IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i4p793-d138731.html
   My bibliography  Save this article

A Case Study of Control and Improved Simplified Swarm Optimization for Economic Dispatch of a Stand-Alone Modular Microgrid

Author

Listed:
  • Xianyong Zhang

    (Department of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Wei-chang Yeh

    (Integration and Collaboration Laboratory, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 46804804, Taiwan)

  • Yunzhi Jiang

    (School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Yaohong Huang

    (Department of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Yingwang Xiao

    (Department of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Li Li

    (Department of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

Abstract

Due to the complex configuration and control framework, the conventional microgrid is not cost-effective for engineering applications with small or medium capacity. A stand-alone modular microgrid with separated AC bus and decentralized control strategy is proposed in this paper. Each module is a self-powered system, which consists of wind and solar power, a storage battery, load and three-port converter. The modules are interconnected by three-port converters to form the microgrid. Characteristics, operation principle, control of the modular microgrid and the three-port converter are analyzed in detail. Distributed storage batteries enable power exchanges among modules to enhance economic returns. Economic dispatch of the stand-alone modular microgrid is a mixed-integer programming problem. A day-ahead operation optimization model including fuel cost, battery operation cost, and power transmission cost is established. Because there are so many constraints, it is difficult to produce a feasible solution and even more difficult to have an improved solution. An improved simplified swarm optimization (iSSO) method is therefore proposed. The iSSO scheme designs the new update mechanism and survival of the fittest policy. The experimental results from the demonstration project on DongAo Island reflect the effectiveness of the stand-alone modular microgrid and the economic dispatch strategy based on the iSSO method.

Suggested Citation

  • Xianyong Zhang & Wei-chang Yeh & Yunzhi Jiang & Yaohong Huang & Yingwang Xiao & Li Li, 2018. "A Case Study of Control and Improved Simplified Swarm Optimization for Economic Dispatch of a Stand-Alone Modular Microgrid," Energies, MDPI, vol. 11(4), pages 1-21, March.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:793-:d:138731
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/4/793/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/4/793/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    2. Athari, Hamed & Niroomand, Mehdi & Ataei, Mohammad, 2017. "Review and Classification of Control Systems in Grid-tied Inverters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1167-1176.
    3. 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.
    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. Yeh, Wei-Chang & He, Min-Fan & Huang, Chia-Ling & Tan, Shi-Yi & Zhang, Xianyong & Huang, Yaohong & Li, Li, 2020. "New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island," Applied Energy, Elsevier, vol. 263(C).
    2. Meihua Wang & Wei-Chang Yeh & Ta-Chung Chu & Xianyong Zhang & Chia-Ling Huang & Jun Yang, 2018. "Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm," Energies, MDPI, vol. 11(9), pages 1-23, September.
    3. Jingfeng Chen & Ping Yang & Jiajun Peng & Yuqi Huang & Yaosheng Chen & Zhiji Zeng, 2018. "An Improved Multi-Timescale Coordinated Control Strategy for Stand-Alone Microgrid with Hybrid Energy Storage System," Energies, MDPI, vol. 11(8), pages 1-23, August.
    4. Xianyong Zhang & Yaohong Huang & Li Li & Wei-Chang Yeh, 2018. "Power and Capacity Consensus Tracking of Distributed Battery Storage Systems in Modular Microgrids," Energies, MDPI, vol. 11(6), pages 1-25, June.
    5. Yeh, Wei-Chang & Zhu, Wenbo & Tan, Shi-Yi & Wang, Gai-Ge & Yeh, Yuan-Hui, 2022. "Novel general active reliability redundancy allocation problems and algorithm," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

    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. Yeh, Wei-Chang & He, Min-Fan & Huang, Chia-Ling & Tan, Shi-Yi & Zhang, Xianyong & Huang, Yaohong & Li, Li, 2020. "New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island," Applied Energy, Elsevier, vol. 263(C).
    2. Fethi Khlifi & Habib Cherif & Jamel Belhadj, 2021. "Environmental and Economic Optimization and Sizing of a Micro-Grid with Battery Storage for an Industrial Application," Energies, MDPI, vol. 14(18), pages 1-17, September.
    3. Juaidi, Adel & Montoya, Francisco G. & Ibrik, Imad H. & Manzano-Agugliaro, Francisco, 2016. "An overview of renewable energy potential in Palestine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 943-960.
    4. Hang, Yin & Du, Lili & Qu, Ming & Peeta, Srinivas, 2013. "Multi-objective optimization of integrated solar absorption cooling and heating systems for medium-sized office buildings," Renewable Energy, Elsevier, vol. 52(C), pages 67-78.
    5. Zhang, Wei & Zhu, Rui & Liu, Bin & Ramakrishna, Seeram, 2012. "High-performance hybrid solar cells employing metal-free organic dye modified TiO2 as photoelectrode," Applied Energy, Elsevier, vol. 90(1), pages 305-308.
    6. Sherif A. Zaid & Ahmed M. Kassem & Aadel M. Alatwi & Hani Albalawi & Hossam AbdelMeguid & Atef Elemary, 2023. "Optimal Control of an Autonomous Microgrid Integrated with Super Magnetic Energy Storage Using an Artificial Bee Colony Algorithm," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    7. Domenech, B. & Ferrer-Martí, L. & Pastor, R., 2015. "Hierarchical methodology to optimize the design of stand-alone electrification systems for rural communities considering technical and social criteria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 182-196.
    8. Nicolas Martinez & Youssef Benchaabane & Rosa Elvira Silva & Adrian Ilinca & Hussein Ibrahim & Ambrish Chandra & Daniel R. Rousse, 2019. "Computer Model for a Wind–Diesel Hybrid System with Compressed Air Energy Storage," Energies, MDPI, vol. 12(18), pages 1-18, September.
    9. Mwaka I. Juma & Bakari M. M. Mwinyiwiwa & Consalva J. Msigwa & Aviti T. Mushi, 2021. "Design of a Hybrid Energy System with Energy Storage for Standalone DC Microgrid Application," Energies, MDPI, vol. 14(18), pages 1-15, September.
    10. Yiqi Chu & Chengcai Li & Yefang Wang & Jing Li & Jian Li, 2016. "A Long-Term Wind Speed Ensemble Forecasting System with Weather Adapted Correction," Energies, MDPI, vol. 9(11), pages 1-20, October.
    11. Hong, Jin Gi & Zhang, Wen & Luo, Jian & Chen, Yongsheng, 2013. "Modeling of power generation from the mixing of simulated saline and freshwater with a reverse electrodialysis system: The effect of monovalent and multivalent ions," Applied Energy, Elsevier, vol. 110(C), pages 244-251.
    12. Bizon, Nicu, 2019. "Hybrid power sources (HPSs) for space applications: Analysis of PEMFC/Battery/SMES HPS under unknown load containing pulses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 14-37.
    13. Deetjen, Thomas A. & Martin, Henry & Rhodes, Joshua D. & Webber, Michael E., 2018. "Modeling the optimal mix and location of wind and solar with transmission and carbon pricing considerations," Renewable Energy, Elsevier, vol. 120(C), pages 35-50.
    14. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    15. Upadhyay, Subho & Sharma, M.P., 2016. "Selection of a suitable energy management strategy for a hybrid energy system in a remote rural area of India," Energy, Elsevier, vol. 94(C), pages 352-366.
    16. Xiangyuan Zheng & Huadong Zheng & Yu Lei & Yi Li & Wei Li, 2020. "An Offshore Floating Wind–Solar–Aquaculture System: Concept Design and Extreme Response in Survival Conditions," Energies, MDPI, vol. 13(3), pages 1-23, January.
    17. Segurado, R. & Madeira, J.F.A. & Costa, M. & Duić, N. & Carvalho, M.G., 2016. "Optimization of a wind powered desalination and pumped hydro storage system," Applied Energy, Elsevier, vol. 177(C), pages 487-499.
    18. Good, Nicholas & Martínez Ceseña, Eduardo A. & Zhang, Lingxi & Mancarella, Pierluigi, 2016. "Techno-economic and business case assessment of low carbon technologies in distributed multi-energy systems," Applied Energy, Elsevier, vol. 167(C), pages 158-172.
    19. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
    20. 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.

    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:4:p:793-:d:138731. 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.