Roozbeh Bakhshi and Peter A. Sandborn
CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
Renewable energy from wind and solar is considered to be the main alternative to fossil fuels. The costs of renewable energy technologies are high and without tax credits they are not currently competitive with fossil fuels in many markets. Improvements in the performance or reduction in operational costs will have significant impacts on the price of renewable energy and ultimately impact their competitiveness. New technologies targeted at improving the efficiency of the current systems or reducing their life-cycle costs will help; however, these technologies are expensive and detailed cost tradeoff and return on investment (ROI) analysis are required to make business cases for them. In this paper, we formulate an ROI model and describe its implementation in a stochastic discrete-event simulator to calculate financial tradeoffs and enable business cases for technology insertion into wind farms. The new ROI model includes changes in revenue and operations costs (including changes in reliability due to the technology insertion) and introduces the concept of identical timeline conditions to guarantee a meaningful ROI calculation. A case study for using light detection and ranging (LIDAR) to increase the efficiency and improve the reliability of wind turbines in a wind farm is provided.