Analysis of Potential Shifting and Filling Potential of Campus Distribution Network Based on Fuzzy Clustering

• Main Authors: ZHANG Lin, XU Ke, HUANG Yao, LIAO Heng, WANG Long
• Format: Article
• Language: English
• Published: Energy Observer Magazine Co., Ltd. 2020-03-01
• Series: 南方能源建设
• Subjects: big data; peak-valley characteristics; time-of-use electricity price; fuzzy clustering
• Online Access: https://www.energychina.press/en/article/doi/10.16516/j.gedi.issn2095-8676.2020.01.004

[Introduction] The paper aims to excavate the potential physical significance of the large load data of distribution network users in the park, and provide the basis for optimizing the decision-making of the park operators, the characteristics and potential of peak and valley of distribution network are studied in this paper. [Method] Based on the research of time-sharing tariff division method, this paper used the theory of fuzzy mathematics, used membership function and constructed a fuzzy similarity matrix to divide the peak-to-valley period of user load curve with the potential of peak shifting and valley filling. [Result] Through comparison and verification, the result of partition is highly consistent with the actual situation, which proves the effectiveness of this method. On this basis, the peak-valley characteristics and the potential of peak-valley shifting and valley filling of the park distribution network are analyzed and studied. [Conclusion] The research conclusion has theoretical significance and practical value for making safe, economic and reliable operation strategies of the park distribution network.