A Method of Effective Planning and Control of Industrial Facility Energy Consumption
A method of effective planning and control of
industrial facility energy consumption is offered. The method allows
optimally arranging the management and full control of complex
production facilities in accordance with the criteria of minimal
technical and economic losses at the forecasting control. The method
is based on the optimal construction of the power efficiency
characteristics with the prescribed accuracy. The problem of optimal
designing of the forecasting model is solved on the basis of three
criteria: maximizing the weighted sum of the points of forecasting
with the prescribed accuracy; the solving of the problem by the
standard principles at the incomplete statistic data on the basis of
minimization of the regularized function; minimizing the technical
and economic losses due to the forecasting errors.
[1] W.C. Turner, S. Doty, Energy Management Handbook, Library of
Congress Cataloging in Publication Data, 2007.
[2] D. Niu, J. Wang, D.D. Wu, Power load forecasting using support vector
machine and ant colony optimization, Expert Systems with Applications,
2010, vol. 37, pp. 2531–2539.
[3] K. Nolde, M. Morari, Electrical load tracking scheduling of a steel plant,
Compt. Chem. Eng., 2010, vol. 34, pp. 1899–1903.
[4] M. Amina, V.S. Kodogiannis, I. Petrounias, D. Tomtsis, A hybrid
intelligent approach for the prediction of electricity consumption, Electr.
Power Energy Syst., 2012, vol. 43, pp. 1–108.
[5] F.M Andersen, H.V. Larsen, T.K. Boomsma, Longterm forecasting of
hourly electricity load: Identification of consumption profiles and
segmentation of customers, Energy Conver. Manag., 2013, vol. 68, pp.
244–252.
[6] L.S. Kazarinov, D.A. Shnayder, T.A. Barbasova, and oth., Automated
control systems in energy saving (Development experience).
Chelyabinsk: Publisher SUSU, 2010.
[7] L.S. Kazarinov, T.A. Barbasova, O.V. Kolesnikova, A.A. Zakharova.
“Method of multilevel rationing and optimal forecasting of volumes of
electric-energy consumption by an industrial enterprise,” Autom.
Control Comput. Sci., vol. 48 (6), 2015; pp. 324-333.
[8] D. Niu, J. Li, J. Li, D. Liu, “Middle-long power load forecasting based
on particle swarm optimization,” Comput. Math. Appl. vol. 57, 2009,
pp. 1883-1889.
[9] L.S.Kazarinov, A.B. Bordetsky “Optimization algorithm for design
problems with inconsistent specifications,” Information and control
elements and systems. Proceedings of the ChPI, vol. 231. Chelyabinsk,
1979.
[10] I.A. Yapryntseva, “The preparation to control the consumption of fuel in
the JSC "Magnitogorsky Iron and Steel Works" on the Basis of
Mathematical Statistical Dependencies,” Proceedings of the Chelyabinsk
Scientific Center, 2004, pp.96 – 100.
[1] W.C. Turner, S. Doty, Energy Management Handbook, Library of
Congress Cataloging in Publication Data, 2007.
[2] D. Niu, J. Wang, D.D. Wu, Power load forecasting using support vector
machine and ant colony optimization, Expert Systems with Applications,
2010, vol. 37, pp. 2531–2539.
[3] K. Nolde, M. Morari, Electrical load tracking scheduling of a steel plant,
Compt. Chem. Eng., 2010, vol. 34, pp. 1899–1903.
[4] M. Amina, V.S. Kodogiannis, I. Petrounias, D. Tomtsis, A hybrid
intelligent approach for the prediction of electricity consumption, Electr.
Power Energy Syst., 2012, vol. 43, pp. 1–108.
[5] F.M Andersen, H.V. Larsen, T.K. Boomsma, Longterm forecasting of
hourly electricity load: Identification of consumption profiles and
segmentation of customers, Energy Conver. Manag., 2013, vol. 68, pp.
244–252.
[6] L.S. Kazarinov, D.A. Shnayder, T.A. Barbasova, and oth., Automated
control systems in energy saving (Development experience).
Chelyabinsk: Publisher SUSU, 2010.
[7] L.S. Kazarinov, T.A. Barbasova, O.V. Kolesnikova, A.A. Zakharova.
“Method of multilevel rationing and optimal forecasting of volumes of
electric-energy consumption by an industrial enterprise,” Autom.
Control Comput. Sci., vol. 48 (6), 2015; pp. 324-333.
[8] D. Niu, J. Li, J. Li, D. Liu, “Middle-long power load forecasting based
on particle swarm optimization,” Comput. Math. Appl. vol. 57, 2009,
pp. 1883-1889.
[9] L.S.Kazarinov, A.B. Bordetsky “Optimization algorithm for design
problems with inconsistent specifications,” Information and control
elements and systems. Proceedings of the ChPI, vol. 231. Chelyabinsk,
1979.
[10] I.A. Yapryntseva, “The preparation to control the consumption of fuel in
the JSC "Magnitogorsky Iron and Steel Works" on the Basis of
Mathematical Statistical Dependencies,” Proceedings of the Chelyabinsk
Scientific Center, 2004, pp.96 – 100.
@article{"International Journal of Information, Control and Computer Sciences:71414", author = "Aleksandra Aleksandrovna Filimonova and Lev Sergeevich Kazarinov and Tatyana Aleksandrovna Barbasova", title = "A Method of Effective Planning and Control of Industrial Facility Energy Consumption", abstract = "A method of effective planning and control of
industrial facility energy consumption is offered. The method allows
optimally arranging the management and full control of complex
production facilities in accordance with the criteria of minimal
technical and economic losses at the forecasting control. The method
is based on the optimal construction of the power efficiency
characteristics with the prescribed accuracy. The problem of optimal
designing of the forecasting model is solved on the basis of three
criteria: maximizing the weighted sum of the points of forecasting
with the prescribed accuracy; the solving of the problem by the
standard principles at the incomplete statistic data on the basis of
minimization of the regularized function; minimizing the technical
and economic losses due to the forecasting errors.", keywords = "Energy consumption, energy efficiency, energy
management system, forecasting model, power efficiency
characteristics.", volume = "9", number = "12", pages = "2421-5", }