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ArticleName Analysis of distortion-related electric power losses in aluminum industry
DOI 10.17580/tsm.2019.04.11
ArticleAuthor Shklyarskiy Ya. E., Shklyarskiy A. Ya., Zamyatin Е. О.

Saint-Petersburg Mining University, Saint Petersburg, Russia:

Ya. E. Shklyarskiy, DSc (Eng.), Head of the Department of General Electrical Engineering, e-mail:
A. Ya. Shklyarskiy, PhD (Eng.), Associate Professor at the Department of Electric Power and Electromechanics, e-mail:
Е. О. Zamyatin, Assistant Lecturer at the Department of General Electrical Engineering, e-mail:


It is a well-known fact that aluminium industry consumes a lot of electric power. In fact, aluminium industry accounts for more than 10% of the total electric power consumed in all of Russia. According to the Russian Federal State Statistics Service, aluminium industry’s specific electric power consumption per 1 ton of product is double the consumption of oil or ferrous metals industries. A factor to be noted here is the power losses, which can exceed 3% of all the electric power consumed by a production site. Non-linear users were found to be a typical feature of aluminium producers. With the help of system analysis, the authors identified factors associated with power losses. They include higher-order harmonics and reactive power. The developed ranking function can help identify users which cause most losses in terms of reactive power consumption and higher-order harmonics. The authors propose to apply the Pareto principle and the obtained ranking function to only choose those users for compensation that create most electric power losses, while applying a certain limit to the reduction optimum. The efficiency of the developed method was verified through simulation in a programme created in MS Excel. The authors used a case study of one particular electric power network, which is a part of the electric power supply system of an aluminium site, to demonstrate that with the total annual power consumption of 170 500 MW·h, the losses can be reduced by 65%, i.e. from 6046.9 to 3930.5 MW·h/year. Considering that the price of electric power is 2.39 rub/kW·h, this can save 5058.24 th rub/year.

keywords Electric power quality, active power losses, energy efficiency, aluminium industry, simulation, Pareto principle, system analysis

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