IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v112y2013icp1424-1437.html
   My bibliography  Save this article

An integrated model for long-term power generation planning toward future smart electricity systems

Author

Listed:
  • Zhang, Qi
  • Mclellan, Benjamin C.
  • Tezuka, Tetsuo
  • Ishihara, Keiichi N.

Abstract

In the present study, an integrated planning model was developed to find economically/environmentally optimized paths toward future smart electricity systems with high level penetration of intermittent renewable energy and new controllable electric devices at the supply and demand sides respectively for regional scale. The integrated model is used to (i) plan the best power generation and capacity mixes to meet future electricity demand subject to various constraints using an optimization model; (ii) obtain detailed operation patterns of power plants and new controllable electric devices using an hour-by-hour simulation model based on the obtained optimized power generation mix. As a case study, the model was applied to power generation planning in the Tokyo area, Japan, out to 2030 in light of the Fukushima Accident. The paths toward best generation mixes of smart electricity systems in 2030 based on fossil fuel, hydro power, nuclear and renewable energy were obtained and the feasibility of the integrated model was proven.

Suggested Citation

  • Zhang, Qi & Mclellan, Benjamin C. & Tezuka, Tetsuo & Ishihara, Keiichi N., 2013. "An integrated model for long-term power generation planning toward future smart electricity systems," Applied Energy, Elsevier, vol. 112(C), pages 1424-1437.
    • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:1424-1437
    DOI: 10.1016/j.apenergy.2013.03.073
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913002699
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.03.073?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. Dong, C. & Huang, G.H. & Cai, Y.P. & Xu, Y., 2011. "An interval-parameter minimax regret programming approach for power management systems planning under uncertainty," Applied Energy, Elsevier, vol. 88(8), pages 2835-2845, August.
    2. Foley, A.M. & Ó Gallachóir, B.P. & Hur, J. & Baldick, R. & McKeogh, E.J., 2010. "A strategic review of electricity systems models," Energy, Elsevier, vol. 35(12), pages 4522-4530.
    3. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
    4. Zhang, Qi & Mclellan, Benjamin C. & Tezuka, Tetsuo & Ishihara, Keiichi N., 2012. "Economic and environmental analysis of power generation expansion in Japan considering Fukushima nuclear accident using a multi-objective optimization model," Energy, Elsevier, vol. 44(1), pages 986-995.
    5. Lund, Henrik & Kempton, Willett, 2008. "Integration of renewable energy into the transport and electricity sectors through V2G," Energy Policy, Elsevier, vol. 36(9), pages 3578-3587, September.
    6. Yuan, Ao & He, Wenqing & Wang, Binhuan & Qin, Gengsheng, 2012. "U-statistic with side information," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 20-38.
    7. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    8. Prasad, A. Rajendra & Natarajan, E., 2006. "Optimization of integrated photovoltaic–wind power generation systems with battery storage," Energy, Elsevier, vol. 31(12), pages 1943-1954.
    9. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    10. Purvins, Arturs & Zubaryeva, Alyona & Llorente, Maria & Tzimas, Evangelos & Mercier, Arnaud, 2011. "Challenges and options for a large wind power uptake by the European electricity system," Applied Energy, Elsevier, vol. 88(5), pages 1461-1469, May.
    11. Denholm, Paul & Margolis, Robert M., 2007. "Evaluating the limits of solar photovoltaics (PV) in traditional electric power systems," Energy Policy, Elsevier, vol. 35(5), pages 2852-2861, May.
    12. Nansai, Keisuke & Tohno, Susumu & Kono, Motoki & Kasahara, Mikio, 2002. "Effects of electric vehicles (EV) on environmental loads with consideration of regional differences of electric power generation and charging characteristic of EV users in Japan," Applied Energy, Elsevier, vol. 71(2), pages 111-125, February.
    13. Cai, Y.P. & Huang, G.H. & Tan, Q. & Yang, Z.F., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2779-2790, August.
    14. Zhang, Qi & Tezuka, Tetsuo & Ishihara, Keiichi N. & Mclellan, Benjamin C., 2012. "Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan," Renewable Energy, Elsevier, vol. 44(C), pages 99-108.
    15. Cai, Y.P. & Huang, G.H. & Tan, Q. & Liu, L., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part II. Case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3051-3073, August.
    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. Zhang, Qi & Ishihara, Keiichi N. & Mclellan, Benjamin C. & Tezuka, Tetsuo, 2012. "Scenario analysis on future electricity supply and demand in Japan," Energy, Elsevier, vol. 38(1), pages 376-385.
    2. Trotter, Philipp A. & Cooper, Nathanial J. & Wilson, Peter R., 2019. "A multi-criteria, long-term energy planning optimisation model with integrated on-grid and off-grid electrification – The case of Uganda," Applied Energy, Elsevier, vol. 243(C), pages 288-312.
    3. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    4. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    5. Nunes, Pedro & Farias, Tiago & Brito, Miguel C., 2015. "Day charging electric vehicles with excess solar electricity for a sustainable energy system," Energy, Elsevier, vol. 80(C), pages 263-274.
    6. Soares M.C. Borba, Bruno & Szklo, Alexandre & Schaeffer, Roberto, 2012. "Plug-in hybrid electric vehicles as a way to maximize the integration of variable renewable energy in power systems: The case of wind generation in northeastern Brazil," Energy, Elsevier, vol. 37(1), pages 469-481.
    7. Caballero, F. & Sauma, E. & Yanine, F., 2013. "Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block," Energy, Elsevier, vol. 61(C), pages 248-261.
    8. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    9. Welsch, M. & Howells, M. & Bazilian, M. & DeCarolis, J.F. & Hermann, S. & Rogner, H.H., 2012. "Modelling elements of Smart Grids – Enhancing the OSeMOSYS (Open Source Energy Modelling System) code," Energy, Elsevier, vol. 46(1), pages 337-350.
    10. Verzijlbergh, Remco & Brancucci Martínez-Anido, Carlo & Lukszo, Zofia & de Vries, Laurens, 2014. "Does controlled electric vehicle charging substitute cross-border transmission capacity?," Applied Energy, Elsevier, vol. 120(C), pages 169-180.
    11. Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad, 2011. "Large-scale integration of wind power into the existing Chinese energy system," Energy, Elsevier, vol. 36(8), pages 4753-4760.
    12. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    13. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    14. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    15. Vithayasrichareon, Peerapat & Riesz, Jenny & MacGill, Iain F., 2015. "Using renewables to hedge against future electricity industry uncertainties—An Australian case study," Energy Policy, Elsevier, vol. 76(C), pages 43-56.
    16. Zhang, Qi & Tezuka, Tetsuo & Ishihara, Keiichi N. & Mclellan, Benjamin C., 2012. "Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan," Renewable Energy, Elsevier, vol. 44(C), pages 99-108.
    17. Rae, Callum & Kerr, Sandy & Maroto-Valer, M. Mercedes, 2020. "Upscaling smart local energy systems: A review of technical barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    18. Md. Nasimul Islam Maruf, 2019. "Sector Coupling in the North Sea Region—A Review on the Energy System Modelling Perspective," Energies, MDPI, vol. 12(22), pages 1-35, November.
    19. Martin-Martínez, F. & Sánchez-Miralles, A. & Rivier, M., 2016. "A literature review of Microgrids: A functional layer based classification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1133-1153.
    20. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.

    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:112:y:2013:i:c:p:1424-1437. 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.