IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i1p255-d127982.html
   My bibliography  Save this article

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

Author

Listed:
  • Kadir Doğanşahin

    (Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey)

  • Bedri Kekezoğlu

    (Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey)

  • Recep Yumurtacı

    (Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey)

  • Ozan Erdinç

    (Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey
    Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento (INESC-ID), Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal)

  • João P. S. Catalão

    (Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento (INESC-ID), Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
    Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC-TEC) and the Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
    Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, 6201-001 Covilha, Portugal)

Abstract

Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number of such applications increases daily. As conventional power systems do not have an infrastructure that is compatible with these energy sources and generation systems, such integration applications may cause various problems in power systems. Therefore, planning is an essential part of DG integration, especially for power systems with intermittent renewable energy sources with the objective of minimizing problems and maximizing benefits. In this study, a mathematical model is proposed to calculate the maximum permissible DG integration capacity without causing overvoltage problems in the power systems. In the proposed mathematical model, both the minimum loading condition and maximum generation condition are taken into consideration. In order to prove the effectiveness and the consistency of the proposed mathematical model, it is applied to a test system with different case studies, and the results are compared with the results obtained from other models in the literature.

Suggested Citation

  • Kadir Doğanşahin & Bedri Kekezoğlu & Recep Yumurtacı & Ozan Erdinç & João P. S. Catalão, 2018. "Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads," Energies, MDPI, vol. 11(1), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:255-:d:127982
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/1/255/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/1/255/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Singh, Bindeshwar & Sharma, Janmejay, 2017. "A review on distributed generation planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 529-544.
    2. Vasiliki Vita, 2017. "Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks," Energies, MDPI, vol. 10(9), pages 1-13, September.
    3. Sultana, U. & Khairuddin, Azhar B. & Aman, M.M. & Mokhtar, A.S. & Zareen, N., 2016. "A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 363-378.
    4. Prakash, Prem & Khatod, Dheeraj K., 2016. "Optimal sizing and siting techniques for distributed generation in distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 111-130.
    5. Pepermans, G. & Driesen, J. & Haeseldonckx, D. & Belmans, R. & D'haeseleer, W., 2005. "Distributed generation: definition, benefits and issues," Energy Policy, Elsevier, vol. 33(6), pages 787-798, April.
    6. Pierluigi Caramia & Enrica Di Mambro & Pietro Varilone & Paola Verde, 2017. "Impact of Distributed Generation on the Voltage Sag Performance of Transmission Systems," Energies, MDPI, vol. 10(7), pages 1-19, July.
    7. Viral, Rajkumar & Khatod, D.K., 2012. "Optimal planning of distributed generation systems in distribution system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5146-5165.
    8. 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.
    9. Mohsin Shahzad & Ishtiaq Ahmad & Wolfgang Gawlik & Peter Palensky, 2016. "Load Concentration Factor Based Analytical Method for Optimal Placement of Multiple Distribution Generators for Loss Minimization and Voltage Profile Improvement," Energies, MDPI, vol. 9(4), pages 1-21, April.
    10. 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.
    11. Esmaili, Masoud & Firozjaee, Esmail Chaktan & Shayanfar, Heidar Ali, 2014. "Optimal placement of distributed generations considering voltage stability and power losses with observing voltage-related constraints," Applied Energy, Elsevier, vol. 113(C), pages 1252-1260.
    12. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
    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. Ghaeth Fandi & Ibrahim Ahmad & Famous O. Igbinovia & Zdenek Muller & Josef Tlusty & Vladimir Krepl, 2018. "Voltage Regulation and Power Loss Minimization in Radial Distribution Systems via Reactive Power Injection and Distributed Generation Unit Placement," Energies, MDPI, vol. 11(6), pages 1-17, May.
    2. Evangelos S. Chatzistylianos & Georgios N. Psarros & Stavros A. Papathanassiou, 2024. "Export Constraints Applicable to Renewable Generation to Enhance Grid Hosting Capacity," Energies, MDPI, vol. 17(11), pages 1-30, May.
    3. Luis Fernando Grisales-Noreña & Daniel Gonzalez Montoya & Carlos Andres Ramos-Paja, 2018. "Optimal Sizing and Location of Distributed Generators Based on PBIL and PSO Techniques," Energies, MDPI, vol. 11(4), pages 1-27, April.
    4. Hyun-Tae Kim & Jungju Lee & Myungseok Yoon & Moon-Jeong Lee & Namhun Cho & Sungyun Choi, 2020. "Continuation Power Flow Based Distributed Energy Resource Hosting Capacity Estimation Considering Renewable Energy Uncertainty and Stability in Distribution Systems," Energies, MDPI, vol. 13(17), pages 1-16, August.

    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. Vikas Singh Bhadoria & Nidhi Singh Pal & Vivek Shrivastava, 2019. "Artificial immune system based approach for size and location optimization of distributed generation in distribution system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 339-349, June.
    2. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    3. Zeeshan Memon Anjum & Dalila Mat Said & Mohammad Yusri Hassan & Zohaib Hussain Leghari & Gul Sahar, 2022. "Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-38, April.
    4. Eshan Karunarathne & Jagadeesh Pasupuleti & Janaka Ekanayake & Dilini Almeida, 2020. "Optimal Placement and Sizing of DGs in Distribution Networks Using MLPSO Algorithm," Energies, MDPI, vol. 13(23), pages 1-25, November.
    5. Razavi, Seyed-Ehsan & Rahimi, Ehsan & Javadi, Mohammad Sadegh & Nezhad, Ali Esmaeel & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Impact of distributed generation on protection and voltage regulation of distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 157-167.
    6. Sultana, U. & Khairuddin, Azhar B. & Aman, M.M. & Mokhtar, A.S. & Zareen, N., 2016. "A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 363-378.
    7. Prakash, Prem & Khatod, Dheeraj K., 2016. "Optimal sizing and siting techniques for distributed generation in distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 111-130.
    8. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    9. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
    10. Syed Ali Abbas Kazmi & Abdul Kashif Janjua & Dong Ryeol Shin, 2018. "Enhanced Voltage Stability Assessment Index Based Planning Approach for Mesh Distribution Systems," Energies, MDPI, vol. 11(5), pages 1-36, May.
    11. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    12. Jain, Sanjay & Kalambe, Shilpa & Agnihotri, Ganga & Mishra, Anuprita, 2017. "Distributed generation deployment: State-of-the-art of distribution system planning in sustainable era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 363-385.
    13. Mohsin Shahzad & Waseem Akram & Muhammad Arif & Uzair Khan & Barkat Ullah, 2021. "Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm," Energies, MDPI, vol. 14(6), pages 1-13, March.
    14. Rani, Preeti & Parkash, Ved & Sharma, Naveen Kumar, 2024. "Technological aspects, utilization and impact on power system for distributed generation: A comprehensive survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    15. Karatepe, Engin & Ugranlı, Faruk & Hiyama, Takashi, 2015. "Comparison of single- and multiple-distributed generation concepts in terms of power loss, voltage profile, and line flows under uncertain scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 317-327.
    16. 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.
    17. José A. G. Cararo & João Caetano Neto & Wagner A. Vilela Júnior & Márcio R. C. Reis & Gabriel A. Wainer & Paulo V. dos Santos & Wesley P. Calixto, 2021. "Spatial Model of Optimization Applied in the Distributed Generation Photovoltaic to Adjust Voltage Levels," Energies, MDPI, vol. 14(22), pages 1-37, November.
    18. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    19. Prem Prakash & Duli Chand Meena & Hasmat Malik & Majed A. Alotaibi & Irfan Ahmad Khan, 2022. "A Novel Analytical Approach for Optimal Integration of Renewable Energy Sources in Distribution Systems," Energies, MDPI, vol. 15(4), pages 1-23, February.
    20. Funcke, Simon & Bauknecht, Dierk, 2016. "Typology of centralised and decentralised visions for electricity infrastructure," Utilities Policy, Elsevier, vol. 40(C), pages 67-74.

    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:11:y:2018:i:1:p:255-:d:127982. 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.