IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i4p847-d139631.html
   My bibliography  Save this article

Grey Wolf Optimization-Based Optimum Energy-Management and Battery-Sizing Method for Grid-Connected Microgrids

Author

Listed:
  • Kutaiba Sabah Nimma

    (Australian Maritime College, University of Tasmania, Newnham, TAS 7248, Australia)

  • Monaaf D. A. Al-Falahi

    (Australian Maritime College, University of Tasmania, Newnham, TAS 7248, Australia)

  • Hung Duc Nguyen

    (Australian Maritime College, University of Tasmania, Newnham, TAS 7248, Australia)

  • S. D. G. Jayasinghe

    (Australian Maritime College, University of Tasmania, Newnham, TAS 7248, Australia)

  • Thair S. Mahmoud

    (School of Engineering, Edith Cowan University, Joondalup, WA 6027, Australia)

  • Michael Negnevitsky

    (Center for Renewable Energy and Power System School of Engineering, University of Tasmania, Hobart, TAS 7005, Australia)

Abstract

In the revolution of green energy development, microgrids with renewable energy sources such as solar, wind and fuel cells are becoming a popular and effective way of controlling and managing these sources. On the other hand, owing to the intermittency and wide range of dynamic responses of renewable energy sources, battery energy-storage systems have become an integral feature of microgrids. Intelligent energy management and battery sizing are essential requirements in the microgrids to ensure the optimal use of the renewable sources and reduce conventional fuel utilization in such complex systems. This paper presents a novel approach to meet these requirements by using the grey wolf optimization (GWO) technique. The proposed algorithm is implemented for different scenarios, and the numerical simulation results are compared with other optimization methods including the genetic algorithm (GA), particle swarm optimization (PSO), the Bat algorithm (BA), and the improved bat algorithm (IBA). The proposed method (GWO) shows outstanding results and superior performance compared with other algorithms in terms of solution quality and computational efficiency. The numerical results show that the GWO with a smart utilization of battery energy storage (BES) helped to minimize the operational costs of microgrid by 33.185% in comparison with GA, PSO, BA and IBA.

Suggested Citation

  • Kutaiba Sabah Nimma & Monaaf D. A. Al-Falahi & Hung Duc Nguyen & S. D. G. Jayasinghe & Thair S. Mahmoud & Michael Negnevitsky, 2018. "Grey Wolf Optimization-Based Optimum Energy-Management and Battery-Sizing Method for Grid-Connected Microgrids," Energies, MDPI, vol. 11(4), pages 1-27, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:847-:d:139631
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/4/847/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/4/847/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sanajaoba, Sarangthem & Fernandez, Eugene, 2016. "Maiden application of Cuckoo Search algorithm for optimal sizing of a remote hybrid renewable energy System," Renewable Energy, Elsevier, vol. 96(PA), pages 1-10.
    2. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    3. Bridier, Laurent & Hernández-Torres, David & David, Mathieu & Lauret, Phillipe, 2016. "A heuristic approach for optimal sizing of ESS coupled with intermittent renewable sources systems," Renewable Energy, Elsevier, vol. 91(C), pages 155-165.
    4. Malheiro, André & Castro, Pedro M. & Lima, Ricardo M. & Estanqueiro, Ana, 2015. "Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems," Renewable Energy, Elsevier, vol. 83(C), pages 646-657.
    5. Rigo-Mariani, R. & Sareni, B. & Roboam, X., 2017. "Fast power flow scheduling and sensitivity analysis for sizing a microgrid with storage," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 114-127.
    6. repec:dar:wpaper:74992 is not listed on IDEAS
    7. Berrada, Asmae & Loudiyi, Khalid, 2016. "Operation, sizing, and economic evaluation of storage for solar and wind power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1117-1129.
    8. Zhang, Xinan & Bao, Jie & Wang, Ruigang & Zheng, Chaoxu & Skyllas-Kazacos, Maria, 2017. "Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage," Renewable Energy, Elsevier, vol. 100(C), pages 18-34.
    9. 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.
    10. Schneider, Maximilian & Biel, K. & Pfaller, S. & Schaede, Hendrik & Rinderknecht, Stephan & Glock, C. H., 2015. "Optimal Sizing of Electrical Energy Storage Systems using Inventory Models," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 74986, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Fossati, Juan P. & Galarza, Ainhoa & Martín-Villate, Ander & Fontán, Luis, 2015. "A method for optimal sizing energy storage systems for microgrids," Renewable Energy, Elsevier, vol. 77(C), pages 539-549.
    12. Rigo-Mariani, Rémy & Sareni, Bruno & Roboam, Xavier & Turpin, Christophe, 2014. "Optimal power dispatching strategies in smart-microgrids with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 649-658.
    13. Pierre-Louis Poirion, 2016. "Robust linear programming; optimal sizing of an hybrid energy stand-alone system," 4OR, Springer, vol. 14(1), pages 103-104, March.
    14. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.
    15. Billionnet, Alain & Costa, Marie-Christine & Poirion, Pierre-Louis, 2016. "Robust optimal sizing of a hybrid energy stand-alone system," European Journal of Operational Research, Elsevier, vol. 254(2), pages 565-575.
    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. Salil Madhav Dubey & Hari Mohan Dubey & Surender Reddy Salkuti, 2022. "Modified Quasi-Opposition-Based Grey Wolf Optimization for Mathematical and Electrical Benchmark Problems," Energies, MDPI, vol. 15(15), pages 1-29, August.
    2. Al-Falahi, Monaaf D.A. & Jayasinghe, Shantha D.G. & Enshaei, Hossein, 2019. "Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries," Energy, Elsevier, vol. 187(C).
    3. Monaaf D. A. Al-Falahi & Tomasz Tarasiuk & Shantha Gamini Jayasinghe & Zheming Jin & Hossein Enshaei & Josep M. Guerrero, 2018. "AC Ship Microgrids: Control and Power Management Optimization," Energies, MDPI, vol. 11(6), pages 1-20, June.
    4. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    5. Jun-Mo Kim & Jeong Lee & Jin-Wook Kim & Junsin Yi & Chung-Yuen Won, 2021. "Power Conversion System Operation to Reduce the Electricity Purchasing Cost of Energy Storage Systems," Energies, MDPI, vol. 14(16), pages 1-20, August.
    6. Bo Li & Yudong Wang & Jian Li & Shengxian Cao, 2018. "A Fully Distributed Approach for Economic Dispatch Problem of Smart Grid," Energies, MDPI, vol. 11(8), pages 1-21, August.
    7. Bing Zeng & Jiang Guo & Wenqiang Zhu & Zhihuai Xiao & Fang Yuan & Sixu Huang, 2019. "A Transformer Fault Diagnosis Model Based On Hybrid Grey Wolf Optimizer and LS-SVM," Energies, MDPI, vol. 12(21), pages 1-18, November.
    8. Lucas Schmeling & Patrik Schönfeldt & Peter Klement & Steffen Wehkamp & Benedikt Hanke & Carsten Agert, 2020. "Development of a Decision-Making Framework for Distributed Energy Systems in a German District," Energies, MDPI, vol. 13(3), pages 1-22, January.
    9. El-Bidairi, Kutaiba S. & Nguyen, Hung Duc & Mahmoud, Thair S. & Jayasinghe, S.D.G. & Guerrero, Josep M., 2020. "Optimal sizing of Battery Energy Storage Systems for dynamic frequency control in an islanded microgrid: A case study of Flinders Island, Australia," Energy, Elsevier, vol. 195(C).
    10. Damian Hasterok & Rui Castro & Marcin Landrat & Krzysztof Pikoń & Markus Doepfert & Hugo Morais, 2021. "Polish Energy Transition 2040: Energy Mix Optimization Using Grey Wolf Optimizer," Energies, MDPI, vol. 14(2), pages 1-27, January.
    11. Rovick Tarife & Yosuke Nakanishi & Yining Chen & Yicheng Zhou & Noel Estoperez & Anacita Tahud, 2022. "Optimization of Hybrid Renewable Energy Microgrid for Rural Agricultural Area in Southern Philippines," Energies, MDPI, vol. 15(6), pages 1-29, March.
    12. Nissim Amar & Aaron Shmaryahu & Michael Coletti & Ilan Aharon, 2021. "Sizing Procedure for System Hybridization Based on Experimental Source Modeling in Grid Application," Energies, MDPI, vol. 14(15), pages 1-19, 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. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    2. Yuan, Qiheng & Zhou, Keliang & Yao, Jing, 2020. "A new measure of wind power variability with implications for the optimal sizing of standalone wind power systems," Renewable Energy, Elsevier, vol. 150(C), pages 538-549.
    3. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    4. Abbas Hamze & Yassine Ouazene & Nazir Chebbo & Imane Maatouk, 2019. "Multisources of Energy Contracting Strategy with an Ecofriendly Factor and Demand Uncertainties," Energies, MDPI, vol. 12(20), pages 1-24, October.
    5. Coelho, Vitor N. & Coelho, Igor M. & Coelho, Bruno N. & Cohen, Miri Weiss & Reis, Agnaldo J.R. & Silva, Sidelmo M. & Souza, Marcone J.F. & Fleming, Peter J. & Guimarães, Frederico G., 2016. "Multi-objective energy storage power dispatching using plug-in vehicles in a smart-microgrid," Renewable Energy, Elsevier, vol. 89(C), pages 730-742.
    6. Wen, Shuli & Lan, Hai & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun & Cheng, Peng, 2016. "Allocation of ESS by interval optimization method considering impact of ship swinging on hybrid PV/diesel ship power system," Applied Energy, Elsevier, vol. 175(C), pages 158-167.
    7. Izadbakhsh, Maziar & Gandomkar, Majid & Rezvani, Alireza & Ahmadi, Abdollah, 2015. "Short-term resource scheduling of a renewable energy based micro grid," Renewable Energy, Elsevier, vol. 75(C), pages 598-606.
    8. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    9. Tingli Cheng & Minyou Chen & Yingxiang Wang & Bo Li & Muhammad Arshad Shehzad Hassan & Tao Chen & Ruilin Xu, 2018. "Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage," Complexity, Hindawi, vol. 2018, pages 1-13, June.
    10. Pourmohammadi, Pardis & Saif, Ahmed, 2023. "Robust metamodel-based simulation-optimization approaches for designing hybrid renewable energy systems," Applied Energy, Elsevier, vol. 341(C).
    11. Daniel Reich & Giovanna Oriti, 2021. "Rightsizing the Design of a Hybrid Microgrid," Energies, MDPI, vol. 14(14), pages 1-22, July.
    12. Pablo Benalcazar & Adam Suski & Jacek Kamiński, 2020. "Optimal Sizing and Scheduling of Hybrid Energy Systems: The Cases of Morona Santiago and the Galapagos Islands," Energies, MDPI, vol. 13(15), pages 1-20, August.
    13. Sharma, Sharmistha & Bhattacharjee, Subhadeep & Bhattacharya, Aniruddha, 2018. "Probabilistic operation cost minimization of Micro-Grid," Energy, Elsevier, vol. 148(C), pages 1116-1139.
    14. Chang, Hsiu-Chuan & Ghaddar, Bissan & Nathwani, Jatin, 2022. "Shared community energy storage allocation and optimization," Applied Energy, Elsevier, vol. 318(C).
    15. Mallol-Poyato, R. & Salcedo-Sanz, S. & Jiménez-Fernández, S. & Díaz-Villar, P., 2015. "Optimal discharge scheduling of energy storage systems in MicroGrids based on hyper-heuristics," Renewable Energy, Elsevier, vol. 83(C), pages 13-24.
    16. Haixiang Zang & Mian Guo & Zeyu Qian & Zhinong Wei & Guoqiang Sun, 2016. "A Novel Method for Fast Configuration of Energy Storage Capacity in Stand-Alone and Grid-Connected Wind Energy Systems," Sustainability, MDPI, vol. 8(12), pages 1-9, December.
    17. Balderrama, Sergio & Lombardi, Francesco & Riva, Fabio & Canedo, Walter & Colombo, Emanuela & Quoilin, Sylvain, 2019. "A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community," Energy, Elsevier, vol. 188(C).
    18. Bourbon, R. & Ngueveu, S.U. & Roboam, X. & Sareni, B. & Turpin, C. & Hernandez-Torres, D., 2019. "Energy management optimization of a smart wind power plant comparing heuristic and linear programming methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 418-431.
    19. Yuan, Shengxi & Kocaman, Ayse Selin & Modi, Vijay, 2017. "Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente," Renewable Energy, Elsevier, vol. 105(C), pages 167-174.
    20. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(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:jeners:v:11:y:2018:i:4:p:847-:d:139631. 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.