| 000 -LEADER |
|---|
| fixed length control field |
03336nam a22003497c 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
00006687 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
ES-MaONT |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20220711055452.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
210907s2021 |||||rt|||i001 0 eng d |
| 024 ## - OTHER STANDARD IDENTIFIER |
|---|
| Additional codes following the standard number or code |
. |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
ES-MaONT |
| 110 ## - MAIN ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
World Economic Forum |
| 9 (RLIN) |
2608 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Harnessing Artificial Intelligence to Accelerate the Energy Transition |
| Statement of responsibility, etc. |
/ World Economic Forum ; In collaboration with BloombergNEF and Deutsche Energie-Agentur (dena) |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Geneva : |
| Name of publisher, distributor, etc. |
World Economic Forum. |
| Date of publication, distribution, etc. |
2021 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
24 p. : |
| Other physical details |
il., tablas, gráf. ; |
| Dimensions |
1 documento PDF |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
texto (visual) |
| Source |
isbdcontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
electrónico |
| Source |
isbdmedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
recurso en línea |
| Source |
rdacarrier |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
White Papers ; |
| Volume/sequential designation |
September 2021 |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
The efforts to decarbonize the global energy system are leading to an increasingly integrated and electrified energy system, with much more interaction between the power, transport, industry and building sectors. The move to decarbonize the energy supply is also leading to high levels of decentralization in the power sector. This will require much higher levels of coordination and flexibility from all sector players – including consumers – in order to manage this increasingly complex system and optimize it for minimal greenhouse gas emissions. AI has tremendous potential to support and accelerate a reliable and lowest-cost energy transition, with potential applications ranging from optimizing and efficiently integrating variable renewable energy resources into the power grid, to supporting a proactive and autonomous electricity distribution system, to opening up new revenue streams for demand-side flexibility. AI could also be a crucial accelerator in the search for performance materials that support the next generation of clean energy and storage technologies. However, despite its promise, AI’s use in the energy sector is limited, with it primarily deployed in pilot projects for predictive asset maintenance. While it is useful there, a much greater opportunity exists for AI to help accelerate the global energy transition than is currently realized. The nine “AI for the energy transition” principles (see below) aim at creating a common understanding of what is needed to unlock the potential of AI across the energy sector and how to safely and responsibly adopt AI to accelerate the energy transition. The principles are split into three areas: those that govern AI use, those that will help design AI to be fit for purpose, and those that enable AI’s deployment and are aimed at helping to create collaborative industry and policy practices. |
| 540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE |
|---|
| Terms governing use and reproduction |
All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, including photocopying and recording, or by any information storage and retrieval system. |
| Jurisdiction |
World Economic Forum |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
4348 |
| Topical term or geographic name entry element |
Inteligencia Artificial |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
2345 |
| Topical term or geographic name entry element |
Industrias |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
energy transition |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
energy sector |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
renewable energy |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
create collaborative |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
design AI |
| 830 0# - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
White Papers (World Economic Forum) |
| 9 (RLIN) |
5156 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://www3.weforum.org/docs/WEF_Harnessing_AI_to_accelerate_the_Energy_Transition_2021.pdf">http://www3.weforum.org/docs/WEF_Harnessing_AI_to_accelerate_the_Energy_Transition_2021.pdf</a> |
| Nonpublic note |
Abierto |
| Public note |
Acceso al documento |
| Electronic format type |
pdf |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Informes |