CONTROL OF ENERGY EFFICIENCY IN INDUSTRY AND HOUSING AND COMMUNAL SERVICES
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UDC 621, 620.9
Multilevel resourсe planning and load management of a metallurgical plant
Filimonova Aleksandra Aleksandrovna, postgraduate student Automation and Control Department of SUSU, al_ekca@mail.ru
Abstract
Decision-making features for resource planning and load management of the metallurgical production processes are considered. Examined features evaluate made decisions in multilevel structure of the enterprise.
A method of resolution of interlevel contradictions in decision-making process based on an aggregate indicator is developed. The offered indicator – the index of power consumption cost reduction – allows to coordinate detailed representations of resources consumption dynamics at the local level of separate processes and generalized representations at the upper technical and economic level.
For the purposes of cost minimization under time-of-day electricity rate conditions a method of short-term rationing and forecasting of electrical energy consumption is developed. The offered method is founded on integral estimation of power consumption charts efficiency. Evaluation of the method on the real data from arc-furnace melting shop is made. Shift of the equipment operation chart of the arc-furnace melting shop provided an option to reduce electric energy costs by 8.2%.
A method of resolution of interlevel contradictions in decision-making process based on an aggregate indicator is developed. The offered indicator – the index of power consumption cost reduction – allows to coordinate detailed representations of resources consumption dynamics at the local level of separate processes and generalized representations at the upper technical and economic level.
For the purposes of cost minimization under time-of-day electricity rate conditions a method of short-term rationing and forecasting of electrical energy consumption is developed. The offered method is founded on integral estimation of power consumption charts efficiency. Evaluation of the method on the real data from arc-furnace melting shop is made. Shift of the equipment operation chart of the arc-furnace melting shop provided an option to reduce electric energy costs by 8.2%.
Keywords
energy efficiency, forecasting, energy consumption
References
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2. Nolde K., Morari M. Electrical Load Tracking Scheduling of a Steel Plant. Computers & Chemical Engineering. – 2010. – №34. – pp. 1899–1903. DOI:10.1016/j.compchemeng.2010.01.011
3. Niu D., Li J., Li J., Liu D. Middle-long Power Load Forecasting Based on Particle Swarm Optimization. Computers & Mathematics with Applications. – 2009. – №57. – pp. 1883–1889. DOI: 10.1016/j.camwa.2008.10.044
4. Pielow A., Sioshansi R., Roberts M.C. Modeling Short-run Electricity Demand with Long-term Growth Rates and Consumer Price Elasticity in Commercial and Industrial Sectors. Energy. – 2012. – №46. – pp. 1–540. DOI: 10.1016/j.energy.2012.07.059
5. Dordonnat V, Koopman SJ, Ooms M. Dynamic Factors in Periodic Time-varying Regressions with an Application to Hourly Electricity Load Modeling. Computational Statistics & Data Analysis. – 2012. – 56. – pp. 3134–3152. DOI:10.1016/j.csda.2011.04.002
6. Nagi J., Yap K.S., Nagi F., Tiong S.K., Ahmed S.K. A Computational Intelligence Scheme for the Prediction of the Daily Peak Load. Applied Soft Computing. – 2011. – №11. – pp. 4773–4788. DOI: 10.1016/j.asoc.2011.07.005
7. Lin C.W., Moodie C.L. Hierarchical Production Planning for a Modern Steel Manufacturing System. International Journal of Production Research. – 1989. – №27(4) . – pp. 613–628.
8. Kazarinov L.S., Barbasova T.A., Kolesnikova O.V., Zakharova A.A. Method of Multilevel Rationing and Optimal Forecasting of Volumes of Electric-energy Consumption by an Industrial Enterprise. Automatic Control and Computer Sciences. – 2015. – №48 (6) . – pp. 324–333. DOI: 10.3103/S0146411614060054