IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p8108-d854566.html
   My bibliography  Save this article

Survey of Simulation Tools to Assess Techno-Economic Benefits of Smart Grid Technology in Integrated T&D Systems

Author

Listed:
  • Fernando Salinas-Herrera

    (Département de Génie Électrique et de Génie Informatique, Université Laval, Québec, QC G1V 0A6, Canada)

  • Ali Moeini

    (Hydro-Québec, Montréal, QC H2Z 1A4, Canada)

  • Innocent Kamwa

    (Département de Génie Électrique et de Génie Informatique, Université Laval, Québec, QC G1V 0A6, Canada)

Abstract

In order to succeed in the energy transition, the power system must become more flexible in order to enable the economical hosting of more intermittent distributed energy resources (DER) and smart grid technologies. New technical solutions, generally based on the connection of various components coupled to the power system via smart power electronic converters or through ICT, can help to take up these challenges. Such innovations (e.g., decarbonization technologies and smart grids) may reduce the costs of future power systems and the environmental footprint. In this regard, the techno-economic assessment of smart grid technologies is a matter of interest, especially in the urge to develop more credible options for deep decarbonization pathways over the long term. This work presents a literature survey of existing simulation tools to assess the techno-economic benefits of smart grid technologies in integrated T&D systems. We include the state-of-the-art tools and categorize them in their multiple aspects, cover smart grid technology, approach methods, and research topics, and include (or complete) the analysis with other dimensions (smart-grid related) of key interest for future power systems analysis such as environmental considerations, techno-economic aspects (social welfare), spatial scope, time resolution (granularity), and temporal scope, among others. We surveyed more than 40 publications, and 36 approaches were identified for the analysis of integrated T&D systems. As a relatively new research area, there are various promising candidates to properly simulate integrated T&D systems. Nevertheless, there is not yet a consensus on a specific framework that should be adopted by researchers in academia and industry. Moreover, as the power system is evolving rapidly towards a smart grid system, novel technologies and flexibility solutions are still under study to be integrated on a large scale. This review aims to offer new criteria for researchers in terms of smart-grid related dimensions and the state-of-the-art trending of simulation tools that holistically evaluate techno-economic aspects of the future power systems in an integrated T&D systems environment. As an imperative research matter for future energy systems, this article seeks to contribute to the discussion of which pathway the scientific community should focus on for a successful shift towards decarbonized energy systems.

Suggested Citation

  • Fernando Salinas-Herrera & Ali Moeini & Innocent Kamwa, 2022. "Survey of Simulation Tools to Assess Techno-Economic Benefits of Smart Grid Technology in Integrated T&D Systems," Sustainability, MDPI, vol. 14(13), pages 1-36, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:8108-:d:854566
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/8108/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/13/8108/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    2. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    3. Nguyen, Hieu Trung & Battula, Swathi & Takkala, Rohit Reddy & Wang, Zhaoyu & Tesfatsion, Leigh, 2019. "An integrated transmission and distribution test system for evaluation of transactive energy designs," Applied Energy, Elsevier, vol. 240(C), pages 666-679.
    4. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    5. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    6. Wolisz, Henryk & Schütz, Thomas & Blanke, Tobias & Hagenkamp, Markus & Kohrn, Markus & Wesseling, Mark & Müller, Dirk, 2017. "Cost optimal sizing of smart buildings' energy system components considering changing end-consumer electricity markets," Energy, Elsevier, vol. 137(C), pages 715-728.
    7. Hermann, Alexander & Jensen, Tue Vissing & Østergaard, Jacob & Kazempour, Jalal, 2022. "A complementarity model for electric power transmission-distribution coordination under uncertainty," European Journal of Operational Research, Elsevier, vol. 299(1), pages 313-329.
    8. Vogt, Mike & Marten, Frank & Braun, Martin, 2018. "A survey and statistical analysis of smart grid co-simulations," Applied Energy, Elsevier, vol. 222(C), pages 67-78.
    9. Pavičević, Matija & Kavvadias, Konstantinos & Pukšec, Tomislav & Quoilin, Sylvain, 2019. "Comparison of different model formulations for modelling future power systems with high shares of renewables – The Dispa-SET Balkans model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    11. Ulf Philipp Müller & Birgit Schachler & Malte Scharf & Wolf-Dieter Bunke & Stephan Günther & Julian Bartels & Guido Pleßmann, 2019. "Integrated Techno-Economic Power System Planning of Transmission and Distribution Grids," Energies, MDPI, vol. 12(11), pages 1-30, May.
    12. Han, Xingning & Chen, Xinyu & McElroy, Michael B. & Liao, Shiwu & Nielsen, Chris P. & Wen, Jinyu, 2019. "Modeling formulation and validation for accelerated simulation and flexibility assessment on large scale power systems under higher renewable penetrations," Applied Energy, Elsevier, vol. 237(C), pages 145-154.
    13. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    14. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    15. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    16. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    17. Francisco Munoz & Enzo Sauma & Benjamin Hobbs, 2013. "Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards," Journal of Regulatory Economics, Springer, vol. 43(3), pages 305-338, June.
    18. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
    19. Sidhu, Arjan S. & Pollitt, Michael G. & Anaya, Karim L., 2018. "A social cost benefit analysis of grid-scale electrical energy storage projects: A case study," Applied Energy, Elsevier, vol. 212(C), pages 881-894.
    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. 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).
    2. Vrionis, Constantinos & Tsalavoutis, Vasilios & Tolis, Athanasios, 2020. "A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach," Applied Energy, Elsevier, vol. 259(C).
    3. Bissiri, M. & Moura, P. & Figueiredo, N.C. & Silva, P.P., 2020. "Towards a renewables-based future for West African States: A review of power systems planning approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    5. Hilbers, Adriaan P. & Brayshaw, David J. & Gandy, Axel, 2023. "Reducing climate risk in energy system planning: A posteriori time series aggregation for models with storage," Applied Energy, Elsevier, vol. 334(C).
    6. Karl-Kiên Cao & Kai von Krbek & Manuel Wetzel & Felix Cebulla & Sebastian Schreck, 2019. "Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models," Energies, MDPI, vol. 12(24), pages 1-51, December.
    7. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "Integrating supply and demand-side management in renewable-based energy systems," Energy, Elsevier, vol. 232(C).
    8. Pavičević, Matija & Kavvadias, Konstantinos & Pukšec, Tomislav & Quoilin, Sylvain, 2019. "Comparison of different model formulations for modelling future power systems with high shares of renewables – The Dispa-SET Balkans model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. Gonzato, Sebastian & Bruninx, Kenneth & Delarue, Erik, 2021. "Long term storage in generation expansion planning models with a reduced temporal scope," Applied Energy, Elsevier, vol. 298(C).
    10. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    11. Borasio, M. & Moret, S., 2022. "Deep decarbonisation of regional energy systems: A novel modelling approach and its application to the Italian energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    12. Kuepper, Lucas Elias & Teichgraeber, Holger & Baumgärtner, Nils & Bardow, André & Brandt, Adam R., 2022. "Wind data introduce error in time-series reduction for capacity expansion modelling," Energy, Elsevier, vol. 256(C).
    13. Yeganefar, Ali & Amin-Naseri, Mohammad Reza & Sheikh-El-Eslami, Mohammad Kazem, 2020. "Improvement of representative days selection in power system planning by incorporating the extreme days of the net load to take account of the variability and intermittency of renewable resources," Applied Energy, Elsevier, vol. 272(C).
    14. Prina, Matteo Giacomo & Casalicchio, Valeria & Kaldemeyer, Cord & Manzolini, Giampaolo & Moser, David & Wanitschke, Alexander & Sparber, Wolfram, 2020. "Multi-objective investment optimization for energy system models in high temporal and spatial resolution," Applied Energy, Elsevier, vol. 264(C).
    15. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    16. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    17. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    18. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    19. Fridgen, Gilbert & Keller, Robert & Körner, Marc-Fabian & Schöpf, Michael, 2020. "A holistic view on sector coupling," Energy Policy, Elsevier, vol. 147(C).
    20. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.

    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:gam:jsusta:v:14:y:2022:i:13:p:8108-:d:854566. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.