Decision support for evaluating energy demand in vinification processes using fuzzy sets theory

Authors

  • N Musee Department of Process Engineering University of Stellenbosch
  • L Lorenzen Department of Process Engineering University of Stellenbosch
  • C Aldrich Department of Process Engineering University of Stellenbosch

DOI:

https://doi.org/10.17159/2413-3051/2006/v17i4a3190

Keywords:

fuzzy logic, energy minimization, vinification, wine industry, maceration 1

Abstract

The current trend associated with high energy demand, depletion of energy reserves and low potential of renewable energy sources linked with strong industrial growth, is increasingly becoming unsustainable. As a result, production costs have increased considerably in the process industries, mainly owing to skewed energy demand and supply realities. A feasible strategy for meeting these challenges is to reduce energy consumption per unit throughput. However, to obtain a workable solution, decision makers may have to deal with energy management variables that are ambiguous, which makes solving the energy minimization problem with conventional numerical approaches very difficult. In this paper, we consider an alternative approach based on fuzzy logic to qualitatively evaluate the energy demand associated with an industrial cooling process. The model was formulated based on Mamdani fuzzy logic inferencing and implemented in MATLAB 6.5 via the Fuzzy Logic toolbox. The energy demands pertaining to specific variables were independently estimated, followed by an estimate of the overall energy consumption. The procedure is demonstrated via a case study of cooling at the maceration stage of a vinification process in the wine industry.

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Published

2006-11-01

How to Cite

Musee, N., Lorenzen, L., & Aldrich, C. (2006). Decision support for evaluating energy demand in vinification processes using fuzzy sets theory. Journal of Energy in Southern Africa, 17(4), 4–18. https://doi.org/10.17159/2413-3051/2006/v17i4a3190