energy informatics: overview - universitetet i oslofolk.uio.no › yanzhang › in5410-2020 ›...
TRANSCRIPT
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Energy Informatics: overview
Yan Zhang
Professor, University of Oslo, Norway
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Learning Objectives
Throughout this lecture, it is aimed for the students to be able to
• Learn the basic concepts in the new field of Energy Informatics
• Understand the emerging ICT (Information & Communication Technologies) challenges related to electric vehicles as an example
• Understand ICT problems in related scenarios through examples, including sharing economy, smart buildings, renewable energy systems, intelligent transport, and smart city
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Industry Invited Talk Today
• Speaker: Jan Bråten, Chief Economist / Sjeføkonom, Statnett
• Title: Power Market: The Green revolution and the role of ICT
• Statnett: Statnett is Norway’s national main grid owner and operator
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Outline
• Energy Informatics
– Definition and scope
• Electric Vehicles (EV) as an example
– Concepts
– Typical ICT problems related to EV
• Computer engineering & science problems in sharing economy, smart buildings, renewable energy sources, intelligent transport, smart cities
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“Energy Informatics” is NOT about the traditional concepts
Energy Informatics
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“Energy Informatics” focuses on state-of-the-art computer science for sustainable future energy systems
Energy Informatics
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ChinaGermany
USA
Energy Informatics alternative terms: Internet of energy; Energy Internet
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Energy Informatics: definition
A new field covering the use of ICT (Information and Communication Technology) to address energy challenges
8
Energy areas• Smart grid; smart energy networks• Smart building• Smart cities• Water systems• Oil/Gas systems• Transport systems,• Electric vehicles• Vehicle-to-Grid (V2G) systems• PV systems• Wind systems
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Energy informatics: scope
Etter Goebel et al, Energy Informatics: Current and Future Research Directions, 2013
Energy Efficiency Renewable Energy Supply
Smart Energy-Saving Systems Smart Grids
Transportation
Systems
Data
Centers
Commercial
Buildings
Residential
Buildings
Factories
Power
Systems
Electric
Mobility
Renewable
Energy
Electricity
markets
Energy
Storage
Themes
Goals
Use cases
Database &
Big DataHCI
Mngt Info
Systems
Distributed
Systems
Information
SecurityOptimization
and Control
Embedded
Systems
Machine
LearningNetworking
Behavioral
IS Research
Middleware
SystemsEconomics
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ELECTRIC VEHICLES AS AN EXAMPLE
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Electric Vehicles (EV)
Charging Station
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In 10-15 years, only Electric vehilces will be sold over theworld
• Norway: Stoppe sellin bensin- og dieselbiler by 2025
• Germany: all new cars must be electricby 2030
• China: all private cars will be electricvehicles by 2030
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An important computer engineering problem: where and how many charging stations should be deployed?
Machine learning for traffic flow prediction: how many cars pass this position during 8:00-9:00?
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Another problem: how to protect your privacy?
• Self-driving cars, Tesla’s autopilot driving are the future
• Q: how does Tesla’s autopilot system build?
– “Tesla’s sensors are constantly recording information about its environment and how the driver is navigating through it.” (qz.com)
• This is typical privacy intrusion of modern digital life.
• EU GDPR (General Data Protection Regulation): July 8, 2019, British Airline faces 183Million GBP fines
https://www.tesla.com/blog/most-peculiar-test-drive
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MORE ICT CHALLENGES IN ENERGY SECTORS
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Sharing Economics: Selling your power to neighbors
• Brooklyn Microgrid: In your house roof, you have solar power. The power can be used by yourself. If you are not able to use all power, you can sell to your neighbors.
• A typical computer engineering problem: how to decide the energy selling/buying price?
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Energy Sharing: Selling your power to neighbors in Norway
• Halden: a small town at the border between Norway and Sweden
Halden
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Smart Buildings
• A computer has an operation system, e.g., Windows, iOS
• Smart building has its own “Operation Systems” to monitor and management the infrastructure
• A typical computer engineering problem: how to adjust the temperature in the building with both energy-efficiency and people’s comfort considerations? machine learning method is very promising!
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Self-driving Cars and Intelligent Transport Systems
• Transport systems use power
– Electric vehicles
– Signal
– Road infrastructures
• Computer science problems
– Information exchange for accident avoidance
– Information exchange for powermanagement
https://robotik.dfki-bremen.de/en/research/robot-
systems/eo-smart-connecting-1.html
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Wind Power
• Equinor (originally Statoil) puts enormousinvestment in offshore wind power.
• Wind power is highly dependent onweather. Machine learning and Data Analytics for wind power forecast is an important computer science problem
future
history data𝒕 𝒕+4848hours
??Wind speed in Gardermoen
https://www.equinor.com/en/what-we-do/new-
energy-solutions/our-offshore-wind-projects.html
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Thank you!