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Optimal energy performance on allocating energy crops

Version 2 2024-03-12, 18:15
Version 1 2024-03-01, 11:38
journal contribution
posted on 2024-03-12, 18:15 authored by Efthymios C. Rodias, Maria Lampridi, Alessandro Sopegno, Remigio Berruto, George Banias, Dionysis BochtisDionysis Bochtis, Patrizia Busato

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.

History

School affiliated with

  • Lincoln Institute for Agri-Food Technology (Research Outputs)

Publication Title

Biosystems Engineering

Volume

181

Pages/Article Number

Nov-27

ISSN

15375110

Date Submitted

2019-12-23

Date Accepted

2019-05-01

Date of First Publication

2019-05-01

Date of Final Publication

2019-05-01

Date Document First Uploaded

2019-12-15

ePrints ID

39225

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