Diese Präsentation wurde erfolgreich gemeldet.
Die SlideShare-Präsentation wird heruntergeladen. ×

Session 3 - Presentation by Luis Munuera

Weitere Verwandte Inhalte

Weitere von OECD Environment

Ähnliche Bücher

Kostenlos mit einer 30-tägigen Testversion von Scribd

Alle anzeigen

Session 3 - Presentation by Luis Munuera

  1. 1. © OECD/IEA 2015© OECD/IEA 2015 New data sources in energy systems Green Growth and Sustainable Development Forum Luis Munuera, PhD Energy Technology and Policy Division International Energy Agency
  2. 2. © OECD/IEA 2015 Reaching 2°C requires a drop in the carbon intensity of energy, which has been stable for 50 years Data from Boden et al. (2013), Smil (2010) and IEA (2015)
  3. 3. © OECD/IEA 2015 The energy sector innovates slowly… Data from Smil (2010) and IEA (2015), 2DS scenario
  4. 4. © OECD/IEA 2015 …and electricity systems are particularly late adopters % of distribution grids older than 40 years
  5. 5. © OECD/IEA 2015 Alternative and distributed energy is accelerating  Decentralised energy taking off – and geography shifting  Non-OECD countries overtake distributed PV in OECD in 4-5 years  Global EV deployment close to on track for two-degree pathway
  6. 6. © OECD/IEA 2015 Batteries Smart meters Smart metering becoming mainstream, residential-scale batteries are next Consumers increasingly looking for more control, insight on their energy use
  7. 7. © OECD/IEA 2015 Future energy systems are more diverse, dynamic, localised First generation smart metering, uncontrollable DG Second generation smart metering, smart charging, smart DG Distributed ‘intelligence’ with local control, local balancing/markets Existing data in standard operations Behavioral, demographic, smart home, internet of things IT/OT mainstreaming (data volume x2 every 2 years) Today ~3 Zb
  8. 8. © OECD/IEA 2015 Future energy systems are more diverse, dynamic, localised First generation smart metering, uncontrollable DG Second generation smart metering, smart charging, smart DG Distributed ‘intelligence’ with local control, local balancing/markets Existing data in standard operations Behavioral, demographic, smart home, internet of things IT/OT mainstreaming (data volume x2 every 2 years) Today ~3 Zb Physical network layer: Improved operations and grid planning EWE, Germany
  9. 9. © OECD/IEA 2015 But systemic gaps along the innovation chain need to be addressed  Institutional and technical: How to accelerate demonstration and deployment for regulated, built-up systems?  Only in Europe, 107 kilometers of distribution networks... • Overseen by 2,400 DSOs, 200 of them with more than 100k customers.  Centralised infrastructure, centralised energy markets, not standardised
  10. 10. © OECD/IEA 2015  Behavioral: How will consumers adopt and react to technologies that bring them closer to their energy use?  Relationship between energy utilities and telcos?  Data security  Data privacy, access and ownership But systemic gaps along the innovation chain need to be addressed

Hinweis der Redaktion

  • Prosumers and positive energy communities
    Integrate EVs
    A lot more information on what is happening in the energy system -> an increase in orders of magnitude
    But we know energy is one of those sectors where you can’t rip everything out and start over. Difficult and costly to physically expand grids
    How does this interact in practice?
  • Key triggers to data growth
     Improve the reliability and resiliency of electric grid  Optimize the asset management and operations costs  Share the data/intelligence for improved decision making  Integrate legacy systems for improved data flow  Improved data analytics and enterprise intelligence
    Situational Awareness/Predictive Forecasting
  • Safety: with radio frequency communication layer, North America customers are becoming reluctant about installation of Smart Meters, which they consider being a risk for their health. Rightly or wrongly (depending on the technology used), this concern would have to be taken into account for Internet of Things generalization.
    Security: Whether using encryption for data exchanges or avoid any system intrusions to access to remote controls (disconnect Smart Meter), security is a major issue for massive deployment of Smart Meters. Internet of Things will be confronted to this major concern for example when health or Smart Cities services rely on the devices.
    Privacy: Data access and use of the data collected are subject to numerous debates regarding Smart Meters: you may deduct when you are eating, whether you are at home or not, etc ... The data is available, you simply need to interpret it. Internet of Things will have to provide answers to this question in order to avoid rejection in some cases.
    Roles and responsibilities have to be clear
    Standardisation is a key factor for success – Automation -> less faults / human mistakes – Neutrality – Costs-efficiency • Access to data has to be easy and neutral for all stakeholders – Of course by ensuring data privacy and security

×