Optimization of the Contracted Electric Power by Means of Genetic Algorithms

Alfredo Alcayde, Raul Baños, Francisco M. Arrabal-Campos and Francisco G. Montoya
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Alfredo Alcayde: Department of Engineering, University of Almería, 04120 Almería, Spain
Raul Baños: Department of Engineering, University of Almería, 04120 Almería, Spain
Francisco M. Arrabal-Campos: Department of Engineering, University of Almería, 04120 Almería, Spain
Francisco G. Montoya: Department of Engineering, University of Almería, 04120 Almería, Spain

Energies, 2019, vol. 12, issue 7, 1-13

Abstract: An adequate selection of an energy provider and tariff requires us to analyze the different alternatives to choose one that satisfies your needs. In particular, choosing the right electricity tariff is essential for reducing company costs and improving competitiveness. This paper analyzes the energy consumption of large consumers that make intensive use of electricity and proposes the use of genetic algorithms for optimizing the tariff selection. The aim is to minimize electricity costs including two factors: the cost of power contracted and the heavy penalties for excess of power demand over the power contracted in certain time periods. In order to validate the proposed methodology, a case study based on the real data of energy consumption of a large Spanish university is presented. The results obtained show that the genetic algorithm and other bio-inspired approaches are able to reduce the costs associated to the electricity bill.

Keywords: electric power contracts; electric energy costs; cost minimization; evolutionary computation; bio-inspired algorithms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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