Optimal energy performance on allocating energy crops

Rodias, Efthymios C., Lampridi, Maria, Sopegno, Alessandro , Berruto, Remigio, Banias, George, Bochtis, Dionysis and Busato, Patrizia (2019) Optimal energy performance on allocating energy crops. Biosystems Engineering, 181 . pp. 11-27. ISSN 15375110

Full content URL: http://doi.org/10.1016/j.biosystemseng.2019.02.007

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There is a variety of crops that may be considered as potential biomass production crops. In order to select the best suitable for cultivation crop for a given area, a number of several factors should be taken into account. During the crop selection process, a common framework should be followed focussing on financial or energy performance. Combining multiple crops and multiple fields for the extraction of the best allocation requires a model to evaluate various and complex factors given a specific objective. This paper studies the maximisation of total energy gained from the biomass production by energy crops, reduced by the energy costs of the production process. The tool calculates the energy balance using multiple crops allocated to multiple fields. Both binary programming and linear programming methods are employed to solve the allocation problem. Each crop is assigned to a field (or a combination of crops are allocated to each field) with the aim of maximising the energy balance provided by the production system. For the demonstration of the tool, a hypothetical case study of three different crops cultivated for a decade (Miscanthus x giganteus, Arundo donax, and Panicum virgatum) and allocated to 40 dispersed fields around a biogas plant in Italy is presented. The objective of the best allocation is the maximisation of energy balance showing that the linear solution is slightly better than the binary one in the basic scenario while focussing on suggesting alternative scenarios that would have an optimal energy balance.

Keywords:decision support systems, optimisation, Simulation
Subjects:H Engineering > H650 Systems Engineering
G Mathematical and Computer Sciences > G200 Operational Research
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
ID Code:39225
Deposited On:23 Dec 2019 09:48

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