Page 37 - UN Executive Briefing on Unlocking the potential of virtual worlds and the metaverse for the Sustainable Development Goals

UN Executive Briefing on Unlocking the potential of virtual worlds and
the metaverse for the Sustainable Development Goals

trained models and optimization algorithms; (3) optimizing control of energy storage by using
ML that accounts for storage capacity, including building thermal storage capacity, forecasts
load profiles, and manages charge-discharge processes; and (4) decreasing peak energy
consumption (at design phase). The areas for further improvement include implementation
of reinforcement learning of control strategies to take into account all factors and restrictions
that cannot be accurately described by physical models (e.g., prevent stack effect in buildings,
control infiltrations, noise from ventilation); the recognition of users’ patterns and actual
motives of human behaviour, including through Natural Language Processing functionality to
analyse users’ feedback; and the use of visual analytics to provide additional information. A
set of additional AI services is being developed, which is aimed at combining energy savings
opportunities with equipment health and efficiency analysis using the same data and models.
These are designed as scalable and replicable solutions requiring reduced deployment time
at similar industrial sites.

Related SDG:
• SDG7 Affordable and clean energy
• SDG9 Industry, innovation and infrastructure
• SDG11 Sustainable cities and communities
• SDG12 Responsible consumption and production

Relevant links:

Webpage at unece.org: https:// unece .org/ sustainable -energy/ energy -efficiency/ digitalization
-energy

Documents and materials:
• “Digitalization: enabling the new phase of energy efficiency” (GEEE-7/2020/INF.3)
• “Digitalization: Accelerating the Electricity System Transformation” (ECE/ENERGY/
GE.6/2022/4-ECE/ENERGY/GE.5/2022/4)
• “Addressing Behavioural Barriers to Energy Digitalization” (ECE/ENERGY/GE.6/2022/5)
• “Challenges of big data and analytics-driven demand-side management” (GEEE-9/2022/
INF.3)
• “Key considerations and solutions to ensure cyber resiliency in smart integrated energy
systems” (ECE/ENERGY/GE.6/2023/3-ECE/ENERGY/GE.5/2023/3)
• “Improving efficiency and reliability of energy systems by means of Big Data analytics”
(ECE/ENERGY/GE.6/2023/4-ECE/ENERGY/GE.5/2023/4)
• Case Study on “Grid Edge Management Reference Architecture and Policy
Recommendations for Interoperability and Resilience”
• Case study on “Cyber Resilience of Critical Energy Infrastructure”

Contact: Igor Litvinyuk, Economic Affairs Officer, UNECE (litvinyuk@ un .org)

Project 2: UNECE Platform for Resilient Energy Systems

Countries across the ECE region are in great need of tools to make informed decisions on
how to design and build resilient energy systems (i.e., those in which energy makes an optimal
contribution to a country’s social, economic and environmental development and is able to

29