Research on investment benefit evaluation of distribution network based on improved clustering algorithm

Po Hu; Tongtong Han; Yunjia Wang

doi:10.1117/12.2672177

21 March 2023 Research on investment benefit evaluation of distribution network based on improved clustering algorithm

Po Hu, Tongtong Han, Yunjia Wang

Proceedings Volume 12609, International Conference on Computer Application and Information Security (ICCAIS 2022); 126091J (2023) https://doi.org/10.1117/12.2672177
Event: International Conference on Computer Application and Information Security (ICCAIS 2022), 2022, ONLINE, ONLINE

Abstract

In order to objectively evaluate the input-output level of distribution network projects and improve the investment benefit of the distribution network, this paper considers the multi-dimensional driving factors, constructs a comprehensive and systematic investment benefit evaluation system, and proposes a cluster evaluation model of the distribution network investment benefit. In this model, the genetic algorithm and particle swarm optimization algorithm are applied to the K-means clustering model to realize collaborative clustering and improve the clustering effect. A heuristic algorithm is added to enhance the clustering efficiency, and the effectiveness and accuracy of the improved clustering algorithm proposed in this paper are verified by experiments. Finally, it is applied to an example to evaluate the investment benefit by clustering. Then the comprehensive post-evaluation of electric power investment projects is carried out by using the solved results, so as to realize the lean management and control of investment in distribution network construction and transformation of power grid companies.

Citation Download Citation

Po Hu, Tongtong Han, and Yunjia Wang "Research on investment benefit evaluation of distribution network based on improved clustering algorithm", Proc. SPIE 12609, International Conference on Computer Application and Information Security (ICCAIS 2022), 126091J (21 March 2023); https://doi.org/10.1117/12.2672177

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