ABB has developed new simulation features that enhance its eMine™ Consultative Studies offering. These features use a patented algorithm to optimize the placement of electric infrastructure in mines, facilitating a cost-effective and low-emission transition from diesel to electric haulage.

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_{Eike Fokken, Ruben Huehnerbein, Matthias Biskoping, ABB Corporate Research, Mannheim, Germany, eike.fokken@de.abb.com, ruben.huehnerbein@de.abb.com, matthias.biskoping@de.abb.com

Francisco Canales-Perez, Salmane El-Messoussi, ABB Process Industries, Baden, Switzerland, francisco.canales-perez@ch.abb.com, salmane.el-messoussi@ch.abb.com}

As global industries pivot towards carbon neutrality, the mining sector faces mounting pressure to reduce its environmental footprint. Mining operations contribute between 4 and 7 percent of global CO₂ emissions [1], with diesel-powered haulage accounting for nearly a third of a mine’s total emissions [2]. The shift to electrified mining is not only environmentally necessary but also increasingly economically desirable due to stricter emissions regulations, rising demand for carbon-neutral products and the falling cost of renewable energy.

Transitioning to electric trucks can significantly reduce emissions and operational costs, but requires robust and well-placed electrical infrastructure.

Structured studies to guide the transition

To make sure the transition to electric haulage is both effective and futureproof, ABB’s eMine Consultative Studies offer a structured, data-driven evaluation of electrification strategies tailored to each mine’s unique context. Built around an “Identify–Assess–Plan” framework, these studies help mining operators navigate the complex trade-offs of decarbonization by combining technical insight with economic analysis. Through close collaboration with stakeholders, ABB gathers site-specific data and explores multiple haulage methods and scenarios, taking into account mine evolution and altering routes, production targets and energy availability. Central to this approach is a simulation tools suite [3] that models how haulage performance, energy demand and infrastructure needs evolve over the life of the mine. These tools enable scenario-based assessments of different propulsion technologies and energy transfer solutions, supporting well-informed, long-term decision-making.

One particularly critical question now addressed by the tools suite is: “How does one place dynamic and stationary energy transfer systems, such as trolley lines and charging stations, in a way that remains effective as the mine shifts over time.” Until now, this task has relied heavily on expert judgment and manual planning. While this hands-on approach brings valuable experience into the process, it can be challenging to get everything just right, especially as mines change and grow over time. Planning for the long-term – sometimes 20 years or more – adds another layer of complexity that is hard to manage without the right tools.

The challenge: planning for a moving target

Unlike static industrial settings, mines evolve continuously. Resource locations shift, road networks change and operational demands fluctuate – sometimes on a weekly basis. This dynamic nature makes infrastructure planning especially challenging. Battery-powered trucks, for example, while cleaner, have limited range compared to their diesel counterparts, necessitating frequent charging or continuous power supply via dynamic energy transfer systems. Poorly planned infrastructure can lead to high costs and inefficiency.

What sets the newly developed placement features of the simulation suite apart is their explicit modeling of the mine’s full operational lifetime. This long-term perspective is rarely addressed in traditional infrastructure planning due to the mathematical complexity involved.

ABB’s approach: a lifetime-aware optimization engine

By tackling this mathematical complexity, ABB overcomes the challenges of lifetime planning by integrating time-evolving road networks and energy demands into a unified optimization framework. Three key elements are addressed simultaneously:

Mathematical modeling of a mine’s road network as a graph, with nodes representing dig sites, processors and dumps, and edges representing roads.
Power consumption estimates for electric and diesel trucks of each road segment to understand optimization opportunities for electric haulage.
Time-aware optimization algorithms that determine the most cost-effective and emission-efficient placement of stationary and dynamic energy transfer systems over the mine’s entire lifecycle.

Powerful features for planning

The additional capacity to determine optimal energy placement strengthens the ability of ABB’s study experts to analyze and compare infrastructure scenarios over the lifetime of the mine, accounting for shifting road networks, production targets and energy needs. This ability enables the balancing of capital and installation costs, energy pricing or consumption and carbon emissions across all phases of the mine’s evolution, primarily using the information gathered during initial consultations with a site’s mining operators. Configurable inputs further enrich this analysis:

CO₂ source customization, allowing users to define emission factors for different energy sources.
Vehicle performance settings, including speed, efficiency and recuperation settings.
Relocation cost modeling, which accounts for the reuse of infrastructure as the mine evolves, thereby reducing the overall incurred cost.

As part of the broader simulation suite, these optimization features strengthen ABB’s ability to deliver high-impact consultative studies by enabling more informed, lifetime-aware decisions around mine electrification and infrastructure deployment.

Dynamic energy transfer infrastructure placement optimization

As mentioned, one of the two new main features of the tools suite is the strategic placement of dynamic energy transfer solutions, such as overhead catenary (trolley) systems, that enable electric haul trucks to operate continuously while their battery is being charged on the fly »01. The optimal placement of this charging infrastructure is critical for reducing emissions and operational costs but is mathematically intricate.

The dynamic nature of a mine presents a big challenge for infrastructure placement − the road layout in an open-pit mine, for example, changes continuously over time. To enable accurate and meaningful optimized placement, first, the detailed structural data for each year of the mine’s lifetime is automatically captured for later use in the optimization process. Gathering this information manually is a complex, time-consuming and error-prone task as it involves tracking how roads appear, disappear, shift, or extend as excavation progresses. This gathered data is then consolidated in a unified, time-aware graph model.

The unified graph represents the whole life of the mine and is fed into a robust and flexible optimization engine that can adapt to different targeted mine configurations, budgets and sustainability goals. As is often the case in capital expenditure optimization, the best investments must be chosen on a predefined budget, which is computationally surprisingly difficult. It presents a so-called nondeterministic polynomial (NP)-complete problem. The restriction here is that only fixed investments with a set price can be made, rather than choosing expenses freely within the given budget. For this specific task, ABB’s optimization group devised a heuristic approach to produce good placement solutions. With this optimization engine foundation, different scenarios and sensitivities can be explored, assessing the optimal infrastructure placement and impact on the overall performance of the mine eg, in terms of throughput of material »02.

Intelligent charging station placement for battery-powered haulage

In addition to dynamic energy transfer infrastructure planning, the simulation tools now support the optimal placement of charging stations for electric haul trucks. This feature enables users to explore how various vehicle and infrastructure parameters impact the number and location of chargers required throughout the mine.

By adjusting key inputs, such as installation cost per charger, battery capacity and minimum energy threshold (ie, the fraction of the battery state of charge a vehicle must retain to safely reach a charger), ABB’s study experts can explore repercussions of different configurations on charger placement. For example, increasing battery capacity allows vehicles to travel longer distances between charges, thereby reducing the number of chargers required. Similarly, raising the minimum energy threshold results in fewer chargers (as a high threshold enables long journeys to the nearest charger), but may lead to less efficient use of each battery cycle. Each choice of inputs leads to a complex optimization challenge. The task at hand is to find the optimal number and positions of charging stations. Yet, the optimization must also ensure that, from any point along a haul route, a vehicle can reach a charger before its battery is depleted. The combination of all constraints and optimization goals yields another optimization problem, which is also NP-complete.

To address this challenge, ABB optimization researchers implemented a custom heuristic algorithm for the simulation suite that supports the technical-economic tradeoff of the stationary charging station placement, tailored for ABB’s mining customers and their real-world needs »03.

Driving sustainable transformation in mining

The additional optimization features described here represent a significant step forward in further supporting and enabling the evaluation of technically and economically optimal, electrified mine operations. By continuously expanding the simulation tools suite with advanced optimization techniques and integrating it within the eMine Consultative Studies framework, ABB is enabling mining companies to make smarter, more sustainable infrastructure decisions through comprehensive site-wide assessments. With the ability to model and assess the full lifetime of a mine and adapt to evolving conditions, ABB empowers operators to reduce emissions, lower costs and confidently navigate through the energy transition. As the industry moves toward a carbon-neutral future, a diligent, integrated assessment supported by simulations within a robust consulting framework will be essential in turning ambition into action.

References
McKinsey Sustainability, “Climate risk and decarbonization: What every mining CEO needs to know.” Available: https://www.mckinsey.com/capabilities/sustainability/our-insights/climate-risk-and-decarbonization-what-every-mining-ceo-needs-to-know. [Accessed June 3, 2025.]

Micromine, “How To Decarbonize Haulage At Your Mine (And Why It Matters).” Available: https://www.micromine.com/how-to-decarbonize-haulage-at-your-mine/#. [Accessed June 3, 2025.]

ABB, “Electrifying Haulage.” Available: https://global.abb/group/en/innovation/news/elecrifying-haulage. [Accessed June 3, 2025.]

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