Submit an Article
Become a reviewer
Vol 236
Pages:
245-248
Download volume:
RUS ENG

Application of automation systems for monitoring and energy efficiency accounting indicators of mining enterprises compressor facility operation

Authors:
A. V. Ugolnikov1
N. V. Makarov2
About authors
  • 1 — Ph.D. Head of department Ural State Mining University
  • 2 — Ph.D. Head of department Ural State Mining University
Date submitted:
2018-11-13
Date accepted:
2019-01-23
Date published:
2019-04-23

Abstract

The balance of electricity consumption a significant part is occupied by the production of compressed air at the mining enterprises. Many compressor stations of enterprises are equipped with automated parameter management systems that allow reliable, uninterrupted and safe operation of the compressor facilities. But the majority of automation systems at compressor stations do not perform the function of monitoring the energy efficiency indicators of the operation of a compressor station. The article discusses the issue of including compressed air flow sensors (flow meters) in an automated control system of a compressor station, which allows you to control the production of compressed air and the consumption of electrical energy for its production. Monitoring and recording of these parameters makes it possible, using microprocessor technology, to control one of the main indicators of energy efficiency – the specific energy consumption for producing one cubic meter of compressed air, determine how efficiently the compressor station works, and take appropriate measures to reduce specific energy consumption in time. . The use of additional functions of automated control and monitoring systems will allow the development and application of energy-saving measures aimed at improving the energy efficiency of the enterprise, which will lead to a reduction in the cost of finished products and increase their competitiveness

Keywords:
automated control system energy efficiency energy efficiency indicators specific energy consumption compressor station microprocessor controller
Угольников А.В., Макаров Н.В. Применение систем автоматизации для контроля и учета показателей энергоэффективности эксплуатации компрессорного хозяйства горных предприятий // Записки Горного института. 2019. Т. 236. С. 245-248. DOI: 10.31897/PMI.2019.2.245
Ugolnikov A.V., Makarov N.V. Application of automation systems for monitoring and energy efficiency accounting indicators of mining enterprises compressor facility operation // Journal of Mining Institute. 2019. Vol. 236. p. 245-248. DOI: 10.31897/PMI.2019.2.245
10.31897/pmi.2019.2.245
Go to volume 236

References

  1. Ankhimyuk V.L., Oleiko O.F., Mikheev N.N. Automatic control theory. Minsk: Dizain PRO, 2000, p. 351 (in Russian).
  2. Minyaev Yu.N., Ugol'nikov A.V., Molodtsov V.V. Technical realization of re-engineering of mine compressor installations. Gornyi informatsionno-analiticheskii byulleten'. 2007. N 2, p. 325-329 (in Russian).
  3. Minyaev Yu.N. Energy audit. Modernization of air compressor facilities of industrial enterprises. Ekaterinburg: NPO «Radikal», 2006, p. 154 (in Russian).
  4. Minyaev Yu.N. Energy saving in the production and distribution of compressed air in industrial enterprises.Ekaterinburg: Izd-vo UGGGA, 2002, p. 131 (in Russian).
  5. Ovcharenko N.I. Automation of power plants and electric power systems. Мoscow: Izd-vo NTs ENAS, 2000, p. 504 (in Russian).
  6. Khronusov G.S. Formation of effective modes of power consumption of industrial enterprises. Ekaterinburg: Izd-vo UGGGA, 1998. Part 1, p. 339 (in Russian).
  7. Energy saving in systems of heat supply, ventilation and air conditioning: Spravochnoe posobie. Pod red. L.D.Boguslavskogo i V.I.Livchaka. Мoscow: Stroiizdat, 1990, p. 624 (in Russian).
  8. Bolognani S., Peretti L., Zigliotto M., Bertotto E. Commissioning of Electromecanical Confession Models for High-Dynamic PMSM Drives. IEEE Trans. on Industrial Electron. 2010. Vol. 57. N 3, p. 986-993.
  9. De Souza Glauce, Odloak Darci, Zanin Antonio C. Real Time Optimization (RTO) with Model Predictive Control (MPC). Computer Aided Chemical Engineering. 2009. Vol. 27, p. 1365-1370.
  10. Dougherty Danielle, Cooper Doug. A practical multiple model adaptive strategy for single-loop MPC Original Research. Control Engineering Practice. 2003. Vol. 11. Iss. 2, p. 141-159.
  11. Feuiillete D., Amet J.P. Introduction du SPC (Statistical process control) sur le train a bandes de Sollac Florange. Rev. Met. 1988. Vol. 85. N 4, p. 325-330.
  12. Maciejowski J.M. Predictive control with constraints. Englewood Cliffs: Prentice Hall. 2002, p. 290.
  13. Muske K.R., Rawlings J.B. Model predictive control with linear models. A.I.CH.E. Journal. 1993. Vol. 39. N 2, p. 262-287.
  14. Nonlineary predictive control. Theory and practice / B.Kouvaritakis, M.Cannon (Eds.). London: The IEE, 2001, p. 413-428.

Similar articles

Produc-tion of Silver Ruble and participation of the Saint-Petersburg Mining university in the development of monetary industry of Russia
2019 V. Yu. Bazhin, N. M. Telyakov, T. A. Aleksandrova, D. V. Gorlenkov
Estimation of critical depth of deposits by rock bump hazard condition
2019 V. N. Tyupin
Prospects of geomechanics development in the context of new technological paradigm
2019 V. L. Trushko, A. G. Protosenya
Refined assessment of seismic microzonation with a priori data optimisation
2019 I. B. Movchan, A. A. Yakovleva
Development and research of formation technologies on specialized presses with subsequent sintering of high-density details from iron-based powders
2019 A. M. Dmitriev, N. V. Korobov, A. Zh. Badalyan
Effect of chalk thermal treatment mode on its strength
2019 V. A. Lipin, D. A. Trufanov