Assessments of data centers for provision of frequency regulation
There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Fu, Yangyang [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Risky business: Psychopathy, framing effects, and financial outcomes - Costello, Thomas H. ELSEVIER, 2018, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:277 ; year:2020 ; day:1 ; month:11 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.apenergy.2020.115621 |
|---|
| Katalog-ID: |
ELV051654458 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV051654458 | ||
| 003 | DE-627 | ||
| 005 | 20230626032259.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 210910s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.apenergy.2020.115621 |2 doi | |
| 028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica |
| 035 | |a (DE-627)ELV051654458 | ||
| 035 | |a (ELSEVIER)S0306-2619(20)31124-7 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 150 |a 300 |q VZ |
| 084 | |a 77.52 |2 bkl | ||
| 100 | 1 | |a Fu, Yangyang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Assessments of data centers for provision of frequency regulation |
| 264 | 1 | |c 2020transfer abstract | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. | ||
| 520 | |a There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. | ||
| 650 | 7 | |a Regulation capacity |2 Elsevier | |
| 650 | 7 | |a Frequency regulation flexibility factor |2 Elsevier | |
| 650 | 7 | |a Frequency regulation |2 Elsevier | |
| 650 | 7 | |a Data center |2 Elsevier | |
| 700 | 1 | |a Han, Xu |4 oth | |
| 700 | 1 | |a Baker, Kyri |4 oth | |
| 700 | 1 | |a Zuo, Wangda |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Costello, Thomas H. ELSEVIER |t Risky business: Psychopathy, framing effects, and financial outcomes |d 2018 |g Amsterdam [u.a.] |w (DE-627)ELV001651005 |
| 773 | 1 | 8 | |g volume:277 |g year:2020 |g day:1 |g month:11 |g pages:0 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.apenergy.2020.115621 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 936 | b | k | |a 77.52 |j Differentielle Psychologie |q VZ |
| 951 | |a AR | ||
| 952 | |d 277 |j 2020 |b 1 |c 1101 |h 0 | ||
| author_variant |
y f yf |
|---|---|
| matchkey_str |
fuyangyanghanxubakerkyrizuowangda:2020----:sesetodtcnesopoiinfrq |
| hierarchy_sort_str |
2020transfer abstract |
| bklnumber |
77.52 |
| publishDate |
2020 |
| allfields |
10.1016/j.apenergy.2020.115621 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica (DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 DE-627 ger DE-627 rakwb eng 150 300 VZ 77.52 bkl Fu, Yangyang verfasserin aut Assessments of data centers for provision of frequency regulation 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier Han, Xu oth Baker, Kyri oth Zuo, Wangda oth Enthalten in Elsevier Science Costello, Thomas H. ELSEVIER Risky business: Psychopathy, framing effects, and financial outcomes 2018 Amsterdam [u.a.] (DE-627)ELV001651005 volume:277 year:2020 day:1 month:11 pages:0 https://doi.org/10.1016/j.apenergy.2020.115621 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 77.52 Differentielle Psychologie VZ AR 277 2020 1 1101 0 |
| spelling |
10.1016/j.apenergy.2020.115621 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica (DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 DE-627 ger DE-627 rakwb eng 150 300 VZ 77.52 bkl Fu, Yangyang verfasserin aut Assessments of data centers for provision of frequency regulation 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier Han, Xu oth Baker, Kyri oth Zuo, Wangda oth Enthalten in Elsevier Science Costello, Thomas H. ELSEVIER Risky business: Psychopathy, framing effects, and financial outcomes 2018 Amsterdam [u.a.] (DE-627)ELV001651005 volume:277 year:2020 day:1 month:11 pages:0 https://doi.org/10.1016/j.apenergy.2020.115621 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 77.52 Differentielle Psychologie VZ AR 277 2020 1 1101 0 |
| allfields_unstemmed |
10.1016/j.apenergy.2020.115621 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica (DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 DE-627 ger DE-627 rakwb eng 150 300 VZ 77.52 bkl Fu, Yangyang verfasserin aut Assessments of data centers for provision of frequency regulation 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier Han, Xu oth Baker, Kyri oth Zuo, Wangda oth Enthalten in Elsevier Science Costello, Thomas H. ELSEVIER Risky business: Psychopathy, framing effects, and financial outcomes 2018 Amsterdam [u.a.] (DE-627)ELV001651005 volume:277 year:2020 day:1 month:11 pages:0 https://doi.org/10.1016/j.apenergy.2020.115621 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 77.52 Differentielle Psychologie VZ AR 277 2020 1 1101 0 |
| allfieldsGer |
10.1016/j.apenergy.2020.115621 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica (DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 DE-627 ger DE-627 rakwb eng 150 300 VZ 77.52 bkl Fu, Yangyang verfasserin aut Assessments of data centers for provision of frequency regulation 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier Han, Xu oth Baker, Kyri oth Zuo, Wangda oth Enthalten in Elsevier Science Costello, Thomas H. ELSEVIER Risky business: Psychopathy, framing effects, and financial outcomes 2018 Amsterdam [u.a.] (DE-627)ELV001651005 volume:277 year:2020 day:1 month:11 pages:0 https://doi.org/10.1016/j.apenergy.2020.115621 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 77.52 Differentielle Psychologie VZ AR 277 2020 1 1101 0 |
| allfieldsSound |
10.1016/j.apenergy.2020.115621 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica (DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 DE-627 ger DE-627 rakwb eng 150 300 VZ 77.52 bkl Fu, Yangyang verfasserin aut Assessments of data centers for provision of frequency regulation 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier Han, Xu oth Baker, Kyri oth Zuo, Wangda oth Enthalten in Elsevier Science Costello, Thomas H. ELSEVIER Risky business: Psychopathy, framing effects, and financial outcomes 2018 Amsterdam [u.a.] (DE-627)ELV001651005 volume:277 year:2020 day:1 month:11 pages:0 https://doi.org/10.1016/j.apenergy.2020.115621 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 77.52 Differentielle Psychologie VZ AR 277 2020 1 1101 0 |
| language |
English |
| source |
Enthalten in Risky business: Psychopathy, framing effects, and financial outcomes Amsterdam [u.a.] volume:277 year:2020 day:1 month:11 pages:0 |
| sourceStr |
Enthalten in Risky business: Psychopathy, framing effects, and financial outcomes Amsterdam [u.a.] volume:277 year:2020 day:1 month:11 pages:0 |
| format_phy_str_mv |
Article |
| bklname |
Differentielle Psychologie |
| institution |
findex.gbv.de |
| topic_facet |
Regulation capacity Frequency regulation flexibility factor Frequency regulation Data center |
| dewey-raw |
150 |
| isfreeaccess_bool |
false |
| container_title |
Risky business: Psychopathy, framing effects, and financial outcomes |
| authorswithroles_txt_mv |
Fu, Yangyang @@aut@@ Han, Xu @@oth@@ Baker, Kyri @@oth@@ Zuo, Wangda @@oth@@ |
| publishDateDaySort_date |
2020-01-01T00:00:00Z |
| hierarchy_top_id |
ELV001651005 |
| dewey-sort |
3150 |
| id |
ELV051654458 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV051654458</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626032259.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210910s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.apenergy.2020.115621</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV051654458</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0306-2619(20)31124-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">150</subfield><subfield code="a">300</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">77.52</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fu, Yangyang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessments of data centers for provision of frequency regulation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Regulation capacity</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Frequency regulation flexibility factor</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Frequency regulation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data center</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Han, Xu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Baker, Kyri</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zuo, Wangda</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Costello, Thomas H. ELSEVIER</subfield><subfield code="t">Risky business: Psychopathy, framing effects, and financial outcomes</subfield><subfield code="d">2018</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV001651005</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:277</subfield><subfield code="g">year:2020</subfield><subfield code="g">day:1</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.apenergy.2020.115621</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">77.52</subfield><subfield code="j">Differentielle Psychologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">277</subfield><subfield code="j">2020</subfield><subfield code="b">1</subfield><subfield code="c">1101</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| author |
Fu, Yangyang |
| spellingShingle |
Fu, Yangyang ddc 150 bkl 77.52 Elsevier Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Assessments of data centers for provision of frequency regulation |
| authorStr |
Fu, Yangyang |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV001651005 |
| format |
electronic Article |
| dewey-ones |
150 - Psychology 300 - Social sciences |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
150 300 VZ 77.52 bkl Assessments of data centers for provision of frequency regulation Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center Elsevier |
| topic |
ddc 150 bkl 77.52 Elsevier Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center |
| topic_unstemmed |
ddc 150 bkl 77.52 Elsevier Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center |
| topic_browse |
ddc 150 bkl 77.52 Elsevier Regulation capacity Elsevier Frequency regulation flexibility factor Elsevier Frequency regulation Elsevier Data center |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
x h xh k b kb w z wz |
| hierarchy_parent_title |
Risky business: Psychopathy, framing effects, and financial outcomes |
| hierarchy_parent_id |
ELV001651005 |
| dewey-tens |
150 - Psychology 300 - Social sciences, sociology & anthropology |
| hierarchy_top_title |
Risky business: Psychopathy, framing effects, and financial outcomes |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV001651005 |
| title |
Assessments of data centers for provision of frequency regulation |
| ctrlnum |
(DE-627)ELV051654458 (ELSEVIER)S0306-2619(20)31124-7 |
| title_full |
Assessments of data centers for provision of frequency regulation |
| author_sort |
Fu, Yangyang |
| journal |
Risky business: Psychopathy, framing effects, and financial outcomes |
| journalStr |
Risky business: Psychopathy, framing effects, and financial outcomes |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
100 - Philosophy & psychology 300 - Social sciences |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| container_start_page |
0 |
| author_browse |
Fu, Yangyang |
| container_volume |
277 |
| class |
150 300 VZ 77.52 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Fu, Yangyang |
| doi_str_mv |
10.1016/j.apenergy.2020.115621 |
| dewey-full |
150 300 |
| title_sort |
assessments of data centers for provision of frequency regulation |
| title_auth |
Assessments of data centers for provision of frequency regulation |
| abstract |
There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. |
| abstractGer |
There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. |
| abstract_unstemmed |
There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U |
| title_short |
Assessments of data centers for provision of frequency regulation |
| url |
https://doi.org/10.1016/j.apenergy.2020.115621 |
| remote_bool |
true |
| author2 |
Han, Xu Baker, Kyri Zuo, Wangda |
| author2Str |
Han, Xu Baker, Kyri Zuo, Wangda |
| ppnlink |
ELV001651005 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth |
| doi_str |
10.1016/j.apenergy.2020.115621 |
| up_date |
2024-07-06T20:51:25.148Z |
| _version_ |
1803864333509197824 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV051654458</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626032259.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210910s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.apenergy.2020.115621</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001267.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV051654458</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0306-2619(20)31124-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">150</subfield><subfield code="a">300</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">77.52</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fu, Yangyang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessments of data centers for provision of frequency regulation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation-based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. When chillers are deactivated, both strategies have a similar regulation capacity.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Regulation capacity</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Frequency regulation flexibility factor</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Frequency regulation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data center</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Han, Xu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Baker, Kyri</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zuo, Wangda</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Costello, Thomas H. ELSEVIER</subfield><subfield code="t">Risky business: Psychopathy, framing effects, and financial outcomes</subfield><subfield code="d">2018</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV001651005</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:277</subfield><subfield code="g">year:2020</subfield><subfield code="g">day:1</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.apenergy.2020.115621</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">77.52</subfield><subfield code="j">Differentielle Psychologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">277</subfield><subfield code="j">2020</subfield><subfield code="b">1</subfield><subfield code="c">1101</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| score |
7.400467 |