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Industrial Demand-Side Management by Means of Differential Evolution Considering Energy Price and Labour Cost

Author

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  • Alessandro Niccolai

    (Department of Energy, Politecnico di Milano, 20133 Milan, Italy)

  • Gaia Gianna Taje

    (Department of Energy, Politecnico di Milano, 20133 Milan, Italy)

  • Davide Mosca

    (Ratti S.p.a. Società Benefit, 22070 Guanzate, Italy)

  • Fabrizio Trombello

    (Ratti S.p.a. Società Benefit, 22070 Guanzate, Italy)

  • Emanuele Ogliari

    (Department of Energy, Politecnico di Milano, 20133 Milan, Italy)

Abstract

In the context of the high dependency on fossil fuels, the strong efforts aiming to shift towards a more sustainable world are having significant economic and political impacts. The electricity market is now encouraging prosumers to consume their own production, and thus reduce grid exchanges. Self-consumption can be increased using storage systems or rescheduling the loads. This effort involves not only residential prosumers but also industrial ones. The rescheduling process is an optimisation problem that can be effectively solved with evolutionary algorithms (EAs). In this paper, a specific procedure for bridging demand-side management from the theoretical application to a practical industrial scenario was introduced. In particular, the toroidal correction was used in the differential evolution with the aim of preventing the local minima worsening the effectiveness of the proposed method. Moreover, to achieve reasonable solutions, two different cost contributions have been considered: the energy cost and the labour cost. The method was tested on real data from a historical textile factory, Ratti S.p.A. Due to the nature of the loads, the design variables were the starting time of the 30 shiftable loads. The application of this procedure achieves a reduction in the total cost of approximately 99,500 EUR/year.

Suggested Citation

  • Alessandro Niccolai & Gaia Gianna Taje & Davide Mosca & Fabrizio Trombello & Emanuele Ogliari, 2022. "Industrial Demand-Side Management by Means of Differential Evolution Considering Energy Price and Labour Cost," Mathematics, MDPI, vol. 10(19), pages 1-16, October.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3605-:d:932244
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    References listed on IDEAS

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    Cited by:

    1. Yong-Hyuk Kim & Fabio Caraffini, 2023. "Preface to “Swarm and Evolutionary Computation—Bridging Theory and Practice”," Mathematics, MDPI, vol. 11(5), pages 1-3, March.

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