Mining Fleet Energy Storage Scheduling for Safe Continuous Operation
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Solution Overview
Problem
Fleets of mining machines face inefficiencies in energy storage utilization, requiring safe and optimized management of energy resources across defined working and servicing areas to enhance productivity, cost-effectiveness, and safety.
Innovation Solution
A system comprising autonomous mining machines with on-board sensors, interchangeable energy storages, spatial localization, and a fog- and/or cloud-computation system that computes and deploys optimized energy storage utilization based on data from machines, energy storages, and spatial localization, aiming to optimize energy use for productivity, cost, or safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated servicing areas are used for refueling and charging, then safety is improved, but machine productivity deteriorates due to additional travel time to and from servicing areas
Solution Approach 1:
The servicing area is segmented into multiple zones including a working area and a dedicated servicing area. Machines can perform energy storage operations in the servicing area while maintaining spatial separation from active working zones, allowing simultaneous work and refueling activities without compromising safety or productivity
Solution Approach 2:
Energy storages are pre-charged or pre-refueled in the servicing area before being transferred to working machines. This preliminary preparation allows machines to receive fully charged energy storages without extended waiting times, maintaining productivity while ensuring safe handling in dedicated zones
2Productivity
If multiple mining machines operate simultaneously in a working area, then productivity is improved, but energy storage management complexity increases
Solution Approach 1:
A communication network connects all mining machines, energy storages, and the servicing area through sensors and controllers. This feedback system continuously monitors energy storage status, machine locations, and operational needs, enabling centralized coordination that manages multiple machines simultaneously without increasing operational complexity
Solution Approach 2:
Energy storages are designed as interchangeable units that can serve multiple machines universally. A single energy storage unit can be transferred between different mining machines based on operational needs, simplifying management by standardizing energy storage interfaces and protocols across the entire fleet
3Loss of energy
If energy storages are frequently transferred between machines and servicing areas, then energy utilization efficiency is improved, but operational time is reduced due to transfer operations
Solution Approach 1:
Energy storages are pre-charged to optimal levels in the servicing area before transfer to working machines. This preliminary charging ensures that transferred energy storages are ready for immediate use, minimizing idle time and maximizing operational time while maintaining high energy utilization efficiency
Solution Approach 2:
The system enables continuous operation by maintaining a pipeline of charged energy storages ready for transfer. While one machine is using an energy storage, another is being charged in the servicing area, ensuring continuous useful action without interruption and minimizing time loss during transfers
Data Source
AI summary
A system including a fleet of at least partially autonomous mining machines and a method of computing an optimized energy storage utilization in such a system. Data is acquired relating to: a shared work assignment; each respective mining machine; each respective energy storage; a location of each mining machine and each energy storage in the mining environment. The acquired data is provided to a fog- and/or cloud-computation system which is used to compute an optimized energy storage utilization with respect to at least one of the following optimization targets productivity, cost or safety. A workflow information for the performance of the shared work assignment based on the optimized energy storage utilization is deployed to the fleet of mining machines.