Sustainable energy management of solar greenhouses using open weather data on MACQU platform

Abstract

Precision energy management is very important for sustainability development of solar greenhouses, since huge energy demand for agricultural production both in quantity and quality. A proactive energy management, according to the optimal energy utilization in a look-ahead period with weather prediction, is presented and tested in this research. A multi-input-multi-output linear model of the energy balance of solar greenhouses based on on-line identification system can simulate greenhouse behavior and allow for predictive control. The good time allocation of available solar energy can be achieved by intelligent use of controls, such as store/retrieve fans and ventilation windows, i.e. solar energy to warm up the air or to be stored in the storage elements (wall, soil, etc.) or to be exhausted to outside. The proactive energy management can select an optimal trajectory of air temperature for the forecasted weather period to minimize plants' thermal 'cost' defined by an 'expert' in terms of set-points for the specific crop. The selection of temperature trajectory is formulated as a generalized traveling salesman problem (GTSP) with precedence constraints and is solved by a genetic algorithm (GA) in this research. The simulation study showed good potential for energy saving and timely allocation to prevent excessive crop stress. The active control elements in addition to predefining and applying, within energy constraints, optimal climate in the greenhouse, it also reduces the energy deficit, i.e. the working hours of the 'heater' in the sustained freezing weather, as well as the ventilation hours, that is, more energy harvest in the warm days. This intelligent solar greenhouse management system is being migrated to the web for serving a 'customer base' in the Internet Plus era. The capacity, of the concrete ground CAUA system (CAUA is an abbreviations from both China Agricultural University and Agricultural University of Athens), to implement web 'updates' of criteria, open weather data and models, on which control actions are based, is what makes use of Cloud Data for closing the loop of an effective Internet of Things (IoT) system, based on MACQU (MAnagement and Control for QUality) technological platform.

Closed-loop agriculture systems meta-research using text mining

“…To understand how the sun could be used to save energy, a Smith predictor was used in order to achieve the balance between the various spectrums of light in unison with the sun. Since the sun can be interrupted by clouds, a study applied cloud data to determine when a system should use reserved energy resources and when it is most efficient to do so (Li et al, 2018). By integrating weather information into the system controls for an intelligent solar greenhouse, the system can use data to drive its decision-making regarding climate control in the greenhouse.…”

Effects of organic amendments on soil properties and growth characteristics of Melon (Cucumis melo L.) under saline irrigation

“…where, C i and C f are the initial and final concentrations of Na + before and after amendments addition, mg/L; V is volume of NaCl solution, mL; m is the dosage of amendments, g. 2.3.3 Field capacity (FC), permanent wilting point (PWP) and available water capacity (AWC) of soil FC and PWP were determined at 0.33 and 15.0 bar (matrix potentials), respectively, using pressure plate apparatus. The AWC was determined as follows [25] :…”

Design Optimization of Proportional Plus Derivative Band Parameters Used in Greenhouse Ventilation by Response Surface Methodology

“…In order to control ventilation more precisely, many studies have been performed to design control systems by designing a model through the interpretation of physical phenomena occurring in the greenhouse (Villarreal-Guerrero et al, 2012;Hong and Lee, 2014;Montoya et al, 2016;Li et al, 2018). Such models can be classified into two types.…”