The increasing share of renewable energy sources (RES) in the European energy system leads to higher volatility in space and time for infeeds and load flows. Forecasting the variable infeed thus becomes hence of primordial importance. Besides the forecast level itself, forecast errors in particular trigger the need for short-term flexibility. Hence appropriate forecast modelling is a prerequisite to simulate and assess the capability of different market designs to provide appropriate incentives for flexibilities. 

The present report focuses on modelling of forecast updates as a key input to market simulations. Therefore, a general forecast update methodology is proposed including forecast update processes for wind, photovoltaic generation and load at a European scale. 

The provided forecast update methodologies are applicable for various look-ahead times depending on the market designs and reflecting the different fundamental characteristics of wind, solar and load. Applicability is mainly limited by data availability. As such forecast error observations are scarce, the time series produced for the market simulations should converge to simulated infeed time series that are based on actual meteorological observations. For modelling forecast paths, this results in a multivariate formulation of the corresponding distribution function, usually implemented using a copula-approach. 

The methods for assessing errors of either wind, solar or load forecasts have proven to be generally applicable in order to provide the market models with error forecast time series. The preliminary results of all methods show that further research is needed either on calibration or on the effects of a higher degree of specification on the production of the market models. 

D2.1 Methodology for error forecasts at European scale

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