IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2019i1p41-d300011.html
   My bibliography  Save this article

The Use of Black-Box Optimization Method for Determination of the Bus Connection Capacity in Electric Power Grid

Author

Listed:
  • Andrzej Wędzik

    (Lodz University of Technology, Institute of Electrical Power Engineering, Stefanowskiego Str. 18/22, PL 90-924 Łódź, Poland)

  • Tomasz Siewierski

    (Lodz University of Technology, Institute of Electrical Power Engineering, Stefanowskiego Str. 18/22, PL 90-924 Łódź, Poland)

  • Michał Szypowski

    (Lodz University of Technology, Institute of Electrical Power Engineering, Stefanowskiego Str. 18/22, PL 90-924 Łódź, Poland)

Abstract

One of the main tasks of the Power System Operators is to ensure a proper, safe, and trouble-free operation and development of power grids. Growth of power system is inseparably linked to a connection of both renewable and classical new energy sources. For network operators and potential investors, it is essential to know the place and volume of generation capacity that can be connected to the grid. A publication of such data is currently a legal obligation for many operators. This paper proposes a method of determining the bus connection capacity in power grid of any type with the use of black-box optimization. Calculations and analyses were performed with a full, nonlinear model of the analyzed network. Obtained results show the effectiveness of this method for both single and multiple nodes in any configuration. All the constraints relevant for the proper and safe system operation, such as bus voltages, line loads, and short-circuit currents, both in a steady-state and (n-1) contingency states, are taken into consideration. Calculations confirmed the good convergence and repeatability of the method for all three tested computational algorithms. This has also confirmed the possibility of use of open source software to extend the functionality of Siemens PSS ® E commercial power system calculation software.

Suggested Citation

  • Andrzej Wędzik & Tomasz Siewierski & Michał Szypowski, 2019. "The Use of Black-Box Optimization Method for Determination of the Bus Connection Capacity in Electric Power Grid," Energies, MDPI, vol. 13(1), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:41-:d:300011
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/1/41/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/1/41/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Santarelli, M. & Pellegrino, D., 2005. "Mathematical optimization of a RES-H2 plant using a black box algorithm," Renewable Energy, Elsevier, vol. 30(4), pages 493-510.
    2. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    3. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    4. Hachicha, Wafik & Ammeri, Ahmed & Masmoudi, Faouzi & Chachoub, Habib, 2010. "A comprehensive literature classification of simulation optimisation methods," MPRA Paper 27652, University Library of Munich, Germany.
    5. Pisciella, P. & Vespucci, M.T. & Bertocchi, M. & Zigrino, S., 2016. "A time consistent risk averse three-stage stochastic mixed integer optimization model for power generation capacity expansion," Energy Economics, Elsevier, vol. 53(C), pages 203-211.
    6. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    7. Mokgonyana, Lesiba & Zhang, Jiangfeng & Li, Hailong & Hu, Yihua, 2017. "Optimal location and capacity planning for distributed generation with independent power production and self-generation," Applied Energy, Elsevier, vol. 188(C), pages 140-150.
    8. Paulescu, Marius & Brabec, Marek & Boata, Remus & Badescu, Viorel, 2017. "Structured, physically inspired (gray box) models versus black box modeling for forecasting the output power of photovoltaic plants," Energy, Elsevier, vol. 121(C), pages 792-802.
    9. Afful-Dadzie, Anthony & Afful-Dadzie, Eric & Awudu, Iddrisu & Banuro, Joseph Kwaku, 2017. "Power generation capacity planning under budget constraint in developing countries," Applied Energy, Elsevier, vol. 188(C), pages 71-82.
    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. Moret, Stefano & Babonneau, Frédéric & Bierlaire, Michel & Maréchal, François, 2020. "Overcapacity in European power systems: Analysis and robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    2. Acha, Salvador & Mariaud, Arthur & Shah, Nilay & Markides, Christos N., 2018. "Optimal design and operation of distributed low-carbon energy technologies in commercial buildings," Energy, Elsevier, vol. 142(C), pages 578-591.
    3. Jonas Bjerg Thomsen & Francesco Ferri & Jens Peter Kofoed & Kevin Black, 2018. "Cost Optimization of Mooring Solutions for Large Floating Wave Energy Converters," Energies, MDPI, vol. 11(1), pages 1-23, January.
    4. Ali A. Radwan & Ahmed A. Zaki Diab & Abo-Hashima M. Elsayed & Hassan Haes Alhelou & Pierluigi Siano, 2020. "Active Distribution Network Modeling for Enhancing Sustainable Power System Performance; a Case Study in Egypt," Sustainability, MDPI, vol. 12(21), pages 1-22, October.
    5. Zheng, Liang & Xue, Xinfeng & Xu, Chengcheng & Ran, Bin, 2019. "A stochastic simulation-based optimization method for equitable and efficient network-wide signal timing under uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 287-308.
    6. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    7. Wang, Zhiwen & Shen, Chen & Liu, Feng, 2018. "A conditional model of wind power forecast errors and its application in scenario generation," Applied Energy, Elsevier, vol. 212(C), pages 771-785.
    8. Nasreddine Belbachir & Mohamed Zellagui & Samir Settoul & Claude Ziad El-Bayeh & Ragab A. El-Sehiemy, 2023. "Multi Dimension-Based Optimal Allocation of Uncertain Renewable Distributed Generation Outputs with Seasonal Source-Load Power Uncertainties in Electrical Distribution Network Using Marine Predator Al," Energies, MDPI, vol. 16(4), pages 1-24, February.
    9. Gabriela Simonet & Julie Subervie & Driss Ezzine-De-Blas & Marina Cromberg & Amy Duchelle, 2015. "Paying smallholders not to cut down the amazon forest: impact evaluation of a REDD+ pilot project," Working Papers 1514, Chaire Economie du climat.
    10. Somayeh Moazeni & Warren B. Powell & Boris Defourny & Belgacem Bouzaiene-Ayari, 2017. "Parallel Nonstationary Direct Policy Search for Risk-Averse Stochastic Optimization," INFORMS Journal on Computing, INFORMS, vol. 29(2), pages 332-349, May.
    11. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Chen, Runze & Wang, Bin, 2017. "A robust aggregate model and the two-stage solution method to incorporate energy intensive enterprises in power system unit commitment," Applied Energy, Elsevier, vol. 206(C), pages 1364-1378.
    12. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    13. Zheng, Lingwei & Su, Ran & Sun, Xinyu & Guo, Siqi, 2023. "Historical PV-output characteristic extraction based weather-type classification strategy and its forecasting method for the day-ahead prediction of PV output," Energy, Elsevier, vol. 271(C).
    14. Afful-Dadzie, Anthony & Afful-Dadzie, Eric & Awudu, Iddrisu & Banuro, Joseph Kwaku, 2017. "Power generation capacity planning under budget constraint in developing countries," Applied Energy, Elsevier, vol. 188(C), pages 71-82.
    15. Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," Energy Economics, Elsevier, vol. 92(C).
    16. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    17. Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    18. Tianyu Lu & Hongyu Li, 2024. "Can China’s Regional Industrial Chain Innovation and Reform Policy Make the Impossible Triangle of Energy Attainable? A Causal Inference Study on the Effect of Improving Industrial Chain Resilience," Energies, MDPI, vol. 17(10), pages 1-33, May.
    19. Da Liu & Kun Sun & Han Huang & Pingzhou Tang, 2018. "Monthly Load Forecasting Based on Economic Data by Decomposition Integration Theory," Sustainability, MDPI, vol. 10(9), pages 1-22, September.
    20. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.

    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:gam:jeners:v:13:y:2019:i:1:p:41-:d:300011. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.