Sensitivity analysis of the DehumReq model to evaluate the impact of predominant factors on dehumidification requirement of greenhouses in cold regions
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引用次数: 3
Abstract
In this study, the sensitivity of a novel dehumidification requirement model (DehumReq) is analyzed to evaluate the effect of the predominant factors on the dehumidification needs of the greenhouses. The hourly dehumidification demand and sensitivity coefficient (SC) are estimated for three different seasons: warm (July), mild (May), and cold (November), by using the local sensitivity analysis method. Based on SC values, the solar radiation, air exchange, leaf area index (LAI), and indoor setpoints (temperature, relative humidity (RH), and water vapor partial pressure (WVPP)) have significant impact on the dehumidification needs, and the impact varies from season to season. Most parameters have a higher SC in summer, whereas solar radiation and LAI have a higher SC in mild season. The dehumidification load increases 4 times of its base value with increasing solar radiation by 200 W/m2, and the highest LAI (10) caused 5 times increment of the load. The changing of WVPP from its base value (1.5 kPa) to maximum (2.9 kPa) reduces the load 70% in summer. Air exchange was found to be the most crucial parameter because it is the main dehumidification approach that has a large range and is easily adjustable for any greenhouses. Sufficient air exchange by ventilation or infiltration will reduce the dehumidification load to zero in May and November and minimizes it to only nighttime load in July. For the other parameters, higher ambient air RH and indoor air speed will result in higher the dehumidification load; whereas higher inner surface condensation will result in lower dehumidification load. The result of this study will assist in the selection of the most efficient moisture control strategies and techniques for greenhouse humidity control.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining