IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6351-d650013.html
   My bibliography  Save this article

Optimization of the Configuration and Operating States of Hybrid AC/DC Low Voltage Microgrid Using a Clonal Selection Algorithm with a Modified Hypermutation Operator

Author

Listed:
  • Łukasz Rokicki

    (Faculty of Electrical Engineering, Warsaw University of Technology, Koszykowa 75 Street, 00-662 Warsaw, Poland)

Abstract

The issue of optimization of the configuration and operating states in low voltage microgrids is important both from the point of view of the proper operation of the microgrid and its impact on the medium voltage distribution network to which such microgrid is connected. Suboptimal microgrid configuration may cause problems in networks managed by distribution system operators, as well as for electricity consumers and owners of microsources and energy storage systems connected to the microgrid. Structures particularly sensitive to incorrect determination of the operating states of individual devices are hybrid microgrids that combine an alternating current and direct current networks with the use of a bidirectional power electronic converter. An analysis of available literature shows that evolutionary and swarm optimization algorithms are the most frequently chosen for the optimization of power systems. The research presented in this article concerns the assessment of the possibilities of using artificial immune systems, operating on the basis of the CLONALG algorithm, as tools enabling the effective optimization of low voltage hybrid microgrids. In his research, the author developed a model of a hybrid low voltage microgrid, formulated three optimization tasks, and implemented an algorithm for solving the formulated tasks based on an artificial immune system using the CLONALG algorithm. The conducted research consisted of performing a 24 h simulation of microgrid operation for each of the formulated optimization tasks (divided into 10 min independent optimization periods). A novelty in the conducted research was the modification of the hypermutation operator, which is the key mechanism for the functioning of the CLONALG algorithm. In order to verify the changes introduced in the CLONALG algorithm and to assess the effectiveness of the artificial immune system in solving optimization tasks, optimization was also carried out with the use of an evolutionary algorithm, commonly used in solving such tasks. Based on the analysis of the obtained results of optimization calculations, it can be concluded that the artificial immune system proposed in this article, operating on the basis of the CLONALG algorithm with a modified hypermutation operator, in most of the analyzed cases obtained better results than the evolutionary algorithm. In several cases, both algorithms obtained identical results, which also proves that the CLONALG algorithm can be considered as an effective tool for optimizing modern power structures, such as low voltage microgrids, including hybrid AC/DC microgrids.

Suggested Citation

  • Łukasz Rokicki, 2021. "Optimization of the Configuration and Operating States of Hybrid AC/DC Low Voltage Microgrid Using a Clonal Selection Algorithm with a Modified Hypermutation Operator," Energies, MDPI, vol. 14(19), pages 1-24, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6351-:d:650013
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6351/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6351/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Ehsan Sedgh Gooya, 2021. "Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends," Energies, MDPI, vol. 14(14), pages 1-45, July.
    2. Dwi Riana Aryani & Hwachang Song, 2016. "Coordination Control Strategy for AC/DC Hybrid Microgrids in Stand-Alone Mode," Energies, MDPI, vol. 9(6), pages 1-20, June.
    3. Jing Li & Hongda Cai & Pengcheng Yang & Wei Wei, 2021. "A Bus-Sectionalized Hybrid AC/DC Microgrid: Concept, Control Paradigm, and Implementation," Energies, MDPI, vol. 14(12), pages 1-24, June.
    4. Shahriar Rahman Fahim & Subrata K. Sarker & S. M. Muyeen & Md. Rafiqul Islam Sheikh & Sajal K. Das, 2020. "Microgrid Fault Detection and Classification: Machine Learning Based Approach, Comparison, and Reviews," Energies, MDPI, vol. 13(13), pages 1-22, July.
    5. Xiong Wu & Zhao Wang & Tao Ding & Zhiyi Li, 2019. "Hybrid AC/DC Microgrid Planning with Optimal Placement of DC Feeders," Energies, MDPI, vol. 12(9), pages 1-23, May.
    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. Bo Hu & Nan Wang & Zaiming Yu & Yunqing Cao & Dongsheng Yang & Li Sun, 2021. "Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory," Energies, MDPI, vol. 15(1), pages 1-21, December.
    2. Grzegorz Dudek & Paweł Piotrowski & Dariusz Baczyński, 2023. "Intelligent Forecasting and Optimization in Electrical Power Systems: Advances in Models and Applications," Energies, MDPI, vol. 16(7), pages 1-11, March.

    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. Muhammad Umair Safder & Mohammad J. Sanjari & Ameer Hamza & Rasoul Garmabdari & Md. Alamgir Hossain & Junwei Lu, 2023. "Enhancing Microgrid Stability and Energy Management: Techniques, Challenges, and Future Directions," Energies, MDPI, vol. 16(18), pages 1-28, September.
    2. Yalin Liang & Yuyao He & Yun Niu, 2022. "Robust Errorless-Control-Targeted Technique Based on MPC for Microgrid with Uncertain Electric Vehicle Energy Storage Systems," Energies, MDPI, vol. 15(4), pages 1-23, February.
    3. Wenzheng Xu & Nelson Hon Lung Chan & Siu Wing Or & Siu Lau Ho & Ka Wing Chan, 2017. "A New Control Method for a Bi-Directional Phase-Shift-Controlled DC-DC Converter with an Extended Load Range," Energies, MDPI, vol. 10(10), pages 1-17, October.
    4. Spyridon Chapaloglou & Babak Abdolmaleki & Elisabetta Tedeschi, 2023. "Optimal Generation Capacity Allocation and Droop Control Design for Current Sharing in DC Microgrids," Energies, MDPI, vol. 16(12), pages 1-17, June.
    5. Lei Chen & Xiude Tu & Hongkun Chen & Jun Yang & Yayi Wu & Xin Shu & Li Ren, 2016. "Technical Evaluation of Superconducting Fault Current Limiters Used in a Micro-Grid by Considering the Fault Characteristics of Distributed Generation, Energy Storage and Power Loads," Energies, MDPI, vol. 9(10), pages 1-21, September.
    6. Jingpeng Yue & Zhijian Hu & Chendan Li & Juan C. Vasquez & Josep M. Guerrero, 2017. "Economic Power Schedule and Transactive Energy through an Intelligent Centralized Energy Management System for a DC Residential Distribution System," Energies, MDPI, vol. 10(7), pages 1-14, July.
    7. Danilo Santoro & Nicola Delmonte & Marco Simonazzi & Andrea Toscani & Nicholas Rocchi & Giovanna Sozzi & Paolo Cova & Roberto Menozzi, 2023. "Local Power Distribution—A Review of Nanogrid Architectures, Control Strategies, and Converters," Sustainability, MDPI, vol. 15(3), pages 1-29, February.
    8. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    9. Abdulgader Alsharif & Chee Wei Tan & Razman Ayop & Ahmed Al Smin & Abdussalam Ali Ahmed & Farag Hamed Kuwil & Mohamed Mohamed Khaleel, 2023. "Impact of Electric Vehicle on Residential Power Distribution Considering Energy Management Strategy and Stochastic Monte Carlo Algorithm," Energies, MDPI, vol. 16(3), pages 1-22, January.
    10. Yijin Li & Jianhua Lin & Geng Niu & Ming Wu & Xuteng Wei, 2021. "A Hilbert–Huang Transform-Based Adaptive Fault Detection and Classification Method for Microgrids," Energies, MDPI, vol. 14(16), pages 1-16, August.
    11. Mokesioluwa Fanoro & Mladen Božanić & Saurabh Sinha, 2022. "A Review of the Impact of Battery Degradation on Energy Management Systems with a Special Emphasis on Electric Vehicles," Energies, MDPI, vol. 15(16), pages 1-29, August.
    12. Omar Makram Kamel & Ahmed A. Zaki Diab & Mohamed Metwally Mahmoud & Ameena Saad Al-Sumaiti & Hamdy M. Sultan, 2023. "Performance Enhancement of an Islanded Microgrid with the Support of Electrical Vehicle and STATCOM Systems," Energies, MDPI, vol. 16(4), pages 1-19, February.
    13. Mahdi Shahparasti & Mehdi Savaghebi & Majid Hosseinpour & Navid Rasekh, 2020. "Enhanced Circular Chain Control for Parallel Operation of Inverters in UPS Systems," Sustainability, MDPI, vol. 12(19), pages 1-16, September.
    14. Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
    15. Sadaqat Ali & Zhixue Zheng & Michel Aillerie & Jean-Paul Sawicki & Marie-Cécile Péra & Daniel Hissel, 2021. "A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications," Energies, MDPI, vol. 14(14), pages 1-26, July.
    16. Robert Salas-Puente & Silvia Marzal & Raúl González-Medina & Emilio Figueres & Gabriel Garcera, 2017. "Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode," Energies, MDPI, vol. 10(10), pages 1-25, October.
    17. Raad Salih Jawad & Hafedh Abid, 2023. "HVDC Fault Detection and Classification with Artificial Neural Network Based on ACO-DWT Method," Energies, MDPI, vol. 16(3), pages 1-18, January.
    18. Nur Najihah Abu Bakar & Josep M. Guerrero & Juan C. Vasquez & Najmeh Bazmohammadi & Yun Yu & Abdullah Abusorrah & Yusuf A. Al-Turki, 2021. "A Review of the Conceptualization and Operational Management of Seaport Microgrids on the Shore and Seaside," Energies, MDPI, vol. 14(23), pages 1-31, November.
    19. Daud Mustafa Minhas & Josef Meiers & Georg Frey, 2022. "Electric Vehicle Battery Storage Concentric Intelligent Home Energy Management System Using Real Life Data Sets," Energies, MDPI, vol. 15(5), pages 1-29, February.
    20. Jannis N. Kahlen & Michael Andres & Albert Moser, 2021. "Improving Machine-Learning Diagnostics with Model-Based Data Augmentation Showcased for a Transformer Fault," Energies, MDPI, vol. 14(20), pages 1-20, October.

    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:14:y:2021:i:19:p:6351-:d:650013. 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.