IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i8p2694-d161248.html
   My bibliography  Save this article

Application of Multi-Species Differential Evolution Algorithm in Sustainable Microgrid Model

Author

Listed:
  • Hui-Juan Zhang

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Yi-Bo Feng

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Kuo-Ping Lin

    (Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan)

Abstract

The safety and stability of microgrid (MG) operations are closely related to the capacity of distributed energy resources. A conventional MG model usually adopts investment cost as an objective function. Recently, the issue of environmental protection has been gradually emphasized. Therefore, the objective function of the proposed sustainable microgrid (SMG) model in this study considers the investment cost and environmental protective cost and the decision variable is the capacity of the distributed power. Moreover, weather and electric power load data from the National Centers for Environmental Information database (2010) were analyzed in Matlab program for the case study of Alabaster city, United States of America (USA). For the sake of a stable and economical SMG operation, this study also attempts to use a multi-objective capacity optimal model for effectively solving SMG under a multi-population differential evolution (MPDE) algorithm with dominant population (DP), which can improve the convergence speed in an SMG model. At the same time, considering that different scheduling strategies will also affect the optimization results, two strategies are proposed for the priority order of distributed generation sources. The optimization results under the two scheduling strategies show that the validation of the MPDE algorithm in SMG capacity optimization problems can economize investment costs and enable an environmentally friendly power supply.

Suggested Citation

  • Hui-Juan Zhang & Yi-Bo Feng & Kuo-Ping Lin, 2018. "Application of Multi-Species Differential Evolution Algorithm in Sustainable Microgrid Model," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2694-:d:161248
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/8/2694/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/8/2694/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrao, Iván & Figueres, Emilio & Garcerá, Gabriel & González-Medina, Raúl, 2015. "Microgrid architectures for low voltage distributed generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 415-424.
    2. Fathima, A. Hina & Palanisamy, K., 2015. "Optimization in microgrids with hybrid energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 431-446.
    3. Muis, Z.A. & Hashim, H. & Manan, Z.A. & Taha, F.M. & Douglas, P.L., 2010. "Optimal planning of renewable energy-integrated electricity generation schemes with CO2 reduction target," Renewable Energy, Elsevier, vol. 35(11), pages 2562-2570.
    4. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    5. Umeozor, Evar Chinedu & Trifkovic, Milana, 2016. "Operational scheduling of microgrids via parametric programming," Applied Energy, Elsevier, vol. 180(C), pages 672-681.
    6. Hafez, Omar & Bhattacharya, Kankar, 2012. "Optimal planning and design of a renewable energy based supply system for microgrids," Renewable Energy, Elsevier, vol. 45(C), pages 7-15.
    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. Silvia Jiménez-Fernández & Carlos Camacho-Gómez & Ricardo Mallol-Poyato & Juan Carlos Fernández & Javier Del Ser & Antonio Portilla-Figueras & Sancho Salcedo-Sanz, 2018. "Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm," Sustainability, MDPI, vol. 11(1), pages 1-21, December.

    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. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    2. Li, Tianxiao & Li, Zheng & Li, Weiqi, 2020. "Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model," Renewable Energy, Elsevier, vol. 156(C), pages 851-863.
    3. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2016. "Optimal design and techno-economic analysis of an autonomous small isolated microgrid aiming at high RES penetration," Energy, Elsevier, vol. 116(P1), pages 364-379.
    4. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    5. Roslan, M.F. & Hannan, M.A. & Ker, Pin Jern & Uddin, M.N., 2019. "Microgrid control methods toward achieving sustainable energy management," Applied Energy, Elsevier, vol. 240(C), pages 583-607.
    6. Burmester, Daniel & Rayudu, Ramesh & Seah, Winston & Akinyele, Daniel, 2017. "A review of nanogrid topologies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 760-775.
    7. Tomar, Vivek & Tiwari, G.N., 2017. "Techno-economic evaluation of grid connected PV system for households with feed in tariff and time of day tariff regulation in New Delhi – A sustainable approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 822-835.
    8. Cardoso, Gonçalo & Brouhard, Thomas & DeForest, Nicholas & Wang, Dai & Heleno, Miguel & Kotzur, Leander, 2018. "Battery aging in multi-energy microgrid design using mixed integer linear programming," Applied Energy, Elsevier, vol. 231(C), pages 1059-1069.
    9. Unamuno, Eneko & Barrena, Jon Andoni, 2015. "Hybrid ac/dc microgrids—Part I: Review and classification of topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1251-1259.
    10. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    11. Unamuno, Eneko & Barrena, Jon Andoni, 2015. "Hybrid ac/dc microgrids—Part II: Review and classification of control strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1123-1134.
    12. Baruah, Abhinandan & Basu, Mousumi & Amuley, Deeshank, 2021. "Modeling of an autonomous hybrid renewable energy system for electrification of a township: A case study for Sikkim, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    13. Cardoso, G. & Stadler, M. & Mashayekh, S. & Hartvigsson, E., 2017. "The impact of ancillary services in optimal DER investment decisions," Energy, Elsevier, vol. 130(C), pages 99-112.
    14. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    15. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    16. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    17. Jun He & Zimu Mao & Wentao Huang & Bohan Zhang & Jianbo Xiao & Zuoming Zhang & Xinyu Liu, 2024. "Low-Carbon Economic Dispatch of Virtual Power Plants Considering the Combined Operation of Oxygen-Enriched Combustion and Power-to-Ammonia," Sustainability, MDPI, vol. 16(10), pages 1-21, May.
    18. Ye, Bin & Yang, Peng & Jiang, Jingjing & Miao, Lixin & Shen, Bo & Li, Ji, 2017. "Feasibility and economic analysis of a renewable energy powered special town in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 40-50.
    19. Zhou, P. & Jin, R.Y. & Fan, L.W., 2016. "Reliability and economic evaluation of power system with renewables: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 537-547.
    20. Jaszczur, Marek & Hassan, Qusay & Palej, Patryk & Abdulateef, Jasim, 2020. "Multi-Objective optimisation of a micro-grid hybrid power system for household application," Energy, Elsevier, vol. 202(C).

    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:jsusta:v:10:y:2018:i:8:p:2694-:d:161248. 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.