Direct Power Supply Identification Method of PV Power Based on Affinity Propagation Clustering-Reference-Cited by-同舟云学术

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Direct Power Supply Identification Method of PV Power Based on Affinity Propagation Clustering

Published:2023 Issue: Volume: Page:218-228
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:
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Author:

Deng Hanjun,He Xing,Huang Rui,Su Yuping,Zhang Suihan,Zeng Wenwei

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-31733-0_19

Reference17 articles.

1. Singh, A.K., Parida, S.K.: A review on distributed generation allocation and planning in deregulated electricity market. Renew. Sustain. Energy Rev. 82, 4132–4141 (2018)

2. Nguyen, S., Peng, W., Sokolowski, P., et al.: Optimizing rooftop photovoltaic distributed generation with battery storage for peer-to-peer energy trading. Appl. Energy 228, 2567–2580 (2018)

3. Georgilakis, P.S., Hatziargyriou, N.D.: Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans. Power Syst. 28(3), 3420–3428 (2013)

4. Jokar, P., Arianpoo, N., Leung, V.C.M.: Electricity theft detection in AMI using customers’ consumption patterns. IEEE Trans. Smart Grid 7(1), 216–226 (2015)

5. Shaaban, M., Tariq, U., Ismail, M., et al.: Data-driven detection of electricity theft cyberattacks in PV generation. IEEE Syst. J. (2021)

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