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A novel tool for the evaluation and assessment of demand response activities in the industrial sector

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  • Rodríguez-García, Javier
  • Álvarez-Bel, Carlos
  • Carbonell-Carretero, José-Francisco
  • Alcázar-Ortega, Manuel
  • Peñalvo-López, Elisa

Abstract

This paper introduces a novel tool for industrial customers to perform a cost-benefit analysis regarding the implementation of Demand Response (DR) strategies in their facilities with the final goal of softening the impact of RES intermittency in the grid. The dynamic simulation tool focuses on assessing the participation of industries in reserve energy markets in the same conditions as generators offering capacity reserve, energy reserve or both of them and taking into account all the technical restrictions of production processes as well as possible extra costs due to the implementation of DR (additional labour cost, productivity losses, etc.) Main innovations of the methodology are the DR assessment carried out per process and the introduction of the “margin of decision” as a decision making strategy for the energy consumer.

Suggested Citation

  • Rodríguez-García, Javier & Álvarez-Bel, Carlos & Carbonell-Carretero, José-Francisco & Alcázar-Ortega, Manuel & Peñalvo-López, Elisa, 2016. "A novel tool for the evaluation and assessment of demand response activities in the industrial sector," Energy, Elsevier, vol. 113(C), pages 1136-1146.
    • Handle: RePEc:eee:energy:v:113:y:2016:i:c:p:1136-1146
    DOI: 10.1016/j.energy.2016.07.146
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    References listed on IDEAS

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    7. Alcázar-Ortega, Manuel & Álvarez-Bel, Carlos & Escrivá-Escrivá, Guillermo & Domijan, Alexander, 2012. "Evaluation and assessment of demand response potential applied to the meat industry," Applied Energy, Elsevier, vol. 92(C), pages 84-91.
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    4. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    5. Javier Rodríguez-García & David Ribó-Pérez & Carlos Álvarez-Bel & Elisa Peñalvo-López, 2019. "Novel Conceptual Architecture for the Next-Generation Electricity Markets to Enhance a Large Penetration of Renewable Energy," Energies, MDPI, vol. 12(13), pages 1-23, July.
    6. Braeuer, Fritz & Rominger, Julian & McKenna, Russell & Fichtner, Wolf, 2019. "Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry," Applied Energy, Elsevier, vol. 239(C), pages 1424-1440.
    7. Fatras, Nicolas & Ma, Zheng & Duan, Hongbo & Jørgensen, Bo Nørregaard, 2022. "A systematic review of electricity market liberalisation and its alignment with industrial consumer participation: A comparison between the Nordics and China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).
    9. Schipfer, F. & Mäki, E. & Schmieder, U. & Lange, N. & Schildhauer, T. & Hennig, C. & Thrän, D., 2022. "Status of and expectations for flexible bioenergy to support resource efficiency and to accelerate the energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    10. Kirchem, Dana & Lynch, Muireann Á & Casey, Eoin & Bertsch, Valentin, 2019. "Demand response within the energy-for-water-nexus: A review," Papers WP637, Economic and Social Research Institute (ESRI).
    11. Jun Dong & Huijuan Huo & Dongran Liu & Rong Li, 2017. "Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach," Sustainability, MDPI, vol. 9(8), pages 1-32, July.
    12. Gómez, Javier & Chicaiza, William D. & Escaño, Juan M. & Bordons, Carlos, 2023. "A renewable energy optimisation approach with production planning for a real industrial process: An application of genetic algorithms," Renewable Energy, Elsevier, vol. 215(C).

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