Mathematical modeling of production and biorefinery of energy crops

Abstract

Mathematical models have been widely used to simulate all aspects of bioenergy production systems including the growth kinetics of energy crops, conversion processes, production economics, supply logistics and environmental impacts. There is limited commercial experience to produce and process energy crops at a large scale around the world. Those models can provide powerful tools to design a bioenergy system and evaluate its technical feasibility, economics and environmental impacts. A crop growth model can be used to estimate the yields of energy crops in a region under different growth conditions. A geographical information system (GIS) model can be used to maximize the energy production of energy crops by indentifying suitable land to grow them based on their specific characteristics and the current use of the land. A combination of process models and reaction kinetics provides advanced computational tools for the design

Modeling Biowaste Biorefineries: A Review

“…Several biorefinery supply chain models have already been published. The most recent ones include, amongst others, the contributions of Wang et al (2015), Cambero et al (2016), Martinkus et al (2018), and Jonkman et al (2019). Jonkman et al (2019), for instance, presented a decision support tool for the sustainable design of a biorefinery supply chain network, taking local actors and their individual objectives into account.…”

“…Jonkman et al (2019) applied their developed modeling framework and decision support tool to the supply chain design of biorefinery using sugars beets as feedstock, located in the Netherlands. Wang et al (2015) on the other hand provided a mathematical model for the growth of energy crops. For the sake of simplicity, Wang et al (2015) does not consider temperature, fertilizers, and water as potential limiting factors.…”

“…Wang et al (2015) on the other hand provided a mathematical model for the growth of energy crops. For the sake of simplicity, Wang et al (2015) does not consider temperature, fertilizers, and water as potential limiting factors. The potential growth rate of energy crops (EC) is then defined by (Wang et al, 2015):…”

“…with G EC the energy crop growth index, ǫ the crop radiation utilization factor, φ the solar radiation, f PR the amount of radiation that is used in photosynthetic processes, k the leaf canopy extinction coefficient, LAI the leaf area index, and HI the harvest index (Wang et al, 2015). Another possibility of estimating the expected annually biomass harvest, is to incorporate Geographic Information Systems (GIS) into the strategic planning and supply chain developing process.…”

“…To obtain an economically viable biorefinery, these fluctuations need to be taken into account in the designing phase. To speed up the designing (and eventually implementation) of biowaste biorefineries, whilst taking the multitude of possible feedstocks into account, rigorous models are needed (Wang et al, 2015). The main goal of this contribution is to give the reader an overview of already existing models, as well as assessing their properties and extent.…”