COVID-19 impact on wind and solar energy sector and cost of energy prediction based on machine learning.

ABSTRACT: This study examines the impact of the COVID-19 pandemic on renewable energy sectors across seven countries through techno-economic analysis and machine learning (ML). In China, the renewable fraction decreased in grid-connected systems due to 14.6 % higher diesel fuel prices. They reduced grid electricity prices, with Cost of Energy (COE) reductions driven by a 2.8 % inflation decrease and a 3 % discount rate cut. The increase in renewable energy adoption in the USA during the pandemic was driven by decreased initial and operational costs of renewable components, a significant rise in diesel fuel prices, and government policy changes, despite a reduction in renewable energy sell-back prices and rising capital and annual costs due to expanded renewable capacity. Canada noted a shift to stan

SUBMITTER: Ghanbari Motlagh S 

PROVIDER: S-EPMC11399668 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature