Research on Optimization Scheduling Technology Based on Distributed Power Cluster Model and Advanced Algorithms
DOI: 10.23977/jeeem.2024.070207 | Downloads: 1 | Views: 114
Author(s)
Ziyuan Peng 1, Haibo Yuan 1, Heng Shen 1, Bowen Yang 1, Ziye Wang 1
Affiliation(s)
1 State Grid Hubei Electric Power Co., Ltd., Xianning Power Supply Company, Xianning, 437100, China
Corresponding Author
Ziyuan PengABSTRACT
With the extensive grid connection of various new energy sources, the traditional centralized economic dispatching mode is facing challenges in the new power system. This paper presents an optimal scheduling technology based on distributed power cluster model and advanced algorithm. By constructing edge clustering models of some new energy sources and analyzing their fluctuation characteristics, an optimization method for distributed economic scheduling is proposed based on the traditional consistency algorithm. In addition, a two-layer optimal planning model of AC-DC hybrid microgrid cluster is established. In the upper layer model, node coupling and power balance are considered to realize the cluster division of regional nodes. The bottom optimization configuration model aims to minimize the total cost, and uses optimization software to analyze and obtain optimal configuration results. Simulation results show that the proposed optimization scheduling technology has significant advantages in the field energy consumption of distributed power supply, reducing system cost, improving scheduling efficiency, etc. It provides a new theory and technical support for the optimization scheduling of distributed power supply system.
KEYWORDS
Distributed Power System, Renewable Energy, Optimization Scheduling Technology, Edge Cluster Model, Advanced AlgorithmsCITE THIS PAPER
Ziyuan Peng, Haibo Yuan, Heng Shen, Bowen Yang, Ziye Wang, Research on Optimization Scheduling Technology Based on Distributed Power Cluster Model and Advanced Algorithms. Journal of Electrotechnology, Electrical Engineering and Management (2024) Vol. 7: 47-54. DOI: http://dx.doi.org/10.23977/jeeem.2024.070207.
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