Continuous Adjoint Formulation for Wind Farm Layout Optimization a 2d Implementation

Abstract

Optimization of wind farm layout has practical significance for the full utilization of wind energy. A novel wind farm layout optimization model is proposed in this paper. Both the continuous coordinate and the multi-hub height model are considered comprehensively. These two important factors are often discussed in isolation in previous studies. ADEG (Adaptive Differential Evolution with Greedy Method) is proposed to solve the above model. In ADEG, the differential evolution algorithm with parameter adaptive mechanism is used to improve the global search ability. The greedy algorithm is also introduced in ADEG to improve the local search ability. It balances the exploration and exploitation of the ADEG to improve the quality of the solution. The experimental results show that when the number of wind turbines is 5, 10, 20, 30 and 50 respectively, the output power of ADEG is 5.59%, 1.16%, 0.81%, 0.22% and 0.63% higher than that of DEEM (Differential Evolution with a new Encoding Mechanism) under the condition of multi-hub height model. When the number of wind turbines is 5 and 10 respectively, the output power of ADEG in the multi-hub height model is 1.96% and 0.07% higher than that in the fixed hub height model.

Keywords

• Differential evolution algorithm
• Self-adaptation parameter
• Wind farm layout optimization

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Acknowledgement

This paper was supported in part by Project funded by China Postdoctoral Science Foundation under Grant 2020M671552, in part by Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 2019K223, in part by NUPTSF(NY220060), in part by the Opening Project of Jiangsu Key Laboratory of Data Science and Smart Software (No. 2020DS301) in part by Natural Science Foundation of Jiangsu Province of China under Grant BK20191381, in part by the National Natural Science Foundation of China under Grant No. 61802207.

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Authors and Affiliations

1. Nanjing University of Posts and Telecommunications, Nanjing, 210000, China

   Jianming Zhu, Shanshan Lin, Junzhe Wen, Jin Qin, Wenqing Yan & Bin Xu

2. NanJing Pharmaceutical Co., Ltd., Nanjing, 210012, China

   Jin Qin & Bin Xu

3. Jiangsu Key Laboratory of Data Science and Smart Software, Jinling Institute of Technology, Nanjing, 211169, China

   Bin Xu

Corresponding author

Correspondence to Bin Xu .

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Editors and Affiliations

1. Nanjing University of Information Science and Technology, Nanjing, China

   Xingming Sun

2. Nanjing University of Information Science and Technology, Nanjing, China

   Prof. Xiaorui Zhang

3. Jinan University, Guangzhou, China

   Zhihua Xia

4. Purdue University, West Lafayette, IN, USA

   Prof. Dr. Elisa Bertino

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Zhu, J., Lin, S., Wen, J., Qin, J., Yan, W., Xu, B. (2021). Discrete Multi-height Wind Farm Layout Optimization for Optimal Energy Output. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1422. Springer, Cham. https://doi.org/10.1007/978-3-030-78615-1_21

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• DOI : https://doi.org/10.1007/978-3-030-78615-1_21

• Published: 29 June 2021

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