IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v194y2022icp236-253.html
   My bibliography  Save this article

Microgrid distributed energy resources planning based on a long-term dynamic microsimulation

Author

Listed:
  • Wang, Beibei
  • Chen, Li
  • Wang, Jiale
  • Zhao, Shengnan

Abstract

In this paper, we study a DERs simulation platform that can adapt to dynamic infrastructure changes. We present a long-term dynamic-planning simulation platform focused on DERs based on MATLAB and TCP/IP network communication via GridLAB-D. This platform can capture critical features of DERs by combining MATLAB’s ability to optimize control with GridLAB-D’s capacity for accurate and discrete event-based microsimulations. The proposed platform architecture is divided into inner and outer layers. The outer layer simulates changes in the external environment (i.e., changes in load level as well as the price of diesel fuel and planned equipment components) and equipment characteristics (i.e., the running lives of batteries and diesel generators). These features provide dynamic scenarios and re-planning boundary conditions that can be used to inform the inner layer simulation. The inner layer presents an operational simulation of the planned microgrid that leverages day-ahead scheduling and the real-time adjustments associated with uncertainties in DER output. Simulation results have shown our proposed planning scheme will result in increased profits and improved resource utilization efficiency during the entire 10-year cycle. Compared to traditional planning scheme, our proposed planning scheme can perform dynamic adjustments to the configuration of various DERs according to changing external factors and network conditions.

Suggested Citation

  • Wang, Beibei & Chen, Li & Wang, Jiale & Zhao, Shengnan, 2022. "Microgrid distributed energy resources planning based on a long-term dynamic microsimulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 236-253.
  • Handle: RePEc:eee:matcom:v:194:y:2022:i:c:p:236-253
    DOI: 10.1016/j.matcom.2021.11.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475421004134
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2021.11.017?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. David P. Chassin & Jason C. Fuller & Ned Djilali, 2014. "GridLAB-D: An Agent-Based Simulation Framework for Smart Grids," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-12, June.
    2. Singh, Antriksh & Willi, David & Chokani, Ndaona & Abhari, Reza S., 2014. "Optimal power flow analysis of a Switzerland׳s transmission system for long-term capacity planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 596-607.
    3. Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
    4. 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.
    5. Jeon, Chanwoong & Shin, Juneseuk, 2014. "Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case," Energy, Elsevier, vol. 66(C), pages 447-457.
    6. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    7. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2013. "Analytical strategies for renewable distributed generation integration considering energy loss minimization," Applied Energy, Elsevier, vol. 105(C), pages 75-85.
    8. Jordehi, A. Rezaee, 2015. "Optimisation of electric distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1088-1100.
    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. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    2. Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
    3. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    4. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    5. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    6. Zhigang Duan & Yamin Yan & Xiaohan Yan & Qi Liao & Wan Zhang & Yongtu Liang & Tianqi Xia, 2017. "An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand," Energies, MDPI, vol. 11(1), pages 1-23, December.
    7. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    8. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Design and operation optimization of organic Rankine cycle coupled trigeneration systems," Energy, Elsevier, vol. 142(C), pages 666-677.
    9. Allegrini, Jonas & Orehounig, Kristina & Mavromatidis, Georgios & Ruesch, Florian & Dorer, Viktor & Evins, Ralph, 2015. "A review of modelling approaches and tools for the simulation of district-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1391-1404.
    10. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    11. Ehsan, Ali & Yang, Qiang, 2019. "State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review," Applied Energy, Elsevier, vol. 239(C), pages 1509-1523.
    12. 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.
    13. Morstyn, Thomas & Collett, Katherine A. & Vijay, Avinash & Deakin, Matthew & Wheeler, Scot & Bhagavathy, Sivapriya M. & Fele, Filiberto & McCulloch, Malcolm D., 2020. "OPEN: An open-source platform for developing smart local energy system applications," Applied Energy, Elsevier, vol. 275(C).
    14. Jiaxin Lu & Weijun Wang & Yingchao Zhang & Song Cheng, 2017. "Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER," Energies, MDPI, vol. 10(10), pages 1-17, October.
    15. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    16. Singh, Bharat & Kumar, Ashwani, 2023. "Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program," Energy, Elsevier, vol. 278(PA).
    17. Primitivo Díaz & Marco Pérez-Cisneros & Erik Cuevas & Omar Avalos & Jorge Gálvez & Salvador Hinojosa & Daniel Zaldivar, 2018. "An Improved Crow Search Algorithm Applied to Energy Problems," Energies, MDPI, vol. 11(3), pages 1-22, March.
    18. Lim, Juin Yau & Safder, Usman & How, Bing Shen & Ifaei, Pouya & Yoo, Chang Kyoo, 2021. "Nationwide sustainable renewable energy and Power-to-X deployment planning in South Korea assisted with forecasting model," Applied Energy, Elsevier, vol. 283(C).
    19. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    20. Costa-Campi, Maria Teresa & Daví-Arderius, Daniel & Trujillo-Baute, Elisa, 2018. "The economic impact of electricity losses," Energy Economics, Elsevier, vol. 75(C), pages 309-322.

    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:matcom:v:194:y:2022:i:c:p:236-253. 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/mathematics-and-computers-in-simulation/ .

    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.