Seasonality in transition: Renewables, electricity price shapes and seasonal priors

Abstract Seasonal price shapes underpin electricity forward curves, solar power purchase agreement valuation and flexible-asset scheduling, yet historical priors may become stale as renewable penetration rises. We develop transition-dependent seasonality, linking the Fourier representation of electricity price shapes to solar and wind penetration, and derive a decision-based criterion for updating a prior in linear optimisation. European evidence documents a broad decline in summer prices relative to winter, concentrated at midday. The solar channel is identifiable within the day, whereas the model’s common-effect restriction fails for wind. Out of sample, transition-dependent seasonality reduces systematic overvaluation and average absolute valuation errors for solar power purchase agreements relative to historical shapes, although its benefits depend on penetration forecasts and do not consistently extend to longer horizons or futures calibrated curves. Gains for monthly baseload shapes are not significant. For flexible assets, updated priors often leave optimal schedules unchanged, and average operating gains remain statistically insignificant. These results identify where transition-adjusted seasonality matters for valuation and where it adds less operational value.