IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v207y2017icp176-194.html
   My bibliography  Save this article

Corrective receding horizon scheduling of flexible distributed multi-energy microgrids

Author

Listed:
  • Holjevac, Ninoslav
  • Capuder, Tomislav
  • Zhang, Ning
  • Kuzle, Igor
  • Kang, Chongqing

Abstract

The goal of the paper is to provide a comprehensive operational flexibility evaluation of different Multi-energy Microgrid (MEM) options. This is done by incorporating Mixed Integer Liner Programming (MILP) model for annual simulations and expanding it with Receding Horizon Model Predictive Control (RH-MPC) algorithm for short term daily operational analyses. The model optimizes flows of various energy vectors: heat, fossil fuels (natural gas), cooling and electricity, coordinating different microgrid elements with the goal of serving final consumer needs and actively participating in energy markets.

Suggested Citation

  • Holjevac, Ninoslav & Capuder, Tomislav & Zhang, Ning & Kuzle, Igor & Kang, Chongqing, 2017. "Corrective receding horizon scheduling of flexible distributed multi-energy microgrids," Applied Energy, Elsevier, vol. 207(C), pages 176-194.
    • Handle: RePEc:eee:appene:v:207:y:2017:i:c:p:176-194
    DOI: 10.1016/j.apenergy.2017.06.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917307973
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.06.045?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    3. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2016. "Low carbon technologies as providers of operational flexibility in future power systems," Applied Energy, Elsevier, vol. 168(C), pages 724-738.
    4. Holjevac, Ninoslav & Capuder, Tomislav & Kuzle, Igor, 2015. "Adaptive control for evaluation of flexibility benefits in microgrid systems," Energy, Elsevier, vol. 92(P3), pages 487-504.
    5. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    6. Parisio, Alessandra & Rikos, Evangelos & Tzamalis, George & Glielmo, Luigi, 2014. "Use of model predictive control for experimental microgrid optimization," Applied Energy, Elsevier, vol. 115(C), pages 37-46.
    7. Capuder, Tomislav & Mancarella, Pierluigi, 2014. "Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options," Energy, Elsevier, vol. 71(C), pages 516-533.
    8. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    9. Mashayekh, Salman & Stadler, Michael & Cardoso, Gonçalo & Heleno, Miguel, 2017. "A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids," Applied Energy, Elsevier, vol. 187(C), pages 154-168.
    10. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    11. Hanna, Ryan & Ghonima, Mohamed & Kleissl, Jan & Tynan, George & Victor, David G., 2017. "Evaluating business models for microgrids: Interactions of technology and policy," Energy Policy, Elsevier, vol. 103(C), pages 47-61.
    12. Majzoobi, Alireza & Khodaei, Amin, 2017. "Application of microgrids in providing ancillary services to the utility grid," Energy, Elsevier, vol. 123(C), pages 555-563.
    13. Troy, Niamh & Denny, Eleanor & O'Malley, Mark, 2010. "Base-load cycling on a system with significant wind penetration," MPRA Paper 34848, University Library of Munich, Germany.
    14. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    15. Verda, Vittorio & Colella, Francesco, 2011. "Primary energy savings through thermal storage in district heating networks," Energy, Elsevier, vol. 36(7), pages 4278-4286.
    16. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    17. Baringo, L. & Conejo, A.J., 2011. "Wind power investment within a market environment," Applied Energy, Elsevier, vol. 88(9), pages 3239-3247.
    Full references (including those not matched with items on IDEAS)

    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. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    2. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    3. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    4. Candas, Soner & Reveron Baecker, Beneharo & Mohapatra, Anurag & Hamacher, Thomas, 2023. "Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination," Applied Energy, Elsevier, vol. 343(C).
    5. Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
    6. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    7. Carvallo, Claudio & Jalil-Vega, Francisca & Moreno, Rodrigo, 2023. "A multi-energy multi-microgrid system planning model for decarbonisation and decontamination of isolated systems," Applied Energy, Elsevier, vol. 343(C).
    8. Good, Nicholas & Martínez Ceseña, Eduardo A. & Heltorp, Christopher & Mancarella, Pierluigi, 2019. "A transactive energy modelling and assessment framework for demand response business cases in smart distributed multi-energy systems," Energy, Elsevier, vol. 184(C), pages 165-179.
    9. Scheller, Fabian & Burgenmeister, Balthasar & Kondziella, Hendrik & Kühne, Stefan & Reichelt, David G. & Bruckner, Thomas, 2018. "Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach," Applied Energy, Elsevier, vol. 228(C), pages 2009-2023.
    10. Kate Doubleday & Faeza Hafiz & Andrew Parker & Tarek Elgindy & Anthony Florita & Gregor Henze & Graziano Salvalai & Shanti Pless & Bri‐Mathias Hodge, 2019. "Integrated distribution system and urban district planning with high renewable penetrations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    11. Holjevac, Ninoslav & Capuder, Tomislav & Kuzle, Igor, 2015. "Adaptive control for evaluation of flexibility benefits in microgrid systems," Energy, Elsevier, vol. 92(P3), pages 487-504.
    12. Timo Kannengießer & Maximilian Hoffmann & Leander Kotzur & Peter Stenzel & Fabian Schuetz & Klaus Peters & Stefan Nykamp & Detlef Stolten & Martin Robinius, 2019. "Reducing Computational Load for Mixed Integer Linear Programming: An Example for a District and an Island Energy System," Energies, MDPI, vol. 12(14), pages 1-27, July.
    13. Perera, A.T.D. & Coccolo, Silvia & Scartezzini, Jean-Louis & Mauree, Dasaraden, 2018. "Quantifying the impact of urban climate by extending the boundaries of urban energy system modeling," Applied Energy, Elsevier, vol. 222(C), pages 847-860.
    14. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    15. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).
    16. De Mel, Ishanki & Klymenko, Oleksiy V. & Short, Michael, 2024. "Discrete optimal designs for distributed energy systems with nonconvex multiphase optimal power flow," Applied Energy, Elsevier, vol. 353(PB).
    17. Dominković, D.F. & Bačeković, I. & Sveinbjörnsson, D. & Pedersen, A.S. & Krajačić, G., 2017. "On the way towards smart energy supply in cities: The impact of interconnecting geographically distributed district heating grids on the energy system," Energy, Elsevier, vol. 137(C), pages 941-960.
    18. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    19. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    20. Matija Kostelac & Lin Herenčić & Tomislav Capuder, 2022. "Planning and Operational Aspects of Individual and Clustered Multi-Energy Microgrid Options," Energies, MDPI, vol. 15(4), pages 1-17, February.

    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:207:y:2017:i:c:p:176-194. 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.