Real options valuation of photovoltaic power investments in existing buildings

Renewable power generation based on solar energy is deemed to be a key instrument to reduce the carbon footprint of modern economies. Collectively, buildings are an energy-intensive consumption sector. Therefore, existing building rooftops are seen as a target for massively deploying photovoltaic (PV) distributed generation. Nevertheless, estimating the benefits and risks of investing in rooftop PV systems is indeed a challenging task due to the large uncertainties that affect tariffs, technology costs, and regulatory policy. After reviewing the literature and identifying the current gaps, this article develops a method based on Real Options theory for appraising investments in PV generation systems to be installed on the rooftop of existing buildings. The option value of differing the investment decision and the problem of the optimal time to invest in irreversible PV assets are addressed by an advanced valuation method based on stochastic simulation, linear regression, and backward dynamic programming. In this work, returns of self-generation PV investments are subjected to uncertainties upon declining investment costs and fluctuating electricity tariffs, which are represented by appropriate exogenous stochastic processes. In order to test the practicability of the proposed decision-making framework, the valuation of an exemplary rooftop PV-system in a government building is considered. Results show that while standard appraisal methods wrongly reject the rooftop PV project now and in the future, the option valuation method finds optimal to hold the opportunity open in order to reconsider to invest later. In addition, the method provides an objective value of the opportunity cost of using the building rooftop for another purpose. The proposed valuation approach would result in better investment allocation and faster development of distributed PV power capacity contributing thereby to enhance the sustainability of current energy systems.