scholarly journals Model investigations into assessing optimal power consumption modes for major pump stations of iron ore underground mines

2021 ◽  
Vol 280 ◽  
pp. 05012
Author(s):  
Igor Sinchuk ◽  
Tetyana Beridze ◽  
Irina Kasatkina ◽  
Roman Krasnopolsky ◽  
Oleg Dozorenko ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Information Technologies ◽  
Iron Ore ◽  
Time Of Day ◽  
Underground Mines ◽  
Electricity Cost ◽  
Mining Depth ◽  
Pump Stations ◽  
Power Costs

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.

scholarly journals Investigation and optimization of main materials consumption when mining iron ores at deep levels of the Underground Mine Group of the PJSC “ArcelorMittal Kryvyi Rih”

2020 ◽  
Vol 201 ◽  
pp. 01026
Author(s):  
Mykola Stupnik ◽  
Vsevolod Kalinichenko ◽  
Olena Kalinichenko ◽  
Sofiia Yakovlieva
Keyword(s):  
Strain State ◽  
Iron Ore ◽  
Deep Levels ◽  
Underground Mine ◽  
Underground Mines ◽  
Iron Ores ◽  
Efficient Technology ◽  
Mining Depth ◽  
Geological Conditions ◽  
Qualitative Characteristics

The work considers conditions of deep levels of the Underground Mine Group for underground ore mining (as underground mines) of the Mining Department of the PJSC “ArcelorMittal Kryvyi Rih” (the PJSC “ArcelorMittal Kryvyi Rih”). The research aims to improve indicators of mined ore mass extraction when mining rich iron ores through studying and optimizing consumption of explosives, enhancing mining technology to provide fulfilment of the underground iron ore mining program. During the research, there are analyzed mining geological and technical conditions of the deposit mining as well as current technologies of iron ore mining at the Underground Mine Group of the PJSC “ArcelorMittal Kryvyi Rih”. The work analyzes the achieved indices and consumption of explosives for drilling and blasting at the Underground Mine Group. The mining geological and technical conditions of the deposit mining as well as current technologies of mining, parameters of preparatory operations, the nomenclature and qualitative characteristics of many types of explosives are determined to have changed. This complicates planning consumption of explosives and making their estimates for work sites. However, this is a reason for selecting highly efficient technology and machinery in deteriorating mining and geological conditions of operating at over 1200 m depths. The work determines dependencies of a stress value on a mining depth and physical properties of rocks, as well as parameters of drilling and blasting operations considering the stress-strain state of the massif under high rock pressure at deep levels of the Mining Group of the PJSC “ArcelorMittal Kryvyi Rih”.

scholarly journals The Numerical Simulation of the Airflow Distribution and Energy Efficiency in Data Centers with Three Types of Aisle Layout

2019 ◽  
Vol 11 (18) ◽  
pp. 4937 ◽  
Author(s):  
Jing Ni ◽  
Bowen Jin ◽  
Shanglei Ning ◽  
Xiaowei Wang
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Air Conditioning ◽  
Data Centers ◽  
Simulation Method ◽  
Cooling Capacity ◽  
Energy Utilization ◽  
Improve Energy Efficiency ◽  
Electricity Cost ◽  
Airflow Distribution

The energy consumption of fast-growing data centers is drawing attentions from not only energy organizations and institutions all over the world, but also charity groups, such as Greenpeace, and research shows that the power consumption of air conditioning makes up a large proportion of the electricity cost in data centers. Therefore, more detailed investigations of air conditioning power consumption are warranted. Three types of airflow distributions with different aisle layouts (the open aisle, the closed cold aisle, and the closed hot aisle) were investigated with Computational Fluid Dynamics (CFD) methods in a typical data center of four rows of racks in this study. To evaluate the results of thermal and bypass phenomenon, the temperature increase index (β) and the energy utilization index (ηr) were used. The simulations show that there is a better trend of the β index and ηr index both closed cold aisle and closed hot aisle compared with free open aisle. Especially with high air flow rate, the β index decreases and the ηr index increases considerably. Moreover, the results prove the closed aisles (both closed cold aisle and closed hot aisle) can not only significantly improve the airflow distribution, but also reduce the mixture of cold and heat flow, and therefore improve energy efficiency. In addition, it proves the design of the closed aisles can meet the increasing density of installations and our simulation method could evaluate the cooling capacity easily.

scholarly journals ON TACTICS OF DEVELOPING ARCHITECTURE OF THE GENERALIZED ALGORITHM OF ENERGY-ORIENTED POWER CONSUMPTION CONTROL AT IRON ORE UNDERGROUND MINING COMPANIES

2021 ◽  
Vol 1 (53) ◽  
pp. 51-63
Author(s):  
I. Sinchuk ◽  
◽  
A. Kupin ◽  
V. Baranovskyi ◽  
Keyword(s):  
Power Consumption ◽  
Objective Function ◽  
Iron Ore ◽  
Underground Mining ◽  
Time Of Day ◽  
Total Power ◽  
Positive Trend ◽  
Technological Parameters ◽  
Consumption Control ◽  
Number Of Iterations

Purpose. The article substantiates and confirms the thesis about the need for energy-oriented power consumption control levels in power complexes: the system of power supply at iron ore underground mining enterprises on the basis of experiment data analysis. Methodology. It is estimated that along with the current positive trend suitable for developing architecture of power consumption control levels when a limited number of energy-intensive enterprises consume about 80 % of the total power produced, their functioning modes in day hours vary. Analysis of varied realtime modes of power consumption in hours indicates absence of enterprises’ control over this process. Results. The suggested methods enable forecasting efficiency of power consumption control in hours in any variant of time-of-day tariff integration. In non-standard and changeable conditions of technological parameters in mining production, on the basis of the results of stochastic optimization analysis, it is proven that even when applying a small number of iterations N = 10, it is possible to improve the initial solution by over 60 % (the initial value of the objective function is I* = 27.7 and the final value on the last iteration is I* = 10.7). There are determined required vectors to specify a connection of the time-of-day tariff of ore mining (Р*) and the corresponding power consumption (Е*) which corresponds to the suboptimal value of the objective function (I*). The obtained results can be applied to developing recommendations for a more efficient planning of an enterprise’s performance. Practical value. The suggested algorithm implemented in power consumption control systems enables receiving a final result with any quality required for the level. If the quality of the obtained results needs improving, the number of iterations is to be increased by two or three orders of magnitude.

scholarly journals Power and Performance Evaluation of Memory-Intensive Applications

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4089
Author(s):  
Kaiqiang Zhang ◽  
Dongyang Ou ◽  
Congfeng Jiang ◽  
Yeliang Qiu ◽  
Longchuan Yan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Job Scheduling ◽  
Memory System ◽  
Processor Core ◽  
Memory Efficiency ◽  
And Performance ◽  
Reasonable Use ◽  
Server System

In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the non-energy proportion of DRAM. Furthermore, modern servers usually use NUMA architecture to replace the original SMP architecture to increase its memory bandwidth. It is of great significance to study the energy efficiency of these two different memory architectures. Therefore, in order to explore the power consumption characteristics of servers under memory-intensive workload, this paper evaluates the power consumption and performance of memory-intensive applications in different generations of real rack servers. Through analysis, we find that: (1) Workload intensity and concurrent execution threads affects server power consumption, but a fully utilized memory system may not necessarily bring good energy efficiency indicators. (2) Even if the memory system is not fully utilized, the memory capacity of each processor core has a significant impact on application performance and server power consumption. (3) When running memory-intensive applications, memory utilization is not always a good indicator of server power consumption. (4) The reasonable use of the NUMA architecture will improve the memory energy efficiency significantly. The experimental results show that reasonable use of NUMA architecture can improve memory efficiency by 16% compared with SMP architecture, while unreasonable use of NUMA architecture reduces memory efficiency by 13%. The findings we present in this paper provide useful insights and guidance for system designers and data center operators to help them in energy-efficiency-aware job scheduling and energy conservation.

scholarly journals Massive MIMO: Achievable Energy Efficiency for 5G systems with Multi-user Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 6527-6534
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Path Loss ◽  
Antenna System ◽  
Base Station ◽  
Small Cells ◽  
Limiting Factors ◽  
Improve Energy Efficiency ◽  
User Terminal ◽  
Simulation Results

Massive Multi-Input and Multi-Output (MIMO) antenna system potentially provides a promising solution to improve energy efficiency (EE) for 5G wireless systems. The aim of this paper is to enhance EE and its limiting factors are explored. The maximum EE of 48 Mbit/Joule was achieved with 15 user terminal (UT)s. This problem is related to the uplink spectral efficiency with upper bound for future wireless networks. The maximal EE is obtained by optimizing a number of base station (BS) antennas, pilot reuse factor, and BSs density. We presented a power consumption model by deriving Shannon capacity calculations with closed-form expressions. The simulation result highlights the EE maximization with optimizing variables of circuit power consumption, hardware impairments, and path-loss exponent. Small cells achieve high EE and saturate to a constant value with BSs density. The MRC scheme achieves maximum EE of 36 Mbit/Joule with 12 UTs. The simulation results show that peak EE is obtained by deploying massive BS antennas, where the interference and pilot contamination are mitigated by coherent processing. The simulation results were implemented by using MATLAB 2018b.

scholarly journals Optimizing Power Consumption of Freight Railroad Bearings Using Laboratory Experimental Data

2020 ◽  
Author(s):  
Carlos E. Lopez ◽  
Constantine Tarawneh ◽  
Arturo Fuentes ◽  
Harry Siegal
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Optimal Operating ◽  
Speed Condition ◽  
Load Train ◽  
Train Speed ◽  
Railroad Bearings ◽  
Railroad Bearing ◽  
The University

Abstract Based on projected freight truck fuel efficiency, freight railroad and equipment suppliers need to identify, evaluate and implement technologies and/or operating practices to maintain traditional railroad economic competitiveness. The railway industry uses systems that record the total energy efficiency of a train but not energy efficiency or consumption by components. Lowering the energy consumption of certain train components will result in an increase in its overall energy efficiency, which will yield cost benefits for all the stakeholders. One component of interest is the railroad bearing whose power consumption varies depending on several factors that include railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Being able to quantify the bearing power consumption, as a function of the variables mentioned earlier, would make it possible to obtain optimal operating condition ranges that minimize energy consumption and maximize train energy efficiency. Several theoretical studies were performed to estimate the power consumption within railroad bearings, but those studies lacked experimental validation. For almost a decade now, the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV) has been collecting power consumption data for railroad bearings under various loads, speeds, ambient temperatures, and bearing condition. The objective of this ongoing study is to use the experimentally acquired power consumption to come up with a correlation that can be used to quantify the bearing power consumption as a function of load, speed, ambient temperature, and bearing condition. Once obtained, the model can then be used to determine optimal operating practices that maximize the railroad bearing energy efficiency. In addition, the developed model will provide insight into possible areas of improvement for the next generation of energy efficient railroad bearings. This paper will discuss ongoing work including experimental setup and findings of energy consumption of bearings as function of railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Findings of energy consumption are converted into approximations of diesel gallons to quantify the effect of nominal energy consumption of the bearings and show economic value and environmental impact.

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