Fuzzy C-Means Clustering Applied to Load Profiling of Industrial Customers
被引:5
作者:
Dedic, Adisa
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JP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & HercegJP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & Herceg
Dedic, Adisa
[1
]
Konjic, Tatjana
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机构:
Univ Tuzla, Fac Elect Engn, Tuzla, Bosnia & HercegJP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & Herceg
Konjic, Tatjana
[2
]
Calasan, Martin
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Univ Montenegro, Fac Elect Engn, Podgorica 81000, MontenegroJP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & Herceg
Calasan, Martin
[3
]
Dedic, Zehrudin
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Deling Doo, Tuzla, Bosnia & HercegJP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & Herceg
Dedic, Zehrudin
[4
]
机构:
[1] JP EP BiH, Publ Enterprise Elect Power Ind Bosnia & Herzegov, Tuzla, Bosnia & Herceg
[2] Univ Tuzla, Fac Elect Engn, Tuzla, Bosnia & Herceg
[3] Univ Montenegro, Fac Elect Engn, Podgorica 81000, Montenegro
Nowadays, knowing load profiles of different customers in electricity market-oriented operation of power system is very important. Smart metering system provides more than enough information about it. However, even if there is a load measurement on each customer in the system, it is economically unjustified and it is time consuming to conduct a detailed analysis each of them. In this study, unlike literature approaches, the different industrial load profiles are observed. The fuzzy c-means clustering is applied to get typical load curves representing different type of industry. For that purpose, the detailed statistical analysis and calculations of load shape factors of the industrial customers for different period of the year have been carried out. Customer's 15-min load was collected by developing Advanced Metering Infrastructure in the power system of Bosnia and Herzegovina. According to available data, statistical analysis and applied fuzzy c-means clustering, three typical load profiles for different industrial customers are proposed.