Life cycle assessment and cost benefit analysis of concentrated solar thermal gasification of biomass for continuous electricity generation

Yi Fang, Xian Li, Simon Ascher, Yize Li, Leilei Dai, Roger Ruan, Siming You

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The hybridization of solar and biomass energy systems is a promising technology for mitigating the issues of energy generation-related greenhouse gas emissions and high energy prices. The global warming potential and economic feasibility of a hybrid solar-bioenergy system, comprised of a concentrated solar tower, biomass gasifier, thermal storage, and combined cycle gas turbine, have been evaluated by using life cycle assessment and cost benefit analysis, respectively. Sensitivity analysis is carried out to identify the hotspots of costs and emissions. The net present worth of the proposed system at the 30th year was calculated to be about €–0.7 billion. There are two suggestions to enhance the economic viability of the system, allowing for a payback period of less than 10 years. The first suggestion involves reducing the O&M cost of the system by 19% at 43.9 €/MWh, and the second suggestion entails increasing the overall efficiency of the system by 20%. This system can save 787.7 kg of CO2-eq/tonwaste-wood and generate a total of about 0.8 million MWh of electricity each year. The findings provide scientific evidence for the design and deployment of the hybrid technology to enhance energy security, while reducing carbon emissions. Overall, this study highlights the potential benefits of hybrid solar-bioenergy systems and encourages the adoption of sustainable energy practices for a greener future.

Original languageEnglish (US)
Article number128709
JournalEnergy
Volume284
DOIs
StatePublished - Dec 1 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Biomass
  • Concentrated solar thermal
  • Cost benefit analysis
  • Gasification
  • Life cycle assessment
  • Producer gas
  • Sensitivity analysis

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