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Oksana A. Gavrina
Oksana A. Gavrina
Ph.D., Associate Professor
North Caucasian Mining and Metallurgical Institute (State Technological University)
, Ph.D., Associate Professor
North Caucasian Mining and Metallurgical Institute (State Technological University)
Vladikavkaz
Russia
514
Total cited
11
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Articles

Energy industry
  • Date submitted
    2023-03-14
  • Date accepted
    2023-06-20
  • Date published
    2023-07-19

Forecasting planned electricity consumption for the united power system using machine learning

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The paper presents the results of studies of the predictive models development based on retrospective data on planned electricity consumption in the region with a significant share of enterprises in the mineral resource complex. Since the energy intensity of the industry remains quite high, the task of rationalizing the consumption of electricity is relevant. One of the ways to improve control accuracy when planning energy costs is to forecast electrical loads. Despite the large number of scientific papers on the topic of electricity consumption forecasting, this problem remains relevant due to the changing requirements of the wholesale electricity and power market to the accuracy of forecasts. Therefore, the purpose of this study is to support management decisions in the process of planning the volume of electricity consumption. To realize this, it is necessary to create a predictive model and determine the prospective power consumption of the power system. For this purpose, the collection and analysis of initial data, their preprocessing, selection of features, creation of models, and their optimization were carried out. The created models are based on historical data on planned power consumption, power system performance (frequency), as well as meteorological data. The research methods were: ensemble methods of machine learning (random forest, gradient boosting algorithms, such as XGBoost and CatBoost) and a long short-term memory recurrent neural network model (LSTM). The models obtained as a result of the conducted studies allow creating short-term forecasts of power consumption with a fairly high precision (for a period from one day to a week). The use of models based on gradient boosting algorithms and neural network models made it possible to obtain a forecast with an error of less than 1 %, which makes it possible to recommend the models described in the paper for use in forecasting the planned electricity power consumption of united power systems.

How to cite: Klyuev R.V., Morgoeva A.D., Gavrina O.A., Bosikov I.I., Morgoev I.D. Forecasting planned electricity consumption for the united power system using machine learning // Journal of Mining Institute. 2023. Vol. 261. p. 392-402. EDN FJGZTV
Electromechanics and mechanical engineering
  • Date submitted
    2020-10-05
  • Date accepted
    2021-03-30
  • Date published
    2021-06-24

Improving the efficiency of relay protection at a mining and processing plant

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The paper presents the results of constructing effective relay protection in the power supply system of a mining and processing plant (MPP). A brief description of the MPP is given, the power supply and substitution circuits used to calculate the short-circuit currents are given. A statistical analysis of failures in the electric network of the MPP has been carried out, which makes it possible to draw conclusions about the nature of failures ranges. Analysis of the registered faults shows that a significant part of them are line-to-earth faults, which in most cases turn into multiphase short circuits, which are interrupted by overcurrent protection. In order to improve the efficiency and reliability of the relay protection, the power supply scheme of the MPP was refined and analyzed. The calculation of the short-circuit currents was made, which made it possible to calculate the settings of the relay protection and give recommendations on the place of its installation and adjustment in order to ensure the normal operation of electricity consumers. To reduce the number of failures to the cable insert on the line leaving the administrative and household complex (AHC), and to increase the reliability of power supply to consumers, it is advisable to divide the capacities of the existing 10 kV line into two parallel ones by laying a second line. It is recommended to install a current cut-off on the line outgoing to the AHC, the feasibility of the installation of which was shown by calculations. This will reduce the chance of failures to the cable gland. Data on the setting currents of overcurrent protection and current cut-off are given on the selectivity card.

How to cite: Klyuev R.V., Bosikov I.I., Gavrina O.A. Improving the efficiency of relay protection at a mining and processing plant // Journal of Mining Institute. 2021. Vol. 248. p. 300-311. DOI: 10.31897/PMI.2021.2.14