Valuing investment decisions of renewable energy projects considering changing volatility
Mingming Zhang,
Liyun Liu,
Qunwei Wang () and
Dequn Zhou
Energy Economics, 2020, vol. 92, issue C
Abstract:
Volatility is an important parameter when evaluating investments using the real options method. For renewable energy investments, the volatility of cash flow continuously changes, because as new information and knowledge are gathered, there is less foreseen variation. This paper proposes an extended recombining trinomial tree model, where the changing volatility is used to generate transition probabilities. The changing volatility is generated using a consolidation process where multiple random variables, including the market price of electricity, carbon price, and lending rate, are integrated into a low-dimension stochastic process. A two-factor learning curve is used to model the changes of investment cost. We apply the proposed model to analyze solar photovoltaic (PV) power generation investment in China. The results show volatility with changing feature. Compared with constant volatility, changing volatility may advance investment decisions and change the project value. Complete grid parity policy in the solar PV industry is infeasible because the opportunity cost brought by the option of delaying cannot be offset. The changing volatility may produce a lower and equally effective subsidy level compared with constant volatility. A carbon emission trading scheme is helpful in advancing investments in renewable energy, which is reflected in improvements in project value, advancements in investment decisions, and reductions in the required subsidy level.
Keywords: Changing volatility; Consolidation process; Save-path rate; Project value; Grid parity (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:92:y:2020:i:c:s0140988320302942
DOI: 10.1016/j.eneco.2020.104954
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