A Novel Predictive Automation Methodology for Mine De-Watering and Intermediate Product Transportation Interacting with the Smart Grid

摘要

The evolution of the electrical grid requires flexibility in electricity consumption. Given the tremendous amount of electricity consumed by mineral processing, these facilities could become a grid asset if they can leverage sources of flexibility. While facilities generally try to maximize ore throughput, de-watering represents one source of flexibility due to the holdup capacity of the water table itself and storage tanks to which the water is pumped. A second source of flexibility is intermediate product transportation with storage capabilities at each end. By developing predictive automation algorithms, these holdup capacities can be effectively leveraged. This makes the facility able to respond to grid signals, which can save on demand charges, while also becoming an asset to the grid. This work uses real, facility-level power data and presents a novel automation algorithm for both predicting facility peak demand and proactively automating the de-watering and intermediate product transportation for peak shaving.