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A unique meta-heuristic algorithm for optimization of electricity consumption in energy-intensive industries with stochastic inputs

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Abstract

This study presents an integrated meta-heuristic algorithm for forecasting electricity consumption in energy-intensive industries with stochastic inputs. The algorithm is based on genetic algorithm (GA), conventional regression and analysis of variance (ANOVA). The economic indicators used in this paper are price, value added, number of customers and electricity consumption in the last periods. The proposed algorithm uses ANOVA to select either GA or conventional regression for future demand estimation. Furthermore, if the null hypothesis in ANOVA is rejected, Duncan Multiple Range Test is used to identify which model is closer to actual data at α level of significance. To show the applicability and superiority of the proposed algorithm, the data for electricity consumption in energy-intensive industries of Iran from 1979 to 2009 (in two cases) is used.

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Authors and Affiliations

  1. School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanic, College of Engineering, University of Tehran, Tehran, Iran

    A. Azadeh

  2. Department of Industrial Engineering, Dalhousie University, Halifax, NS, Canada

    P. Sohrabi

  3. School of Business, UNSW, Canberra, BC 2610, Australia

    M. Saberi

Authors
  1. A. Azadeh
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  2. P. Sohrabi
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  3. M. Saberi
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Corresponding author

Correspondence to A. Azadeh.

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Significance

The significance of the proposed algorithm is twofold. First, it is flexible and identifies the best model based on the results of design of experiment and relative error, whereas previous studies consider the best-fitted GA model based on relative error results. Second, the proposed algorithm may identify conventional regression as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that GA always provides the best solutions and estimation.

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Azadeh, A., Sohrabi, P. & Saberi, M. A unique meta-heuristic algorithm for optimization of electricity consumption in energy-intensive industries with stochastic inputs. Int J Adv Manuf Technol 78, 1691–1703 (2015). https://doi.org/10.1007/s00170-014-6720-8

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  • DOI: https://doi.org/10.1007/s00170-014-6720-8

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