A real option model for renewable energy policy evaluation with application to solar PV power generation in China

Mingming Zhang, Dequn Zhou and Peng Zhou

Renewable and Sustainable Energy Reviews, 2014, vol. 40, issue C, 944-955

Abstract: This study proposes a policy evaluation model from the perspective of government and investors. The proposed model, which integrates American option method and two-factor learning curve method, can be used to evaluate the unit decision value and save-path rate for renewable energy development and examine the existence of balance point of interest. Several uncertain factors including non-renewable energy cost, carbon price, renewable energy cost, and price subsidy are all considered in this model. The model has been applied to evaluate the solar photovoltaic (PV) power generation in China. Our empirical results show that real option analysis (ROA) is more effective than net present value analysis (NPV) when handling uncertainty. Under current level of subsidy, the government would suffer loss and the investors could benefit so that it is difficult to achieve the balance of interest during the planning period. With the reduction of subsidy rate, they can achieve the balance of interest.

Keywords: Real option; Unit decision value; Save-path rate; Solar PV power generation (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (48)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1364032114006972
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:40:y:2014:i:c:p:944-955

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/bibliographic
http://www.elsevier. ... 600126/bibliographic

DOI: 10.1016/j.rser.2014.08.021

Access Statistics for this article

Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski

More articles in Renewable and Sustainable Energy Reviews from Elsevier
Bibliographic data for series maintained by Catherine Liu ().