Research Article
Direct Power Supply Identification Method of PV Power Based on Affinity Propagation Clustering
@INPROCEEDINGS{10.1007/978-3-031-31733-0_19, author={Hanjun Deng and Xing He and Rui Huang and Yuping Su and Suihan Zhang and Wenwei Zeng}, title={Direct Power Supply Identification Method of PV Power Based on Affinity Propagation Clustering}, proceedings={Smart Grid and Innovative Frontiers in Telecommunications. 7th EAI International Conference, SmartGIFT 2022, Changsha, China, December 10-12, 2022, Proceedings}, proceedings_a={SMARTGIFT}, year={2023}, month={5}, keywords={Photovoltaic Power Direct Power Supply Identification Affinity Propagation Clustering Correlation Coefficient}, doi={10.1007/978-3-031-31733-0_19} }- Hanjun Deng
Xing He
Rui Huang
Yuping Su
Suihan Zhang
Wenwei Zeng
Year: 2023
Direct Power Supply Identification Method of PV Power Based on Affinity Propagation Clustering
SMARTGIFT
Springer
DOI: 10.1007/978-3-031-31733-0_19
Abstract
At present, the marketization of distributed photovoltaic power generation faces problems such as the trading model is still immature and the trading mechanism is complicated, which makes the management of distributed energy trading very difficult. In this paper, a direct power supply identification method based on affinity propagation (AP) clustering is proposed. First, the historical PV output data of the station or neighboring stations are used to obtain the output data of the “same type” PV arrays for reference. Then, the AP clustering algorithm is used to cluster the power generation data in the same temperature segment, and the PV power sources suspected of direct power supply are identified according to the corresponding relationship between the clustering results and the electricity sales state. Finally, the proposed method is verified by the actual operation data in a certain area. The simulation results verify the effectiveness of the proposed method for the identification of direct PV power supply, and provide a reference for the subsequent on-site inspection of power grid companies.
