The increasingly serious global energy crisis has provided important opportunities for the development of new energy. The concept of sustainable energy development advocated by the state has promoted the development and use of new energy, and a large number of new energy power generation units have been connected to the power system. K-means algorithm is a major breakthrough in the field of clustering analysis. Because of its convenience, it has been widely used in fraud detection, image processing, market analysis and other fields. In this paper, K-means algorithm is used for clustering mining of power grid data. In order to obtain more specific relationships between data, association rules mining based on Apriori algorithm is carried out for clustering results, and regions and systems with unreasonable power grid energy consumption are found; Finally, aiming at the problem area, a scheduling scheme is designed by using fuzzy control method to realize the optimal scheduling of power grid energy.

Ruoxin Lin and Linyuan Fan. Energy Optimal Scheduling Problem Based on Clustering Algorithm. Academic Journal of Energy (2021), Vol. 2, Issue 1: 9-16. https://doi.org/10.38007/RE.2021.020102.

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