Scenario analysis of photovoltaic power output based on improved K-means algorithm

Weiyuan Wang; Fei Dou; Lijun Wang; Kai Xia

doi:10.1117/12.3007692

25 October 2023 Scenario analysis of photovoltaic power output based on improved K-means algorithm

Weiyuan Wang, Fei Dou, Lijun Wang, Kai Xia

Author Affiliations +

Proceedings Volume 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023); 1280157 (2023) https://doi.org/10.1117/12.3007692
Event: Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 2023, Dalian, China

Abstract

For proper grid operation, an accurate description of PV power output is essential. This research proposes a cuckoo-grey wolf-based improved k-means clustering technique. It is also applied to the analysis of photovoltaic power output scenarios. After improving the algorithm, it is applied to the calculation case for simulation, and the final results show that the cumulative distribution curve of the typical scene obtained by the improved k-means algorithm in this paper has the same trend as the cumulative distribution curve of the initial scene, and the difference between them is very small, and the difference degree is close to 0.The simulation results are analyzed to verify the effectiveness of the improved algorithm.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Weiyuan Wang, Fei Dou, Lijun Wang, and Kai Xia "Scenario analysis of photovoltaic power output based on improved K-means algorithm", Proc. SPIE 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 1280157 (25 October 2023); https://doi.org/10.1117/12.3007692

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