Abstract:A techno-economic modelling tool has been developed to examine the feasibility of biomass combined heat and power (CHP) technologies to provide the energy and CO 2 demands of commercial horticultural glasshouses. Using the UK as a case study, energy and CO 2 demands of candidate glasshouse installations on an hourly basis are established using both measured and benchmark datasets. Modelled electrical and thermal generation profiles for a number of commercially available small-scale biomass CHP systems of rated… Show more
“…Biomass is widely available across the UK and comes from a large number of different sources, including combustible agricultural residues, energy crops and wood and woody wastes from forestry and industry [1][2][3]. Biomass, being considered to be a major potential source of green energy in the near future, has generated a considerable amount of interest and may replace much of energy now supplied by these fossil fuels in energy production systems.…”
“…Biomass is widely available across the UK and comes from a large number of different sources, including combustible agricultural residues, energy crops and wood and woody wastes from forestry and industry [1][2][3]. Biomass, being considered to be a major potential source of green energy in the near future, has generated a considerable amount of interest and may replace much of energy now supplied by these fossil fuels in energy production systems.…”
“…(1) is defined as the input exergy and summarized in the following equation. (2) The cogeneration system using the first and the second laws of thermodynamics can be written as [19]. (3) (4) By applying the energy balance to the source and the sink, the input and output heat are described as follow: (5) (6) Finally, the total thermal conductance can be defined as: (7) 2) Optimization method This part presents how to develop and to validate a model based on Lagrange multipliers method.…”
Abstract. This paper presents the modeling, control scheme and optimization of a small scale combined heat and power (SSCHP) in island operating mode. A thermo dynamic model is carried out for SSCHP engine using Carnot machine method, while an optimization technique is formulated to identify CHP engine parameters. In addition, a dynamic model is built based on a system identification toolbox for SSCHP engine to study the dynamic behavior of the SSCHP during operating mode. In island mode, the Fuzzy logic controller (FLC) is used to regulate the inputs of SSCHP, and to match electric load demand. The complete system was represented and simulated in Matlab/Simulink.
“…The quantification of the energy requirements of glasshouse food production has been investigated previously in the literature, for example in studies such as those in ASABE (2008), Chalabi et al (2002), Gupta and Chandra (2002), Moreton and Rowley (2012), Ozkan et al (2011aOzkan et al ( , 2011b, Papadopoulos and Hao (1997), Subi c et al (2015), Mariani et al (2016), Luo et al (2005) and Wass and Barrie (1984). In Papadopoulos and Hao (1997), the authors investigated the effect of the glasshouse cover material in three tomato glasshouses focusing on yields, energy requirements and productivity, whereas Gupta and Chandra (2002) focused on the effects of a glasshouse's design on its energy requirements, with a particular interest in the shape and orientation of a glasshouse in India.…”
a b s t r a c tQuantifying the use of resources in food production and its environmental impact is key to identifying distinctive measures which can be used to develop pathways towards low-carbon food systems. In this paper, a first-principle modelling approach is developed, referred to as gThermaR (Glasshouse-Thermal Requirements). gThermaR is a generic tool that focuses on the energy requirements of protected heated production, by integrating holistic energy, carbon, and cost modelling, food production, data analytics and visualization. The gThermaR tool employs historic data from weather stations, growing schedules and requirements specific to grower and product needs (e.g. set-point temperatures, heating periods, etc.) in order to quantify the heating and cooling requirements of glasshouse food production. In the present paper, a case study is reported that employs a database compiled for the UK. Another relevant feature of the tool is that it can quantify the effects that spatial and annual weather trends can have on these heating and cooling requirements. The main contribution of this work, therefore, concerns the development a tool that can provide a simple integrated approach for performing a wide range of analyses relevant to the thermal requirements of heated glasshouses. The tool is validated through collaborations with industrial partners and showcased in a case study of a heated glasshouse in the UK, offering the capacity to benchmark and compare different glasshouse types and food growth processes. Results from the case study indicate that a significant reduction in the heating requirement and, therefore, carbon footprint, of the facility can be achieved by improving key design and operational parameters. Results indicate savings in the peak daily and annual heating requirements of 44e50% and 51e57% respectively, depending on the region where the glasshouse is located. This improvement is also reflected in the carbon emissions and operating costs for the different energy sources considered. Furthermore, the temporal variability/uncertainty of the annual energy requirements and of the peak daily energy requirements are found to be considerably lowered through improvements to the glasshouse attributes. Overall, gThermaR proves its value in quantifying and identifying key factors that have a significant impact on energy requirements of heated glasshouses. Such valuable outputs are invaluable for stakeholders in the food industry that have an interest in mapping the sustainability and mitigating the carbon footprint of their supply chain processes.
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