A comparison of optimal greenhouse heating setpoint generation algorithms for energy conservation

In this paper, a comparison of two heating set-point generation algorithms is performed, using well-known greenhouse models and data for a variety of weather conditions. Their main difference is that the first method uses meteorological weather forecasts to decide on the most appropriate heating setpoints for energy conservation, while the second method uses past information in order to achieve the desired average for any user-defined period of interest and thus, no advanced weather information is required. Simulation results show that for short integration periods (e.g. 24 hours) the two algorithms have similar performance regarding energy consumption while the first method provides slightly better energy conservation, provided that weather forecasts as well as the greenhouse energy consumption model used by this method are exact. Under the same assumptions, for longer integration periods (e.g. 2 or 3 days), the second method is always comparable to the first. In the case of uncertainty in the forecasts or in the consumption model, the second method appears to be more advantageous and effective, regarding energy conservation and quality of climate. Copyright (C) 2001 IFAC.