up DR model Constraint modelling Consumer behavior Customer-driven DR Customers Customers’ behaviour DR aggregator Economic conditions Electrical loads Electricity Electricity consumption Electricity markets Feasibility studies Markets Mathematical models Optimization Power supply Pricing Stochastic models Stochastic programming |
title | A bottom-up approach for demand response aggregators’ participation in electricity markets |
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