Weather forecast error modelling and performance analysis of automatic greenhouse climate control

In the published simulation studies on greenhouse climate control that employ optimal control, often non-realistic weather forecasts are employed, e.g. realisation of or artificially created used. This research aims to quantify effect forecast errors performance controlled system measured in terms operational return. The return is defined as difference between cost resources (resourceuse×cost) and income through yield (yield×productprice). A stochastic model error was identified based historical observations from a forecasting service. An uncertainty analysis using showed considerable number inputs sensitive errors. study involving three 7day-intervals throughout growing season showed, however, not significantly affected by error, decrease 0.03euro.m?2 (2%) observed with respect case which perfect were results suggest an algorithm (a) updated every 15min full state information, (b) uses 6h (c) similar service used here, able mitigate system.