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Statistical Analysis of Power System Sensitivity Under Random Penetration of Photovoltaic Generation
Author(s) -
Li Yu,
Ishikawa Masato
Publication year - 2017
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1483
Subject(s) - photovoltaic system , voltage , cluster analysis , electronic engineering , electric power system , benchmark (surveying) , grid connected photovoltaic power system , computer science , engineering , power (physics) , electrical engineering , maximum power point tracking , physics , artificial intelligence , geodesy , quantum mechanics , inverter , geography
In this paper, we aim to analyze the characteristics of feeder voltage variation in power systems due to random allocation of solar photovoltaic systems from a data‐driven approach, search the dangerous photovoltaic system allocation patterns along a specific power system. We conducted the investigation on benchmark radial distribution circuits with a random integration of certain amount of photovoltaic systems. Severe voltage deviation occurs along the tail part of each circuit line, and the connecting nodes between feeder and lateral circuit lines tend to be vulnerable to the integration of photovoltaic systems. Different allocation patterns of photovoltaic systems resulted in a data set of voltage variation in the distribution system, k‐Medoids clustering algorithm was proposed in this study to partition this data set into several clusters, which would contribute to the search of photovoltaic system allocation patterns with similar voltage deviation response.