Digital Technologies, Energy, And Climate
Digital technologies, energy, and climateGeorge Kamiya, Strategic Initiatives Office11 December 2019IEA 2019. All rights reserved.
No single or simple solutions to reach sustainable energy goalsEnergy-related CO2 emissions and reductions in the Sustainable Development Scenario by sourceGt CO2Current Trends40Stated Policies Scenario302010Industrial electric motorsBuildingsPowerLight industryCars & trucksHeavy industryAir conditionersAviation and shippingWindSolar PVBiofuels transportOther renewables powerOther renewables end-usesHydroNuclearFuel switch incl. hydrogenElectric vehiclesCCUS powerCCUS industryBehavioural changeResource efficiencyEfficiencyRenewablesFuel switch, CCUSand otherSustainable Development Scenario20102020203020402050IEA (2019). World Energy Outlook 2019.A host of policies and technologies will be needed across every sector to keep climate targets withinreach, and further technology innovation will be essential to aid the pursuit of a 1.5 C stabilisationIEA 2019. All rights reserved.
Tracking progress of technologies and sectors – www.iea.org/tcep Industry Transport Buildings Nuclear power Chemicals Electric vehicles Building envelopes Solar PV Gas-fired power Iron and steel Fuel economy Heating Onshore wind Coal-fired power Cement Trucks & buses Heat pumps Offshore wind CCUS in power Pulp and paper Transport biofuels Cooling Aluminium Aviation Lighting CCUS in industry &transformation Shipping Appliances &equipment Power Renewable power Hydropower Bioenergy Geothermal Rail Data centres andnetworks CSP Ocean Fuelsupply Methane emissions from oil and gas Flaring emissionsIEA 2019. All rights reserved. Energyintegration Energy storage Smart grids Hydrogen Demand responseIEA (2019). Tracking Clean Energy Progress. www.iea.org/tcep.
Digitalization & Energy1. Introduction: A new era of digitalization in energy?2. Energy demand: transport, buildings, and industries3. Energy supply: oil and gas, coal, and power4. System-wide impacts: from energy silos to digitallyinterconnected systems5. Energy use by digital technologieswww.iea.org/digital6. Cross-cutting risks: cyber security, privacy, and economicdisruption7. Policy, including no-regrets recommendationsIEA 2019. All rights reserved.
Rapid growth of the IoT and connected devicesHousehold electricity consumption of appliances and other small plug loads6 000TWh5 0004 0003 0002 000Network-enabled1 0000Not connected2010201520202025203020352040IEA analysisThe growth in network-enabled devices presents opportunities for smart demand responsebut also increases needs for standby powerIEA 2019. All rights reserved.
40Appliances30Lighting20Water heating10Space cooling0Space heatingBy sectorBy end useIEA (2017). Digitalization & Energy.Widespread deployment of smart building controls could reduce energy use by 10% to 2040IEA 2019. All rights reserved.
TransportI) Optimistic scenario:"Have our cake and eat it too"II) Pessimistic scenario:"Dystopian nightmare"Heavy-dutyvehiclesEnergy intensityLight-dutyvehiclesTravel demand Automation, connectivity, sharing,and electrification (ACES) todramatically reshape mobilityEnergy demandTotal roadtransport energy Impacts on energy demanddifficult to predict-80%-40%0%40%80%120%-80% -40%0%40%80% 120%Wadud, MacKenzie and Leiby (2016), “Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles”.Road transport energy demand could halve or double from automation and connectivitydepending on how technology, behavior, and policy evolveIEA 2019. All rights reserved.
Industry25 000TonsCumulative aircraft fuel savingsto 2050Metal demandin 20501 750Million GJ1 50020 0001 25015 0001 00010 0007505005 0000250ConventionalcomponentsAM componentsAluminium alloysNickel alloys0SlowadoptionTitanium alloysMid-rangeadoptionRapidadoptionFuel savingsHuang et al. (2016). Energy and emissions saving potential of additive manufacturing: the caseof lightweight aircraft components. Journal of Cleaner ProductionEnergy use can be incrementally reduced at the plant levelbut widespread use of 3D printing, AI and robotics could herald transformative changesIEA 2019. All rights reserved.
Electricity generation and networks40USD billion (2016)OPEXCAPEX3020Power Power plants and electricitynetworks could see reduced O&Mcosts, extended life time,improved efficiencies andenhanced stability1005% lowerO&M costsEfficiency:Efficiency:5-yr life5% more5% lower totalextensionelectricity output network losses for power plantsper unit of fuel5-yr lifeextensionfor networksIEA (2017). Digitalization & Energy.Digitalization could save around USD 80 billion per year,or about 5% of total annual power generation costsIEA 2019. All rights reserved.
Digitalisation: From end-use to system efficiencySmart homeSmart gridIEA (2019). Energy Efficiency Market Report.Traditional efficiency policy addresses devices individually. Digitalisation, with the right policies,enables a progression to optimising the efficiency of the whole energy system.IEA 2019. All rights reserved.
The digital transformation of the energy systemIEA (2017). Digitalization & Energy.Pre-digital energy systems are defined by unidirectional flows and distinct roles,IEA 2019. All rights reserved.
The digital transformation of the energy systemIEA (2017). Digitalization & Energy.Pre-digital energy systems are defined by unidirectional flows and distinct roles,digital technologies enable a multi-directional and highly integrated energy systemIEA 2019. All rights reserved.
Digitalisation requires policy actionPolicy principles comprising the Readiness for Digital Energy Efficiency frameworkIEA (2019). Energy Efficiency Market Report.Policy makers must engage with a range of challenging issues if the world is toharness digitalisation for greater energy efficiencyIEA 2019. All rights reserved.
Direct and indirect effects of ICTIEA 2019. All rights reserved.Horner, N. C., Shehabi, A., & Azevedo, I. L. (2016). Known unknowns: Indirect energy effects of information andcommunication technology. Environmental Research Letters, 11(10), 103001.
ICT energy useIEA 2019. All rights reserved.
ICT energy use: service demand growth vs. efficiencyGlobal trends in internet traffic, data centre workloads and data centre energy useIndex (2015 100)600Internet traffic500400Data centre workloads30020010002015Data centre energy use201620172018201920202021IEA (2019). Tracking Clean Energy Progress: Data centres and networks; Cisco (2018). Global Cloud Index.Global internet traffic has tripled since 2015, but data centre energy use remains flatIEA 2019. All rights reserved.
ICT energy use: data centresTWh250By end use250200By data centre rage5002015Servers201720192021100Cloud (nonhyperscale)5002015Traditional201720192021IEA (2019). Tracking Clean Energy Progress: Data centres and data transmission networks.Strong efficiency improvements and a shift to hyperscale data centreshave helped to keep global data centre energy demand flatIEA 2019. All rights reserved.
ICT energy use: efficiency trendsComputingKoomey, J. and S. Naffziger (2015), "Moore’s Law Might Be Slowing Down, But NotEnergy Efficiency”, IEEE Spectrum.IEA 2019. All rights reserved.Data transmissionAslan, J., Mayers, K., Koomey, J. G., & France, C. (2018). Electricity intensity of Internet data transmission:Untangling the estimates. Journal of Industrial Ecology, 22(4), 785-798.
ICT energy use: renewable energyGlobal PPA volumes, by ment & University8Consumer Staples6Materials4Communications2Technology02009 2011 2013 2015 2017 2019YTDTop corporate off-takers, 2019Google*AT&T*Microsoft*Facebook*Amazon*QTS Realty Trust*WalmartMcDonald'sBall Corp.SolarHonda01 000Wind2 0003 000MWNotes: * denotes ICT company. 2019 data as of November 2019.Source: BloombergNEF (2019), Corporate PPA Deal Tracker November 2019.ICT companies are leaders in corporate renewable energy procurement, and further efforts to matchfor time and location can reduce environmental impacts of data centres furtherIEA 2019. All rights reserved.
TWhComparing global energy use estimates for data centres8 000IEA/Northwestern/LBNL (2019)Malmodin & Lunden (2018)7 000ShiftProject (2018) - Sobriety6 000ShiftProject (2018) - Higher growth peaked EEShiftProject (2018) - Higher growth higher EE5 000ShiftProject (2018) - Expected updated4 000Andrae (2018) - Best (22.5% EE)3 000Andrae (2018) - Expected (15% EE)Andrae & Edler (2015) - Best2 000Andrae & Edler (2015) - Expected1 000Andrae & Edler (2015) - WorstVan Heddeghem et al. (2014)02010IEA 2019. All rights reserved.2015202020252030Koomey (2011)Global electricity demand in 2030 in the IEA NPS: 30,000 TWh
Questions for longer-term outlooks Continued slowdown in IT efficiency (Koomey’sLaw) and long-term limits to efficiency? Slowdown in PUE improvement? Limits to shifting to hyperscale? Emerging demands and services: AI/ML,blockchain, 5G, AR/VR, connected andautomated vehicles, rebound effects, etc.Uptime Institute (2019). Is PUE actually going up? y-going-up/.Strubell et al. (2019). Energy and Policy Considerations for Deep Learning in NLP.IEA 2019. All rights reserved.Google (2019), Data Centres: Efficiency, y/.
Bitcoin ( ) price and hashrate1E 09ASIC1E 061E 00Digiconomist (2019)80Lower bound [Antminer S9]FPGAGPU1E 03TWh/yrBitcoin mining: 45 TWh in 2018; 30 TWh in 2019-H170CPUBendiksen, Gibbons & Lim (2018-19)Stoll et al. (2019)60Rauchs et al. (2018)1E-031E-062010Hashrate (TH/s)Price ( /USD)20122014201650Krause & Tolaymat (2018)2018De Vries (2018a)*40Energy efficiency (MH/J)1E 05Efficiency of mining hardwareBNEF (2018)301E 04Morgan Stanley (2018)*1E 03Deetman (2017)*1E 01ASIC1E 00FPGA1E-01IEA 2019. All rights reserved.10Hileman & Rauchs (2017)Vranken (2017)GPU1E-021E-031E-01Bevand (2018)201E 02CPU1E 021E 05Hashrate (MH/s)01/201707/201701/201807/201801/201907/20191E 08IEA (2019). Bitcoin energy use: mined the gap.
Further reading IEA reports:- Digitalization & Energy. www.iea.org/digital.- Tracking Clean Energy Progress. www.iea.org/tcep.- Energy Efficiency Market Report 2019. www.iea.org/reports/energy-efficiency-2019. Climate Change AI; Tackling Climate Change with Machine Learning. www.climatechange.ai/. Horner et al. (2017). Known unknowns: indirect energy effects of information andcommunication technology. /103001. Shehabi et al. (2016). United States Data Center Energy Usage -center-energy. Malmodin & Lunden (2018). The Energy and Carbon Footprint of the Global ICT and E&MSectors 2010–2015. www.mdpi.com/2071-1050/10/9/3027.IEA 2019. All rights reserved.
George KamiyaStrategic Initiatives amiya/@GeorgeKamiyaIEA 2019. All rights reserved.
Bitcoin ( ) price and hashrate CPU GPU FPGA ASIC Bitcoin mining: 45 TWh in 2018; 30 TWh in 2019-H1 10 20 30 40 50 60 70 80 01/2017 07/2017 01/2018 07/2018 01/2019 07/2019 r Digiconomist (2019) Lower bound [Antminer S9] Bendiksen, Gibbons & Lim (2018-19) Stoll et al. (2019) Rauchs et al. (2018
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