Özet:

We developed a strategy for coordinated management of power consumption by an enterprise with energy-intensive technological processes in the crushing and enrichment complex. An approach is presented to model power consumption by a complex based on the constructed causal model. We defined energy consumers at a crushing and enrichment complex, energy consumers – regulators and presented a characteristic of electric drives at an enrichment plant. A structure of integrated intelligent system is attached. It provides for the optimization of iron ore production in the periods of limited power supply from the energy system. The system is integrated with the expert and operational subsystems and the management systems at the top level execution of business processes. The main task of expert and operating systems is the diagnosis of problematic situations, estimation of parameters of active, reactive powers and the prediction of output indicators of product quality. These innovations will enable the operating staff and the decision maker to receive in real time: predictive values of reactive, active values of capacity required to ensure planned indicators in production, predictive values of the trajectory in production. In the process of synthesis of control over power consumption by a crushing-enrichment complex, we defined a structure of artificial neural networks. During experimental research, we devised a procedure for training a neural network and the methods for learning. The scope of their application is separated in the system of coordinated situation management. A classification of production situations is established. We studied the modes of ball mills operation in the periods of limited power supply. A model for optimum loading of mills is presented. As a result of research, we developed: optimal setpoints for the exciters of ball mills' synchronous motors; production rules for the expert system to work out the fulfillment of planned production indicators over periods "peak", "half-peak", "night". The devised algorithms, intelligent systems of coordinated control over trajectories in power consumption and production have economic importance for enterprises in the mining-metallurgical sector of Ukraine. This is achieved by reducing specific electricity consumption by 5–7 % from the indicators in 2013, decreasing the losses in production during periods of limited power supply by 3 % from the indicators in 2013. Author Biographies Valentin Khorolskyi, Donetsk National University of Economics and Trade named after Michael Tugan-Baranowski Tramvayna str., 16, Kryvyi Rih, Ukraine, 50005 Doctor of Technical Sciences, professor Department of general engineering disciplines and equipment

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