In order to optimize the energy requirements (heating/cooling) of a multi-zone greenhouse, and investigate its heat recovery potential, a mathematical, dynamic energy model, coded in the MATLAB/Simulink platform, is developed. For validation, a case study in cold climate conditions is evaluated. This dynamic model, based on both energy and water vapor mass balances, was able to calculate the year-round monthly energy demand for the case study. The model calculations were compared with actual energy consumption data and were shown to have an accuracy between 6% and 15.5% for different months. The results highlighted the potential of applying a heat recovery strategy, whether with a Phase Change Material (PCM) or a Heat Recovery Ventilator (HRV). It is shown that using a HRV can reduce the energy demand of the greenhouse by 5% for January and 4% for December. Regarding the greenhouse radiation performance, the south roof contributes the most to solar heat gain in winter and summer, while the north wall makes the minimum contribution. Consequently, it is proposed to increase the area of the south roof and insulate the north wall. Thus, an asymmetrical roof configuration can receive 6% more solar radiation. Calculations show that an east-west greenhouse orientation lowers energy demand by 3%.

The combination of a Solar Assisted Geothermal Heat Pump system (SAGHP) with a multi-zone greenhouse is investigated to take advantage of water flooding in abandoned open pit mines in Canada. The envisioned system includes an Air Handling Unit (AHU), Heat Recovery Ventilation (HRV), daily Thermal Energy Storage (TES), and daily Domestic Hot Water (DHW). The main objective is to satisfy the greenhouse heating, cooling, and dehumidification loads, for the considered application, while minimizing energy consumption. This analysis is conducted using data extracted from a case study of a commercial, multi-zone greenhouse, considering different daily weather conditions throughout a year. To reduce the computation time, a clustering approach based on the K-Means method is applied to obtain a small number of typical weather days. Elbow, Dendrogram, and Silhouette approaches confirmed that it is possible to represent a year as six different Typical Days (TD), which can be further categorized as Heating only (TD1 and TD2), Heating/Cooling (TD3 and TD4), and Cooling only (TD5 and TD6). Dynamic Pinch Approach (DPA) showed a great ability to target the minimum energy consumption and maximize the potential heat recovery for each typical day. The study focuses on energy targeting, with discussion of preliminary design considerations, such as the solar hot water (SHW) system, Thermal Energy Storage (TES), and heat pumping. Results revealed that mine water can significantly improve the energy system efficiency, specifically where heating/cooling or only cooling is dominant (TD3, TD4, TD5, and TD6). For instance, by integrating an AHU with the greenhouse for the TDs where heating/cooling is dominant, 22.5% energy saving is achievable. The incorporation of heat pumping, waste heat recovery, and solar thermal collectors through mixed direct/indirect heat recovery (i.e. via TES) can reduce hot utility usage in the considered application by as much as 40%.

Although some research has been presented about the application of Kernel Least Mean Square (KLMS) algorithm in the estimation and approximation of functions, this algorithm wasn't applied to the control of nonlinear systems. In this paper, an efficient and novel adaptive Control strategy based on Kernel Least Mean Square is introduced to realize the control of a nonlinear aircraft system. Actually the KLMS algorithm is a growing radial basis function (GRBF) network, when Kernel function is a Gaussian function. In this research, based on Lyapunov theory, KLMS is used as an online method for tuning the kernel size to control nonlinear systems. This technique certifies the stability and provides an acceptable accuracy. Finally, we utilize this algorithm to control a nonlinear fighter aircraft by using a dynamic model of the F-18 aircraft.

The authors have requested that this preprint be removed from Research Square.