scholarly journals THE СONTROL OF THE ELECTRIC POWER CONSUMPTION OF THE INDUSTRIAL ENTERPRISES WITH THE USE OF THE TECHNOLOGICAL RESOURCE

2013 ◽  
Vol 0 (1) ◽  
Author(s):  
B. S. Serebrennikov ◽  
K. G. Petrova
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Electric Power Consumption ◽  
Industrial Enterprises ◽  
Technological Resource

scholarly journals System analysis of power consumption by nonferrous metallurgy enterprises on the basis of rank modeling of individual technocenosis castes

2018 ◽  
Vol 226 ◽  
pp. 04018 ◽  
Author(s):  
Roman V. Klyuev ◽  
Igor I. Bosikov ◽  
Oksana A. Gavrina ◽  
Vladimir Ch. Revazov
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Ferrous Metallurgy ◽  
Relative Error ◽  
System Analysis ◽  
Electricity Consumption ◽  
Automated System ◽  
Electric Power Consumption ◽  
Process Equipment ◽  
Industrial Enterprises

To increase energy efficiency at non-ferrous metallurgy enterprises, an integrated system approach for estimation of electricity consumption is needed. The paper presents the results of a rank analysis of the power consumption of individual castes of process equipment on the basis of an integrated energy survey of the enterprise. A methodology for constructing mathematical models for calculating and predicting electric power consumption for all castes of the ranked H-distribution of technocenosis has been developed. For the first time, according to the established regularity of the H-distribution, a mathematical model for predicting power consumption has been developed, including a quantitative analysis of the energy characteristics of consumers by individual castes of technocenosis. A retrospective check of the relative error in the prediction of electricity consumption showed that for the model it does not exceed 2%, which is significantly lower than the relative error of the prediction for a number of models of other types. The received model is recommended for use in the automated system of dispatching control of power consumption for the purposes of short-term forecasting of electric power consumption at industrial enterprises of non-ferrous metallurgy.

Software including the functions of automated analysis of electric power consumption in pipeline oil transportation

2011 ◽  
Vol 8 (1) ◽  
pp. 233-238
Author(s):  
R.M. Bogdanov ◽  
S.V. Lukin
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Data Model ◽  
Automated Analysis ◽  
Petroleum Products ◽  
Electric Power Consumption ◽  
Scientific Center ◽  
Relational Data Model ◽  
Oil Transportation ◽  
Academy Of Sciences

Oil and petroleum products transportation is characterized by a significant cost of electric power. Correct oil and petroleum products accounting and forecasting requires knowledge of many factors. The software for norms of electric power consumption analysis for the planned period was developed at the Ufa Scientific Center of the Russian Academy of Sciences. Based on the principles of the relational data model, a schematic diagram/arrangement for the main oil transportation objects was developed, which allows to hold the initial data and calculated parameters in a structured manner.

Characteristics of losses incurred from restriction of water use and electric power consumption

1985 ◽  
Vol 19 (9) ◽  
pp. 478-483
Author(s):  
S. B. Elakhovskii ◽  
S. I. Sorokina ◽  
E. N. Smirnova
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Water Use ◽  
Electric Power Consumption

Optimization of a Raw Water Source Heat Pump for a Vertical Water Treatment Building

2015 ◽  
Vol 23 (01) ◽  
pp. 1550002
Author(s):  
Sunhee Oh ◽  
Yong Cho ◽  
Rin Yun
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Flow Rate ◽  
Storage Tank ◽  
Water Flow Rate ◽  
Water Source ◽  
Thermal Storage ◽  
Electric Power Consumption ◽  
Air Flow Rate ◽  
Circulating Water

The optimum operation conditions of a raw water source heat pump for a vertical water treatment building were derived by changing operation parameters, such as temperature of thermal storage tank, temperature and inlet air flow rate of the conditioned spaces, and circulating water flow rate between thermal storage tank and air handling unit (AHU) through dynamic simulator of a transient system simulation program (TRNSYS). Minimum electric power consumption was found at temperature of thermal storage tank, which was ranged 18–23°C for cooling season. In heating season, temperature 40–45°C brings the highest coefficient of performance (COP) and temperature range of 30–35°C brings the lowest power consumption. When the temperature of the conditioned spaces was controlled between 27–28°C for cooling season, and 18–20°C for heating season the minimum electric power consumption was obtained. Inlet air flow rate of 1.1 m3/h for the conditioned spaces shows the highest performance of the present system, and effects of circulating water flow rate between thermal storage tank and AHU on minimum electric power consumption of the system were negligible.

scholarly journals Complex statistical data analysis of electric power consumption, consumption of energy resources and production volumes

2020 ◽  
pp. 22-28
Author(s):  
А. Voloshko ◽  
Ya. Bederak ◽  
T. Dzheria
Keyword(s):  
Statistical Analysis ◽  
Power Consumption ◽  
Electric Power ◽  
Distribution Systems ◽  
Energy Resources ◽  
Compressed Air ◽  
Electric Power Consumption ◽  
Supply And Distribution ◽  
Consumption Data ◽  
Complex Statistical Analysis

Aims of this research are development of a complex statistical analysis algorithm for active electric power consumption data, consumption of energy resources and manufacturing products, implementation of statistical analysis in practice. Proposed parameters and criteria, which can help to technical staff in factories, to provide optimal and economical operating of supply and distribution systems as electricity, water, gas, heat, compressed air, etc. for production facilities, based on the collected active electric power consumption data for previous periods, information about consumption dynamic. It is concluded that the statistical analysis of the data, obtained for each type of engineering equipments (water supply and sewage, supply systems of compressed air, gas, electricity and steam) and various consumables coefficients (in the proposed algorithm) make possible to identify "weak areas" and to determine the most rational ways to optimize energy usage.

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