Economic risk analysis of decentralized renewable energy infrastructures - A Monte Carlo Simulation approach

There are several different economic barriers such as high up-front capital costs, high transaction costs and diverse risks (e.g. performance and technical, contract risks, market risks) that keep potential investors or institutional lenders from investing in decentralized renewable energy technologies (RETs). Therefore, suitable business models, specific financing concepts and advanced risk management tools to deal with issues concerning transaction costs and financial risks are required to support RET investments. This article deals with this issue by introducing a Monte Carlo Simulation (MCS) approach to risk analysis based on an entire life-cycle representation of RET-investment projects. By doing this, the authors uncover considerable advantages regarding content and methodology compared to ordinary NPV-estimation or sensitivity analysis. It could be shown that the presented financial analysis combined with MCS aids in optimizing the conceptual design of an investment project with respect to capital returns and risk. Since both issues are decisive for lenders and investors, the double-criteria analysis method presented in this paper facilitates the raising of capital for project investments in decentralized RETs. (C) 2014 Elsevier Ltd. All rights reserved.