4.7 Article

Are we seeing clearly? The need for aligned vision and supporting strategies to deliver net-zero electricity systems

期刊

ENERGY POLICY
卷 147, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.enpol.2020.111902

关键词

Renewable energy; Smart grids; Socio-technical energy transition; Delphi study; Energy vision; Net-zero energy

资金

  1. Oxford Martin Programme on Integrating Renewable Energy - Oxford Martin School, University of Oxford
  2. EnergyREV, the UK's Energy Revolution Research Consortium - UK Research and Innovation [EP/S031863/1]
  3. EPSRC [EP/S031863/1] Funding Source: UKRI

向作者/读者索取更多资源

This paper explores the trends, step changes and innovations that could impact the integration of renewable energy into electricity systems, explores interventions that may be required, and identifies key areas for policy makers to consider. A Delphi approach is used to collect, synthesise, and seek consensus across expert viewpoints. Over sixty experts across a range of geographies including the US, Europe, New-Zealand, Australia, Africa, India and China participated. They identified 26 trends, 20 step changes, and 26 innovations that could lead to major shifts in the design, operation, or management of electricity systems. Findings suggest that key challenges are not technological. Instead they are with delivering an aligned vision, supported by institutional structures, to incentivise, facilitate, and de-risk the delivery of a completely different type of energy system. There is a clear role for government and policy to provide a future energy vision and steer on strategic issues to deliver it; to create space for new actors and business models aligned with this vision; and to create an environment where research, development, demonstration and deployment can promote technologies, system integration and business model innovation at a rate commensurate with delivering net-zero electricity systems.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据