Energiprognoser

Energiprognoser are forecasts of energy variables, including electricity production, consumption, and related market indicators, used by utilities, grid operators, and energy markets to plan operations, scheduling, and reliability measures. They may also cover prices, demand profiles, or net interchange.

Forecasts are typically categorized by horizon: short-term prognoser cover hours to a few days ahead, while medium- to long-term prognoser look weeks to seasons. Forecasts can be point estimates or probabilistic, with prediction intervals to express uncertainty and support risk assessment.

Inputs for energiprognoser include weather forecasts (wind speed, solar irradiation, temperature, precipitation), historical load data, generation capacity and outages, fuel prices, and current market conditions. Methodologies range from statistical time series and regression models to machine learning approaches, often combined with physically based models for renewable generation. Hybrid and ensemble methods are common to improve robustness.

Outputs commonly consist of expected generation by source, total demand, net interchange, and reserve requirements, along with market bids and schedules. Probabilistic results provide uncertainty quantification through quantiles or confidence intervals, aiding decision-making under risk.

Applications span grid operation and security analysis, day-ahead and intraday market optimization, capacity planning, and the integration of variable renewable energy. Challenges include forecast uncertainty, dependence on weather data quality, evolving consumption patterns, model drift, and data security. In Nordic and European markets, energiprognoser are produced by utilities, transmission operators, and meteorological analytics providers, often in collaboration with system operators and market platforms.