{"references": ["W.C. Turner, S. Doty, Energy Management Handbook, Library of\nCongress Cataloging in Publication Data, 2007.", "D. Niu, J. Wang, D.D. Wu, Power load forecasting using support vector\nmachine and ant colony optimization, Expert Systems with Applications,\n2010, vol. 37, pp. 2531\u20132539.", "K. Nolde, M. Morari, Electrical load tracking scheduling of a steel plant,\nCompt. Chem. Eng., 2010, vol. 34, pp. 1899\u20131903.", "M. Amina, V.S. Kodogiannis, I. Petrounias, D. Tomtsis, A hybrid\nintelligent approach for the prediction of electricity consumption, Electr.\nPower Energy Syst., 2012, vol. 43, pp. 1\u2013108.", "F.M Andersen, H.V. Larsen, T.K. Boomsma, Longterm forecasting of\nhourly electricity load: Identification of consumption profiles and\nsegmentation of customers, Energy Conver. Manag., 2013, vol. 68, pp.\n244\u2013252.", "L.S. Kazarinov, D.A. Shnayder, T.A. Barbasova, and oth., Automated\ncontrol systems in energy saving (Development experience).\nChelyabinsk: Publisher SUSU, 2010.", "L.S. Kazarinov, T.A. Barbasova, O.V. Kolesnikova, A.A. Zakharova.\n\"Method of multilevel rationing and optimal forecasting of volumes of\nelectric-energy consumption by an industrial enterprise,\" Autom.\nControl Comput. Sci., vol. 48 (6), 2015; pp. 324-333.", "D. Niu, J. Li, J. Li, D. Liu, \"Middle-long power load forecasting based\non particle swarm optimization,\" Comput. Math. Appl. vol. 57, 2009,\npp. 1883-1889.", "L.S.Kazarinov, A.B. Bordetsky \"Optimization algorithm for design\nproblems with inconsistent specifications,\" Information and control\nelements and systems. Proceedings of the ChPI, vol. 231. Chelyabinsk,\n1979.\n[10] I.A. Yapryntseva, \"The preparation to control the consumption of fuel in\nthe JSC \"Magnitogorsky Iron and Steel Works\" on the Basis of\nMathematical Statistical Dependencies,\" Proceedings of the Chelyabinsk\nScientific Center, 2004, pp.96 \u2013 100."]}

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.