IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v257y2020ics0306261919314023.html
   My bibliography  Save this article

The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment

Author

Listed:
  • Heuberger, Clara F.
  • Bains, Praveen K.
  • Mac Dowell, Niall

Abstract

Power system models have become an essential part of strategic planning and decision-making in the energy transition. While techniques are becoming increasingly sophisticated and manifold, the ability to incorporate high resolution in space and time with long-term planning is limited. We introduce ESONE, the Spatially granular Electricity Systems Optimisation model. ESONE is a mixed-integer linear program, determining investment in power system generation and transmission infrastructure while simultaneously optimising operational schedule and optimal power flow on an hourly basis. Unique data clustering combined with model decomposition and an iterative solution procedure enable computational tractability. We showcase the capabilities of the ESONE model by applying it to the power system of Great Britain under CO2 emissions reduction targets. We investigate the effects of a spatially distributed large-scale roll-out of electric vehicles (EVs). We find EV demand profiles correlate well with offshore and onshore wind power production, reducing curtailment and boosting generation. Time-of-use-tariffs for EV charging can further reduce power supply and transmission infrastructure requirements. In general, Great Britain’s electricity system absorbs additional demand from ambitious deployment of EVs without substantial changes to system design.

Suggested Citation

  • Heuberger, Clara F. & Bains, Praveen K. & Mac Dowell, Niall, 2020. "The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment," Applied Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:appene:v:257:y:2020:i:c:s0306261919314023
    DOI: 10.1016/j.apenergy.2019.113715
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919314023
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.113715?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. Rahman, Imran & Vasant, Pandian M. & Singh, Balbir Singh Mahinder & Abdullah-Al-Wadud, M. & Adnan, Nadia, 2016. "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1039-1047.
    2. Pietzcker, Robert C. & Longden, Thomas & Chen, Wenying & Fu, Sha & Kriegler, Elmar & Kyle, Page & Luderer, Gunnar, 2014. "Long-term transport energy demand and climate policy: Alternative visions on transport decarbonization in energy-economy models," Energy, Elsevier, vol. 64(C), pages 95-108.
    3. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
    4. Jan Abrell & Friedrich Kunz, 2015. "Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market," Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
    5. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2015. "Value of flexible electric vehicles in providing spinning reserve services," Applied Energy, Elsevier, vol. 157(C), pages 60-74.
    6. Schaber, Katrin & Steinke, Florian & Hamacher, Thomas, 2012. "Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where?," Energy Policy, Elsevier, vol. 43(C), pages 123-135.
    7. Bishop, Justin D.K. & Axon, Colin J. & Bonilla, David & Tran, Martino & Banister, David & McCulloch, Malcolm D., 2013. "Evaluating the impact of V2G services on the degradation of batteries in PHEV and EV," Applied Energy, Elsevier, vol. 111(C), pages 206-218.
    8. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    9. Anable, Jillian & Brand, Christian & Tran, Martino & Eyre, Nick, 2012. "Modelling transport energy demand: A socio-technical approach," Energy Policy, Elsevier, vol. 41(C), pages 125-138.
    10. Mwasilu, Francis & Justo, Jackson John & Kim, Eun-Kyung & Do, Ton Duc & Jung, Jin-Woo, 2014. "Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 501-516.
    11. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    12. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    13. Hahn, Tobias & Schönfelder, Martin & Jochem, Patrick & Heuveline, Vincent & Fichtner, Wolf, 2013. "Model-Based Quantification of Load Shift Potentials and Optimized Charging of Electric Vehicles," MPRA Paper 91613, University Library of Munich, Germany, revised 04 Jul 2013.
    14. Lara, Cristiana L. & Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Grossmann, Ignacio E., 2018. "Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1037-1054.
    15. Nelson, James & Johnston, Josiah & Mileva, Ana & Fripp, Matthias & Hoffman, Ian & Petros-Good, Autumn & Blanco, Christian & Kammen, Daniel M., 2012. "High-resolution modeling of the western North American power system demonstrates low-cost and low-carbon futures," Energy Policy, Elsevier, vol. 43(C), pages 436-447.
    16. Munoz, F.D. & Hobbs, B.F. & Watson, J.-P., 2016. "New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints," European Journal of Operational Research, Elsevier, vol. 248(3), pages 888-898.
    17. Hoogvliet, T.W. & Litjens, G.B.M.A. & van Sark, W.G.J.H.M., 2017. "Provision of regulating- and reserve power by electric vehicle owners in the Dutch market," Applied Energy, Elsevier, vol. 190(C), pages 1008-1019.
    18. Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    19. Pudjianto, Danny & Djapic, Predrag & Aunedi, Marko & Gan, Chin Kim & Strbac, Goran & Huang, Sikai & Infield, David, 2013. "Smart control for minimizing distribution network reinforcement cost due to electrification," Energy Policy, Elsevier, vol. 52(C), pages 76-84.
    20. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    21. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    22. Boßmann, T. & Staffell, I., 2015. "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain," Energy, Elsevier, vol. 90(P2), pages 1317-1333.
    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. Aryanpur, Vahid & Balyk, Olexandr & Daly, Hannah & Ó Gallachóir, Brian & Glynn, James, 2022. "Decarbonisation of passenger light-duty vehicles using spatially resolved TIMES-Ireland Model," Applied Energy, Elsevier, vol. 316(C).
    2. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Energy, Elsevier, vol. 290(C).
    3. Mowry, Andrew M. & Mallapragada, Dharik S., 2021. "Grid impacts of highway electric vehicle charging and role for mitigation via energy storage," Energy Policy, Elsevier, vol. 157(C).
    4. Thomas Heggarty & Jean-Yves Bourmaud & Robin Girard & Georges Kariniotakis, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Post-Print hal-04383397, HAL.
    5. Mallapragada, Dharik S. & Junge, Cristian & Wang, Cathy & Pfeifenberger, Hannes & Joskow, Paul L. & Schmalensee, Richard, 2023. "Electricity pricing challenges in future renewables-dominant power systems," Energy Economics, Elsevier, vol. 126(C).
    6. Vassilis M. Charitopoulos & Mathilde Fajardy & Chi Kong Chyong & David M. Reiner, 2022. "The case of 100% electrification of domestic heat in Great Britain," Working Papers EPRG2206, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    7. Mangipinto, Andrea & Lombardi, Francesco & Sanvito, Francesco Davide & Pavičević, Matija & Quoilin, Sylvain & Colombo, Emanuela, 2022. "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries," Applied Energy, Elsevier, vol. 312(C).
    8. Zhang, Haifeng & Tian, Ming & Zhang, Cong & Wang, Bin & Wang, Dai, 2021. "A systematic solution to quantify economic values of vehicle grid integration," Energy, Elsevier, vol. 232(C).
    9. Peng, Jieyang & Kimmig, Andreas & Niu, Zhibin & Wang, Jiahai & Liu, Xiufeng & Ovtcharova, Jivka, 2021. "A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework," Applied Energy, Elsevier, vol. 299(C).
    10. Mallapragada, Dharik S. & Sepulveda, Nestor A. & Jenkins, Jesse D., 2020. "Long-run system value of battery energy storage in future grids with increasing wind and solar generation," Applied Energy, Elsevier, vol. 275(C).
    11. Makeen, Peter & Ghali, Hani A. & Memon, Saim & Duan, Fang, 2023. "Smart techno-economic operation of electric vehicle charging station in Egypt," Energy, Elsevier, vol. 264(C).
    12. Koltsaklis, Nikolaos E. & Knápek, Jaroslav, 2023. "Assessing flexibility options in electricity market clearing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    13. Al-Bahrani, Loau Tawfak & Horan, Ben & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Dynamic economic emission dispatch with load dema nd management for the load demand of electric vehicles during crest shaving and valley filling in smart cities environment," Energy, Elsevier, vol. 195(C).
    14. Lagomarsino, Maria & van der Kam, Mart & Parra, David & Hahnel, Ulf J.J., 2022. "Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging," Energy Policy, Elsevier, vol. 162(C).
    15. Hao, Xu & Lin, Zhenhong & Wang, Hewu & Ou, Shiqi & Ouyang, Minggao, 2020. "Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach," Applied Energy, Elsevier, vol. 275(C).
    16. Zhang, Cong & Greenblatt, Jeffery B. & MacDougall, Pamela & Saxena, Samveg & Jayam Prabhakar, Aditya, 2020. "Quantifying the benefits of electric vehicles on the future electricity grid in the midwestern United States," Applied Energy, Elsevier, vol. 270(C).
    17. Halloran, Claire & Lizana, Jesus & Fele, Filiberto & McCulloch, Malcolm, 2024. "Data-based, high spatiotemporal resolution heat pump demand for power system planning," Applied Energy, Elsevier, vol. 355(C).
    18. Reinert, Christiane & Nilges, Benedikt & Baumgärtner, Nils & Bardow, André, 2024. "This is SpArta: Rigorous Optimization of Regionally Resolved Energy Systems by Spatial Aggregation and Decomposition," Applied Energy, Elsevier, vol. 367(C).
    19. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "A novel stochastic multistage dispatching model of hybrid battery-electric vehicle-supercapacitor storage system to minimize three-phase unbalance," Energy, Elsevier, vol. 296(C).
    20. Strobel, Leo & Schlund, Jonas & Pruckner, Marco, 2022. "Joint analysis of regional and national power system impacts of electric vehicles—A case study for Germany on the county level in 2030," Applied Energy, Elsevier, vol. 315(C).
    21. Demirhan, C. Doga & Tso, William W. & Powell, Joseph B. & Pistikopoulos, Efstratios N., 2021. "A multi-scale energy systems engineering approach towards integrated multi-product network optimization," Applied Energy, Elsevier, vol. 281(C).
    22. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(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. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    2. Mads Raunbak & Timo Zeyer & Kun Zhu & Martin Greiner, 2017. "Principal Mismatch Patterns Across a Simplified Highly Renewable European Electricity Network," Energies, MDPI, vol. 10(12), pages 1-13, November.
    3. Lombardi, Francesco & Rocco, Matteo Vincenzo & Colombo, Emanuela, 2019. "A multi-layer energy modelling methodology to assess the impact of heat-electricity integration strategies: The case of the residential cooking sector in Italy," Energy, Elsevier, vol. 170(C), pages 1249-1260.
    4. Gaizka Saldaña & Jose Ignacio San Martin & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Electric Vehicle into the Grid: Charging Methodologies Aimed at Providing Ancillary Services Considering Battery Degradation," Energies, MDPI, vol. 12(12), pages 1-37, June.
    5. Teichgraeber, Holger & Küpper, Lucas Elias & Brandt, Adam R., 2021. "Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation," Applied Energy, Elsevier, vol. 304(C).
    6. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    7. Eggimann, Sven & Hall, Jim W. & Eyre, Nick, 2019. "A high-resolution spatio-temporal energy demand simulation to explore the potential of heating demand side management with large-scale heat pump diffusion," Applied Energy, Elsevier, vol. 236(C), pages 997-1010.
    8. Clemens Gerbaulet & Casimir Lorenz, 2017. "dynELMOD: A Dynamic Investment and Dispatch Model for the Future European Electricity Market," Data Documentation 88, DIW Berlin, German Institute for Economic Research.
    9. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
    10. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    11. Géremi Gilson Dranka & Paula Ferreira, 2020. "Electric Vehicles and Biofuels Synergies in the Brazilian Energy System," Energies, MDPI, vol. 13(17), pages 1-22, August.
    12. Shirizadeh, Behrang & Quirion, Philippe, 2022. "The importance of renewable gas in achieving carbon-neutrality: Insights from an energy system optimization model," Energy, Elsevier, vol. 255(C).
    13. Bosch, Jonathan & Staffell, Iain & Hawkes, Adam D., 2018. "Temporally explicit and spatially resolved global offshore wind energy potentials," Energy, Elsevier, vol. 163(C), pages 766-781.
    14. Savvidis, Georgios & Siala, Kais & Weissbart, Christoph & Schmidt, Lukas & Borggrefe, Frieder & Kumar, Subhash & Pittel, Karen & Madlener, Reinhard & Hufendiek, Kai, 2019. "The gap between energy policy challenges and model capabilities," Energy Policy, Elsevier, vol. 125(C), pages 503-520.
    15. Frank, Christopher W. & Pospichal, Bernhard & Wahl, Sabrina & Keller, Jan D. & Hense, Andreas & Crewell, Susanne, 2020. "The added value of high resolution regional reanalyses for wind power applications," Renewable Energy, Elsevier, vol. 148(C), pages 1094-1109.
    16. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Seljom, Pernille & Lind, Arne & Wagner, Fabian & Mesfun, Sennai, 2020. "Short-term solar and wind variability in long-term energy system models - A European case study," Energy, Elsevier, vol. 209(C).
    17. Li, Carmen & Chyong, Chi Kong & Reiner, David M. & Roques, Fabien, 2024. "Taking a Portfolio approach to wind and solar deployment: The case of the National Electricity Market in Australia," Applied Energy, Elsevier, vol. 369(C).
    18. Alexis Tantet & Marc Stéfanon & Philippe Drobinski & Jordi Badosa & Silvia Concettini & Anna Cretì & Claudia D’Ambrosio & Dimitri Thomopulos & Peter Tankov, 2019. "e 4 clim 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy," Energies, MDPI, vol. 12(22), pages 1-37, November.
    19. Tómasson, Egill & Söder, Lennart, 2020. "Coordinated optimal strategic demand reserve procurement in multi-area power systems," Applied Energy, Elsevier, vol. 270(C).
    20. Matsuo, Yuhji & Endo, Seiya & Nagatomi, Yu & Shibata, Yoshiaki & Komiyama, Ryoichi & Fujii, Yasumasa, 2020. "Investigating the economics of the power sector under high penetration of variable renewable energies," Applied Energy, Elsevier, vol. 267(C).

    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:257:y:2020:i:c:s0306261919314023. 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.