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Big Data Analysis forEnergy Internet
Junwei CaoResearch Institute of Information Technology,
Tsinghua UniversityTsinghua National Laboratory for Information
Science and TechnologyJuly 20, 2017
IoT & Clouds & Big Data
Future Infrastructure
Energy Internet
Big Data Applications
Outline
Cyber-Energy Infrastructure
Conclusions
Computing Infrastructuralization
Cloud Security
Performance
Evaluation
Physical Resources
- - ..
IaaS
PaaS
SaaS
Resource Scheduling
PrivateClouds
I/O Servers Storage Networking
Virtualization
Encapsulation
Resource Description
Resource Monitoring
SchedulingFault-
toleranceMonitoring
App Enabling
App Composition
Apps
Security
Trust
Privacy
Reliabil
ity
Scalability
Metrics
Hybrid Clouds
Future 5G InfrastructureFuture 5G wireless communication can be enabled by cloud platforms.
Future Network Architecture
Services = Data+Trans.+
Storage+Computing
Radio tower
Sensors
Clouds
Future networks will be a
pool of services.
From Yunjie Liu
Data Center
Cloud+Big Data
Data Center
Data Center Data Center
Mobile Device
Terminals
Mobile Device
Mobile Devices
Sensor Sensor
Sensor
InformationInfrastructure
Future InfrastructuresCyberinfrastructure – NSF’s
vision of 21st century’s infrastructure
Transportation
Telecommunication
Power grids
Internet
• Complex systems• Infrastructures are results of
technology innovation and industrial revolution: water, gas, heating, power grid, transportation……– Sources：Centralized– Channels: professional
managed– Consumers: Convenient、
Cheap、Safe、Reliable• 21st Century’s new
infrastructure?– Cyber-Enabled? (NSF)– Info-Centric? (Berkeley)
Cyberinfrastructure (CI) of US NSF
Cyberinfrastructure links computing
systems, data storage systems,
advanced instruments and data
repositories etc.by software and
networks to improve research
productivity and enable break
throughs in other fields .
The challenge of cyberinfrastructure
is to integrate relevant and often
disparate services to provide a useful,
usable, and enabling framework for
research and discovery, which is
characterized by broad access and
“end-to-end” coordination.
• Functions
• Challenges
Interactingnetwork
Multidimensional complex system
Cyber-Physical Systems (CPS)
Integrated Computing
Network distribution
Physics
environment
a) Fusing of computing
resources and physical
resources
Dynamic control
Real-timeperceiving
Information services
b) Fusing network into the
existing infrastructure without
destroying or even disturbing the
physical facilities and computing
logic
Any software or physical
structure can dynamically join
into the system without being
suspended or shutdown
• Fusion
mechanism
• Dynamically access
Conventional Electric Grid
Load IPS
Source
IPS
energy subnet
Intelligent
Power Switch
Future IT Platforms
Berkeley – Information Centric Energy Infrastructure
• Interaction
Suppliers, loads and
energy storages can
interact with each other
in the subnet• Forecastin
g and
adapting
• Fusion
Information overlays on the
energy distribution system
Infrastructures — Centralized and Integrated
Conventional infrastructure: transparent resource accessing
Power grid vs. grid/cloud computing
Infrastructures — Decentralized and Coordinated
Fusion of resources and consumers, decentralized, share, cooperate
Micro-grid vs. Web2.0 and social networking services
Power-aware Computing (since 1994)
Power Supply Issues for Data Centers (since 2005)
• Why are IT companies concerning about energy solutions? (Google, Apple, Microsoft, Facebook, Ali, …)
The world #1 supercomputer from China (2016-
)
From Internetto Energy Internet
？？？
1960 1970 2000 2011
Special Purpose Electronic Network
Computer Local-Area Network
DARPA-Net:• IP • TCP
1980 1990
Internet
World Wide Web
Global Energy Internet
Energy Apps
Energy Internet
2015
Distributed Energy Systems/Renewable Energy/Energy Storage
Energy Microgrid
Energy Internet ArchitectureEnergy Internet can be concluded as an internet based WAN for information
and energy fusion. It takes the electrical grid as backbone network and the
microgrid or distributed energy sources as local-area network. With the
integration of information and energy, bidirectional flow and dynamically
balancing of energy is achieved.
“Backbone”
“WAN”
“LAN”
Essentials of Energy Internet
Sharing
Inter-
connection
Openness
Peer-to-
peer
InfrastructureEnergy Internet: an open and peer-to-peer infrastructure for energy exchanging and sharing
CyberInternet of Energy: information exchanging to support energy management and scheduling
ApplicationsDES, microgrids, DSM, active power distribution, FACTS, etc. on top of cyber-energy infrastructure
Business modelsWith support of Internet thinking and Internet finance, new business models are emerging
PoliciesEnergy Internet is considered as the key technology to enable energy revolution in China
Understanding Energy Internet
DC
ACTransformer
Backbone
Energy Router
Energy Router
Energy Router
Energy Internet
DC
ACData Center
Sensor
SensorTransformer
Data Center
Energy Router
Clouds+Big Data
Cyber-EnergyInfrastructure
From Smart Grid (Cyber-Energy Flows) to Energy Internet (Cyber-Energy Infrastructure)
• Data centers require power supply from energy routers• Data centers and energy routers require both energy storage• Energy routers require data monitoring, storage, and analytics for
energy optimization, which can be provided by data centers
Microsoft：Data Plants
AC
Scenarios of future cyber-energy infrastructure
Communication
DC
Heating
Gas
Microgrid
Power Grid
Data Center
Energy Router
DES(CCHP) Smart Community (DSM)
Gas Generation
Cooling
Business and Residence
Wind Generation
Solar Generation
Energy Storage
Loads
EV
EnergyRouter
Smart Metering
Energy Saving
Demand-SidePower Quality
Grid-Side Power Quality
Operation Center
Load Cloud
Policies
Mobile Device
Situation Awareness
Heating
Big Data Analysis for Energy InternetReal-time Power Flow Measurement (UIPQ(t)) Data Clouds Energy Management Energy Trading Visualization
Data Cleaning
Data
Integration
Data Warehouse
Data Processing
Data Mining
Deep Learning
Big Data Applicationsfrom Load Modeling to Load Aggregation
曹军威 | [email protected]
24
500kV Power Grid
DongguanLoads
ShiPai0H DongG0H ……
DER
……
500 kV
220 kV
110 kV
广州负荷区
DER
深圳负荷区
DER
Partially Measured
Other Loads
……
Bottom-up Aggregation
曹军威 | [email protected]
25
ITI（CBEMA）Curve（Revised 2000）ITI（CBEMA）幅值——时间分布图
（深圳马坳中心站2010年5月7日至2012年11月27日）
Duration in Seconds（s）干扰时长（以秒为单位）
Perc
ent
of
Nom
inal V
oltage（
RM
S o
r P
eak E
quiv
ale
nt）
额定电压百分比（
RM
S或者峰值等效值）
事件总数: 849
110: 245; 220: 604
低于额定电压事件: 825
110: 244; 220: 581
高于额定电压事件: 24
110: 1; 220: 23
低于ITI事件: 721
110: 199; 220: 522
高于ITI事件: 24
110: 1; 220: 23
10-3
10-2
10-1
100
101
102
0
25
50
75
100
125
150
175
200
225
250
110KV
220KV
Big Data Applicationsfrom Power Quality to Power Experience
曹军威 | [email protected]
26
G
G
G
G
G
G G
G
1 24
23
2
22
3
9
11
51
25 26 12
52
27
6
14
20
21
19
4
7 8
30 31 33
5
18 34
50
16 29
1328
Big Data Applicationsfrom Voltage Stability to Fault Diagnosis
曹军威 | [email protected]
28
Personalizedrecommendations
Hot sale schemes
E-coupons
Big Data Applicationsfrom Energy Trading to User-Centric
Big Data Applications – Energy “Brain”
曹军威 | [email protected]
29
Output
Layers
Hidden
Layers
Input
Layers
With development of deep learning
algorithms and computing and networking
capability, AI is breaking through to solve NP
hard problems. There are potentials that
autonomous energy/power scheduling could
be achieved.
Conclusions
• National demonstration engineering projects on Energy Internet have been announced by National Energy Administration of China.
• Ongoing research is focused on energy routers, big data and AI applications for energy/power.
• This is an effort of a cross-disciplinary team, including faculty members from EE, CS & RIIT at Tsinghua University.
Fusion of cyber & energy/power infrastructures, technologies and applications are just starting!
