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Valuing the option to prototype: A case study with Generation Integrated Energy Storage
被引:10
作者:
Lai, Chun Sing
[1
,2
,3
]
Locatelli, Giorgio
[1
]
机构:
[1] Univ Leeds, Fac Engn & Phys Sci, Sch Civil Engn, Leeds LS2 9JT, W Yorkshire, England
[2] Guangdong Univ Technol, Sch Automat, Dept Elect Engn, Guangzhou 510006, Peoples R China
[3] Brunel Univ London, Brunel Inst Power Syst, Dept Elect & Elect Engn, Uxbridge UB8 3PH, Middx, England
来源:
基金:
英国工程与自然科学研究理事会;
关键词:
Prototyping;
Real options analysis;
Generation integrated energy storage;
Energy infrastructure;
Investment risk;
REAL-OPTIONS;
CARBON CAPTURE;
HEAT-STORAGE;
MOLTEN-SALT;
POWER;
INVESTMENT;
SYSTEM;
UNCERTAINTY;
DESIGN;
PERFORMANCE;
D O I:
10.1016/j.energy.2020.119290
中图分类号:
O414.1 [热力学];
学科分类号:
摘要:
New energy generation and storage systems are continuously being developed due to climate change, resource scarcity, and environmental laws. Some systems are incremental innovations of existing systems while others are radical innovations. Radical innovation systems are risky investments due to their relevant technical and economic uncertainties. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. Real options analysis is the project appraisal approach for these assessments. This paper aims to introduce and test an algorithm based on real options analysis to quantitatively assess the "option to prototype" in the energy sector. First, the interrelated research areas of prototyping, energy systems, and real options analysis are reviewed. Then, a novel algorithm is presented and applied to an innovative Generation Integrated Energy Storage system: Wind-driven Thermal Pumping to demonstrate the effectiveness of option to prototype and the main parameters influencing this decision. Results show that the cost of the prototype and the market size (number of identical systems to build) are key parameters. (C) 2020 The Author(s). Published by Elsevier Ltd.
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页数:15
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