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Optimization of the Contracted Electric Power by Means of Genetic Algorithms

Author

Listed:
  • 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)

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.

Suggested Citation

  • Alfredo Alcayde & Raul Baños & Francisco M. Arrabal-Campos & Francisco G. Montoya, 2019. "Optimization of the Contracted Electric Power by Means of Genetic Algorithms," Energies, MDPI, vol. 12(7), pages 1-13, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1270-:d:219373
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    References listed on IDEAS

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    Cited by:

    1. Wen-Tung Lee & Shih-Cheng Horng & Chi-Fang Lin, 2019. "Application of Ordinal Optimization to Reactive Volt-Ampere Sources Planning Problems," Energies, MDPI, vol. 12(14), pages 1-16, July.
    2. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.
    3. Raheela Jamal & Baohui Men & Noor Habib Khan & Muhammad Asif Zahoor Raja, 2019. "Hybrid Bio-Inspired Computational Heuristic Paradigm for Integrated Load Dispatch Problems Involving Stochastic Wind," Energies, MDPI, vol. 12(13), pages 1-23, July.

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