IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v238y2019icp1036-1047.html
   My bibliography  Save this article

Robust Optimization of Demand Response Power Bids for Drinking Water Systems

Author

Listed:
  • Mkireb, Chouaïb
  • Dembélé, Abel
  • Jouglet, Antoine
  • Denoeux, Thierry

Abstract

The development of smart grids represents a major breakthrough in the management of electric power and drinking water systems. On the one hand, smart grids have contributed to the development of energy efficiency and demand side management mechanisms such as Demand Response, making it possible to reduce peak load and adapt elastic demand to fluctuation generation. On the other hand, smart water networks and sophisticated Supervisory Control and Data Acquisition systems in the water industry have allowed one to optimize, control and monitor the water flow throughout its entire process. Being a highly energy intensive industry and having an electrical flexibility by the presence of storage elements such as tanks, drinking water systems have the ability to address energy efficiency mechanisms such as Demand Response. In this paper, the French demand response mechanism in spot power markets is presented. Then, a chance constrained problem is formulated to integrate water systems flexibility to power system operation, under water demand uncertainties. Numerical results are discussed based on a real water system in France, demonstrating the relevance of the approach in terms of financial benefits and risk management.

Suggested Citation

  • Mkireb, Chouaïb & Dembélé, Abel & Jouglet, Antoine & Denoeux, Thierry, 2019. "Robust Optimization of Demand Response Power Bids for Drinking Water Systems," Applied Energy, Elsevier, vol. 238(C), pages 1036-1047.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:1036-1047
    DOI: 10.1016/j.apenergy.2019.01.124
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919301461
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.01.124?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rious, Vincent & Perez, Yannick & Roques, Fabien, 2015. "Which electricity market design to encourage the development of demand response?," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 128-138.
    2. D’Ambrosio, Claudia & Lodi, Andrea & Wiese, Sven & Bragalli, Cristiana, 2015. "Mathematical programming techniques in water network optimization," European Journal of Operational Research, Elsevier, vol. 243(3), pages 774-788.
    3. van Staden, Adam Jacobus & Zhang, Jiangfeng & Xia, Xiaohua, 2011. "A model predictive control strategy for load shifting in a water pumping scheme with maximum demand charges," Applied Energy, Elsevier, vol. 88(12), pages 4785-4794.
    4. Ashok, S. & Banerjee, R., 2000. "Load-management applications for the industrial sector," Applied Energy, Elsevier, vol. 66(2), pages 105-111, June.
    5. Boisvert, Richard N. & Cappers, Peter A. & Neenan, Bernie, 2002. "The Benefits of Customer Participation in Wholesale Electricity Markets," The Electricity Journal, Elsevier, vol. 15(3), pages 41-51, April.
    6. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    7. Severin Borenstein, 2005. "The Long-Run Efficiency of Real-Time Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-116.
    8. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    9. Menke, Ruben & Abraham, Edo & Parpas, Panos & Stoianov, Ivan, 2016. "Demonstrating demand response from water distribution system through pump scheduling," Applied Energy, Elsevier, vol. 170(C), pages 377-387.
    10. Finon, Dominique & Pignon, Virginie, 2008. "Capacity mechanisms in imperfect electricity markets," Utilities Policy, Elsevier, vol. 16(3), pages 141-142, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lynch, Muireann Á. & Nolan, Sheila & Devine, Mel T. & O’Malley, Mark, 2019. "The impacts of demand response participation in capacity markets," Applied Energy, Elsevier, vol. 250(C), pages 444-451.
    2. Isaías Faria Silva & Cédric Bentz & Mustapha Bouhtou & Matthieu Chardy & Safia Kedad-Sidhoum, 2024. "Optimization of battery management in telecommunications networks under energy market incentives," Annals of Operations Research, Springer, vol. 332(1), pages 949-988, January.
    3. Nikolaos Kolokas & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "Multi-Step Energy Demand and Generation Forecasting with Confidence Used for Specification-Free Aggregate Demand Optimization," Energies, MDPI, vol. 14(11), pages 1-36, May.
    4. Mennatalla Elbalki & Mostafa F. Shaaban & Ahmed Osman & Ariana Pietrasanta & Mohammed Kamil & Abdelfatah Ali, 2024. "Optimizing Integrated Water and Electrical Networks through a Holistic Water–Energy Nexus Approach," Sustainability, MDPI, vol. 16(9), pages 1-22, April.
    5. Reis, Ana L. & Lopes, Marta A.R. & Andrade-Campos, A. & Henggeler Antunes, Carlos, 2023. "A review of operational control strategies in water supply systems for energy and cost efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    6. Wagner, Lukas Peter & Reinpold, Lasse Matthias & Kilthau, Maximilian & Fay, Alexander, 2023. "A systematic review of modeling approaches for flexible energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    7. Amaral Lopes, Rui & Grønborg Junker, Rune & Martins, João & Murta-Pina, João & Reynders, Glenn & Madsen, Henrik, 2020. "Characterisation and use of energy flexibility in water pumping and storage systems," Applied Energy, Elsevier, vol. 277(C).
    8. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
    9. Soleimani, Borhan & Keihan Asl, Dariush & Estakhr, Javad & Seifi, Ali Reza, 2022. "Integrated optimization of multi-carrier energy systems: Water-energy nexus case," Energy, Elsevier, vol. 257(C).
    10. Majid, A. & van Zyl, J.E. & Hall, J.W., 2022. "The influence of temporal variability and reservoir management on demand-response in the water sector," Applied Energy, Elsevier, vol. 305(C).
    11. Pang, Yuexia & He, Yongxiu & Jiao, Jie & Cai, Hua, 2020. "Power load demand response potential of secondary sectors in China: The case of western Inner Mongolia," Energy, Elsevier, vol. 192(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonvin, Gratien & Demassey, Sophie & Le Pape, Claude & Maïzi, Nadia & Mazauric, Vincent & Samperio, Alfredo, 2017. "A convex mathematical program for pump scheduling in a class of branched water networks," Applied Energy, Elsevier, vol. 185(P2), pages 1702-1711.
    2. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
    3. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    4. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    5. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
    6. Bert Willems & Juulia Zhou, 2020. "The Clean Energy Package and Demand Response: Setting Correct Incentives," Energies, MDPI, vol. 13(21), pages 1-19, October.
    7. Nge, Chee Lim & Ranaweera, Iromi U. & Midtgård, Ole-Morten & Norum, Lars, 2019. "A real-time energy management system for smart grid integrated photovoltaic generation with battery storage," Renewable Energy, Elsevier, vol. 130(C), pages 774-785.
    8. Bergaentzlé, Claire & Clastres, Cédric & Khalfallah, Haikel, 2014. "Demand-side management and European environmental and energy goals: An optimal complementary approach," Energy Policy, Elsevier, vol. 67(C), pages 858-869.
    9. Bren, Austin & Saghafian, Soroush, 2018. "Data-Driven Percentile Optimization for Multi-Class Queueing Systems with Model Ambiguity: Theory and Application," Working Paper Series rwp18-008, Harvard University, John F. Kennedy School of Government.
    10. Majid, A. & van Zyl, J.E. & Hall, J.W., 2022. "The influence of temporal variability and reservoir management on demand-response in the water sector," Applied Energy, Elsevier, vol. 305(C).
    11. Wang, Qipeng & Zhao, Liang, 2023. "Data-driven stochastic robust optimization of sustainable utility system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    12. Cédric Clastres & Haikel Khalfallah, 2020. "Retailers' strategies facing demand response and markets interactions," Working Papers hal-03167543, HAL.
    13. Grani A. Hanasusanto & Vladimir Roitch & Daniel Kuhn & Wolfram Wiesemann, 2017. "Ambiguous Joint Chance Constraints Under Mean and Dispersion Information," Operations Research, INFORMS, vol. 65(3), pages 751-767, June.
    14. Evers, L. & Glorie, K.M. & van der Ster, S. & Barros, A.I. & Monsuur, H., 2012. "The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared," Econometric Institute Research Papers EI 2012-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Claire Bergaentzlé & Cédric Clastres & Haikel Khalfallah, 2014. "Demand-side management and European environmental and energy goals: an optimal complementary approach," Post-Print halshs-00928678, HAL.
    16. Stötzer, Martin & Hauer, Ines & Richter, Marc & Styczynski, Zbigniew A., 2015. "Potential of demand side integration to maximize use of renewable energy sources in Germany," Applied Energy, Elsevier, vol. 146(C), pages 344-352.
    17. Soyster, A.L. & Murphy, F.H., 2017. "Data driven matrix uncertainty for robust linear programming," Omega, Elsevier, vol. 70(C), pages 43-57.
    18. Claire Bergaentzlé & Cédric Clastres, 2013. "Tarifications dynamiques et efficacité énergétique : l'apport des Smart Grids," Post-Print halshs-00822731, HAL.
    19. Hatami-Marbini, Adel & Arabmaldar, Aliasghar, 2021. "Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application," European Journal of Operational Research, Elsevier, vol. 295(2), pages 604-620.
    20. Finn, P. & O’Connell, M. & Fitzpatrick, C., 2013. "Demand side management of a domestic dishwasher: Wind energy gains, financial savings and peak-time load reduction," Applied Energy, Elsevier, vol. 101(C), pages 678-685.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:238:y:2019:i:c:p:1036-1047. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.