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Optimizing wind farm layout for enhanced electricity extraction using a new hybrid PSO-ANN method

Global Energy Interconnection 2024年第3期7卷 254-269页

作者： Mariam El Jaadi Touria Haidi Abdelaziz Belfqih mounia farah Atar Dialmy LAGES Laboratory Hassania School of Public Works(EHTP)Casablanca 20230Morocco LESE Laboratory National School of Electricity and Mechanics(ENSEM)Casablanca 20100Morocco LAGCET Laboratory Hassania School of Public Works(EHTP)Casablanca 20230Morocco

With the growing need for renewable energy,wind farms are playing an important role in generating clean power from wind *** best wind turbine architecture in a wind farm has a major influence on the energy extraction *** paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization(PSO)and artificial neural networks(ANNs).The PSO method was used to explore the solution space and develop preliminary turbine layouts,and the ANN model was used to fine-tune the placements based on the predicted energy *** proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical *** efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches,giving exciting prospects for developing more efficient and sustainable wind *** integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both ***,this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency.A notable increase in power generation is observed across various *** percentage increase in the power generation ranged from approximately 7.7%to 11.1%.Owing to its versatility and adaptability to site-specific conditions,the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.

关键词： Layout optimization Turbine placement Wind energy Hybrid optimization Particle swarm optimization Artificial neural networks Renewable energy Energy efficiency

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