Abstract
The article investigates into the level of energy efficiency of main water pump stations of iron ore underground mines in case of time-of-day electricity rate. There are developed and suggested methods of analyzing the influence of pump electric capacity on electricity cost based on multifactor regressive models. The data on power consumption of iron ore mines indicates a complex character of analyzing the results obtained. However, application of information technologies enables using static materials in a new way including indices of power consumption, costs, water intake, mining depth, the number of pumps and their capacity by synthesizing mathematical models as complicated objects through in-depth procession of static materials and substantiation of the obtained results. For the first time, there are used multifactor regressive models considering multicollinearity and non-linearity of pump capacity in order to study its influence on power costs by using the elasticity factor. Analysis of mathematical simulation results relevant to static materials and applying the algorithm of studying dependency of the consumed power costs on pumps’ capacity reveals some critical values resulting in corresponding effects. The authors recommend to apply the elaborated algorithm to conducting corresponding calculations by for mining enterprises to monitor formation of the strategy of providing energy efficiency under time-of-day electricity rates.
Highlights
Mining enterprises are considered energy-intensive or, to be exact, electric power-intensive [1,2,3,4]
Without generalizing solutions to the energyefficiency problem of all energy-intensive consumers of iron ore underground mines, from all the mentioned issues (Fig. 1), we focus on investigating into power consumption and control levels of major pump stations
After considering the diagram of total power load realization of various combinations of input variables and recognizing dependency of power consumption of corresponding pump stations on controlling and disturbing actions, we can control functioning of the energy-intensive station according to the set criterion
Summary
Mining enterprises are considered energy-intensive or, to be exact, electric power-intensive [1,2,3,4]. Among those, are a limited number of energy-intensive consumers consuming about 90% of the total power (Fig. 1) [8, 9]. Facts like these a priori are highlighting the vectorrelated character of developing the strategy of researching into control over powersupply/consumption of such enterprises by transforming energy-intensive consumers into power regulators [810]. This process is stimulated by the Law on power in Ukraine which has intensified the ‘power load’ on mining enterprises, enhancing this process [8]
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