Presentations

Abstract

Accounting for climate change in wind farm energy yield assessments is challenging. It involves deep uncertainty and requires a long-term view aligned with the more than 20 years lifespan of wind energy assets.  Unlike other financial risks, climate change is not short-term volatility, it represents a gradual but fundamental shift in operating conditions which is influenced by global mitigation and local adaptation efforts.  For wind power this matters: while projections show with high confidence that global temperature will continue to increase over the next 30 years under all scenarios, there is much less agreement on how wind speeds will change. As a result, reducing the impacts of climate change on wind production to just another uncertainty in the EYA might be missing other important factors. Here we apply a methodology developed to integrate physical climate risks into investing decision-making (PCRAM 2.0), to translate climate impacts into financial metrics for a wind farm, and identify the measures that can be taken to reduce those impacts and minimise financial risk. The approach involves the following steps: 1 - Defining the objective: e.g maximise operation yield and log term asset value,... 2 - Assessing materiality: identify hazards material to the wind farm (e.g changes in wind resources, heat stress, extreme winds, etc) and their impacts on financial metrics such as LCOE,NPV and IRR    - for the baseline using historical data for energy yield modelling with detailed operational parameters.   - for climate projections, using CMIP6 models projections across multiple climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). Physical impact analysis could include power curve adjustments, temperature derating (losses above 25°C), and extreme event modelling. Uncertainties in the financial parameters are estimated using Monte Carlo simulations. 3 - Building resilience: identify the adaptation options (e.g improved cooling, turbine controls, structural upgrades, etc) for material physical risks, and the optimal time for their implementation.  We also examine how changes in prevailing wind direction affect energy output and revenue. Even small shifts can alter wake losses—typically 10–15% of gross production—since turbine layouts optimized for historical patterns may perform differently under future wind regimes. The methodology is applied to wind farms across diverse European climates: Northern (high wind, moderate warming), Central (moderate wind, strong warming), Mediterranean (variable wind, extreme warming), and coastal zones (storm-prone). Results show location-specific variation in risk with some minimally affected, while others face significant exposure. This approach turns complex climate projections into clear financial insights. By quantifying potential losses and adaptation costs, it supports transparent, evidence-based investment decisions. As climate effects intensify, such integrated assessment frameworks will be vital for making renewable energy infrastructure truly resilient.