Integrated Data Environment for Analysis and Control of Energy Consumption (IDE-ACE) in Surface Coal Mining
Open Access
- Author:
- Bogunovic, Dragan
- Graduate Program:
- Mining Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 27, 2008
- Committee Members:
- Vladislav Kecojevic, Associate Professor Of Mining Engineering, Committee Chair/Co-Chair
R Larry Grayson, Professor Of Energy And Mineral Engineering, Committee Member
Maochen Ge, Associate Professor Of Mining Engineering, Committee Member
Dongwon Lee, Committee Member
Yaw D Yeboah, Professor Of Energy And Mineral Engineering, Committee Member - Keywords:
- Integrated Data Environment
Energy Consumption
Coal Mining Process Improvement
Carbon Dioxide Emissions - Abstract:
- The U.S. mining industry consumes a significant amount of energy, primarily diesel fuel and electricity. A recent study by the U.S. Department of Energy indicates the energy consumption of about 1,246 trillion Btu (365 billion kWh) annually. The continuous global increases in energy demand, energy prices as well as the environmental impact relating to CO2 emissions represent a substantial challenge for the industry. Currently, coal mines use state-of-the-art technology integrated into sophisticated systems that monitor production and equipment performance in real-time. However, frequent data acquisition results in multiple, unrelated, data storages simultaneously inducing an industry-wide problem of being data rich and information poor. This dissertation presents the results of research work on the development of an integrated data environment system for analysis and control of energy (IDE-ACE) consumption in a surface coal mining operation. The IDE-ACE is able to provide answers to the crucial questions of when, where, and how much energy is being used in the mining production chain. A high energy consumer (equipment) can be isolated by the integrated analytical processes and data recorded in a centralized database. The system integrates additional features that utilize the existing real-time data sources in order to optimize equipment working parameters, lower production costs, and reduce energy consumption and CO2 emission. A case study on an operating surface coal mine is carried out to demonstrate the practical application of the developed system. The methodology developed in this dissertation can be used as a benchmark for calculation of energy consumption in surface coal mining. Additionally, the results of the study indicate that a case study mine is likely to benefit in energy savings of approximately quarter million dollars on the annual basis.