Particle Swarm Optimization Based on K-means Cluster for Day-ahead Allocation Plan of Multiple Photovoltaic Distributed Generation
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Particle Swarm Optimization Based on K-means Cluster for Day-ahead Allocation Plan of Multiple Photovoltaic Distributed Generation
Vol. 43, Issue 4, Pages: 1263-1270(2017)
作者机构:
国网湖北省电力公司信息通信公司
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Published Online:10 April 2017,
Published:2017
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LI Lei, WANG Junxi, HE Yi, et al. Particle Swarm Optimization Based on K-means Cluster for Day-ahead Allocation Plan of Multiple Photovoltaic Distributed Generation[J]. 2017, 43(4): 1263-1270.
DOI:
LI Lei, WANG Junxi, HE Yi, et al. Particle Swarm Optimization Based on K-means Cluster for Day-ahead Allocation Plan of Multiple Photovoltaic Distributed Generation[J]. 2017, 43(4): 1263-1270.DOI:
Particle Swarm Optimization Based on K-means Cluster for Day-ahead Allocation Plan of Multiple Photovoltaic Distributed Generation
In allusion to the scene that multiple photovoltaic distributed generation(PV-DG) will be connected in the distribution power system
particle swarm optimization(PSO) based on K-means cluster for day-ahead allocation plan of multiple PV-DG is proposed. In this algorithm
the hourly network loss of nodes connected with PV-DG is alternately combined with the designed formulas to initially allocate the penetration level of multiple PV-DG connected with nodes
this penetration is used to initialize the particle in the PSO algorithm. Moreover
the ARMA is compared with various predicting parameters the traditional ARMA. The simulation results indicate that the proposed ARMA can improve the predicting accuracy. The comparison is carried on among the PSO based K-means cluster
classical PSO
and fuzzy PSO
the results show that PSO-based K-means cluster can reduce more network loss.