Toward Energy Data Platform in Korea

Transcription

1 Toward Energy Data Platform in Korea 최준균 (Jun Kyun Choi) Korea Advanced Institute of Science and Technology (KAIST)

2 Contents 1 ` Market Trends of Cloud Computing and IoT 2 ` Platform Revolution of Energy Industry 3 ` (Appendix) Toward Energy Eco-System 2

3 Market Trends of Cloud Computing and IoT

4 Future Eco-Society Human World Physical World Future Social Infrastructure 4

5 Technical Challenges for Future Social Infrastructure Internet of Things (The ongoing convergence of evolution of devices) Cloud Computing (Deployment of large shared infrastructure) Big Data (Accumulation of data from sensors and social networks) 5

6 Future Knowledge Convergence Infrastructure Current 1st Stage 1st Stage ICT Convergence Stage Vehicle Robot Industry Ship Energy Health 2nd stage Creative Convergence Construction Machine Military Textile Air 2nd Stage Human & Health care Nano devices, computers & Robotics Huge Complex Industrial systems IT Cyber Reality & Future Human Interface Security & Trust User-centric personal health care technology 3rd Stage Creative Eco-Convergence g Autono System ueco-city U-Eco building & city Intelligent Car, Robot Knowledge Media Self-organized Lifelong education Services Governance Personal & social security Intelligent Disaster Prevention Technology Key Technology Creative Technology Self-assured/Self-organizing IT Vehicle Technology Collective and Collaborative computing Technology Future City and Environment Technology Intelligent Service Robot Technology Personal Assistance and Self-learning Technology Virtual reality technology ICT Concepts Media security and Knowledge Science Technology Future Network and Computing Infrastructure Self-organizing Energy Eco-system Technology (Conformity) (Intelligence) (Resonance) All Connected Things All Computerized Things All Conscious Things 6

7 Cloud Computing Market 7

8 Global Data Volumes and Storage Costs 8

9 Trends of Cloud Computing Costs 9

10 Cost Prediction of Storage and Memory 10

11 Trends of Cloud Data Center 11

12 Evolution of Distributed Computing 12

13 Cost Declining of Cloud Computing 13

14 Overall Costs of Cloud Computing Platform (ref) 14

15 Re-allocate ICT Expenditures Most companies spend roughly 80% of their ICT budget on operations and maintenance. 20% 50% Labor Expense 80% 50% Other Expenses DATACENTER COSTS Plan 5% Deploy 10% Operate 25% Support 10% Facilities 7% Network 11% SW 9% HW 23% Cloud Computing reduces Labor costs Cloud Computing reduces Facilities, Network, Hardware, Software maintenance costs

16 IT Efficiency Challenges Servers Encry ption Tier 1 Tier 2 Clients Storage Apps CLOUD SERVICES 16 Software Deployment License Tracking Managed Mobility DATA MANAGEMENT Software Deployment Licenses tracking Managed Mobility Workf low Chang e Mgmt SECURITY/ STANDARDIZATION Change Management Drive Encryption/ End-Point Protection Windows/Linux Automation/ Scripting Standards Tier 3 STORAGE OPTIMIZATION Tiered Storage Data Deduplication Storage Archiving VIRTUALIZATION Server Consolidation Storage Consolidation Desktop Consolidation On-Demand IT Infrastructure Reliable/Secure Scalable/Flexible Pay for what you use Free Staff Time Application Commoditization Cost Savings SMB to Enterprise Solutions

17 Advantage of Cloud Computing Without Cloud Computing With Cloud Computing Enhanced availability On the network Standardized services Workload A Workload A Automated management Workload A Workload A Workload B Workload C Virtualized resources Service Management Service Management Service Management Hardware Software Storage Networking Service Management Rapid scalability Location independent 17

18 12 TeraFlops GPU Processing Power 18

19 Pascal GPU Module at $1000 s (2016) 19

20 2 Petaflop AI Supercomputer at $399,000 (2018) 20

21 Trends of IoT Market

22 Trends of IoT Market

23 Cost of IoT Modules 23

24 Wireless IoT Modules 24

25 IoT Sensor Modules Multi-sensor module WiFi module Arduino compatible LoRa Module Bluetooth modules Raspberry PI module Intel Edison module Intel Curie module 25

26 Wearable IoT Devices 26

27 Samsung IoT Modules 27

28 Platform Revolution of Energy Industry

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30 Future Hardware and Software Ecosystems How to handle several billions of hardware components and devices? How to arrange several billions of software and business platforms? (Key Strategies) cope with heterogeneous and complex eco-environments 30

31 Smart City Eco-System 31

32 Concept of Cyber Physical System (CPS) 32

33 CPS: Intelligent System for Future Eco-Society Intelligent Systems will exist in environments they sense and perceive, and from which they learn and continually act to achieve their objectives. Intelligent and Self-Learning Computing System 1. sense the real-world environments, 2. perceive the world using world models, 3. adapt to different environments and changes, 4. learn and build knowledge, and 5. act to control their environments. 33

34 Industrial Sensing Intelligence on CPS 34

35 Concept of Smart Grid Network (ref) 35

36 Artificial Intelligence of Smart Grid Traditional Smart Grid Geographical energy delivery and demand response system Limited to SCADA-based electric power management Future Smart Grid Cloud-based Artificial Intelligence Real-time control and intelligent management of distributed and unexpected renewable energy sources Self-healing and predictive operation and management Opportunities of grid security and customer choice Cloud-based AI/ML Algorithm ICT Network Smart Grid Network 36

37 Conceptual Model of Industry

38 Energy-based New Convergence World Electricity Energy Information Technology Telecommunications (Power Sector + Telecommunication) Renewable Automobiles Construction Home Appliances Convergence of Multi-Industries 38

39 39