Version 3
: Received: 29 January 2017 / Approved: 30 January 2017 / Online: 30 January 2017 (12:04:34 CET)
How to cite:
Eissa, M.A.; Tian, B. Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects. Preprints2016, 2016080075. https://doi.org/10.20944/preprints201608.0075.v3
Eissa, M.A.; Tian, B. Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects. Preprints 2016, 2016080075. https://doi.org/10.20944/preprints201608.0075.v3
Eissa, M.A.; Tian, B. Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects. Preprints2016, 2016080075. https://doi.org/10.20944/preprints201608.0075.v3
APA Style
Eissa, M.A., & Tian, B. (2017). Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects. Preprints. https://doi.org/10.20944/preprints201608.0075.v3
Chicago/Turabian Style
Eissa, M.A. and Boping Tian. 2017 "Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects" Preprints. https://doi.org/10.20944/preprints201608.0075.v3
Abstract
Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES). The RES investment is characterized by uncertainty, which is long-term, costly, depend on feed-in-tariff and support schemes. In this paper, we address the real option valuation (ROV) of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price, furthermore the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assess the value of deferred option are discussed. The new three stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM) methods. The numerical methods are integrated with concept of Black-Scholes option pricing theory, and applied in option valuation for solar energy investment with uncertainty. The numerical results of L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our data set refers to the Arab Republic of Egypt.
Keywords
stochastic differential equation; numerical simulation; real option; renewable energy; Egypt
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.