Li Li, Jieyu Li, Haihua Wang, Ts. Georgieva, K. P. Ferentinos, K. G. Arvanitis, N. A. Sygrimis. Sustainable energy management of solar greenhouses using open weather data on MACQU platform[J]. International Journal of Agricultural and Biological Engineering, 2018, 11(1): 74-82. DOI: 10.25165/j.ijabe.20181101.2713
Citation: Li Li, Jieyu Li, Haihua Wang, Ts. Georgieva, K. P. Ferentinos, K. G. Arvanitis, N. A. Sygrimis. Sustainable energy management of solar greenhouses using open weather data on MACQU platform[J]. International Journal of Agricultural and Biological Engineering, 2018, 11(1): 74-82. DOI: 10.25165/j.ijabe.20181101.2713

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

  • 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.
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