IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp1110.html
   My bibliography  Save this paper

Modeling Storage and Demand Management in Electricity Distribution Grids

Author

Listed:
  • Andreas Schröder
  • Jan Siegmeier
  • Murk Creusen

Abstract

Storage devices and demand control may constitute beneficial tools to optimize electricity generation with a large share of intermittent resources through inter-temporal substitution of load. We quantify the related cost reductions in a simulation model of a simplified stylized medium-voltage grid (10kV) under uncertain demand and wind output. Benders Decomposition Method is applied to create a two-stage stochastic program. The model informs an optimal investment sizing decision as regards specific 'smart grid' applications such as storage facilities and meters enabling load control. Model results indicate that central storage facilities are a more promising option for generation cost reductions as compared to demand management. Grid extensions are not appropriate in any of our scenarios. A sensitivity analysis is applied with respect to the market penetration of uncoordinated Plug-In Electric Vehicles which are found to strongly encourage investment into load control equipment for `smart` charging and slightly improve the case for central storage devices.

Suggested Citation

  • Andreas Schröder & Jan Siegmeier & Murk Creusen, 2011. "Modeling Storage and Demand Management in Electricity Distribution Grids," Discussion Papers of DIW Berlin 1110, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1110
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.368984.de/dp1110.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Deok Ki & Park, Sang Yong & Park, Soo Uk, 2007. "Development of assessment model for demand-side management investment programs in Korea," Energy Policy, Elsevier, vol. 35(11), pages 5585-5590, November.
    2. Diaf, S. & Diaf, D. & Belhamel, M. & Haddadi, M. & Louche, A., 2007. "A methodology for optimal sizing of autonomous hybrid PV/wind system," Energy Policy, Elsevier, vol. 35(11), pages 5708-5718, November.
    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. Schroeder, Andreas, 2011. "Modeling storage and demand management in power distribution grids," Applied Energy, Elsevier, vol. 88(12), pages 4700-4712.
    2. Rajanna, S. & Saini, R.P., 2016. "Modeling of integrated renewable energy system for electrification of a remote area in India," Renewable Energy, Elsevier, vol. 90(C), pages 175-187.
    3. Abo-Elyousr, Farag K. & Elnozahy, Ahmed, 2018. "Bi-objective economic feasibility of hybrid micro-grid systems with multiple fuel options for islanded areas in Egypt," Renewable Energy, Elsevier, vol. 128(PA), pages 37-56.
    4. Maleki, Akbar & Pourfayaz, Fathollah & Rosen, Marc A., 2016. "A novel framework for optimal design of hybrid renewable energy-based autonomous energy systems: A case study for Namin, Iran," Energy, Elsevier, vol. 98(C), pages 168-180.
    5. Kebir, Nisrine & Maaroufi, Mohamed, 2017. "Technical losses computation for short-term predictive management enhancement of grid-connected distributed generations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1011-1021.
    6. Khiareddine, Abla & Ben Salah, Chokri & Rekioua, Djamila & Mimouni, Mohamed Faouzi, 2018. "Sizing methodology for hybrid photovoltaic /wind/ hydrogen/battery integrated to energy management strategy for pumping system," Energy, Elsevier, vol. 153(C), pages 743-762.
    7. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    8. Zhou, P. & Jin, R.Y. & Fan, L.W., 2016. "Reliability and economic evaluation of power system with renewables: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 537-547.
    9. Maleki, Akbar & Ameri, Mehran & Keynia, Farshid, 2015. "Scrutiny of multifarious particle swarm optimization for finding the optimal size of a PV/wind/battery hybrid system," Renewable Energy, Elsevier, vol. 80(C), pages 552-563.
    10. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    11. Al-Sharafi, Abdullah & Sahin, Ahmet Z. & Ayar, Tahir & Yilbas, Bekir S., 2017. "Techno-economic analysis and optimization of solar and wind energy systems for power generation and hydrogen production in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 33-49.
    12. Lee, Deok Joo & Hwang, Jooho, 2010. "Decision support for selecting exportable nuclear technology using the analytic hierarchy process: A Korean case," Energy Policy, Elsevier, vol. 38(1), pages 161-167, January.
    13. Ahadi, Pedram & Fakhrabadi, Farbod & Pourshaghaghy, Alireza & Kowsary, Farshad, 2023. "Optimal site selection for a solar power plant in Iran via the Analytic Hierarchy Process (AHP)," Renewable Energy, Elsevier, vol. 215(C).
    14. Hoicka, Christina E. & Rowlands, Ian H., 2011. "Solar and wind resource complementarity: Advancing options for renewable electricity integration in Ontario, Canada," Renewable Energy, Elsevier, vol. 36(1), pages 97-107.
    15. Rafique, M. Mujahid & Rehman, S. & Alhems, Luai M., 2018. "Developing zero energy and sustainable villages – A case study for communities of the future," Renewable Energy, Elsevier, vol. 127(C), pages 565-574.
    16. Wissem, Zghal & Gueorgui, Kantchev & Hédi, Kchaou, 2012. "Modeling and technical–economic optimization of an autonomous photovoltaic system," Energy, Elsevier, vol. 37(1), pages 263-272.
    17. Jiang, X.S. & Jing, Z.X. & Li, Y.Z. & Wu, Q.H. & Tang, W.H., 2014. "Modelling and operation optimization of an integrated energy based direct district water-heating system," Energy, Elsevier, vol. 64(C), pages 375-388.
    18. Ma, Tao & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2014. "Technical feasibility study on a standalone hybrid solar-wind system with pumped hydro storage for a remote island in Hong Kong," Renewable Energy, Elsevier, vol. 69(C), pages 7-15.
    19. Sinha, Sunanda & Chandel, S.S., 2015. "Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 755-769.
    20. Wang, Yun & Duan, Xiaocong & Zou, Runmin & Zhang, Fan & Li, Yifen & Hu, Qinghua, 2023. "A novel data-driven deep learning approach for wind turbine power curve modeling," Energy, Elsevier, vol. 270(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:diw:diwwpp:dp1110. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    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.