Digital twin role for sustainable and resilient renewable power plants: A systematic literature review

Abstract

Transitioning to sustainable and resilient energy generation presents challenges in optimizing resource and storage utilization, reducing operational costs, and addressing environmental impacts within renewable energy power plants. The shift away from fossil fuels in the energy sector requires innovative solutions to enhance sustainability and resilience. This study aims to explore the role of Digital Twin (DT) technology – a digital replica of a physical object or process with bidirectional communication – in promoting sustainability within power plants, an area that remains underexplored. Using a Sytematic Literature Review (SLR) of 61 peer-reviewed papers, this research examines six key categories of DT application: predictive analysis, performance optimization, risk assessment, model evaluation, process traceability, and human–machine interaction. The findings indicate that DT holds significant potential to improve power plant sustainability by enabling cost reductions, optimizing energy usage, and minimizing environmental impact through waste reduction and carbon emission management. This study underscores DT’s importance in supporting the energy sector’s transition towards sustainable practices and enhancing the resilience of renewable energy systems. • Investigation of the Digital Twins (DT) role in energy sustainability and resilience. • Exploring the challenges in the transition towards sustainable energy systems. • Systematic Literature Review identifying research gaps in DT adoption in power plants. • DT decision support described for efficiency and resilience in power plants. • DT role in improving energy systems using artificial intelligence is discussed.