Gorbachev Kuzbass State Technical University, Kemerovo, Russia:

A. G. Zakharova, Professor, Doctor of Engineering Sciences, zaharova8@gmail.com

The author proposes to predict electric energy consumption in a coal mine using the botom-up flow modeling based on the hierarchy of constituents. At the top of the model hierarchy is a ‘system’ (coal mine) composed of lower scale objects or ‘subsystems’ (ensemble of mining equipment grouped based on a certain criterion, e.g. mining equipment of extraction panels, mining equipment of permanent roadways, etc.). The state of the object ‘system’ is described with a set of characteristics which assign admissible states for each ‘subsystem’. Each object ‘subsystem’ is composed of the objects of the next lower level of the hierarchy, and the state of each ‘subsystem’ is described with a set of characteristics which assign states for that lower level objects named ‘members’ (cutter–loaders, conveyors, main mine drainage pumps, reloaders, etc.). This problem is solved using one of the most promising methods for the numerical modeling of random processes – direct simulation Monte Carlo method. Mining equipment is a system possessing finite number of states, and each simulation of evolution of states uses the method of probabilistic automata to generate transitions between the states according to a certain pre-set rule. Using the Microsoft Solutions Framework, the programmable solution is constructed for the numerical modeling of the Markov processes of a system evolution under random impacts and is implemented as a stand-alone application for Windows XP based on Microsoft Visual Basic 10.0. The test of the programmable solution using an exactly solvable model of a machine operating cycle has shown that the resultant current average values otained to an accuracy not higher than 11% offer sufficient information on distribution of probabilities for the analyzed parameters of the system. The energy consumption regularities found for individual members, subsystems and the system–mine as a whole using the proposed model are applicable to solving problems of energy efficiency improvement both in the stage of mine design and under normal operation.

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