English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

Fuzzy C-Means Clustering Applied to Load Profiling of Industrial Customers