Leveraging Renewable Energy in Data Centers

Ricardo Bianchini on tour2012

Motivation• Datacenters consume large amounts of energy• Energy cost is not the only problem– Brown sources: coal, natural gas…

• Lots of small and medium datacenters• Use renewable sources for datacenters– Solar panels, wind turbines…– “Green" datacenters

Renewable sources has lower environmental impact

Wind (o

ffshore)

Hydroelectr

ic

Wind (o

nshore)

Biogas

Solar therm

al

Biomass

Solar PV

Geoterhemal

Nuclear

Natural gas

Diesel

Heavy oilCoal

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1000CO2 generation per source (CO2/kWh)

Wastes lastthousands of years

Motivation• Datacenters consume large amounts of energy• Energy cost is not the only problem– Brown sources: coal, natural gas…

• Lots of small and medium datacenters• Use renewable sources for datacenters– Solar panels, wind turbines…– “Green" datacenters

Renewable approaches for“green” datacenters

• Centralized generation– Utilities install renewable power plants– Green pricing: users pay for a green percentage

• Compensation systems– CO2 offsets– Renewable Electricity Credits (RECs)

• Distributed generation– Connect to close renewable power plants– Self-generation

Why distributed generation?

• Energy independence– Stable costs– Resilient to external failures

• Reduce transmission and conversion losses– From 41% to 30% losses (even <5%)

• Long lifetime– Installations can be reused

• Allow local energy management– Control which energy to use and when

Why solar and wind?

• Medium/high availability• Suitable for small/medium installations– Initial cost/W is lower– No wastes– Easy to install– Easy to maintain

Why solar?

• Solar PV cost scalability is linear– Small installations have similar $/W as large– Better for distributed generation

• Solar availability is higher than windWind Solar

Price of PV energy is decreasing19

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Grid electricity price(2011 c/kWh)

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PV panels cost(2011 $/W)

• PV energy already cheaper than utility in some locations [1]

Problems and challenges

• Require large extensions of land– Bad for large datacenters

• Low/medium efficiency– Efficiency lower than 40%– Increasing every year

• Variability– Batteries: losses, economic and environmental cost– Net metering: losses, limited availability– Smarter management

Parasol (remove)

• Construction– Structure– Solar panels

• Installation– Servers: software

• Lessons learned– Not as easy as it seems– Hard to deal with facilities crowd– Setting it on the roof has extra cost– Easier to just put solar panels in the roof and use a regular room– Flexibility for research purposes is hard– Metering everywhere: temperature, power

Parasol

• We are building a µDatacenter• Powered by– PV panels– Electricity grid– Batteries

• Research framework– Manage solar-powered datacenter– Software to exploit renewable energy– Free cooling

Parasol description• Installed on the roof• Steel structure

– Container to host the IT– 10 PV panels: 3 kW

• Backup energy systems– Batteries: 32 kWh– Power grid

• IT equipment– 2 42U racks– 64 Atom servers (so far)– 2 switches

• Cooling system– Free cooling– Air conditioner– Heater

Structure craning and assembling

Container and solar panels

Electrical and cooling

IT equipment

Green systems

• Handle renewable energy variability– Smart energy management

• GreenSlot [SC‘11]– Schedule batch jobs (SLURM)

• GreenHadoop [EUROSYS’12]– Schedule data-processing jobs (MapReduce)

Green systems approach

• Predict green energy availability– Weather forecast

• Schedule jobs– Maximize green energy use– If green not available, consume cheap brown

• May delay jobs but must meet deadlines• Manage data availability• Send to sleep (S3) idle servers to save energy

J1

GreenSlot behavior

J2

Time

J1

J2

Now

Nod

esPow

er

J1J2

Schedule:

Brown electricity priceJob deadlineScheduling window

J1, J2

J1J3

J4

GreenSlot behavior

J2

Time

J1

J2

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J3

Nod

esPow

er

J3J4

Schedule:

Now

J3, J4

Brown electricity priceJob deadlineScheduling window

J1

J4

J3

GreenSlot behavior

J2

Time

J2

J1J3

Nod

esPow

er

J4

J4

Schedule: J4 Weather prediction was wrong

NowBrown electricity priceJob deadlineScheduling window

J1

J4

J5J3

GreenSlot behavior

J2

Time

J2

J1J3 J5

Nod

esPow

er

J4

J5

Schedule:

Now

J5

Brown electricity priceJob deadlineScheduling window

Future directions

• Collect data of the data center– Real workloads– Temperatures

• ???

Leveraging Renewable Energy in Data Centers

Ricardo Bianchini on tour2012