Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case
2014
Jeon, Chanwoong | Shin, Juneseuk
A new long-term technology valuation method for renewable energy technologies that combines system dynamics with Monte Carlo simulation is proposed. Existing valuation methods using surveys or cash flows are suitable for technologies characterized by short lifecycles and little uncertainty, but are not appropriate for renewable energy technologies affected by various uncertainties over the long term. A variety of macro- and micro-factors interact in sophisticated ways, create uncertainty, and make valuation difficult. System dynamics provides a good method of structuring these complex interactions. Monte Carlo simulation can consider long-term uncertainties in valuation. Using the advantages of both methods, our method can improve not only the long-term reliability of probabilistic technology valuation but also R&D decisions and investments on both the private and public sides. Korean photovoltaic power generation, a representative renewable technology, is used as an example.
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