IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i1p410-d474813.html
   My bibliography  Save this article

An Evaluation on Wind Energy Potential Using Multi-Objective Optimization Based Non-Dominated Sorting Genetic Algorithm III

Author

Listed:
  • Senthilkumar Subramanian

    (Department of Electrical and Electronics Engineering, College of Engineering, Anna University, Chennai 600025, India)

  • Chandramohan Sankaralingam

    (Department of Electrical and Electronics Engineering, College of Engineering, Anna University, Chennai 600025, India)

  • Rajvikram Madurai Elavarasan

    (Clean and Resilient Energy Systems Laboratory, Texas A&M University, Galveston, TX 77553, USA)

  • Raghavendra Rajan Vijayaraghavan

    (Research and Development Laboratory, Innovate Educational Institute, Chennai 600069, India)

  • Kannadasan Raju

    (Department of Electrical and Electronics Engineering, Sri Venkateswara College of Engineering, Chennai 602117, India)

  • Lucian Mihet-Popa

    (Faculty of Electrical Engineering, Ostfold University College, No-1757 Halden, Norway)

Abstract

Wind energy is an abundant renewable energy resource that has been extensively used worldwide in recent years. The present work proposes a new Multi-Objective Optimization (MOO) based genetic algorithm (GA) model for a wind energy system. The proposed algorithm consists of non-dominated sorting which focuses to maximize the power extraction of the wind turbine, minimize the cost of generating energy, and the lifetime of the battery. Additionally, the performance characteristics of the wind turbine and battery energy storage system (BESS) are analyzed specifically torque, current, voltage, state of charge (SOC), and internal resistance. The complete analysis is carried out in the MATLAB/Simulink platform. The simulated results are compared with existing optimization techniques such as single-objective, multi-objective, and non-dominating sorting GA II (Genetic Algorithm-II). From the observed results, the non-dominated sorting genetic algorithm (NSGA III) optimization algorithm offers superior performance notably higher turbine power output with higher torque rate, lower speed variation, reduced energy cost, and lesser degradation rate of the battery. This result attested to the fact that the proposed optimization tool can extract a higher rate of power from a self-excited induction generator (SEIG) when compared with a conventional optimization tool.

Suggested Citation

  • Senthilkumar Subramanian & Chandramohan Sankaralingam & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan & Kannadasan Raju & Lucian Mihet-Popa, 2021. "An Evaluation on Wind Energy Potential Using Multi-Objective Optimization Based Non-Dominated Sorting Genetic Algorithm III," Sustainability, MDPI, vol. 13(1), pages 1-29, January.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:1:p:410-:d:474813
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/1/410/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/1/410/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    2. Wang, Rui & Xiong, Jian & He, Min-fan & Gao, Liang & Wang, Ling, 2020. "Multi-objective optimal design of hybrid renewable energy system under multiple scenarios," Renewable Energy, Elsevier, vol. 151(C), pages 226-237.
    3. Rajvikram Madurai Elavarasan & Leoponraj Selvamanohar & Kannadasan Raju & Raghavendra Rajan Vijayaraghavan & Ramkumar Subburaj & Mohammad Nurunnabi & Irfan Ahmad Khan & Syed Afridhis & Akshaya Harihar, 2020. "A Holistic Review of the Present and Future Drivers of the Renewable Energy Mix in Maharashtra, State of India," Sustainability, MDPI, vol. 12(16), pages 1-33, August.
    4. Fei Zhao & Jinsha Yuan & Ning Wang, 2019. "Dynamic Economic Dispatch Model of Microgrid Containing Energy Storage Components Based on a Variant of NSGA-II Algorithm," Energies, MDPI, vol. 12(5), pages 1-14, March.
    5. Graditi, G. & Adinolfi, G. & Tina, G.M., 2014. "Photovoltaic optimizer boost converters: Temperature influence and electro-thermal design," Applied Energy, Elsevier, vol. 115(C), pages 140-150.
    6. Zhang, Debao & Liu, Junwei & Jiao, Shifei & Tian, Hao & Lou, Chengzhi & Zhou, Zhihua & Zhang, Ji & Wang, Chendong & Zuo, Jian, 2019. "Research on the configuration and operation effect of the hybrid solar-wind-battery power generation system based on NSGA-II," Energy, Elsevier, vol. 189(C).
    7. Mohanasundaram Anthony & Valsalal Prasad & Kannadasan Raju & Mohammed H. Alsharif & Zong Woo Geem & Junhee Hong, 2020. "Design of Rotor Blades for Vertical Axis Wind Turbine with Wind Flow Modifier for Low Wind Profile Areas," Sustainability, MDPI, vol. 12(19), pages 1-26, September.
    8. Mohamad M. Alayat & Youssef Kassem & Hüseyin Çamur, 2018. "Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus," Energies, MDPI, vol. 11(10), pages 1-22, October.
    9. Liu, Ye & Wu, Xiaogang & Du, Jiuyu & Song, Ziyou & Wu, Guoliang, 2020. "Optimal sizing of a wind-energy storage system considering battery life," Renewable Energy, Elsevier, vol. 147(P1), pages 2470-2483.
    10. Chan, C.M. & Bai, H.L. & He, D.Q., 2018. "Blade shape optimization of the Savonius wind turbine using a genetic algorithm," Applied Energy, Elsevier, vol. 213(C), pages 148-157.
    11. Pagnini, Luisa C. & Burlando, Massimiliano & Repetto, Maria Pia, 2015. "Experimental power curve of small-size wind turbines in turbulent urban environment," Applied Energy, Elsevier, vol. 154(C), pages 112-121.
    12. Abdelkader, Abbassi & Rabeh, Abbassi & Mohamed Ali, Dami & Mohamed, Jemli, 2018. "Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage," Energy, Elsevier, vol. 163(C), pages 351-363.
    13. Bordin, Chiara & Anuta, Harold Oghenetejiri & Crossland, Andrew & Gutierrez, Isabel Lascurain & Dent, Chris J. & Vigo, Daniele, 2017. "A linear programming approach for battery degradation analysis and optimization in offgrid power systems with solar energy integration," Renewable Energy, Elsevier, vol. 101(C), pages 417-430.
    14. Mohamed, Mohamed A. & Eltamaly, Ali M. & Alolah, Abdulrahman I., 2017. "Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 515-524.
    15. Adelaja, Adesoji & McKeown, Charles & Calnin, Benjamin & Hailu, Yohannes, 2012. "Assessing offshore wind potential," Energy Policy, Elsevier, vol. 42(C), pages 191-200.
    16. Krishnamoorthy R & Udhayakumar K & Kannadasan Raju & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization," Energies, MDPI, vol. 13(12), pages 1-41, June.
    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. Chen, Jie & Huang, Shoujun & Shahabi, Laleh, 2021. "Economic and environmental operation of power systems including combined cooling, heating, power and energy storage resources using developed multi-objective grey wolf algorithm," Applied Energy, Elsevier, vol. 298(C).
    2. Thiyagarajan Rameshkumar & Perumal Chandrasekar & Raju Kannadasan & Venkatraman Thiyagarajan & Mohammed H. Alsharif & James Hyungkwan Kim, 2022. "Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    3. Ayman A. Aly & Bassem F. Felemban & Ardashir Mohammadzadeh & Oscar Castillo & Andrzej Bartoszewicz, 2021. "Frequency Regulation System: A Deep Learning Identification, Type-3 Fuzzy Control and LMI Stability Analysis," Energies, MDPI, vol. 14(22), pages 1-21, November.
    4. Balasubbareddy Mallala & Venkata Prasad Papana & Ravindra Sangu & Kowstubha Palle & Venkata Krishna Reddy Chinthalacheruvu, 2022. "Multi-Objective Optimal Power Flow Solution Using a Non-Dominated Sorting Hybrid Fruit Fly-Based Artificial Bee Colony," Energies, MDPI, vol. 15(11), pages 1-16, June.
    5. Varadharajan Sankaralingam Sriraja Balaguru & Nesamony Jothi Swaroopan & Kannadasan Raju & Mohammed H. Alsharif & Mun-Kyeom Kim, 2021. "Techno-Economic Investigation of Wind Energy Potential in Selected Sites with Uncertainty Factors," Sustainability, MDPI, vol. 13(4), pages 1-31, February.
    6. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).

    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. Vijayaraja Loganathan & Dhanasekar Ravikumar & Rupa Kesavan & Kanakasri Venkatesan & Raadha Saminathan & Raju Kannadasan & Mahalingam Sudhakaran & Mohammed H. Alsharif & Zong Woo Geem & Junhee Hong, 2022. "A Case Study on Renewable Energy Sources, Power Demand, and Policies in the States of South India—Development of a Thermoelectric Model," Sustainability, MDPI, vol. 14(14), pages 1-29, July.
    2. Kisvari, Adam & Lin, Zi & Liu, Xiaolei, 2021. "Wind power forecasting – A data-driven method along with gated recurrent neural network," Renewable Energy, Elsevier, vol. 163(C), pages 1895-1909.
    3. Varadharajan Sankaralingam Sriraja Balaguru & Nesamony Jothi Swaroopan & Kannadasan Raju & Mohammed H. Alsharif & Mun-Kyeom Kim, 2021. "Techno-Economic Investigation of Wind Energy Potential in Selected Sites with Uncertainty Factors," Sustainability, MDPI, vol. 13(4), pages 1-31, February.
    4. Marugán, Alberto Pliego & Márquez, Fausto Pedro García & Perez, Jesus María Pinar & Ruiz-Hernández, Diego, 2018. "A survey of artificial neural network in wind energy systems," Applied Energy, Elsevier, vol. 228(C), pages 1822-1836.
    5. Mohanasundaram Anthony & Valsalal Prasad & Kannadasan Raju & Mohammed H. Alsharif & Zong Woo Geem & Junhee Hong, 2020. "Design of Rotor Blades for Vertical Axis Wind Turbine with Wind Flow Modifier for Low Wind Profile Areas," Sustainability, MDPI, vol. 12(19), pages 1-26, September.
    6. Sachin Kumar & Kumari Sarita & Akanksha Singh S Vardhan & Rajvikram Madurai Elavarasan & R. K. Saket & Narottam Das, 2020. "Reliability Assessment of Wind-Solar PV Integrated Distribution System Using Electrical Loss Minimization Technique," Energies, MDPI, vol. 13(21), pages 1-30, October.
    7. Mageswaran Rengasamy & Sivasankar Gangatharan & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "The Motivation for Incorporation of Microgrid Technology in Rooftop Solar Photovoltaic Deployment to Enhance Energy Economics," Sustainability, MDPI, vol. 12(24), pages 1-27, December.
    8. Sadeghi, Delnia & Ahmadi, Seyed Ehsan & Amiri, Nima & Satinder, & Marzband, Mousa & Abusorrah, Abdullah & Rawa, Muhyaddin, 2022. "Designing, optimizing and comparing distributed generation technologies as a substitute system for reducing life cycle costs, CO2 emissions, and power losses in residential buildings," Energy, Elsevier, vol. 253(C).
    9. Siddik Shakul Hameed & Ramesh Ramadoss & Kannadasan Raju & GM Shafiullah, 2022. "A Framework-Based Wind Forecasting to Assess Wind Potential with Improved Grey Wolf Optimization and Support Vector Regression," Sustainability, MDPI, vol. 14(7), pages 1-29, April.
    10. Fioriti, Davide & Pintus, Salvatore & Lutzemberger, Giovanni & Poli, Davide, 2020. "Economic multi-objective approach to design off-grid microgrids: A support for business decision making," Renewable Energy, Elsevier, vol. 159(C), pages 693-704.
    11. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions," Applied Energy, Elsevier, vol. 242(C), pages 1383-1395.
    12. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    13. Thiyagarajan Rameshkumar & Perumal Chandrasekar & Raju Kannadasan & Venkatraman Thiyagarajan & Mohammed H. Alsharif & James Hyungkwan Kim, 2022. "Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    14. Nirbheram, Joshi Sukhdev & Mahesh, Aeidapu & Bhimaraju, Ambati, 2024. "Techno-economic optimization of standalone photovoltaic-wind turbine-battery energy storage system hybrid energy system considering the degradation of the components," Renewable Energy, Elsevier, vol. 222(C).
    15. Mani Rajalakshmi & Sankaralingam Chandramohan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "Design and Validation of BAT Algorithm-Based Photovoltaic System Using Simplified High Gain Quasi Boost Inverter," Energies, MDPI, vol. 14(4), pages 1-24, February.
    16. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    17. Arenas-López, J. Pablo & Badaoui, Mohamed, 2020. "The Ornstein-Uhlenbeck process for estimating wind power under a memoryless transformation," Energy, Elsevier, vol. 213(C).
    18. Ziyu Zhang & Peng Huang & Haocheng Sun, 2020. "A Novel Analytical Wake Model with a Cosine-Shaped Velocity Deficit," Energies, MDPI, vol. 13(13), pages 1-20, June.
    19. Yin, Linfei & Zhang, Bin, 2021. "Time series generative adversarial network controller for long-term smart generation control of microgrids," Applied Energy, Elsevier, vol. 281(C).
    20. Georgios Delagrammatikas & Spyridon Roukanas, 2023. "Offshore Wind Farm in the Southeast Aegean Sea and Energy Security," Energies, MDPI, vol. 16(13), pages 1-21, July.

    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:13:y:2021:i:1:p:410-:d:474813. 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.