Automated energy efficiency project identification in the gold mining industry

Brand, H. G.; Vosloo, J. C.; Mathews, E.H.

doi:10.1109/icue.2015.7280241

Cited by 12 publications

(10 citation statements)

References 2 publications

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“…Paper [20] represents point of view of its authors as for the optimal integration of EE control process taking into consideration uncertainty of energy supply to an enterprise consuming the EE. Papers [21]- [24] also concern the problem of consumer EE control taking into account changes in electric energy tariff during a day.…”

Section: Review Of Scientific Sources and Statement Of The Problemmentioning

confidence: 99%

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Model studies to identify input parameters of an algorithm controlling electric supply/consumption process by underground iron ore enterprises

Sinchuk,

Strzelecki,

Beridze

et al. 2023

Min. miner. depos.

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Purpose is the development of the research format of a mathematical model to select and assess input parameters of an algorithm controlling distribution of electric energy flows in the monitoring structure of electricity supply/consumption by using equipment of mining enterprises engaged in underground iron ore raw materials extraction. Methods. The analytical research involved a theory of random processes adapted to the real conditions. For the purpose, results of experimental measurements have been applied obtained under the conditions of active iron ore enterprises using underground procedures of the raw materials mining. Methods of random functions (i.e. elements of correlation theory) have helped identify the basic input and output parameters characterizing rather completely electric supply consumption as a stochastic process to develop a control algorithm for the process. Findings. A mathematical model of an electric supply/consumption complex as a stochastic process has been developed to assess its features as well as its levels of influence on the economic operational indices of electric power system of under-ground mining enterprises. Formation of the algorithm to control distribution of electric power flows among consumers of the analyzed types of iron ore enterprises took into consideration stochastic nature of the mentioned complex activity. Originality. The procedure of electric supply/consumption by underground iron ore enterprises has been analyzed in the format of process of a stochastic process of their operation. For the first time, the synthesized mathematical model has been built; both average and disperse stochastic characteristics of electric consumption capacity have been identified; average period of electric energy consumption as a stationary random function during the specified time has been determined; and average number of electric consumption peaks for the interval has been defined as well as average duration of their surges. Analysis of the electric supply/consumption process as a stochastic process has helped solve a problem of the peak influence on the modes of electric energy consumption by receivers of the enterprises, i.e. the random function crossing the specified electric consumption level. Practical implications. According to the available computing formats, a calculation procedure of the operation parameters of electric supply/consumption is of insufficient accuracy since average values are applied and stochastic nature of the process is ignored, which is typical for the analyzed mining enterprises. The abovementioned restricts the possibility to develop adequate system to control the electric power process in terms of the types of mining enterprises and specificity of their operational technology. The developed methods of electric supply/consumption functioning dynamics as a stochastic process help expand its use while forming and making efficient managerial decisions in the context of the analyzed process.

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Section: Review Of Scientific Sources and Statement Of The Problemmentioning

confidence: 99%

“…To define the mean number of electric consumption peaks, apply formula (16'); according to (21), it takes the form:…”

Section: Figure 2 Statistically Normalized Correlation Function (22) ...mentioning

confidence: 99%

Model studies to identify input parameters of an algorithm controlling electric supply/consumption process by underground iron ore enterprises

Sinchuk,

Strzelecki,

Beridze

et al. 2023

Min. miner. depos.

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“…As the focus area and the design criteria are set up, the analysis of the system starts by baselining the system to assess the current conditions in the underground environment [73,82]. During this activity, all the information is collected from the respective mine, which includes the following:…”

Section: Step 1: Identify Alternativesmentioning

confidence: 99%

Prioritisation of Environmental Improvement Projects in Deep-Level Mine Ventilation Systems

Swanepoel

Vosloo

Laar

et al. 2023

Mining, Metallurgy & Exploration

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Deep-level underground mining costs in South Africa are continuously rising due to the increased depth at which gold is being mined, resulting in a rise in virgin rock temperature and an increase in cooling requirements. Therefore, mines must evaluate various ventilation and cooling optimisation projects required to be implemented throughout their life of mine (LOM). This study develops a method to identify and prioritise large capital expenditure (CAPEX) underground environmental improvement projects, to improve thermal comfort underground. The solution presents a ‘multi-criteria decision-making’ (MCDM) process, incorporating the ‘analytic hierarchy process’ (AHP) and the ‘technique for order performance by similarity to ideal solution’ (TOPSIS) into the method to provide for scientific decision-making. These projects are evaluated based on four criteria, namely project risk, the impact on the underground thermal comfort, cost, and implementation time. This study’s solution uses ventilation simulations to determine the impact of the projects on the underground environment. The identification and evaluation of an environmental improvement project to best suit the current economic climate, while improving underground conditions and decreasing the safety risk is an essential aspect of the solution developed in this study. The method was implemented on a mechanised deep-level underground mine and showed that surface refrigeration is the most suitable alternative, which was implemented at the case study mine as validation of the developed solution. The study proves that the MCDM method is an adequate solution to incorporate subjective criteria into the decision-making process, resulting in a scientific and structured approach to making significant and complex decisions.

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“…While the water demand in mining processes is continuous, it is possible to develop control strategies to relax upstream water requirements by, for instance, pumping, desalinating, and storing water when the RES-based generation capacity is high. In this sense, [89] identifies additional ancillary processes that can be aligned with EMS and DSM schemes in mining. Although implementing this type of projects will not represent substantial savings, the energy optimization and footprint mitigation in ancillary processes will open the door to pursue optimization milestones and microgrid integration in mines.…”

Section: Microgrids Applications In Miningmentioning

confidence: 99%

An Overview of Microgrids Challenges in the Mining Industry

et al. 2020

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The transition from fossil fuels to renewable energies as power sources in the heavy industries is one of the main climate change mitigation strategies. The carbon footprint in mining is related to its inherent extraction process, its high demand of electric power and water ,and the use of diesel. However, considering its particular power requirements, the integration of microgrids throughout the whole control hierarchy of mining industry is an emergent topic. This paper provides an overview of the opportunities and challenges derived from the synergy between microgrids and the mining industry. Bidirectional and optimal power flow, as well as the integration of power quality have been identified as microgrid features that could potentially enhance mining processes. Recommendations pertaining to the technological transition and the improvement of energy issues in mining environments are also highlighted in this work. INDEX TERMS Mining industry, microgrids, power quality, energy management system, renewable energies.

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Automated energy efficiency project identification in the gold mining industry

Cited by 12 publications

References 2 publications

Model studies to identify input parameters of an algorithm controlling electric supply/consumption process by underground iron ore enterprises

Model studies to identify input parameters of an algorithm controlling electric supply/consumption process by underground iron ore enterprises

Prioritisation of Environmental Improvement Projects in Deep-Level Mine Ventilation Systems

An Overview of Microgrids Challenges in the Mining Industry

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