1. Leveraging Smart System Technologies in National Energy Data Systems: Challenges and Opportunities
Eric Masanet
Head, IEA Energy Demand Technology Unit
EEG Research and Matchmaking Conference Washington, DC, 3-Nov-2016

2. Typical datasets can include:
National energy data systems: overview
Typical datasets can include:
Energy balances
Source:

3. National energy balances
Source:

4. Typical datasets can include:
National energy data systems: overview
Typical datasets can include:
Energy balances
Energy efficiency indicators  
Source:

5. National energy data systems: examples
Source: IEA (2014). Energy Efficiency Indicators: Essentials for Policy Making.

6. Typical datasets can include:
National energy data systems: overview
Typical datasets can include:
Energy balances
Energy efficiency indicators  
Energy-related environmental emissions   
Source:

7. National energy data systems: examples
Source: (EA (2016)

8. Typical datasets can include:
National energy data systems: overview
Typical datasets can include:
Energy balances
Energy efficiency indicators  
Energy-related environmental emissions   
Public energy technology research, development, and demonstration (RD&D) investments
Source:

9. National energy data systems: examples
Source: IEA (2016)

10. Typical datasets can include:
National energy data systems: overview
Typical datasets can include:
Energy balances
Energy efficiency indicators  
Energy-related environmental emissions   
Public energy technology research, development, and demonstration (RD&D) investments
Fuel prices and taxes
Development indicators (e.g., energy access)
With much variation in comprehensiveness and quality from country to country!
Source:

11. Sound energy policy requires sound data
Myriad end uses in the policy stakeholder system
Understanding dependencies, supplies, and security
Understanding final demand nature and trends
Modeling and analysis of policies and technologies
Guiding R&DD programs and technology investments
Tracking: energy, climate, and development progress
UN sustainable development goals (SDGs)
Paris Agreement GHG emissions commitments and reporting
Green growth indicators
Effectiveness of policies
Impacts of investments

12. Data disaggregation vs. requirements
Source: IEA (2014). Energy Efficiency Indicators: Essentials for Policy Making.

13. Disaggregation and progress tracking
+15%
-35%
Index: 1990=1. Data for IEA18 (Australia, Austria, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Netherlands, Norway, Slovakia, Spain, Sweden, Switzerland, UK, USA). Source: IEA energy efficiency indicators database. TC: Temperature Corrected.

14. Greater insights via data matching
Percentage change in median gas consumption by UK property type
Structure of domestic NEED
Source: UK DECC (2016). Summary of analysis using the National Energy Efficiency Data-Framework (NEED)

15. Dimensions of robust national data systems
Possible challenges in developing countries
Energy within overall policy priority
May be not enough / not in synergy with other objectives
Overall data governance
Lack of trust / lack of legal framework /lack of enforcement
Resources for energy statistics
May be poor / ineffectively allocated across areas / competing areas for statistics
Institutional arrangements/ flexibility
Structural inefficiencies/unawareness of other work/competing priorities for different stakeholders/multiple data requests/lack of data sharing
Data collection practices
Not effective, well designed/lack of training,/lack of expertise/not based on innovative tools/lack of resources
IT infrastructure
General availability (e.g. internet)/lack of expertise/lack of resources
Methodologies
Unawareness of / discrepancy of national system with international methodologies/lack of training

16. Smart systems: an enabling data resource?
Smart Homes
Smart Irrigation
Smart Grids

17. Smart system barriers and opportunities
Literature is sparse on smart systems for national data
Key opportunities:
Major synergistic benefits with smart system deployment
Unprecedented disaggregation and data matching, leading to new insights on energy system trends and opportunities
Data collection efficiencies with proper upfront protocols
Key challenges and barriers
Lack of smart system data standards
The “big data” problem
Privacy and confidentiality
Complexity and uncharted territory
Cost and infrastructure

18. Priority research opportunities
A roadmap for leveraging smart systems in national energy data systems
Develop and propose a taxonomy of components, institutions, stakeholders, and information flows
Identify opportunities and technical data characteristics for maximum synergies
Identify major barriers (technical, economic, legal, behavioral, and policy)
Propose priority actions, policies, and timelines for key system stakeholders
Tailored advice for developed and developing economies

19. Priority research opportunities
Technical assessment of smart metering and remote sensing technologies in the developing country context
Systematic review of technical needs
Need for predictive maintenance
Low-cost options for data collection and reporting
Need for interoperability with legacy equipment
Assessment and design of standards for metering and sensing equipment in developing economies
Engagement with major standards organizations (IEC, ISO)
Match needs to a review of readiness in EEG countries of focus

20. Priority research opportunities
Enable improved capacity for robust national data systems, particularly in developing countries
Identify major technical and non-technical barriers limiting the development of data collection and use
Identify and share good practices for data collection and use, with particular focus on energy demand
Workshops, training, interviews
Focus on opportunities for leveraging technologies
Propose priority actions in specific country contexts
Reports/white papers to synthesize outcomes for knowledge transfer

21. Thank you! And thanks to my IEA coauthors:
Duncan Millard, Head, IEA Energy Data Centre
Luis Munuera, Smart Grids Technology Lead
Roberta Quadrelli, Head, Energy Balances, Prices, Emissions, Efficiency, IEA Energy Data Centre