Optimization of wind turbine micro-siting for reducing the sensitivity of power generation to wind direction |
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| Affiliation: | 1. Department of Control Science and Engineering, Tongji University, Shanghai 201804, PR China;2. Key Laboratory of Enhanced Heat Transfer and Energy Conservation of the Ministry of Education, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, Guangdong, PR China;3. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, PR China;1. Department of Chemical Engineering, National Taiwan University of Science and Technology, 43, Keelung Rd., Sec. 4, Taipei 106-07, Taiwan;2. Department of Chemical Engineering, Institut Teknologi Sepuluh Nopember, Kampus ITS Keputih Sukolilo, Surabaya 60111, Indonesia;3. Department of Chemical Engineering, Widya Mandala Surabaya Catholic University, Kalijudan 37, Surabaya 60114, Indonesia;4. Department of Chemical Engineering, University of San Carlos – Talamban Campus, Nasipit, Talamban, Cebu City 6000, Philippines;1. Andalusian Institute for Earth System Research, Universidad de Granada, Av. del Mediterráneo s/n., 18006 Granada, Spain;2. Universidad de Málaga, Escuela Técnica Superior de Ingeniería Industrial, Campus de Teatinos, 29071 Málaga, Spain;1. Department of Mechanical Engineering, Recep Tayyip Erdoğam University, 52349 Rize, Turkey;2. Department of Mechanical Engineering, Yildiz Technical University, 34349 Besiktas, Istanbul, Turkey;3. Department of Mechanical Engineering, Istanbul Aydın University, 34455 Florya, Istanbul, Turkey;1. Department of Architecture, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;2. Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan |
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| Abstract: | In the optimization of wind turbine micro-siting of wind farms, the major target is to maximize the total energy yield. But considering from the aspect of the power grid, the sensitivity of wind power generation to varying incoming wind direction is also an essential factor. However, most existing optimization approaches on wind turbine micro-siting are focused on increasing the total power yield only. In this paper, by employing computational fluid dynamics and the virtual particle model for the simulation of turbine wake flow, a sensitivity index is proposed to quantitatively evaluate the variation of power generation under varying wind direction. Typical turbine layouts obtained by existing power optimization approaches are evaluated for stability. Results indicate that regularly arranged turbine layouts are not suitable for stable power production. Based on solutions from the power optimization, a second-stage optimization using Particle Swarm Optimization algorithm is presented. The proposed optimization method adjusts the positions of the turbines locally, aiming at increasing the stability of wind farm power generation without damaging its advantage of high power yield. Case studies on flat terrain and complex terrain both demonstrate the effectiveness of the present local adjustment optimization method. |
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| Keywords: | Wind farm Stability Sensitivity Wake flow |
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