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

• Published in: Heliyon 2024-09, Vol.10 (17), p.e36662, Article e36662
• Main Authors: Ghanbari Motlagh, Saheb, Razi Astaraei, Fatemeh, Montazeri, Mohammad, Bayat, Mohsen
• Format: Article
• Language: English
• Subjects: Coronavirus disease of 2019; Hybrid renewable energy system; Machine learning; Renewable energy; Techno-economic
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e36662

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 standalone systems with 50 % lower PV sell-back prices, 2 % lower WT prices, and a 48 % fuel cost rise, reducing COE except in grid/WT scenarios. Germany managed rising electricity and fuel costs, decreasing COE despite inflation. India expanded standalone HRESs driven by a sevenfold PV capacity increase, lowering COE. Japan saw stable COE with minimal variation. Iran faced economic challenges with a 104 % inflation increase, impacting COE despite a grid-connected COE decrease. Machine learning forecasts suggest that COVID-19 may cause an increase in COE in China and India due to pandemic effects. •Economic impacts of the COVID-19 lockdown on the renewable energy sector are investigated.•Techno-economic analysis is used to investigate the impact of COVID-19 on the cost of energy.•The impacts of inflation and discount changes on renewable systems are investigated.•A database containing details of renewable systems was gathered using published papers.•Machine Learning is used to predict renewable COE changes related to COVID-19.