A Game-Theoretic Framework for Multiperiod-Multicompany Demand Response Management in the Smart Grid

By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set thei...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on control systems technology Vol. 29; no. 3; pp. 1019 - 1034
Main Authors:	Alshehri, Khaled, Liu, Ji, Chen, Xudong, Basar, Tamer
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Closed form solutions Companies Consumers Demand side management Demand-side management (DSM) Distributed algorithms Energy consumption Energy management Equilibrium Exact solutions Game theory Games Incentives Load management power system economics Smart grid Smart grids Subdivisions Uniqueness Utilities
ISSN:	1063-6536, 1558-0865
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set their prices and consumers respond by choosing their demands. We show that the underlying game has a unique equilibrium at which the companies maximize their revenues, while the consumers maximize their utilities subject to their local constraints. Closed-form expressions are provided for the optimal strategies of all players. Based on these solutions, a power-allocation game has been formulated, which is shown to admit a unique pure-strategy Nash equilibrium, for which closed-form expressions are also provided. This equilibrium is found under the assumption that companies can freely allocate their power across the time horizon, but we also demonstrate that it is possible to relax this assumption. We further provide a fast distributed algorithm for the computation of all optimal strategies using only local information. We also study the effect of variations in the number of periods (subdivisions of the time horizon) and the number of consumers. As a consequence, we are able to find an appropriate company-to-consumer ratio when the number of consumers participating in demand response exceeds some threshold. Furthermore, we show, both analytically and numerically, that the multiperiod scheme provides incentives for energy consumers to participate in demand response compared with the single-period framework studied by Maharjan et al. In our framework, we provide a condition for the minimum budget consumers need and carry out case studies using real-life data to demonstrate the benefits of the approach, which show potential savings of up to 30% and equilibrium prices that have low volatility.
AbstractList	By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set their prices and consumers respond by choosing their demands. We show that the underlying game has a unique equilibrium at which the companies maximize their revenues, while the consumers maximize their utilities subject to their local constraints. Closed-form expressions are provided for the optimal strategies of all players. Based on these solutions, a power-allocation game has been formulated, which is shown to admit a unique pure-strategy Nash equilibrium, for which closed-form expressions are also provided. This equilibrium is found under the assumption that companies can freely allocate their power across the time horizon, but we also demonstrate that it is possible to relax this assumption. We further provide a fast distributed algorithm for the computation of all optimal strategies using only local information. We also study the effect of variations in the number of periods (subdivisions of the time horizon) and the number of consumers. As a consequence, we are able to find an appropriate company-to-consumer ratio when the number of consumers participating in demand response exceeds some threshold. Furthermore, we show, both analytically and numerically, that the multiperiod scheme provides incentives for energy consumers to participate in demand response compared with the single-period framework studied by Maharjan et al. In our framework, we provide a condition for the minimum budget consumers need and carry out case studies using real-life data to demonstrate the benefits of the approach, which show potential savings of up to 30% and equilibrium prices that have low volatility.
Author	Liu, Ji Basar, Tamer Alshehri, Khaled Chen, Xudong
Author_xml	– sequence: 1 givenname: Khaled orcidid: 0000-0001-9761-0830 surname: Alshehri fullname: Alshehri, Khaled email: kalshehri@kfupm.edu.sa organization: Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia – sequence: 2 givenname: Ji orcidid: 0000-0003-2871-9888 surname: Liu fullname: Liu, Ji email: ji.liu@stonybrook.edu organization: Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA – sequence: 3 givenname: Xudong orcidid: 0000-0002-0135-0606 surname: Chen fullname: Chen, Xudong email: xudong.chen@colorado.edu organization: Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA – sequence: 4 givenname: Tamer orcidid: 0000-0003-4406-7875 surname: Basar fullname: Basar, Tamer email: basar1@illinois.edu organization: Department of Electrical and Computer Engineering, University of Illinois at Urbana--Champaign, Urbana, IL, USA
BookMark	eNp9UctOwzAQtBBItIUPQFwscU7xI07sY1VoQWqFRMM5cpMNdWns4LhC_XsSWnHgwGlnpZmd0ewQnVtnAaEbSsaUEnWfTVfZmBFGxkxJxVJ2hgZUCBkRmYjzDpOER4ngySUatu2WEBoLlg5QOcFzXUOUbcB5CKbAM9_tX85_4Mp5vNzvgmnAG1dGP7hwdaPtAT9ArW2JX6FtnG0BL7XV71CDDdhYHDaAV7X2Ac-9Ka_QRaV3LVyf5gi9zR6z6VO0eJk_TyeLqGCKh6jSpVinCUiZ6DhRvKIVU1AKWRQypYyC5qAKpQSBOBZkHQsuylQBgCBCAOEjdHe823j3uYc25Fu397azzJmgPCZEip5Fj6zCu7b1UOWNN13WQ05J3peZ92XmfZn5qcxOk_7RFCboYJwNXpvdv8rbo9J0OX-dVPcWRRj_BtY8hBM
CODEN	IETTE2
CitedBy_id	crossref_primary_10_1109_ACCESS_2022_3188642 crossref_primary_10_1109_JSYST_2022_3153516 crossref_primary_10_1109_TSG_2021_3078905 crossref_primary_10_1109_TASE_2023_3336640 crossref_primary_10_1109_TPWRS_2022_3169409 crossref_primary_10_1016_j_simpat_2024_102918 crossref_primary_10_1109_JSYST_2022_3189727 crossref_primary_10_1109_TSMC_2024_3517577 crossref_primary_10_1007_s11424_025_4242_0 crossref_primary_10_1109_TSG_2024_3440315 crossref_primary_10_1016_j_dcan_2024_06_005 crossref_primary_10_1016_j_ifacsc_2025_100296 crossref_primary_10_1109_TCYB_2022_3142035 crossref_primary_10_1109_TCST_2024_3425210 crossref_primary_10_1109_TSG_2024_3417535
Cites_doi	10.1109/TETC.2013.2273457 10.1007/978-0-8176-8216-3 10.1023/A:1021294828483 10.3390/en10091342 10.1016/j.apenergy.2017.05.150 10.1109/TSG.2015.2445491 10.1109/INM.2011.5990666 10.1109/TAC.1982.1102918 10.1109/TSG.2015.2431324 10.1109/TSG.2012.2211901 10.1109/JSAC.2014.2332119 10.1109/TPWRS.2002.807052 10.1016/j.tej.2007.01.006 10.1109/TPWRS.2015.2395452 10.1109/TPWRS.2004.825894 10.1109/TSG.2013.2284664 10.1109/TSG.2013.2295024 10.1109/TPWRS.2003.810692 10.1109/TSG.2010.2089069 10.1109/SmartGridComm.2011.6102331 10.1109/INFCOMW.2012.6193526 10.1016/j.apenergy.2016.09.051 10.1016/j.apenergy.2015.04.083 10.1109/TSG.2012.2223766 10.1109/PESGM.2014.6939412 10.1214/aoms/1177729893 10.1109/TETC.2014.2335541 10.1109/ICC.2012.6364562 10.3390/en7117499 10.1109/MSP.2012.2186410 10.1109/TPWRS.2012.2205021 10.1109/61.25627 10.1109/TIE.2014.2341556 10.1109/TSG.2014.2376522 10.1109/CDC.2015.7403145 10.1109/TSG.2012.2185075 10.1109/MSP.2012.2186531 10.1016/j.ifacol.2017.08.2383 10.1109/EPEC.2015.7379950 10.1109/COMST.2014.2341586 10.1109/TII.2011.2158841 10.1109/TSG.2017.2734113 10.1109/TSG.2014.2302245 10.1038/sj.jors.2600523
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021
DBID	97E RIA RIE AAYXX CITATION 7SP 7TB 8FD FR3 L7M
DOI	10.1109/TCST.2020.2989272
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) CrossRef Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Engineering Research Database Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Engineering Research Database Technology Research Database Mechanical & Transportation Engineering Abstracts Advanced Technologies Database with Aerospace Electronics & Communications Abstracts
DatabaseTitleList	Engineering Research Database
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1558-0865
EndPage	1034
ExternalDocumentID	10_1109_TCST_2020_2989272 9086902
Genre	orig-research
GrantInformation_xml	– fundername: U.S. Air Force Office of Scientific Research (AFOSR) MURI grantid: FA9550-10-1-0573 funderid: 10.13039/100000181 – fundername: AFOSR grantid: FA9550-19-1-0353 funderid: 10.13039/100000181 – fundername: King Fahd University of Petroleum and Minerals (KFUPM) funderid: 10.13039/501100004055
GroupedDBID	-~X .DC 0R~ 29I 4.4 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACBEA ACGFO ACGFS ACIWK ACKIV AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ H~9 ICLAB IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TN5 VH1 AAYXX CITATION 7SP 7TB 8FD FR3 L7M
ID	FETCH-LOGICAL-c293t-fad5b76e886a4693f1f29ed58cc87121ea3e9c9950e4450b4535d79eee5055e03
IEDL.DBID	RIE
ISICitedReferencesCount	19
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000640767400008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1063-6536
IngestDate	Mon Jun 30 05:15:26 EDT 2025 Sat Nov 29 03:51:40 EST 2025 Tue Nov 18 21:32:25 EST 2025 Wed Aug 27 02:28:58 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	3
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c293t-fad5b76e886a4693f1f29ed58cc87121ea3e9c9950e4450b4535d79eee5055e03
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0001-9761-0830 0000-0003-4406-7875 0000-0003-2871-9888 0000-0002-0135-0606
PQID	2513400850
PQPubID	85425
PageCount	16
ParticipantIDs	crossref_citationtrail_10_1109_TCST_2020_2989272 proquest_journals_2513400850 crossref_primary_10_1109_TCST_2020_2989272 ieee_primary_9086902
PublicationCentury	2000
PublicationDate	2021-May 2021-5-00 20210501
PublicationDateYYYYMMDD	2021-05-01
PublicationDate_xml	– month: 05 year: 2021 text: 2021-May
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE transactions on control systems technology
PublicationTitleAbbrev	TCST
PublicationYear	2021
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref12 ref15 srikant (ref35) 2004 ref14 ref53 ref52 ref11 ref10 ba?ar (ref38) 2002; 115 ref17 ref16 ref19 ref18 bose (ref42) 2018 gan (ref49) 2003; 18 ref51 albadi (ref1) 2007 ref50 ba?ar (ref37) 2002; 1 ref46 ref48 mohsenian-rad (ref23) 2010; 1 ref43 lund (ref44) 2016 ref8 ba?ar (ref34) 1999 ref7 ref9 ref4 ref3 ref6 ref5 ref40 alshehri (ref45) 2019 ref36 ref30 ref33 ref32 ref2 ref39 bertsekas (ref41) 2008 ref24 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 jia (ref31) 2013 (ref47) 2010
References_xml	– ident: ref30 doi: 10.1109/TETC.2013.2273457 – year: 2004 ident: ref35 publication-title: The Mathematics of Internet Congestion Control doi: 10.1007/978-0-8176-8216-3 – volume: 115 start-page: 479 year: 2002 ident: ref38 article-title: A Stackelberg network game with a large number of followers publication-title: J Optim Theory Appl doi: 10.1023/A:1021294828483 – ident: ref22 doi: 10.3390/en10091342 – ident: ref8 doi: 10.1016/j.apenergy.2017.05.150 – ident: ref25 doi: 10.1109/TSG.2015.2445491 – ident: ref40 doi: 10.1109/INM.2011.5990666 – ident: ref9 doi: 10.1109/TAC.1982.1102918 – ident: ref20 doi: 10.1109/TSG.2015.2431324 – ident: ref14 doi: 10.1109/TSG.2012.2211901 – ident: ref29 doi: 10.1109/JSAC.2014.2332119 – volume: 18 start-page: 53 year: 2003 ident: ref49 article-title: Energy and reserve market designs with explicit consideration to lost opportunity costs publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2002.807052 – volume: 1 start-page: 294 year: 2002 ident: ref37 article-title: Revenue-maximizing pricing and capacity expansion in a many-users regime publication-title: Proc 21st Annu Joint Conf IEEE Comput Commun Soc – ident: ref4 doi: 10.1016/j.tej.2007.01.006 – ident: ref52 doi: 10.1109/TPWRS.2015.2395452 – ident: ref50 doi: 10.1109/TPWRS.2004.825894 – ident: ref13 doi: 10.1109/TSG.2013.2284664 – start-page: 5608 year: 2013 ident: ref31 article-title: Day ahead dynamic pricing for demand response in dynamic environments publication-title: Proc 52nd IEEE Conf Decis Control – ident: ref16 doi: 10.1109/TSG.2013.2295024 – ident: ref3 doi: 10.1109/TPWRS.2003.810692 – year: 1999 ident: ref34 publication-title: Dynamic Noncooperative Game Theory – volume: 1 start-page: 320 year: 2010 ident: ref23 article-title: Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid publication-title: IEEE Trans Smart Grid doi: 10.1109/TSG.2010.2089069 – start-page: 1 year: 2007 ident: ref1 article-title: Demand response in electricity markets: An overview publication-title: Proc IEEE Power Eng Soc Gen Meeting – ident: ref12 doi: 10.1109/SmartGridComm.2011.6102331 – ident: ref27 doi: 10.1109/INFCOMW.2012.6193526 – ident: ref43 doi: 10.1016/j.apenergy.2016.09.051 – ident: ref5 doi: 10.1016/j.apenergy.2015.04.083 – ident: ref11 doi: 10.1109/TSG.2012.2223766 – year: 2008 ident: ref41 publication-title: Nonlinear Programming – ident: ref17 doi: 10.1109/PESGM.2014.6939412 – ident: ref53 doi: 10.1214/aoms/1177729893 – ident: ref21 doi: 10.1109/TETC.2014.2335541 – year: 2016 ident: ref44 article-title: EcoGrid EU deliverable 6.7: Overall evaluations and conclusions – ident: ref26 doi: 10.1109/ICC.2012.6364562 – ident: ref15 doi: 10.3390/en7117499 – ident: ref10 doi: 10.1109/MSP.2012.2186410 – year: 2010 ident: ref47 publication-title: Communications Requirements of Smart Grid Technologies – ident: ref48 doi: 10.1109/TPWRS.2012.2205021 – ident: ref51 doi: 10.1109/61.25627 – ident: ref19 doi: 10.1109/TIE.2014.2341556 – ident: ref32 doi: 10.1109/TSG.2014.2376522 – ident: ref33 doi: 10.1109/CDC.2015.7403145 – year: 2019 ident: ref45 publication-title: Multi-period demand response – start-page: 29 year: 2018 ident: ref42 article-title: Some emerging challenges in electricity markets publication-title: Smart gird control Overview and research opprtunities – ident: ref39 doi: 10.1109/TSG.2012.2185075 – ident: ref6 doi: 10.1109/MSP.2012.2186531 – ident: ref46 doi: 10.1016/j.ifacol.2017.08.2383 – ident: ref18 doi: 10.1109/EPEC.2015.7379950 – ident: ref7 doi: 10.1109/COMST.2014.2341586 – ident: ref2 doi: 10.1109/TII.2011.2158841 – ident: ref28 doi: 10.1109/TSG.2017.2734113 – ident: ref24 doi: 10.1109/TSG.2014.2302245 – ident: ref36 doi: 10.1038/sj.jors.2600523
SSID	ssj0014527
Score	2.4558318
Snippet	By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	1019
SubjectTerms	Algorithms Closed form solutions Companies Consumers Demand side management Demand-side management (DSM) Distributed algorithms Energy consumption Energy management Equilibrium Exact solutions Game theory Games Incentives Load management power system economics Smart grid Smart grids Subdivisions Uniqueness Utilities
Title	A Game-Theoretic Framework for Multiperiod-Multicompany Demand Response Management in the Smart Grid
URI	https://ieeexplore.ieee.org/document/9086902 https://www.proquest.com/docview/2513400850
Volume	29
WOSCitedRecordID	wos000640767400008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-0865 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014527 issn: 1063-6536 databaseCode: RIE dateStart: 19930101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA4qHvTgrylOp-TgSYy2adI2R1GnBxmiU3YrSd4rDFwnc_r3m6TdVBTBWw4JtPnS96P53vcIOVKx23qjgYGwignJgWllYsa5NmkOkRFBrPrpNuv18sFA3S2Qk3ktDCIG8hme-mG4y4exffO_ys5U5PsnOYO7mGVpXas1vzEQdXtWl-EkLA1Xku1GT_Osf_HQd5kgj0693DjP-DcfFJqq_LDEwb101__3YBtkrQkj6XmN-yZZwGqLrH4RF2wROKfXeoSsPytVpN0ZEYu6SJWG0luvczwGFsa2Ng30Eke6Anpfs2eRfjJk6LCiLmCkDyN34Oj1ZAjb5LF71b-4YU1PBWadY5-yUoM0WYp5nmqXGSdlXHKFIHNrXerEY9QJKquUjFAI6aCSiYRMuTd2oZLEKNkhS9W4wl1CBTgrq7PS8MQI5KBSDqAMxiCVyUtsk2i2y4VtBMd934vnIiQekSo8MIUHpmiAaZPj-ZKXWm3jr8ktj8R8YgNCm3RmUBbN9_hauCguEUGeb-_3VftkhXu2SqAydsjSdPKGB2TZvk-Hr5PDcNQ-ANRu0Wc
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NT9wwEB0hitT2ALQUsZS2PnCqakgcO4mPiHah6rJCkFbcItszkVZis9Wy8PuxnezSqlWl3nywpcTPmY_4zRuAQ536rbcGOUqnuVQCudE25UIYm5eYWBnFqn-MivG4vLnRl2vwaVULQ0SRfEZHYRjv8nHm7sOvsmOdhP5J3uA-U1KKpKvWWt0ZyK5Bq89xMp7HS8lBr6h5XJ1eVz4XFMlREBwXhfjNC8W2Kn_Y4uhghlv_92jbsNkHkuykQ_4VrFH7Gl7-Ii-4A3jCzsyUeLUsVmTDJRWL-ViVxeLboHQ8Qx7HrjMO7DNNTYvsquPPEnviyLBJy3zIyK6n_sixs_kE38D34Zfq9Jz3XRW48659wRuDyhY5lWVufG6cNWkjNKEqnfPJk0jJZKSd1iohKZUHS2UKC-3f2AdLipJsF9bbWUt7wCR6O2uKxorMShKoc4GoLaWotC0bGkCy3OXa9ZLjofPFbR1Tj0TXAZg6AFP3wAzg42rJz05v41-TdwISq4k9CAM4WEJZ91_kXe3juExGgb79v6_6AM_Pq4tRPfo6_vYWXojAXYnExgNYX8zv6R1suIfF5G7-Ph67R-D61K4
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Game-Theoretic+Framework+for+Multiperiod-Multicompany+Demand+Response+Management+in+the+Smart+Grid&rft.jtitle=IEEE+transactions+on+control+systems+technology&rft.au=Alshehri%2C+Khaled&rft.au=Liu%2C+Ji&rft.au=Chen%2C+Xudong&rft.au=Basar%2C+Tamer&rft.date=2021-05-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=1063-6536&rft.eissn=1558-0865&rft.volume=29&rft.issue=3&rft.spage=1019&rft_id=info:doi/10.1109%2FTCST.2020.2989272&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1063-6536&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1063-6536&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1063-6536&client=summon