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Proportional–integral–derivative optimization algorithm for double-fed induction generator with the maximum wind power tracking technique

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Abstract

This paper proposes a novel control-centric optimization algorithm, i.e., proportional–integral–derivative optimization algorithm. The proposed optimization algorithm is inspired by the conventional proportional–integral–derivative controller. The proposed optimization algorithm consists of two types of controllers, i.e., explorative controllers with variable parameters and exploitative controllers with fixed parameters. In the exploration process of the approach, multiple explorative controllers with variable parameters move toward the global optimal solution domain. In the exploitation process of the approach, multiple exploitative controllers with fixed parameters moving toward to local optimal solution. The case studies results obtained by the proposed proportional–integral–derivative optimization algorithm under a total of eight basic mathematical optimization problems and the parameters optimization problem of the double-fed induction generator with the maximum wind power tracking technique show that the proportional–integral–derivative optimization algorithm can explore and exploit the global optimal solution effectively.

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Acknowledgements

This work was supported by Natural Science Foundation of Guangxi Province under Grant. AD19245001 and 2020GXNSFBA159025.

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Authors and Affiliations

  1. College of Electrical Engineering, Guangxi University, Nanning, 530004, Guangxi, People’s Republic of China

    Linfei Yin & Qi Gao

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  1. Linfei Yin
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  2. Qi Gao
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Correspondence to Linfei Yin.

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Yin, L., Gao, Q. Proportional–integral–derivative optimization algorithm for double-fed induction generator with the maximum wind power tracking technique. Soft Comput 25, 3097–3111 (2021). https://doi.org/10.1007/s00500-020-05365-x

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