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Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system

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  • Fathy, Ahmed
  • Rezk, Hegazy
  • Yousri, Dalia
  • Kandil, Tarek
  • Abo-Khalil, Ahmed G.

Abstract

The operation of the wind energy conversion (WEC) system is affected by the weather conditions as its generated power is dependent on the wind speed. It is essential to monitor the maximum generated power from the WEC system, this requires installing a maximum power point tracker (MPPT). This paper proposes a recent metaheuristic optimization approach named bald eagle search (BES) optimizer to design MPPT for WEC system operated at variable wind speed for tracking its global maximum power. The BES is selected as it can explore new search spaces, this helps in enhancing its divergence to avoid stuck in local optima and guarantee global solution. The proposed BES controls the DC-DC boost converter MOSFET at the terminals of a permanent magnet synchronous generator (PMSG) driven by wind turbine (WT). The BES adapts the MOSFET duty cycle such that the generated output power is enhanced. The proposed tracker is investigated on WEC operated at constant wind speed, variable wind speed, and real measured wind speed collected via Al-Jouf stations affiliated to the Saudi Arabia meteorological authority. Comparison to other approaches of particle swarm optimizer (PSO), aquila optimizer (AO), dingo optimization algorithm (DOA), sparrow search algorithm (SSA), and sooty tern optimization algorithm (STOA) is presented. Moreover, set of nonparametric tests such as Wilcoxon sign-rank test, Friedman test, ANOVA table, and Multiple comparison test are performed for statistical justification. According to the results, the BES has Friedman average rank of 1.1; meanwhile, the followed technique (DOA) has an average rank of 2.0250 that proves the superiority of the optimizer. Furthermore, the attained p-value of 1.6419e-54 based on the ANOVA table affirms the existence of significant differences among the algorithms. Therefore, the obtained results confirmed the competence and superiority of the proposed BES-MPPT in extracting the best global maximum power in all studied cases.

Suggested Citation

  • Fathy, Ahmed & Rezk, Hegazy & Yousri, Dalia & Kandil, Tarek & Abo-Khalil, Ahmed G., 2022. "Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system," Energy, Elsevier, vol. 249(C).
    • Handle: RePEc:eee:energy:v:249:y:2022:i:c:s0360544222005643
    DOI: 10.1016/j.energy.2022.123661
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    1. Karabacak, Murat, 2019. "A new perturb and observe based higher order sliding mode MPPT control of wind turbines eliminating the rotor inertial effect," Renewable Energy, Elsevier, vol. 133(C), pages 807-827.
    2. Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
    3. Ibanez-Lopez, A.S. & Moratilla-Soria, B.Y., 2017. "An assessment of Spain's new alternative energy support framework and its long-term impact on wind power development and system costs through behavioral dynamic simulation," Energy, Elsevier, vol. 138(C), pages 629-646.
    4. Silva, Nuno & Fuinhas, José Alberto & Koengkan, Matheus, 2021. "Assessing the advancement of new renewable energy sources in Latin American and Caribbean countries," Energy, Elsevier, vol. 237(C).
    5. Mai, Trieu & Lopez, Anthony & Mowers, Matthew & Lantz, Eric, 2021. "Interactions of wind energy project siting, wind resource potential, and the evolution of the U.S. power system," Energy, Elsevier, vol. 223(C).
    6. Tripathi, S.M. & Tiwari, A.N. & Singh, Deependra, 2015. "Grid-integrated permanent magnet synchronous generator based wind energy conversion systems: A technology review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1288-1305.
    7. Zhao, Baining & Qian, Tong & Tang, Wenhu & Liang, Qiheng, 2022. "A data-enhanced distributionally robust optimization method for economic dispatch of integrated electricity and natural gas systems with wind uncertainty," Energy, Elsevier, vol. 243(C).
    8. Lap-Arparat, Pongpak & Leephakpreeda, Thananchai, 2019. "Real-time maximized power generation of vertical axis wind turbines based on characteristic curves of power coefficients via fuzzy pulse width modulation load regulation," Energy, Elsevier, vol. 182(C), pages 975-987.
    9. Olaofe, Z.O., 2018. "Review of energy systems deployment and development of offshore wind energy resource map at the coastal regions of Africa," Energy, Elsevier, vol. 161(C), pages 1096-1114.
    10. Gu, Bo & Meng, Hang & Ge, Mingwei & Zhang, Hongtao & Liu, Xinyu, 2021. "Cooperative multiagent optimization method for wind farm power delivery maximization," Energy, Elsevier, vol. 233(C).
    11. Arango-Aramburo, Santiago & Bernal-García, Sebastián & Larsen, Erik R., 2021. "Renewable energy sources and the cycles in deregulated electricity markets," Energy, Elsevier, vol. 223(C).
    12. A. G. Olabi & Tabbi Wilberforce & Khaled Elsaid & Tareq Salameh & Enas Taha Sayed & Khaled Saleh Husain & Mohammad Ali Abdelkareem, 2021. "Selection Guidelines for Wind Energy Technologies," Energies, MDPI, vol. 14(11), pages 1-34, June.
    13. Medjber, Ahmed & Guessoum, Abderrezak & Belmili, Hocine & Mellit, Adel, 2016. "New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system," Energy, Elsevier, vol. 106(C), pages 137-146.
    14. Nair, Purusothmn Nair S. Bhasker & Tan, Raymond R. & Foo, Dominic C.Y., 2021. "A generic algebraic targeting approach for integration of renewable energy sources, CO2 capture and storage and negative emission technologies in carbon-constrained energy planning," Energy, Elsevier, vol. 235(C).
    15. Qian, Guo-Wei & Ishihara, Takeshi, 2021. "Wind farm power maximization through wake steering with a new multiple wake model for prediction of turbulence intensity," Energy, Elsevier, vol. 220(C).
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