Posters

Abstract

Long-term energy yield assessments (LTYAs) play a central role in the financing of wind and solar projects, as uncertainty levels directly affect debt sizing, cost of capital, and downside energy metrics such as P90. While yield assessments are commonly produced at single-asset level, portfolios of renewable assets benefit from diversification effects that can materially reduce aggregate uncertainty and enhance P90 energy yield levels. The assessment of the portfolio effect is increasingly relevant for investors and lenders assessing multi-asset portfolios. Portfolio benefits arise from imperfect correlation between uncertainty components across projects. These components include inter-annual resource variability, measurement uncertainty, modelling assumptions, and technology-specific effects. We approach portfolio uncertainty through a covariance-based propagation framework aligned with the financial portfolio theory, where individual project uncertainties are combined through a variance–covariance matrix weighted by project energy contributions. Several diversification routes are typically observed: * Geographical diversification reduces exposure to correlated interannual climate variability, particularly for wind portfolios spanning different weather regimes. * Technological diversification through varying turbine models, hub heights, or PV technologies limits common-mode modelling and performance uncertainties. * Methodological and data source diversification such as independent measurement campaigns or different modelling approaches, further de-correlates systematic errors. * Resource complementarity introduces additional benefits in hybrid portfolios, as wind and solar production are often weakly correlated on an interannual basis, while their uncertainty structures differ. In our analysis we aim to evaluate energy yield uncertainty reductions on a European portfolio and evaluate financial implications in debt sizing and P90 levels.