Digitilising the energy sector: A comprehensive digital twin framework for biomass gasification power plant with CO2 capture

• A systematic review of digital twin applications in power plants is presented. • The definitions, classifications and case studies of digital twin applications in power plants are presented. • The key requirements for biomass gasification digital twin are presented. • Proposed digital twin framework for biomass gasification power plant is presented. • The prospective research directions on the proposed digital twin for a biomass gasification power plant are suggested. The push to decarbonize the energy sector by incorporating renewable sources is increasing the complexity of power plant operations. One potential solution is to digitize power plants through digital twin (DT) technology, which can improve operational efficiencies and reduce maintenance costs. However, the application of DT in power plants remains in its early stages, with no existing implementations focused on gasification technology. This study aims to develop a comprehensive digital twin framework for a biomass gasification power plant with CO2 capture (DT-BGPP). An overview of existing DT research in power plants and their classifications was conducted to assess the current state of the field and identify gaps. Based on this analysis, essential characteristics for the DT-BGPP framework were defined, leading to the identification of its main components. The classification revealed a common gap in mid-tier categories, with most available power plant Dts lacking complete bidirectional data flow with their physical counterparts. The key components of DT-BGPP include a high-order science-informed dynamic model, a data-driven model, actual data, pre-executed localized simulations, and a system genome. Recommendations for advancing the proposed DT-BGPP include establishing connections between all framework components to achieve a fully integrated digital twin for a biomass gasification power plant with CO 2 capture.

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Publication Details

Journal
Cleaner Energy Systems
Published
2025-01-22
DOI
https://doi.org/10.1016/j.cles.2025.100175
Citations
17
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
21.12

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article

Digitilising the energy sector: A comprehensive digital twin framework for biomass gasification power plant with CO2 capture

Bilainu Oboirien, Peter Akhator
17 citations
Cleaner Energy Systems
Digital Transformation in Industry
21.12
article

Digitilising the energy sector: A comprehensive digital twin framework for biomass gasification power plant with CO2 capture

Bilainu Oboirien, Peter Akhator
article en
17 citations

Abstract

• A systematic review of digital twin applications in power plants is presented. • The definitions, classifications and case studies of digital twin applications in power plants are presented. • The key requirements for biomass gasification digital twin are presented. • Proposed digital twin framework for biomass gasification power plant is presented. • The prospective research directions on the proposed digital twin for a biomass gasification power plant are suggested. The push to decarbonize the energy sector by incorporating renewable sources is increasing the complexity of power plant operations. One potential solution is to digitize power plants through digital twin (DT) technology, which can improve operational efficiencies and reduce maintenance costs. However, the application of DT in power plants remains in its early stages, with no existing implementations focused on gasification technology. This study aims to develop a comprehensive digital twin framework for a biomass gasification power plant with CO2 capture (DT-BGPP). An overview of existing DT research in power plants and their classifications was conducted to assess the current state of the field and identify gaps. Based on this analysis, essential characteristics for the DT-BGPP framework were defined, leading to the identification of its main components. The classification revealed a common gap in mid-tier categories, with most available power plant Dts lacking complete bidirectional data flow with their physical counterparts. The key components of DT-BGPP include a high-order science-informed dynamic model, a data-driven model, actual data, pre-executed localized simulations, and a system genome. Recommendations for advancing the proposed DT-BGPP include establishing connections between all framework components to achieve a fully integrated digital twin for a biomass gasification power plant with CO 2 capture.

Cleaner Energy SystemsVol. 10
University of Johannesburg (ZA), University of Benin (NG)
Tertiary Education Trust Fund
Affordable and clean energy
Openalex Percentile: Top 1%
Digital Transformation in Industry
21.12
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