IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v207y2023icp765-771.html
   My bibliography  Save this article

Net load disaggregation at secondary substation level

Author

Listed:
  • Toro-Cárdenas, Mateo
  • Moreira, Inês
  • Morais, Hugo
  • Carvalho, Pedro M.S.
  • Ferreira, Luis A.F.M.

Abstract

With more and more micro-generation being connected to the low-voltage network, it becomes increasingly difficult for operators to anticipate the loading condition of their networks. Several facts concur with such difficulty, one being the frequent lack of knowledge about the generation component of the measured net load. The generation component is typically more volatile than the natural load and is impossible to predict without reliable information on the grid’s renewable installed capacity. In this context, the objective of this paper is to propose a non-intrusive methodology to estimate distributed generation’ installed capacity. Relying upon net-load historical data obtained at the secondary substation level and on historical meteorological data, the paper presents algorithms that proved effective in determining an approximation of the renewable embedded capacity. The accuracy and effectiveness of the proposed algorithms are illustrated in the paper with real data, for real use cases in the distribution systems.

Suggested Citation

  • Toro-Cárdenas, Mateo & Moreira, Inês & Morais, Hugo & Carvalho, Pedro M.S. & Ferreira, Luis A.F.M., 2023. "Net load disaggregation at secondary substation level," Renewable Energy, Elsevier, vol. 207(C), pages 765-771.
    • Handle: RePEc:eee:renene:v:207:y:2023:i:c:p:765-771
    DOI: 10.1016/j.renene.2022.11.034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122016743
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.11.034?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. Pierro, Marco & Gentili, Damiano & Liolli, Fabio Romano & Cornaro, Cristina & Moser, David & Betti, Alessandro & Moschella, Michela & Collino, Elena & Ronzio, Dario & van der Meer, Dennis, 2022. "Progress in regional PV power forecasting: A sensitivity analysis on the Italian case study," Renewable Energy, Elsevier, vol. 189(C), pages 983-996.
    2. 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.
    3. Moreno Jaramillo, Andres F. & Laverty, David M. & Morrow, D. John & Martinez del Rincon, Jesús & Foley, Aoife M., 2021. "Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks," Renewable Energy, Elsevier, vol. 179(C), pages 445-466.
    4. Hosseini, Sayed Saeed & Agbossou, Kodjo & Kelouwani, Sousso & Cardenas, Alben, 2017. "Non-intrusive load monitoring through home energy management systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1266-1274.
    5. Sevdari, Kristian & Calearo, Lisa & Andersen, Peter Bach & Marinelli, Mattia, 2022. "Ancillary services and electric vehicles: An overview from charging clusters and chargers technology perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Kryonidis, Georgios C. & Kontis, Eleftherios O. & Papadopoulos, Theofilos A. & Pippi, Kalliopi D. & Nousdilis, Angelos I. & Barzegkar-Ntovom, Georgios A. & Boubaris, Alexandros D. & Papanikolaou, Nick, 2021. "Ancillary services in active distribution networks: A review of technological trends from operational and online analysis perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    7. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    8. Hyeongpil Bang & Dwi Riana Aryani & Hwachang Song, 2021. "Application of Battery Energy Storage Systems for Relief of Generation Curtailment in Terms of Transient Stability," Energies, MDPI, vol. 14(13), pages 1-14, June.
    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. Hu, Jiaxiang & Hu, Weihao & Cao, Di & Sun, Xinwu & Chen, Jianjun & Huang, Yuehui & Chen, Zhe & Blaabjerg, Frede, 2024. "Probabilistic net load forecasting based on transformer network and Gaussian process-enabled residual modeling learning method," Renewable Energy, Elsevier, vol. 225(C).
    2. Weixian Che & Yanfeng Wang & Wenwei Zhu & Lexin Hong & Can Fang & Huijun Wu & Jia Liu, 2024. "A Review of Carbon Emission Reduction During the Operation Stage of Substations," Sustainability, MDPI, vol. 16(22), pages 1-22, November.

    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. Joel Alpízar-Castillo & Laura Ramirez-Elizondo & Pavol Bauer, 2022. "Assessing the Role of Energy Storage in Multiple Energy Carriers toward Providing Ancillary Services: A Review," Energies, MDPI, vol. 16(1), pages 1-31, December.
    2. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    3. Theofilos A. Papadopoulos & Kalliopi D. Pippi & Georgios A. Barzegkar-Ntovom & Eleftherios O. Kontis & Angelos I. Nousdilis & Christos L. Athanasiadis & Georgios C. Kryonidis, 2023. "Validation of a Holistic System for Operational Analysis and Provision of Ancillary Services in Active Distribution Networks," Energies, MDPI, vol. 16(6), pages 1-27, March.
    4. Abbaspour, M. & Satkin, M. & Mohammadi-Ivatloo, B. & Hoseinzadeh Lotfi, F. & Noorollahi, Y., 2013. "Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)," Renewable Energy, Elsevier, vol. 51(C), pages 53-59.
    5. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    6. İsmail Hakkı Çavdar & Vahit Feryad, 2021. "Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid," Energies, MDPI, vol. 14(15), pages 1-21, July.
    7. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    8. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    9. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Saher Javaid & Mineo Kaneko & Yasuo Tan, 2021. "Safe Operation Conditions of Electrical Power System Considering Power Balanceability among Power Generators, Loads, and Storage Devices," Energies, MDPI, vol. 14(15), pages 1-27, July.
    11. Llaria, Alvaro & Curea, Octavian & Jiménez, Jaime & Camblong, Haritza, 2011. "Survey on microgrids: Unplanned islanding and related inverter control techniques," Renewable Energy, Elsevier, vol. 36(8), pages 2052-2061.
    12. Tang, Ruoli & Li, Xin & Lai, Jingang, 2018. "A novel optimal energy-management strategy for a maritime hybrid energy system based on large-scale global optimization," Applied Energy, Elsevier, vol. 228(C), pages 254-264.
    13. Farhad Farokhi, 2019. "Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon," Papers 1908.03995, arXiv.org, revised Jan 2020.
    14. Tong, Ziqiang & Mansouri, Seyed Amir & Huang, Shoujun & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos, 2023. "The role of smart communities integrated with renewable energy resources, smart homes and electric vehicles in providing ancillary services: A tri-stage optimization mechanism," Applied Energy, Elsevier, vol. 351(C).
    15. Se-Hyeok Choi & Akhtar Hussain & Hak-Man Kim, 2018. "Adaptive Robust Optimization-Based Optimal Operation of Microgrids Considering Uncertainties in Arrival and Departure Times of Electric Vehicles," Energies, MDPI, vol. 11(10), pages 1-16, October.
    16. Batas Bjelic, Ilija & Ciric, Rade M., 2014. "Optimal distributed generation planning at a local level – A review of Serbian renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 79-86.
    17. Soha, Tamás & Munkácsy, Béla & Harmat, Ádám & Csontos, Csaba & Horváth, Gergely & Tamás, László & Csüllög, Gábor & Daróczi, Henriett & Sáfián, Fanni & Szabó, Mária, 2017. "GIS-based assessment of the opportunities for small-scale pumped hydro energy storage in middle-mountain areas focusing on artificial landscape features," Energy, Elsevier, vol. 141(C), pages 1363-1373.
    18. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    19. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Xu, Wenya & Wang, Zixuan, 2022. "Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration," Energy, Elsevier, vol. 238(PB).
    20. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.

    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:renene:v:207:y:2023:i:c:p:765-771. 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/renewable-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.