Author
Abstract
This chapter explores investment decision-making and operational optimization for carbon capture, utilization, and storage (CCUS) projects in the power industry, focusing on a case study of a Hubei-based power company. Key factors influencing CCUS adoption are categorized into external uncertainties—including climate policies, subsidy frameworks, technological advancements, and market dynamics—and internal challenges such as production variability, operational management complexities, and plant-specific characteristics. Immature carbon pricing mechanisms and fluctuating subsidy policies critically shape project feasibility, while technological progress introduces path dependency through cost-reduction trends and innovation cycles. The chapter integrates real options theory for project-level investment analysis and portfolio optimization models at the enterprise level, addressing risks under climate and market uncertainties. Operational challenges are examined through mixed-integer programming frameworks to balance emission reduction targets with economic viability. Findings highlight the interplay between carbon price dynamics and technological readiness: rising carbon prices incentivize earlier retrofitting, whereas anticipated cost reductions delay investments. For coal-biomass cofiring plants, operational strategies must reconcile energy losses from CCUS integration with carbon market incentives, requiring policy and market alignment to achieve scalability. The analysis underscores the importance of adaptive decision-making tools, scenario-based planning, and interdisciplinary methodologies to navigate the uncertainties inherent in low-carbon energy transitions. This chapter provides a structured framework for understanding CCUS investment and operational trade-offs, offering pedagogical insights for energy economics and sustainable infrastructure planning.
Suggested Citation
Yi-Ming Wei, 2025.
"Investment Decision and Operational Optimization of CCUS Projects,"
Springer Books, in: Carbon Mitigation System Engineering, chapter 16, pages 369-411,
Springer.
Handle:
RePEc:spr:sprchp:978-981-95-0371-1_16
DOI: 10.1007/978-981-95-0371-1_16
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