Improving the accuracy of forecasting is becoming increasingly important for both, developers and grid operators. The former to calculate the envisaged financial returns, the latter, as more renewables are put onto the system. Today, new technologies like short-term solar irradiance forecasting algorithms based on machine learning methodologies can precisely predict future 5-30 min solar irradiance under difference weather conditions. This session will feature the latest approaches and methods e.g. how an artificial neural network model is used to develop a prediction model designed to produce an accurate solar power forecasts. Moreover, light shall be shed on PV systems being combined with electrical energy storage (ees) systems.
This session is jointly organized by Intersolar and CSEM.