A Decision Support System for the Continuous Economic Evaluation of Wind Farms

Abstract. This paper presents a decision support system that integrates digital twin technology with advanced economic evaluation tools to enable continuous and holistic assessment of wind farm investments. The framework combines real-time turbine health data, including remaining useful life estimates derived from SCADA and condition monitoring systems, with financial models employing discounted cash flow, scenario testing, Monte Carlo simulations, and real-options valuation. Implemented through the open-source DigiWind platform, the system adheres to FAIR data principles and provides a flexible, interoperable environment for asset management. A case study on an 8 MW wind turbine in Germany demonstrates the framework’s ability to guide decisions such as life extension, repowering, decommissioning, or sale under volatile market conditions. Results highlight the importance of coupling technical reliability forecasts with market-based financial outlooks to capture both risks and upside potential, offering a scalable and transparent tool for investors, operators, and policymakers navigating the evolving wind energy sector.