Optimal Solar Greenhouses Design Using Multiobjective Genetic Algorithm

Abstract

In greenhouse horticulture, solar energy is the key to extending the greenhouse using seasonal or daily thermal storage technology and decreasing the energy consumption rate, especially in subtropical climate areas. Therefore, the present research aims to reach the optimal physical parameters of common greenhouses in northern areas of Iran to harness the best possible amount of solar energy in a year. Three common types of greenhouses, including even-span, modified arch and Quonset types, are considered. Three-floor area sizes are investigated for each shape to find the optimal physical parameters based on each greenhouse size. A mathematical model is proposed that uses the total solar fraction to compute the radiation loss and the available hourly transmitted solar radiation inside the greenhouse. The best design parameters for each type and size of greenhouses are obtained through a multi-objective optimization technique to give maximum and minimum available solar energy in winter and summer. The results show that optimized greenhouses can capture sufficient solar radiation in cold months of a year for growing offseason vegetables in Rasht city. The optimal wall height and roof angle for an even-span greenhouse are found to be 3.8 m and 16°, respectively. The results also revealed that in a modified arch greenhouse, the ellipse aspect ratio for small and large sizes is 0.8 and for medium size is 0.25. For Quonset type, ellipse aspect ratio to width ratio for medium and large sizes is 0.6 and for small size is 0.8. The findings of the study showed that the Quonset greenhouse offers the highest performance compared to other greenhouses for the efficient use of solar energy throughout the year.

Keywords

• Solar radiation
• greenhouse design
• multi-objective optimization
• genetic algorithm
• total solar fraction