Wind Turbine Optimal Positioning using Particle Swarm Optimization
DOI:
https://doi.org/10.30537/jvt7q207Keywords:
Wind Turbine Layout, PSO Algorithm, Wake Effect, EnergyAbstract
The wind farms are alternatively used as renewable and emission free energy sources. The wind farms heavily rely on the speed and direction of wind available in environment. So the most fundamental problem with the wind farms is the placement and arrangement of wind turbines. It is crucial task to maximize the energy output by putting wind turbines in suitable position. To solve this problem of wind farm layout optimization (WFLO), this paper presents a three step strategy using Particle Swarm Optimization (PSO) technique. The main objective of this technique is to decreasing wake effect, while upstream wind flow is disturbed by other upstream turbines. To solve this problem, three different case scenarios are discussed with different levels of wake and non-wake effects. The paper introduces rules for wind turbine placement that integrate spacing constraints with diagonal farm orientation and Jensen wake modeling into PSO Search process. Python programming is used for the development of PSO algorithm, and achieved notable enhancement in the total energy output as compared to previous methods. In different cases and scenarios 0.65%, 1.95%, and 1.74% efficiency is achieved as compared to previous schemes. These findings demonstrate that proposed scheme not only effective in optimizing the layout of wind turbines placement, but also favorable in reducing the overall objective function. This scheme offers a practical and efficient solution for wind farm developers to increase performance and output energy.
References
[1] J. F. M. J. G. &. R. A. L. (Manwell, Wind Energy Explained: Theory, Design and Application, John Wiley & Sons,, 2010.
[2] T. J. N. S. D. &. B. E. Burton, Wind Energy Handbook, John Wiley & Sons, 2011.
[3] T. Ackermann, Wind Power in Power Systems, John Wiley & Son, 2012.
[4] E. Hau, Wind Turbines: Fundamentals, Technologies, Application, Economics, Springe, 2013.
[5] Z. W. G. a. J. Hong, "Improved Formulation for the Optimization of Wind Turbine," Mathematical Problems in Engineering, pp. 5- 6, 2013.
[6] L. H. a. J. J. Philip Asaah, "Optimal Placement of Wind Turbines in Wind," JOURNAL OF MODERN POWER SYSTEMSAND CLEAN ENERGY,, Vols. 9, NO. 2, March 2021, no. March 2021, pp. 7-9, 2021.
[7] P. M. a. K. Mitra, "Determination of optimal layout of wind turbines inside a wind," in Fifth Indian Control Conference (ICC), Delhi, 2019.
[8] C. B. M. a. M. Deshmukh, "A new approach to optimise placement of wind turbines using," International Journal of Sustainable Energy, vol. 34, pp. 9-11, 2015.
[9] J.-R. F.-A. Jos ́e-Francisco Herbert-Acero, "Linear Wind Farm Layout Optimization through," in Mexican International Conference on Artificial Intelligence, Mexico, 2009.
[10] V. W. Priti Sood, "Optimal placement of wind turbines: A Monte," in IEEE International Conference on Electro/Information Technology, 2010.
[11] O. T. M. T. Ü. Ç. S. Sisbot, "Optimal positioning of wind turbines on Gökc ̧ eada," Wind Energy, 2010.
[12] P. S. G. A. P. Biswas, Optimal Placement of Wind Turbines in a Windfarm, IEEE Congress on Evolutionary Computation, 2017.
[13] W. H. M. S. Z. C. P. Hou, "Optimized Placement of Wind Turbines in," in IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015.
[14] P. S. S. A. T. NAGARAJA RAO SULAKE, "A Review of Wind Farm Layout Optimization Techniques for Optimal Placement of Wind Turbines," International Journal of Renewable Energy Research- IJRER, 2023.
[15] İ. K. H. K. Mehmet BEŞKİRLİ, "Optimal Placement of Wind Turbines Using Novel Binary Invasive Weed Optimization," International Standard Serial Number, 2019.
[16] J. F. E. Carlos M. Ituarte-Villarreal, "Optimization of wind turbine placement using a viral based optimization algorithm," in Complex Adaptive Systems, 2011.
[17] P.-E. S. Y. S. T.-Y. W. W. T. Yuan-Kang Wu, "Economics- and Reliability-Based Design for an Offshore Wind Farm," IEEE transactions on industry applications, 2017.
[18] K. M. J. L. John Tzanos, "Optimal Wind Turbine Placement via Randomized Optimization Techniques," 2011.
[19] T. H. D. B. Mariam El jaadi, "Particle swarm optimization for the optimal layout of wind turbines inside a wind farm," IAES International Journal of Artificial Intelligence (IJ-AI), 2023.
[20] J. W. G. Y. X. Z. Chunqiu Wan, "Optimal Micro-siting of Wind Farms by Particle Swarm Optimization," in International Conference on Swarm Intelligence, 2010.
[21] R. Y. M. S. S. M. R. Rahmani, "Implementing Particle Swarm Optimization in Wind Farm to Place Wind Turbines," AUSTRALIAN JOURNAL OF BASIC AND APPLIED SCIENCES, 2013.
[22] M. M. I. A. A. A. Elbaset, "Particle Swarm Optimization for layout design of utility interconnected wind parks," in IEEE PES Innovative Smart Grid Technologies Conference, 2018.
[23] M. Y. H. A. R. e. a. R. Shakoor, "The modelling of wind farm layout optimization for the reduction of wake losses," Indian Journal of Science and Technology, vol. 8, no. Aug,2015, pp. 1-9, 2015.
[24] C. P. a. B. D. G. Mosetti, "“Optimization of wind turbine positioning in large windfarm by means of genetic algorithm," Journal of Wind Engineering and Industrial aerodynamics, vol. 51, no. Jan. 1994, pp. 105-116, 1994.
[25] A. Mittal, "Optimization of the layout of large wind farms using genetic alorithm," in Case Western Reserve University,, Ohio,USA, 2010.
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