4 research outputs found
Factors affecting energy consumption and productivity in greenhouses
Aim of study: To investigate the impact factors affecting the greenhouse environment on energy consumption and productivity.Area of study: Alborz province of Iran during the period 2018–2020.Material and methods: In this study, 18 active units of greenhouse owners in Alborz province of Iran that had necessary standards were identified. Then, upper and lower amplitudes of the variables affecting productivity and energy consumption in greenhouses were calculated using a type-2 fuzzy neural network, Matlab 2017 software. Area, temperature, energy exchange, environmental evapotranspiration and relative humidity were studied as indicators.Main results: With each unit of temperature, energy consumption and productivity increased by 0.737% and 0.741%, respectively; with each unit of energy exchange, they increased by 0.813% and 0.696%, respectively; with each unit of evaporation and transpiration of the environment, they increased by 0.593% and 0.869%, respectively; and with each unit of humidity, they increased by 0.398% and 0.509%, respectively.Research highlights: The factors affecting the greenhouse environment such as area, temperature, evapotranspiration and relative humidity had a significant effect on productivity in studying greenhouses and therefore increasing their productivity. According to the results, the model’s ability in energy consumption was better than that for energy efficiency prediction. Also, greenhouse ranking was done by FAHP method
Optimization of shape and direction of the greenhouse using gray wolf algorithm
Greenhouse structure is one of the most important factors in the greenhouse industry; increasing energy prices is a major challenge for greenhouse owners. Greenhouses should be so designed that they have high light transmission especially in winter and at the same time satisfy the requirements of the construction cost and the safety against the loads which may be imposed upon them. In this research, the goal is to optimize the shape and direction of the greenhouse to minimize the energy required for heating. The design parameters in this work are determined for two different types of greenhouses with the target functions, with the gray wolf optimization method. Optimization of energy consumption for different models of greenhouse and different materials was performed using gray wolf algorithm. Accordingly, in each case, the best design parameters and greenhouse model were obtained and energy consumption was calculated in summer and winter. At the end of the study, the gray wolf algorithm was compared with the particle swarm algorithm, which indicated that the gray wolf algorithm was powerful
Construction and evaluation of solar system for fuzzy control of intelligent irrigation system
Restriction of water resources requires optimal use of agricultural water resources. In this regard, the use of new technologies to increase irrigation efficiency. In arid and extremely arid regions such as Iran, the time and duration of irrigation is the key to achieving sustainable irrigation. Therefore, in this research, after constructing a garden in Imam Khomeini Higher Education Center with an area of ​​500 square meters, and installing equipment related to irrigation and fertilization, a fuzzy control system was designed to optimize water consumption and inputs, intelligent irrigation and fertilization system. The present study presents a practical solution based on artificial intelligence in which all stages of design and implementation are described. In this system, a microcontroller was first used to process and store data on soil moisture, ambient temperature and solar radiation. The fuzzy logic controller then takes these three inputs and based on the table of rules created for a specific product, produces the desired irrigation time and duration. Experimental results showed that, the developed system accurately compensates for the amount of water lost through evapotranspiration. It seems that the use of fuzzy control has a great impact on irrigation management and planning in the near future