Expected Accuracy Range of Cost Estimates for Small Modular Reactors at the Early Concept Design Stage
Expected Accuracy Range of Cost Estimates for Small Modular Reactors at the Early Concept Design Stage
复制标题
小型模块化反应堆早期概念设计阶段成本估算的预期准确度范围
DOI:
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发表时间:
2018
期刊:
影响因子:
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通讯作者:
L. Newnes
中科院分区:
文献类型:
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作者:
A. Agar;A. Fry;M. Goodfellow;Y. Goh;L. Newnes
Life cycle cost is an important consideration for the development and selection of new power generation technology. Large nuclear power plants (NPPs) have been subject to capital cost escalation, stemming from delays related to late design changes, procurement issues for major components, and regulatory enforced changes. These factors have contributed to the significant risk premium associated with gigawatt scale “Gen III+” designs, which have incurred significant financing costs. Large NPPs have become prohibitively expensive for many utility investors in liberalized markets and smaller economies.
The challenge of reducing upfront capital costs is one of the requirements that have driven the development of innovative Small Modular Reactors (SMRs). These designs are said to offer reduced unit cost and reduced risk due to certainty of delivery, which could lead to a lower cost of capital for a utility customer. By offering a product with more cost certainty the SMR could restore investor confidence in nuclear power. The life cycle cost estimates associated with the different SMR designs are uncertain at the early stage of development. However, designers need to understand, with some confidence, the impact of technical decisions at the early development phase on the life cycle cost.
This study presents an overview of cost uncertainty associated with the early design stage of the SMR. The types of cost estimating approaches available at the concept design phase are identified and categorized in terms of their expected accuracy ranges. The Overnight Cost of Construction (OCC) is an important driver of the life cycle cost of a power generation project. The expected accuracy ranges from each estimating method are used to illustrate the sensitivity of cost uncertainty to the level of design maturity. By understanding the sources and impact of cost uncertainty decision making during product development can be optimized to meet both technical and commercial requirements.