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E^2DC 2014 1Cambridge, UK 30/06/2014
Project FP7 – SMARTCITIES – 2013 Grant Agreement n°: 609211
Green nEtworked data centres as energYproSumErs in smaRt city environments
Enabling Green Data Centres in Smart Cities
Massimo Bertoncini, Engineering Ingegneria Informatica, Project Coordinator
Vasiliki Georgiadou , Green IT Amsterdam
3rd International Workshop on Energy Efficient Data Centres | Cambridge, UK | June 10, 2014
E^2DC 2014 2Cambridge, UK 30/06/2014
Project Identity Card
• Acronym: GEYSER• Full Title: Green nEtworked data centres as energY proSumerS
in smaRt city encironments• Starting Date: 1 November 2013• Duration: 36 months• EU Maximum financial grant: 2.979.000,00 €• Partners: 10• Country coverage: Italy, Greece, Ireland, Romania, Germany
Switzerland, The Netherlands
E^2DC 2014 3Cambridge, UK 30/06/2014
The Consortium
E^2DC 2014 4Cambridge, UK 30/06/2014
GEYSER Consortium
Academy/R&D
TUC, RWTH, ZHAW
Industrial Players:
ICT Players (ENG, SiLO)
Smart Grids/Data Centres
Technology/Solution Providers
(ABB)
Smart Energy Intelligent SaaS
Providers (Wattics)
End users
ASM Terni (Power DSO)
SARA (DC Operator),
GITA (Green IT/Smart City )
ENG (DC Owner/Cloud Service
Provider)
Builds on the legacy of the FP7 GAMES European R&D project
E^2DC 2014 5Cambridge, UK 30/06/2014
• Data centre energy efficiency is clearly becoming more and more an urgent issue to address for DC Operation and Strategic Managers– Need to focus on intelligent solutions addressing DC performance AND energy
management and optimization
• One solution to mitigate energy costs has recently been data/application migration trend towards free-cooled data centres located in Norway, Iceland or in the middle of some cold nowhere (“follow-the-least-energy cost” strategy)
– Major drawbacks• Customers security concerns
• Data networking costs are not negligible and affect the overall performance cost
• Only a financial-driven exercise
• No impact on the overall environmental sustainability and resource efficiency
• On the other hand a significant share of data centres are situated within urban contexts (Bank. Hospitals, public/private offices)
Background: Data centres ARE a local affair!
E^2DC 2014 6Cambridge, UK 30/06/2014
Smart City and Local Self-sustainable systems
• The trend is for managing and solving locally (at district/city levels) the major city challenges/requirements, reducing in this way value chain length and costs (es. Sustainable agriculture, zero waste, local energy supply systems reducing transmission losses)
• The long-term goal is to move forward towards sustainable locallyoptimized urban contexts
E^2DC 2014 7Cambridge, UK 30/06/2014
Local Sustainable Energy Supply Systems
• Rising shares of fluctuating Renewable Energy Sources (PV farms, Wind farms, biomass) are distributed along Low or Medium Voltage branches of the electricity networks
• However electricity networks traditionally are not specifically designed to accommodate such surplus power and, above all, the bi-directional power flow occurring when a surplus of power locally generated could not be consumed close to the generation point and should be transported somewhere
• The integration of the power generated by distributed RESs has posing serious stability and security problems to the power network operators
• Smart Grid has emerged in the last years as an effective organizational and technological paradigm to allow power distributors to proactively manage their actual power network, and accordingly defer significant investments for grid expansion
E^2DC 2014 8Cambridge, UK 30/06/2014
Smart grids: Flexible Management of Active Energy Resources (1/2)
E^2DC 2014 9Cambridge, UK 30/06/2014
Smart grids: Flexible Management of Active Energy Resources (2/2)
PeakShaving
Load Levelling
Power back to grid
Power back to grid
Optimized consumption
Optimized consumption
E^2DC 2014 10Cambridge, UK 30/06/2014
The state of the art…
• No active links among DCs and Smart Cities (no energy exchange)
• No or very few links with other DCs (no or very few IT load exchange)
E^2DC 2014 11Cambridge, UK 30/06/2014
Data Centre versus System-level Energy Efficiency
• Urban Data Centres are operated in uncoordinated way
• Their Energy efficiency has been so far addressed in an optimal, yet isolated way
• Urban Data Centres have a large yet largely unexploited potential to contribute to smart city local energy consumption optimization and smart grid optimized operation..
• ...provided that DCs would decide to come out from their “ivory tower”
• Energy efficiency should be addresses in a holistic way, by considering the interaction of Data Centres with the relevant stakeholders within urban contexts (electricity distributors, district heating operators, energy suppliers, smart city/district energy managers)
E^2DC 2014 12Cambridge, UK 30/06/2014
Towards a new active role for Data Centres
• DCs are expected to turn on into flexible energy players at the crossroads of Smart City and Smart Energy Grids
• DCs may become collaborative stakeholders within the framework of upper level smart city ecosystems
• DC Energy Efficiency should be managed in synergistic combined way with system-level energy efficiency
• DC may gain substantial (financial) benefits from the integration and collaboration with Utilities (Power Distributors, Energy Traders,...)
– Acting as Energy Prosumers matching utilities reqs may lower DC Energy Efficiency or Operational Performance (and potentially infringe SLAs with customers)
– However fair incentive sharing will reward DC at the extent to outperform penalties due to lowering of energy efficiency or operational performance
E^2DC 2014 13Cambridge, UK 30/06/2014
The GEYSER vision…
Think Global
Act Local
(GLOCAL)
E^2DC 2014 14Cambridge, UK 30/06/2014
Data centres as active connection hubs at the crossroads of Data and Energy Networks
E^2DC 2014 15Cambridge, UK 30/06/2014
The GEYSER approach for integrating Data Center in Smart grids and Smart City
• Data Centres as adjustable adaptive power consumers
• “Follow-the-sun” strategies– Use intermittent renewable energy sources when they are available
• Innovative Value Proposition and Novel service offering to – smart grids and utilities operators
• System services offering tailored to local balancing markets (Voltage regulation, reactive power, congestion management, load leveling, peak shaving
– Energy (power, heat) retailers/suppliers/traders and Smart Ditrict/City Energy Manager
• Energy consumption flexibility to optimize the global district/city energy consumption
• While...
– Optimizing IT load management matching utilities needs for services aimed at more efficient power network stability and security of supply
E^2DC 2014 16Cambridge, UK 30/06/2014
What we are doing
• A monitoring and control middleware framework to be deployed through a set of fully modular plug-ins to current data centres which will include:
• An optimized intelligent pervasive sensing and monitoring infrastructure, which combine techniques from intelligent processing (data mining, learning) and pervasive sensing aimed at:
– off-line energy load profiling
– on-line sensing in real time the actual energy consumption of IT infrastructure (servers) and facility infrastructure, and forecast the energy consumption in the coming time snapshots
• A real time data centre multidimensional optimization control tool, which will produce energy sub-optimal actuation strategies for the cooling subsystems by trading off energy demand of IT infrastructure and cooling, energy flexibility management, renewable energy source supply, network traffic increase over the net against penalties for potential violation of SLAs.
• A smart grid real time green energy marketplace, which includes a smart districts energy management broker and a smart energy (both power and heat) grid simulator.
E^2DC 2014 17Cambridge, UK 30/06/2014
The GEYSER Framework High Level Architecture
StorageGeothermal
Energy
Renewable Energy Sources
Processing Networking
IT Energy Sinks
PV Windmills
Non-Renewable Energy Sources
UPS Electricity Generator
Non-IT Energy Sinks
HAVC Buildings
Non-IT Energy SinksMonitoring & Control
IT Energy SinksMonitoring & Control
Renewable Energy SourcesMonitoring & Control
Non-Renewable Energy Sources Monitoring & Control
Real-time Energy Monitoring/Sensing & Adaptive Control Subsystem
Smart Grid/Smart City Interface Subsystems
Data Centre Adaptive IT Load Migration Broker
Data CentreEnergy Budget Broker
Continuous Monitoring, Feedback & Adaptive Control
Customers QoS &SLA Negotiation Broker
Energy-Budget Situational Awareness
Closed LoopControl for IT Load
Optimization
Closed LoopControl for Energy
Optimization
Real-time Multi-criteria Energy Optimizer
DC Real-time Multi-criteria Energy Efficiency Optimization
Monitoring & On Demand Adaptive Control
Adaptive IT Load Migration Broker
Network of DCs Energy Budget Broker
Customers QoS &SLA Negotiation Broker
Network of DCs Multi-criteria Energy Optimizer
Network of DCs Multi-criteria Energy Efficiency Optimization
Data Security & Privacy
Real-time Energy Marketplace Broker
Continuous Sensing & Control
Smart Grid/Smart City Integration
E^2DC 2014 18Cambridge, UK 30/06/2014
DC level local optimizationDC level local optimization
• monitor, control, reuse and optimize their overall ENERGY consumption & production, from renewable energy sources in particular, within the framework of a unified representation of energy
Smart Grid & Smart City level global optimizationSmart Grid & Smart City level global optimization
• actively involved as energy prosumers within a smart city green energy marketplace
Virtual Data CentreVirtual Data Centre
• positioned at the forefront of a distributed computing architecture in a cloud-oriented networked scenario
Enabling The Next Generation of Data Centres
E^2DC 2014 19Cambridge, UK 30/06/2014
Our Approach: 4 Scenarios…
Scenario "10"-Workload
Federated Data Centres
Scenario "10"-Workload
Federated Data Centres
Scenario "11"-Workload and
Energy Federated Data
Centres
Scenario "11"-Workload and
Energy Federated Data
Centres
Scenario "00"-Single Data
Centre within a Smart
City/District
Scenario "00"-Single Data
Centre within a Smart
City/District
Scenario "01"-Data Centres as
coordinated energy elements within a Smart
City/District
Scenario "01"-Data Centres as
coordinated energy elements within a Smart
City/District
Coordinated Energy Management
IT Workload Relocation
E^2DC 2014 20Cambridge, UK 30/06/2014
Energy (Power, Heat) Trader
DSO
Network Technical
constraintsmgmt
Smart City Energy Mix
Demand
Powerrequest
Heatrequest
Marketplace
Networked Data Center IT Workload
adaptation
Bid Placement
Urban Data Center
Heat
Power
GEYSER - compliant DC for Smart City
E^2DC 2014 21Cambridge, UK 30/06/2014
DSO
Urban Data CenterLoad
FlexibilityAggregation
Local BalancingMarket
Networked Data Center IT Workload
adaptationBuilding prosumer
Smart districtNode
GEYSER – compliant DC for DSO
E^2DC 2014 22Cambridge, UK 30/06/2014
The GEYSER Data Model
GEYSER does not reinvent the wheel but• builds upon EU FP7 GAMES data model• integrates with EU FP7 COOPERATE Neighbourhood Information Model
DC Internal ContextDC Internal Context
DC ComponentsDC Components
Energy ConsumptionEnergy Consumption
Energy ProductionEnergy Production
DC Energy Efficient Optimization ActionsDC Energy Efficient
Optimization Actions
DC Energy Efficient Indicators
DC Energy Efficient Indicators
DC External ContextDC External Context
E^2DC 2014 23Cambridge, UK 30/06/2014
DC Energy Consumption Components
DC Energy Consumption Components
Non-IT Components
Non-IT Components
FacilityFacility
Heating, Ventilation, Air Conditioning
Heating, Ventilation, Air Conditioning
Heat Recovery InfrastructureHeat Recovery Infrastructure
LightingLighting
BuildingBuildingBuilding Energy
Management SystemBuilding Energy
Management System
IT ComponentsIT Components
IT EquipmentIT Equipment
Simple ComponentsSimple Components
ServersServers
StorageStorage
NetworkNetwork
Power Distribution Unit
Power Distribution Unit
Combined Components
Combined Components
Server ClusterServer ClusterApplicationsApplications
The GEYSER Data Model – part 1
E^2DC 2014 24Cambridge, UK 30/06/2014
DC Energy Production Components
DC Energy Production Components
Green Energy SourcesGreen Energy Sources
PVPV
WindWind
GeothermalGeothermal
Brown Energy SourcesBrown Energy Sources Diesel GeneratorDiesel Generator
On-site Energy Storage Components
On-site Energy Storage Components
UPSUPS
The GEYSER Data Model – part 2
E^2DC 2014 25Cambridge, UK 30/06/2014
DC EE Optimization Actions
DC EE Optimization Actions
Energy Consumption
Energy Consumption
Non-IT ResourcesNon-IT Resources
Dynamic adjustment of temperature, humidity, and
lighting
Dynamic adjustment of temperature, humidity, and
lighting
Heat Storage (pre-cooling) and release
Heat Storage (pre-cooling) and release
UPS-based, compressed air storage systems, flywheel, ice
storage tanks
UPS-based, compressed air storage systems, flywheel, ice
storage tanks
IT ResourcesIT Resources
Load Management
Load Management
Energy aware load
management
Energy aware load
management
Dynamic Power
Management
Dynamic Power
Management
Turn on/off DC components
Turn on/off DC components
Energy ProductionEnergy Production
Maximise utilization of green energy producedMaximise utilization of green energy produced
Shift delay tolerant workload to match the
renewable energy production peak
Shift delay tolerant workload to match the
renewable energy production peak
The GEYSER Data Model – part 3
E^2DC 2014 26Cambridge, UK 30/06/2014
DC Monitored Parameters
DC Monitored Parameters
Energy / Power consumption (loads)
Energy / Power consumption (loads)
ITIT
CoolingCooling
TransformerTransformer
LightingLighting
BuildingBuilding
Energy produced locally (electricity or
heat)
Energy produced locally (electricity or
heat)
Heating recoveredHeating recovered
Power demand shiftingPower demand shifting
CO2 emissionsCO2 emissions
PerformancePerformance
Economic performanceEconomic performance
Applications performanceApplications performance
The GEYSER Data Model – part 4
E^2DC 2014 27Cambridge, UK 30/06/2014
Data Model integrated with EU EEB Model via FP7 COOPERATE model
E^2DC 2014 28Cambridge, UK 30/06/2014
The System Architecture: a possible pilot site instance
GEYSER Platform
Wattics API
BMSDC Infrastructure
Equipment(power meters, CRAHs,…)
OPCServer
OPCClient
History DB
History DB
Open Source
GEYSER DB
Open Source
Optimization EngineCloud
OPC SNMP
Display
WebPage
ModbusTCP
Interface
Wattics DBInsights
Wattics DBInsights
WatticsODBC InterfaceODBC Interface
Energy MarketWeather
Forecast
Open Source
Communication Layer
DC IT Equipment(servers,…)
ABB Decathlon
E^2DC 2014 29Cambridge, UK 30/06/2014
The GEYSER Simulation Environment
• All components related to data centres and smart cities are to be represented as models
• Hardware In the Loop: different components in the simulation can be replaced with real hardware:
Hot Aisle
Ch
iller
Ch
iller
Racks
Racks
Sensors
Hydraulic Interface
Thermal Interface
Data Centre Simulator
Smart City Simulator
Grid Simulator
Simulated Onsite Energy Generator
Electrical Interface
DC-Control System
Energy Market
• Real time testing of the complete data centre and interaction with the Grid
• Detailed testing of the data centre operation and its components with a limited model of the grid
• Power Hardware in the Loop of the efficiency of the cooling of one or more computational racks
E^2DC 2014 30Cambridge, UK 30/06/2014
GEYSER Main Innovations
• New generation of DCs as key players in the smart energy city and/or smart grids/DSO
• Considering DC as a stakeholder exchanging ENERGY, including electricity AND heating/cooling
• DC-level optimized management of energy, including DCs Renewable Energy Source powered or with green energy contracted at the meter
• Comprehensive set of Local Balancing Services offered to DSO/electricity operator (e.g. Ancillary services like voltage regulation, demand response/consumption flexibility), going beyond Demand Response
• DC participating to the Optimized ENERGY management of a Smart District/Smart City by Energy provisioning to the Local Energy Marketplace
• Cooperative business models (and enabling IT platform) for nurturing DC cooperation among all the DC ecosystem stakeholders (DCs, energy providers, DSOs, DC End users) by fair incentive sharing
• Optimized ENERGY green energy usage as “rational” behavioural strategy of DCs participating to Smart City real time green energy-led marketplaces
E^2DC 2014 31Cambridge, UK 30/06/2014
The journey has just begun...fancy for more?
http://www.geyser-project.eu/,
http://www.linkedin.com/groups/Networked-Data-Centres-Smart-Grids-7485057,
or just contact us
Any questions?
Thank you for your attention!