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Sloan Foundation grant","award":["G-2017-9723"],"award-info":[{"award-number":["G-2017-9723"]}]},{"DOI":"10.13039\/100007505","name":"Boston University","doi-asserted-by":"publisher","award":["College of Engineering Dean?s Catalyst Award"],"award-info":[{"award-number":["College of Engineering Dean?s Catalyst Award"]}],"id":[{"id":"10.13039\/100007505","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Model. Perform. Eval. Comput. Syst."],"published-print":{"date-parts":[[2019,3,31]]},"abstract":"<jats:p>\n            Power market operators have recently introduced smart grid\n            <jats:italic>demand response<\/jats:italic>\n            (DR), in which electricity consumers regulate their power usage following market requirements. DR helps stabilize the grid and enables integrating a larger amount of intermittent renewable power generation. Data centers provide unique opportunities for DR participation due to their flexibility in both workload servicing and power consumption. While prior studies have focused on data center participation in legacy DR programs such as dynamic energy pricing and peak shaving, this article studies data centers in emerging DR programs, i.e., demand side capacity reserves. Among different types of capacity reserves,\n            <jats:italic>regulation service reserves<\/jats:italic>\n            (RSRs) are especially attractive due to their relatively higher value. This article proposes\n            <jats:bold>EnergyQARE<\/jats:bold>\n            , the\n            <jats:bold>Energy<\/jats:bold>\n            and\n            <jats:bold>Q<\/jats:bold>\n            uality-of-Service (QoS)\n            <jats:bold>A<\/jats:bold>\n            ware\n            <jats:bold>R<\/jats:bold>\n            SR\n            <jats:bold>E<\/jats:bold>\n            nabler, an approach that enables data center RSR provision in real-life scenarios. EnergyQARE not only provides a bidding strategy in RSR provision, but also contains a runtime policy that adaptively modulates data center power through server power management and server provisioning based on workload QoS feedback. To reflect real-life scenarios, this runtime policy handles a heterogeneous set of jobs and considers transition time delay of servers. Simulated numerical results demonstrate that in a general data center scenario, EnergyQARE provides close to 50% of data center average power consumption as reserves to the market and saves up to 44% in data center electricity cost, while still meeting workload QoS constraints. Case studies in this article show that the percentages of savings are not sensitive to a specific type of non-interactive workload, or the size of the data center, although they depend strongly on data center utilization and parameters of server power states.\n          <\/jats:p>","DOI":"10.1145\/3243172","type":"journal-article","created":{"date-parts":[[2019,1,28]],"date-time":"2019-01-28T14:01:39Z","timestamp":1548684099000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["EnergyQARE"],"prefix":"10.1145","volume":"4","author":[{"given":"Hao","family":"Chen","sequence":"first","affiliation":[{"name":"Boston University, Boston, MA, USA"}]},{"given":"Yijia","family":"Zhang","sequence":"additional","affiliation":[{"name":"Boston University, Boston, MA, USA"}]},{"given":"Michael C.","family":"Caramanis","sequence":"additional","affiliation":[{"name":"Boston University, Brookline, MA, USA"}]},{"given":"Ayse K.","family":"Coskun","sequence":"additional","affiliation":[{"name":"Boston University, Boston, MA, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,1,24]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/IGCC.2012.6322252"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the Conference on Design, Automation 8 Test in Europe (DATE\u201914)","author":"Aksanli B."},{"key":"e_1_2_1_3_1","unstructured":"Amazon. 2013. 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