Applying a Novel Investment Evaluation Method with Focus on Risk—A Wind Energy Case Study

Abstract

Renewable energy investments are typically evaluated using traditional discounted cash flow (DCF) methods, such as the net present value (NPV) or the internal rate of return (IRR). These methods utilize the discount rate as an aggregate proxy for risk and the time value of money, which leads to an inadequate modeling of risk. An alternative to these methods represents the decoupled net present value (DNPV). Instead of accounting for risk in the discount rate, the DNPV utilizes so-called synthetic insurance premiums. These allow for the individual and disaggregate pricing of risk and can enhance the quality of investment decisions by facilitating a more detailed and comprehensive representation of the underlying risk structure. To reliably estimate and forecast synthetic insurance premiums requires the availability of appropriate data and expertise in interpreting this data. Thus, the practicality of the results calculated based on the DNPV depends on the quality of the inputs and the expertise of the analyst. After reviewing the main theory of the DNPV, we apply the method to a wind energy investment case to demonstrate its applicability and prospects. To illustrate the calculation of the synthetic insurance premiums, selected risk factors are modeled with probability distributions via Monte Carlo simulation (MCS). Our results show that the DNPV’s seamless integration of risk assessment with investment evaluation is a promising combination and warrants further research.