Microgrid Working Conditions Identification Based on Cluster Analysis—A Case Study From Lambda Microgrid-Reference-Cited by-同舟云学术

Microgrid Working Conditions Identification Based on Cluster Analysis—A Case Study From Lambda Microgrid

Published:2022 Issue: Volume:10 Page:70971-70979
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Jasinski Michal¹^ORCID,Martirano Luigi²^ORCID,Najafi Arsalan¹^ORCID,Homaee Omid¹,Leonowicz Zbigniew¹^ORCID,Kermani Mostafa³^ORCID

Affiliation:

1. Faculty of Electrical Engineering, Wocław University of Science and Technology, Wocław, Poland

2. Department of Astronautical, Electrical and Energy Engineering (DIAEE), Sapienza University of Rome, Rome, Italy

3. Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

Funder

National Science Center of Poland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09805595.pdf?arnumber=9805595

Reference51 articles.

1. Clustering as a tool to support the assessment of power quality in electrical power networks with distributed generation in the mining industry

2. A load curve clustering method based on improved k-means algorithm for virtual power plant and its application;ai;Dianli Jianshe/Electric Power Construction,2020

3. K-means tree: an optimal clustering tree for unsupervised learning

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