Optimal subsidy estimation method using system dynamics and the real option model: Photovoltaic technology case

• We propose a method of estimating optimal financial subsidy and public R&D investment.
• System dynamics is used to analyze a complex system of energy subsidies.
• Appropriate real option valuation models are matched and used to estimate optimal subsidies.
• Our approach can reduce the total Korean photovoltaic subsidy by $US 359.5 million.

In this paper, we propose a method of optimizing financial subsidies and public research and development investments for renewable energy technologies, rather than optimizing financial subsidy alone. By combining system dynamics with real option models, we capture dynamic complex interactions among investors, consumers, and policymakers, as well as future uncertainties of key energy, economic, and environmental factors. Our method thereby makes subsidy optimization more accurate and flexible. To evaluate our model, we apply it to the Korean photovoltaic subsidy and determine that the government can achieve the photovoltaic diffusion target, even if it reduces the total subsidy by $US 359.5 million. The optimal approach is to increase research and development funding by $US 310.4 million while reducing the financial subsidy by $US 669.9 million. Our method helps policymakers optimize their subsidy allocation and therefore reduces subsidy inefficiencies.