Modeling truck/shovel energy efficiency under uncertainty

Transactions of the Society for Mining, Metallurgy, and Exploration , 2011, Vol. 330, No. 1, pp. 573-584

Awuah-Offei, K.; Osei, B.; Askari-Nasab, H.

The U.S. coal mining industry consumes approximately 142 billion kWh/a of energy. The U.S. Department of Energy estimates that the industry’s annual energy consumption could be reduced by 49%. This constitutes nearly $3.7 billion of potential savings on coal production costs at 5.3¢/kWh of energy. Additionally, with climate change regulation on the horizon, any benefits from energy savings in the near future are compounded by associated reductions in CO₂ emissions. Research indicates that operating conditions significantly affect energy efficiency. Modeling and simulation have been shown to be a cheap and reliable means of evaluating the effects of process interactions and operating conditions. The goal of this work was to apply stochastic process simulation to model the energy efficiency of a typical truck-and-shovel mining system and use the model to evaluate production strategies to improve energy efficiency. The research team conducted energy audits of truck-and-shovel overburden removal and used the results to develop regression models describing truck and shovel fuel consumption. The team then built a stochastic simulation model of the truck-and-shovel overburden removal operation and used it to assess a variety of improvement measures by simulation experimentation. Valid fuel consumption models for shovel loading and truck haulage have been formulated, based on the energy audit results. Valid stochastic process models of truck-and-shovel operations have been formulated to study energy efficiency. The following strategies, in decreasing order of impact, provide the most energy savings for truck-and-shovel overburden removal at the mine: (1) shorten haul roads, (2) increase shovel capacity and (3) increase shovel utilization through optimal truck matching. Additional data will be required to adequately describe operator effects on energy efficiency.