IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v374y2024ics0306261924013618.html
   My bibliography  Save this article

A robust optimization model for Optimal Feeder Routing and Battery Storage Systems design

Author

Listed:
  • Zdraveski, Vasko
  • Todorovski, Mirko

Abstract

The increasing integration of small-scale distributed generation units and electric vehicle present significant challenges to the design of urban electrical distribution networks (DN), introducing considerable uncertainties. This paper addresses these complex challenges by proposing an Optimal Feeder Routing and Battery Storage System (OFRBSS) model. The model offers a single-stage, long-term optimization framework that simplifies load uncertainty to two values – minimum and maximum power demand – thereby enhancing simplicity and efficiency in modelling power demand uncertainty. Leveraging the Column and Constraint Generation algorithm, the OFRBSS model optimizes feeder routing and battery storage system installation, enabling distribution system operators to meet operational constraints under worst power demand conditions. This research bridges existing gaps in integrating optimal DN planning, battery storage system sizing, and placement while addressing the critical aspect of power demand uncertainty. The three-level OFRBSS model is transformed into a two-level counterpart through the application of Karush–Kuhn–Tucker conditions.

Suggested Citation

  • Zdraveski, Vasko & Todorovski, Mirko, 2024. "A robust optimization model for Optimal Feeder Routing and Battery Storage Systems design," Applied Energy, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:appene:v:374:y:2024:i:c:s0306261924013618
    DOI: 10.1016/j.apenergy.2024.123978
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924013618
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123978?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. Liang, Hejun & Pirouzi, Sasan, 2024. "Energy management system based on economic Flexi-reliable operation for the smart distribution network including integrated energy system of hydrogen storage and renewable sources," Energy, Elsevier, vol. 293(C).
    2. Motalleb, Mahdi & Reihani, Ehsan & Ghorbani, Reza, 2016. "Optimal placement and sizing of the storage supporting transmission and distribution networks," Renewable Energy, Elsevier, vol. 94(C), pages 651-659.
    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. Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Xiang, Zhi-Bo & Zhang, Sen, 2024. "Economic and low-carbon planning for interconnected integrated energy systems considering emerging technologies and future development trends," Energy, Elsevier, vol. 302(C).
    2. Tee, Wei Hown & Gan, Chin Kim & Sardi, Junainah, 2024. "Benefits of energy storage systems and its potential applications in Malaysia: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    3. Nayeem Chowdhury & Fabrizio Pilo & Giuditta Pisano, 2020. "Optimal Energy Storage System Positioning and Sizing with Robust Optimization," Energies, MDPI, vol. 13(3), pages 1-20, January.
    4. Lim, Kai Zhuo & Lim, Kang Hui & Wee, Xian Bin & Li, Yinan & Wang, Xiaonan, 2020. "Optimal allocation of energy storage and solar photovoltaic systems with residential demand scheduling," Applied Energy, Elsevier, vol. 269(C).
    5. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm," Applied Energy, Elsevier, vol. 232(C), pages 212-228.
    6. Guido Carpinelli & Fabio Mottola & Christian Noce & Angela Russo & Pietro Varilone, 2018. "A New Hybrid Approach Using the Simultaneous Perturbation Stochastic Approximation Method for the Optimal Allocation of Electrical Energy Storage Systems," Energies, MDPI, vol. 11(6), pages 1-20, June.
    7. Antweiler, Werner, 2021. "Microeconomic models of electricity storage: Price Forecasting, arbitrage limits, curtailment insurance, and transmission line utilization," Energy Economics, Elsevier, vol. 101(C).
    8. Ovidiu Ivanov & Mihai-Andrei Luca & Bogdan-Constantin Neagu & Gheorghe Grigoras & Mihai Gavrilas, 2024. "Flexible Energy Storage for Sustainable Load Leveling in Low-Voltage Electricity Distribution Grids with Prosumers," Sustainability, MDPI, vol. 16(10), pages 1-15, May.
    9. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    10. Zhong, Shangpeng & Wang, Xiaoming & Wu, Hongbin & He, Ye & Xu, Bin & Ding, Ming, 2024. "Energy hub management for integrated energy systems: A multi-objective optimization control strategy based on distributed output and energy conversion characteristics," Energy, Elsevier, vol. 306(C).
    11. Pan, Yushu & Ju, Liwei & Yang, Shenbo & Guo, Xinyu & Tan, Zhongfu, 2024. "A multi-objective robust optimal dispatch and cost allocation model for microgrids-shared hybrid energy storage system considering flexible ramping capacity," Applied Energy, Elsevier, vol. 369(C).
    12. Bucciarelli, Martina & Paoletti, Simone & Vicino, Antonio, 2018. "Optimal sizing of energy storage systems under uncertain demand and generation," Applied Energy, Elsevier, vol. 225(C), pages 611-621.
    13. Marczinkowski, Hannah Mareike & Østergaard, Poul Alberg, 2018. "Residential versus communal combination of photovoltaic and battery in smart energy systems," Energy, Elsevier, vol. 152(C), pages 466-475.
    14. Gianni Celli & Fabrizio Pilo & Giuditta Pisano & Simona Ruggeri & Gian Giuseppe Soma, 2021. "Relieving Tensions on Battery Energy Sources Utilization among TSO, DSO, and Service Providers with Multi-Objective Optimization," Energies, MDPI, vol. 14(1), pages 1-22, January.
    15. Grover-Silva, Etta & Girard, Robin & Kariniotakis, George, 2018. "Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm," Applied Energy, Elsevier, vol. 219(C), pages 385-393.
    16. Xin Huang & Keteng Jiang & Shuxin Luo & Haibo Li & Zongxiang Lu, 2024. "Dynamic Calculation Method for Zonal Carbon Emissions in Power Systems Based on the Theory of Production Simulation and Carbon Emission Flow Theory," Sustainability, MDPI, vol. 16(15), pages 1-31, July.
    17. Mohammadali Kiehbadroudinezhad & Adel Merabet & Homa Hosseinzadeh-Bandbafha, 2022. "Review of Latest Advances and Prospects of Energy Storage Systems: Considering Economic, Reliability, Sizing, and Environmental Impacts Approach," Clean Technol., MDPI, vol. 4(2), pages 1-25, June.
    18. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    19. Hao, Junhong & Feng, Xiaolong & Chen, Xiangru & Jin, Xilin & Wang, Xingce & Hao, Tong & Hong, Feng & Du, Xiaoze, 2024. "Optimal scheduling of active distribution network considering symmetric heat and power source-load spatial-temporal characteristics," Applied Energy, Elsevier, vol. 373(C).
    20. Kotarela, F. & Kyritsis, A. & Papanikolaou, N. & Kalogirou, S.A., 2021. "Enhanced nZEB concept incorporating a sustainable Grid Support Scheme," Renewable Energy, Elsevier, vol. 169(C), pages 714-725.

    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:374:y:2024:i:c:s0306261924013618. 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.