IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i23p6409-d456798.html
   My bibliography  Save this article

FPAES: A Hybrid Approach for the Optimal Placement and Sizing of Reactive Compensation in Distribution Grids

Author

Listed:
  • Diego José da Silva

    (Center for Engineering, Modeling and Applied Social Sciences (CECS), Federal University of ABC, Santo André, SP 09210-170, Brazil
    These authors contributed equally to this work.)

  • Edmarcio Antonio Belati

    (Center for Engineering, Modeling and Applied Social Sciences (CECS), Federal University of ABC, Santo André, SP 09210-170, Brazil
    These authors contributed equally to this work.)

  • Eduardo Werley Silva dos Angelos

    (Center for Engineering, Modeling and Applied Social Sciences (CECS), Federal University of ABC, Santo André, SP 09210-170, Brazil
    These authors contributed equally to this work.)

Abstract

Reactive power compensation with Capacitor Banks (CBs) is one of the most successful approaches used in distribution systems, mainly due to their versatility, long-term acceptance in the power industry, and reduced costs. Most allocation methods, however, lack specific strategies to handle the limited discrete nature of CBs sizes seeking to improve the overall optimization and computational performance. We present an algorithm for the Optimal Placement of Capacitor Banks (OPCB) in distribution systems by means of a hybrid Flower Pollination Algorithm (FPA)–Exhaustive Search (ES) approach. The pollination process itself determines the sets of buses for placement, while CBs sizes and the final fitness values of each pollen are selected after a full-search is conducted in the sizing space. As the sizing phase works on the limited search space of predetermined discrete bank values, the computational effort to find the optimum CB capacity is greatly reduced. Tests were performed on distribution systems of 10, 34, and 85 buses with respect to the objective function, final losses, and voltage profile. The algorithm offers an excellent compromise between solution quality and computational effort, when compared to similar approaches.

Suggested Citation

  • Diego José da Silva & Edmarcio Antonio Belati & Eduardo Werley Silva dos Angelos, 2020. "FPAES: A Hybrid Approach for the Optimal Placement and Sizing of Reactive Compensation in Distribution Grids," Energies, MDPI, vol. 13(23), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6409-:d:456798
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/23/6409/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/23/6409/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    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. Cícero Augusto de Souza & Diego Jose da Silva & Priscila Rossoni & Edmarcio Antonio Belati & Ademir Pelizari & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2023. "Multi-Period Optimal Power Flow with Photovoltaic Generation Considering Optimized Power Factor Control," Sustainability, MDPI, vol. 15(19), pages 1-20, September.
    2. Muhammad Junaid Tahir & Muhammad Babar Rasheed & Mohd Khairil Rahmat, 2022. "Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization," Energies, MDPI, vol. 15(7), pages 1-27, March.
    3. Diego Jose da Silva & Edmarcio Antonio Belati & Jesús M. López-Lezama, 2023. "A Mathematical Programming Approach for the Optimal Operation of Storage Systems, Photovoltaic and Wind Power Generation," Energies, MDPI, vol. 16(3), pages 1-24, January.

    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. Chandrasekaran Venkatesan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems," Sustainability, MDPI, vol. 13(6), pages 1-34, March.
    2. Peng Cheng & Zhiyu Xu & Ruiye Li & Chao Shi, 2022. "A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources," Energies, MDPI, vol. 15(13), pages 1-16, June.
    3. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2023. "Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks," Energies, MDPI, vol. 17(1), pages 1-24, December.
    4. Devabalaji Kaliaperumal Rukmani & Yuvaraj Thangaraj & Umashankar Subramaniam & Sitharthan Ramachandran & Rajvikram Madurai Elavarasan & Narottam Das & Luis Baringo & Mohamed Imran Abdul Rasheed, 2020. "A New Approach to Optimal Location and Sizing of DSTATCOM in Radial Distribution Networks Using Bio-Inspired Cuckoo Search Algorithm," Energies, MDPI, vol. 13(18), pages 1-21, September.
    5. Azeredo, Lucas F.S. & Yahyaoui, Imene & Fiorotti, Rodrigo & Fardin, Jussara F. & Garcia-Pereira, Hilel & Rocha, Helder R.O., 2023. "Study of reducing losses, short-circuit currents and harmonics by allocation of distributed generation, capacitor banks and fault current limiters in distribution grids," Applied Energy, Elsevier, vol. 350(C).
    6. Xiaosheng Peng & Kai Cheng & Jianxun Lang & Zuowei Zhang & Tao Cai & Shanxu Duan, 2021. "Short-Term Wind Power Prediction for Wind Farm Clusters Based on SFFS Feature Selection and BLSTM Deep Learning," Energies, MDPI, vol. 14(7), pages 1-18, March.
    7. Pereira, Luan D.L. & Yahyaoui, Imene & Fiorotti, Rodrigo & de Menezes, Luíza S. & Fardin, Jussara F. & Rocha, Helder R.O. & Tadeo, Fernando, 2022. "Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations," Applied Energy, Elsevier, vol. 307(C).
    8. Syed Ali Abbas Kazmi & Usama Ameer Khan & Hafiz Waleed Ahmad & Sajid Ali & Dong Ryeol Shin, 2020. "A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth," Energies, MDPI, vol. 13(6), pages 1-71, March.
    9. Ayat Ali Saleh & Tomonobu Senjyu & Salem Alkhalaf & Majed A. Alotaibi & Ashraf M. Hemeida, 2020. "Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models," Energies, MDPI, vol. 13(21), pages 1-24, November.
    10. Tzu-Chia Chen & José Ricardo Nuñez Alvarez & Ngakan Ketut Acwin Dwijendra & Zainab Jawad Kadhim & Reza Alayi & Ravinder Kumar & Seepana PraveenKumar & Vladimir Ivanovich Velkin, 2023. "Modeling and Optimization of Combined Heating, Power, and Gas Production System Based on Renewable Energies," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    11. Kumar, Abhishek & Meena, Nand K. & Singh, Arvind R. & Deng, Yan & He, Xiangning & Bansal, R.C. & Kumar, Praveen, 2019. "Strategic integration of battery energy storage systems with the provision of distributed ancillary services in active distribution systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Ali Selim & Salah Kamel & Amal A. Mohamed & Ehab E. Elattar, 2021. "Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique," Sustainability, MDPI, vol. 13(12), pages 1-31, June.
    13. Thuan Thanh Nguyen & Bach Hoang Dinh & Thai Dinh Pham & Thang Trung Nguyen, 2020. "Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    14. Anaya, Karim L. & Pollitt, Michael G., 2020. "Reactive power procurement: A review of current trends," Applied Energy, Elsevier, vol. 270(C).
    15. David Steveen Guzmán-Romero & Brandon Cortés-Caicedo & Oscar Danilo Montoya, 2023. "Development of a MATLAB-GAMS Framework for Solving the Problem Regarding the Optimal Location and Sizing of PV Sources in Distribution Networks," Resources, MDPI, vol. 12(3), pages 1-19, March.
    16. Jiang, Tao & Dong, Xinru & Zhang, Rufeng & Li, Xue, 2023. "Strategic active and reactive power scheduling of integrated community energy systems in day-ahead distribution electricity market," Applied Energy, Elsevier, vol. 336(C).
    17. Mohamed A. Elseify & Salah Kamel & Hussein Abdel-Mawgoud & Ehab E. Elattar, 2022. "A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    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. Syed Ali Abbas Kazmi & Hafiz Waleed Ahmad & Dong Ryeol Shin, 2019. "A New Improved Voltage Stability Assessment Index-centered Integrated Planning Approach for Multiple Asset Placement in Mesh Distribution Systems," Energies, MDPI, vol. 12(16), pages 1-41, 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:gam:jeners:v:13:y:2020:i:23:p:6409-:d:456798. 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.