IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v142y2018icp878-895.html
   My bibliography  Save this article

Impact of optimised distributed energy resources on local grid constraints

Author

Listed:
  • Sani Hassan, Abubakar
  • Cipcigan, Liana
  • Jenkins, Nick

Abstract

Optimisation models have been extensively used for finding optimal configuration and operation of distributed energy technologies. The main objective in most of these models is to find the optimal configuration of distributed energy technologies that will meet a certain energy demand with the least cost and emissions. Local grid constraints are not considered in the optimisation of distributed energy resources in most of these models. This implies that some optimal solutions from these models may not be possible to integrate due to a violation of steady state voltage and thermal limits which are important to Distribution Network Operators (DNO). In some cases, where a joint optimisation approach is utilised and local grid constraints are considered, it becomes computationally complex due to the nonlinear nature of Alternating Current (AC) power flow equations for electricity networks.

Suggested Citation

  • Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2018. "Impact of optimised distributed energy resources on local grid constraints," Energy, Elsevier, vol. 142(C), pages 878-895.
    • Handle: RePEc:eee:energy:v:142:y:2018:i:c:p:878-895
    DOI: 10.1016/j.energy.2017.10.074
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217317796
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.10.074?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. Matthew Rowe & Timur Yunusov & Stephen Haben & William Holderbaum & Ben Potter, 2014. "The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction," Energies, MDPI, vol. 7(6), pages 1-24, May.
    2. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    3. Soroudi, Alireza & Ehsan, Mehdi, 2010. "A distribution network expansion planning model considering distributed generation options and techo-economical issues," Energy, Elsevier, vol. 35(8), pages 3364-3374.
    4. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J., 2015. "Assessing low voltage network constraints in distributed energy resources planning," Energy, Elsevier, vol. 84(C), pages 783-793.
    5. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    6. Murphy, Patrick Mark & Twaha, Ssennoga & Murphy, Inês S., 2014. "Analysis of the cost of reliable electricity: A new method for analyzing grid connected solar, diesel and hybrid distributed electricity systems considering an unreliable electric grid, with examples ," Energy, Elsevier, vol. 66(C), pages 523-534.
    7. Kane, Laura & Ault, Graham, 2014. "A review and analysis of renewable energy curtailment schemes and Principles of Access: Transitioning towards business as usual," Energy Policy, Elsevier, vol. 72(C), pages 67-77.
    8. Doagou-Mojarrad, Hasan & Gharehpetian, G.B. & Rastegar, H. & Olamaei, Javad, 2013. "Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm," Energy, Elsevier, vol. 54(C), pages 129-138.
    9. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    10. Steen, David & Stadler, Michael & Cardoso, Gonçalo & Groissböck, Markus & DeForest, Nicholas & Marnay, Chris, 2015. "Modeling of thermal storage systems in MILP distributed energy resource models," Applied Energy, Elsevier, vol. 137(C), pages 782-792.
    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. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
    2. Lenhart, Stephanie & Araújo, Kathleen, 2021. "Microgrid decision-making by public power utilities in the United States: A critical assessment of adoption and technological profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    3. Mao, Jiachen & Jafari, Mehdi & Botterud, Audun, 2022. "Planning low-carbon distributed power systems: Evaluating the role of energy storage," Energy, Elsevier, vol. 238(PA).
    4. Boroomandnia, Arezoo & Rismanchi, Behzad & Wu, Wenyan, 2022. "A review of micro hydro systems in urban areas: Opportunities and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    5. Heleno, Miguel & Sehloff, David & Coelho, Antonio & Valenzuela, Alan, 2020. "Probabilistic impact of electricity tariffs on distribution grids considering adoption of solar and storage technologies," Applied Energy, Elsevier, vol. 279(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. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    2. Aman, M.M. & Jasmon, G.B. & Bakar, A.H.A. & Mokhlis, H., 2014. "A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm," Energy, Elsevier, vol. 66(C), pages 202-215.
    3. Georgiou, Giorgos S. & Christodoulides, Paul & Kalogirou, Soteris A., 2019. "Real-time energy convex optimization, via electrical storage, in buildings – A review," Renewable Energy, Elsevier, vol. 139(C), pages 1355-1365.
    4. 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.
    5. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J., 2015. "Assessing low voltage network constraints in distributed energy resources planning," Energy, Elsevier, vol. 84(C), pages 783-793.
    6. Ahmadigorji, Masoud & Amjady, Nima, 2016. "A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm," Energy, Elsevier, vol. 102(C), pages 199-215.
    7. Bohlayer, Markus & Zöttl, Gregor, 2018. "Low-grade waste heat integration in distributed energy generation systems - An economic optimization approach," Energy, Elsevier, vol. 159(C), pages 327-343.
    8. Cardoso, Gonçalo & Brouhard, Thomas & DeForest, Nicholas & Wang, Dai & Heleno, Miguel & Kotzur, Leander, 2018. "Battery aging in multi-energy microgrid design using mixed integer linear programming," Applied Energy, Elsevier, vol. 231(C), pages 1059-1069.
    9. Qiu, Yueming (Lucy) & Wang, Yi David & Xing, Bo, 2021. "Grid impact of non-residential distributed solar energy and reduced air emissions: Empirical evidence from individual-consumer-level smart meter data," Applied Energy, Elsevier, vol. 290(C).
    10. Peter Horan & Mark B. Luther & Hong Xian Li, 2021. "Guidance on Implementing Renewable Energy Systems in Australian Homes," Energies, MDPI, vol. 14(9), pages 1-24, May.
    11. Flores, Robert J. & Brouwer, Jacob, 2018. "Optimal design of a distributed energy resource system that economically reduces carbon emissions," Applied Energy, Elsevier, vol. 232(C), pages 119-138.
    12. Andoni, Merlinda & Robu, Valentin & Früh, Wolf-Gerrit & Flynn, David, 2017. "Game-theoretic modeling of curtailment rules and network investments with distributed generation," Applied Energy, Elsevier, vol. 201(C), pages 174-187.
    13. Feras Alasali & Stephen Haben & Husam Foudeh & William Holderbaum, 2020. "A Comparative Study of Optimal Energy Management Strategies for Energy Storage with Stochastic Loads," Energies, MDPI, vol. 13(10), pages 1-19, May.
    14. Aste, Niccolò & Manfren, Massimiliano & Marenzi, Giorgia, 2017. "Building Automation and Control Systems and performance optimization: A framework for analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 313-330.
    15. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2016. "A multi-objective optimization framework for risk-controlled integration of renewable generation into electric power systems," Energy, Elsevier, vol. 106(C), pages 712-727.
    16. Mansoor, Muhammad & Stadler, Michael & Zellinger, Michael & Lichtenegger, Klaus & Auer, Hans & Cosic, Armin, 2021. "Optimal planning of thermal energy systems in a microgrid with seasonal storage and piecewise affine cost functions," Energy, Elsevier, vol. 215(PA).
    17. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
    18. Gou, Xing & Chen, Qun & Sun, Yong & Ma, Huan & Li, Bao-Ju, 2021. "Holistic analysis and optimization of distributed energy system considering different transport characteristics of multi-energy and component efficiency variation," Energy, Elsevier, vol. 228(C).
    19. 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.
    20. 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).

    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:energy:v:142:y:2018:i:c:p:878-895. 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.journals.elsevier.com/energy .

    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.