No abstract

Due to the heavy computation load of closed-loop simulations, optimal control of greenhouse climate is usually simulated in an open-loop form to produce control strategies and profit indicators. Open-loop simulations assume the model, measurements, and predictions to be perfect, resulting in too-idealistic indicators. The method of two-time-scale decomposition reduces the computation load, thus facilitating the online implementation of optimal control algorithms. However, the computation time of nonlinear dynamic programming is seldom considered in closed-loop simulations. This paper develops a two-time-scale decomposed closed-loop optimal control algorithm that involves the computation time. The obtained simulation results are closer to reality since it considers the time delay in the implementation. With this algorithm, optimal control of Venlo greenhouse lettuce cultivation is investigated in Lhasa. Results show that compared with open-loop simulations, the corrections in yield and profit indicators can be up to 2.38 kg m−2 and 11.01 CNY m−2, respectively, through closed-loop simulations without considering the computation time. When involving the time delay caused by the computation time, further corrections in yield and profit indicators can be up to 0.1 kg m−2 and 0.87 CNY m−2, respectively. These conservative indicators help investors make wiser decisions before cultivation. Moreover, control inputs and greenhouse climate states are within their bounds most of the time during closed-loop simulations. This verifies that the developed algorithm can be implemented in real time.

Greenhouse technology has advanced over the past few decades in terms of environmental control (e.g., indoor temperature, relative humidity, and CO2 concentration). Ventilation is an effective way to adjust the indoor climate. Natural ventilation has gained significant research attention recently because of its low energy requirement. To evaluate the ventilation effectiveness, the ventilation rate is often used. This review summarizes the published review papers related to greenhouse ventilation. Ventilation models are reported under different conditions, including wind-induced, buoyancy-induced, and combined effects-induced ventilation in greenhouses. The influencing factors are described, such as the wind and buoyancy strength and distribution, greenhouse geometry, and vent arrangement. Various methods assessing natural ventilation in greenhouses are introduced, consisting of tracer gas techniques, the pressure difference method, the energy balance method, the emptying fluid-filling box method, and numerical simulation. The values of the key coefficients deduced and used in the literature are listed. This paper reports what has been done in the world and where we can start to develop dynamic ventilation models for solar and tunnel-type greenhouses in China. Further valuable investigations are discussed. The pressure distribution function in greenhouses with horizontal openings, a model for cross-ventilation induced by combined wind and buoyancy force, and an analytical plant-considered ventilation model with higher applicability are described. To ensure the accuracy of the ventilation models, other environmental variables, especially geography-dependent ones, can be added. More criteria are suggested to evaluate the ventilation performance rather than the ventilation rate to provide a comprehensive assessment.