IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v326y2022ics0306261922011990.html
   My bibliography  Save this article

Expansion planning of active distribution networks achieving their dispatchability via energy storage systems

Author

Listed:
  • Yi, Ji Hyun
  • Cherkaoui, Rachid
  • Paolone, Mario
  • Shchetinin, Dmitry
  • Knezovic, Katarina

Abstract

This paper presents a combined framework for power distribution network expansion planning (DNEP) and energy storage systems (ESSs) allocation in active distribution networks (ADNs) hosting large amount of photovoltaic (PV) generations and loads. The proposed DNEP ensures the reliable operation of the targeted ADN with the objective of achieving its dispatchability while minimizing grid losses by determining the optimal grid expansion to connect new nodes, the reinforcement of existing lines, and the ESS allocation. The allocated ESSs compensate for the stochastic power flows caused by the stochastic loads and generation, allowing ADNs to follow a pre-defined power schedule at the grid connection point. The grid constraints are modeled by using a modified augmented relaxed optimal power flow (AR-OPF) model that convexifies the classical AC-OPF providing the global optimal and the exact solution of the OPF problem for radial networks. The DNEP problem’s complexity is handled by employing a sequential algorithm where new nodes are added one by one, following the priorities determined by the user. In each stage of the sequential planning, the Benders decomposition algorithm determines the optimal solution for investments and ADN operation iteratively. Moreover, the siting and sizing problems associated with the ESSs and line investment are solved separately to enhance the convergence speed. Simulations are conducted on a real 55-node Swiss ADN hosting sizeable stochastic photovoltaic generation.

Suggested Citation

  • Yi, Ji Hyun & Cherkaoui, Rachid & Paolone, Mario & Shchetinin, Dmitry & Knezovic, Katarina, 2022. "Expansion planning of active distribution networks achieving their dispatchability via energy storage systems," Applied Energy, Elsevier, vol. 326(C).
  • Handle: RePEc:eee:appene:v:326:y:2022:i:c:s0306261922011990
    DOI: 10.1016/j.apenergy.2022.119942
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922011990
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.119942?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. Kim, S. & Pollitt, M. & Jin, Y. & Yoon, Y., 2017. "Contractual Framework for the Devolution of System Balancing Responsibility from the Transmission System Operator to Distribution System Operators," Cambridge Working Papers in Economics 1738, Faculty of Economics, University of Cambridge.
    2. Appino, Riccardo Remo & González Ordiano, Jorge Ángel & Mikut, Ralf & Faulwasser, Timm & Hagenmeyer, Veit, 2018. "On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages," Applied Energy, Elsevier, vol. 210(C), pages 1207-1218.
    3. Gupta, Rahul & Sossan, Fabrizio & Paolone, Mario, 2021. "Countrywide PV hosting capacity and energy storage requirements for distribution networks: The case of Switzerland," Applied Energy, Elsevier, vol. 281(C).
    4. Canizes, Bruno & Soares, João & Lezama, Fernando & Silva, Cátia & Vale, Zita & Corchado, Juan M., 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation," Renewable Energy, Elsevier, vol. 138(C), pages 937-954.
    5. Karimi, M. & Mokhlis, H. & Naidu, K. & Uddin, S. & Bakar, A.H.A., 2016. "Photovoltaic penetration issues and impacts in distribution network – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 594-605.
    6. Zhenghui Zhao & Joseph Mutale, 2019. "Optimal Conductor Size Selection in Distribution Networks with High Penetration of Distributed Generation Using Adaptive Genetic Algorithm," Energies, MDPI, vol. 12(11), pages 1-20, May.
    7. Xie, Shiwei & Hu, Zhijian & Zhou, Daming & Li, Yan & Kong, Shunfei & Lin, Weiwei & Zheng, Yunfei, 2018. "Multi-objective active distribution networks expansion planning by scenario-based stochastic programming considering uncertain and random weight of network," Applied Energy, Elsevier, vol. 219(C), pages 207-225.
    8. Muruganantham, B. & Gnanadass, R. & Padhy, N.P., 2017. "Challenges with renewable energy sources and storage in practical distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 125-134.
    9. Fenrick, Steve A. & Getachew, Lullit, 2012. "Cost and reliability comparisons of underground and overhead power lines," Utilities Policy, Elsevier, vol. 20(1), pages 31-37.
    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. Junxiao Zhang & Chengmin Wang & Jing Zuo & Chong Gao & Shurong Zheng & Ran Cheng & Yao Duan & Yawu Wang, 2024. "Multi-Stage Rolling Grid Expansion Planning for Distribution Networks Considering Conditional Value at Risk," Energies, MDPI, vol. 17(20), pages 1-20, October.
    2. Weifeng Xu & Bing Yu & Qing Song & Liguo Weng & Man Luo & Fan Zhang, 2022. "Economic and Low-Carbon-Oriented Distribution Network Planning Considering the Uncertainties of Photovoltaic Generation and Load Demand to Achieve Their Reliability," Energies, MDPI, vol. 15(24), pages 1-15, December.
    3. Xiang, Yue & Dai, Jiakun & Xue, Ping & Liu, Junyong, 2023. "Autonomous topology planning for distribution network expansion: A learning-based decoupled optimization method," Applied Energy, Elsevier, vol. 348(C).
    4. Rastgou, Abdollah, 2024. "Distribution network expansion planning: An updated review of current methods and new challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

    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. Yao, Hongmin & Qin, Wenping & Jing, Xiang & Zhu, Zhilong & Wang, Ke & Han, Xiaoqing & Wang, Peng, 2022. "Possibilistic evaluation of photovoltaic hosting capacity on distribution networks under uncertain environment," Applied Energy, Elsevier, vol. 324(C).
    2. Rastgou, Abdollah, 2024. "Distribution network expansion planning: An updated review of current methods and new challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    3. Tabar, Vahid Sohrabi & Banazadeh, Hamidreza & Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Nasir, Mohammad & Jurado, Francisco, 2022. "Stochastic multi-stage multi-objective expansion of renewable resources and electrical energy storage units in distribution systems considering crypto-currency miners and responsive loads," Renewable Energy, Elsevier, vol. 198(C), pages 1131-1147.
    4. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    5. Hamza Mubarak & Nurulafiqah Nadzirah Mansor & Hazlie Mokhlis & Mahazani Mohamad & Hasmaini Mohamad & Munir Azam Muhammad & Mohammad Al Samman & Suhail Afzal, 2021. "Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    6. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.
    7. Enrico Dalla Maria & Mattia Secchi & David Macii, 2021. "A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation," Energies, MDPI, vol. 15(1), pages 1-20, December.
    8. Firouzmakan, Pouya & Hooshmand, Rahmat-Allah & Bornapour, Mosayeb & Khodabakhshian, Amin, 2019. "A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 355-368.
    9. Sardi, Junainah & Mithulananthan, N. & Hung, Duong Quoc, 2017. "Strategic allocation of community energy storage in a residential system with rooftop PV units," Applied Energy, Elsevier, vol. 206(C), pages 159-171.
    10. Parwal, Arvind & Fregelius, Martin & Temiz, Irinia & Göteman, Malin & Oliveira, Janaina G. de & Boström, Cecilia & Leijon, Mats, 2018. "Energy management for a grid-connected wave energy park through a hybrid energy storage system," Applied Energy, Elsevier, vol. 231(C), pages 399-411.
    11. Michael G. Pollitt & Karim L. Anaya, 2021. "Competition in Markets for Ancillary Services? The Implications of Rising Distributed Generation," The Energy Journal, , vol. 42(1_suppl), pages 1-28, June.
    12. Kishore, T.S. & Singal, S.K., 2014. "Optimal economic planning of power transmission lines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 949-974.
    13. Li, Yinxiao & Wang, Yi & Chen, Qixin, 2020. "Study on the impacts of meteorological factors on distributed photovoltaic accommodation considering dynamic line parameters," Applied Energy, Elsevier, vol. 259(C).
    14. Protopapadaki, Christina & Saelens, Dirk, 2017. "Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties," Applied Energy, Elsevier, vol. 192(C), pages 268-281.
    15. Shi, Jie & Wang, Luhao & Lee, Wei-Jen & Cheng, Xingong & Zong, Xiju, 2019. "Hybrid Energy Storage System (HESS) optimization enabling very short-term wind power generation scheduling based on output feature extraction," Applied Energy, Elsevier, vol. 256(C).
    16. Jingpeng Yue & Zhijian Hu & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2019. "A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    17. Wang, Kai & Peng, Jinqing & Li, Sihui & Li, Houpei & Zou, Bin & Ma, Tao & Ji, Jie, 2024. "Compressor speed control for optimizing energy matching of PV-driven AC systems during the cooling season," Energy, Elsevier, vol. 298(C).
    18. Talaat, M. & Farahat, M.A. & Elkholy, M.H., 2019. "Renewable power integration: Experimental and simulation study to investigate the ability of integrating wave, solar and wind energies," Energy, Elsevier, vol. 170(C), pages 668-682.
    19. Gutiérrez-Alvarez, R. & Guerra, K. & Haro, P., 2023. "Market profitability of CSP-biomass hybrid power plants: Towards a firm supply of renewable energy," Applied Energy, Elsevier, vol. 335(C).
    20. Matej Tazky & Michal Regula & Alena Otcenasova, 2021. "Impact of Changes in a Distribution Network Nature on the Capacitive Reactive Power Flow into the Transmission Network in Slovakia," Energies, MDPI, vol. 14(17), pages 1-16, August.

    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:326:y:2022:i:c:s0306261922011990. 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.