Optimized model-based control of main mine ventilation air flows with minimized energy consumption

TLDR

The strategy aims to further reduce energy consumption of main and booster fans while meeting airflow setpoints and respecting pressure and airflow interaction constraints. It employs a data‑driven dynamical model built from historical and step‑change data to coordinate fan operation across the mine, allowing straightforward deployment and ongoing maintenance. The controller operated stably without re‑calibration, delivering a 40 % drop in fan energy use, a 15 % reduction in total airflow (and associated heating savings), and ventilation performance that correlates with mine production and surpasses previous systems.

Abstract

In early 2018, the Boliden Garpenberg operation implemented an optimized control strategy as an addition to the existing ventilation on demand system. The purpose of the strategy is to further minimize energy use for main and booster fans, whilst also fulfilling airflow setpoints without violating constraints such as min/max differential pressure over fans and interaction of air between areas in mines. Using air flow measurements and a dynamical model of the ventilation system, a mine-wide coordination control of fans can be carried out. The numerical model is data driven and derived from historical operational data or step changes experiments. This makes both initial deployment and lifetime model maintenance, as the mine evolves, a comparably easy operation. The control has been proven to operate in a stable manner over long periods without having to re-calibrate the model. Results prove a 40% decrease in energy use for the fans involved and a greater controllability of air flow. Moreover, a 15% decrease of the total air flow into the mine will give additional proportional heating savings during winter periods. All in all, the multivariable controller shows a correlation between production in the mine and the ventilation system performance superior to all of its predecessors.