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Integration of renewable energy into mining and processing operations is becoming necessary as part of a strategy towards sustainability in the minerals industry. A solar photovoltaic plant along with a battery energy storage system (PV-BESS) can provide a long-term solution to cope with increasing energy costs, thus reducing the tension with other societal competing needs for a key resource such as clean energy. However, sizing these systems is challenging, in face of uncertain ore grindability and solar power availability. In this paper, we present an application of an integrated model to size the PV-BESS, where the variability of ore grindability is modeled using geostatistical tools, solar irradiance variability is captured using a Markov chain simulation model, and the entire system is optimized through linear stochastic optimization, considering a fixed mine schedule for the feed of a semiautogenous grinding (SAG) mill. The main goals are to minimize the costs associated with operating the SAG mill in the presence of a PV-BESS system, understand how the sizing and costs change under the influence of stochastic drivers, and reveal the potential for demand-side management in mines. The size and costs of the necessary infrastructure are determined for a model of estimated grindability and an ensemble of 50 simulated models of grindability, and compared against the sizing and cost of the ground truth. The effect of climate change on solar energy availability is accounted for by forecasting the ratio of excellent, good, and moderate days over bad days in terms of irradiance out to the year 2030. Finally, the effects of stockpiles and feed control according to the processing plant needs, namely a demand-side management approach, are evaluated to reveal the impact on the energy requirements and the sizing of the photovoltaic and storage system. The model is optimized considering a yearly cost function, with hourly resolution for the solar irradiance and hardness models. The results show that integrating solar power into the operation of a SAG mill has potential to reduce the total energy cost by 27%. Robustness against climate change can be achievedwith an increase in total cost of 1%. Finally, use of stockpiles to manage the ore supply to the mill and minimize the energy cost to process it results in a cost reduction of around 2%, which should offset the rehandling cost of managing the stockpiles. [ABSTRACT FROM AUTHOR]

Different forms of flexibility can help in balancing variable generation. This work focuses on industrial demand-side flexibility applied in copper production, which is expected to grow for the build-out of green technologies. This study assesses the potential of capacity-based energy demand flexibility (over-sizing production processes) in an industry embedded in fully renewable energy systems. For this, an optimization model for multi-vector energy systems planning is extended so that it also includes the sizing and operation of a production process. A case study is presented for copper production, with greenfield results until 2050. Results show that flexibility at the concentration and refining stages belongs to the cost-optimal system design, at least over the next decade. At current costs, the potential cost savings in the energy system for the production process through capacity-based demand flexibility range from 5 % to 12 %, depending on the technology scenario. These potential savings are expected to decrease over time if cost reductions of renewable energy supply and storage technologies materialize. Technology scenarios considering seawater pumped-hydro energy storage yield lower costs over the entire projected period. • Endogenous integration of industrial process in optimal energy system planning. • Demand flexibility in copper industry beneficial in rapid energy transition. • Cost savings between 5 and 12 % for current costs of energy technologies. [ABSTRACT FROM AUTHOR]

• New method for water and energy systems planning. • First endogenous integration of coupled desalination and pumped hydro in planning models. • First design of integrated multi-vector systems for copper production. • Renewable-based desalinated water and energy supply economically attractive today. • Renewable-based is the least-cost alternative by 2030. Copper is required for the transformation of global energy systems, and its production is intensive in water and energy. Several studies have investigated the design of renewable energy systems for copper production, aiming at reducing its environmental footprint. Here, we present the first integrated design for desalinated water and energy supply that considers all forms of energy required in the copper production process. For this, we develop an optimization model for planning integrated multi-vector energy and water systems. The model includes -for the first time in an energy system planning model- a concept for integrated pumped-hydro storage using sweater and reverse osmosis desalination. Our results show that water-energy systems for copper production based exclusively on renewables can today achieve costs as low as those of conventional fossil-based systems, when integrating multi-vector planning and seawater pumped-hydro storage. For a case study in Chile and in fully renewable scenarios, the specific cost of supplying energy and desalinated water decreases from 520–670 € per ton of copper at current costs to 330–360 by 2050. By 2030, using seawater pumped-hydro storage makes a fully renewable, multi-energy scenario the least-cost alternative. Such an integrated system is an enabler for reducing the environmental footprint that copper brings into the global energy transition. [ABSTRACT FROM AUTHOR]

• We calculate the optimal electricity supply for large copper mines around the world. • From 2020 onwards, all mines should have solar shares above 25%. • In 2030, the first fully solar mines should be established. • In the long-term, Chile and Peru have the lowest electricity costs. • In most locations, low-cost solar energy makes up for costs from declining ore grades. Extracting copper is energy-intensive. At the same time, copper is a key material for building the energy systems of the future. Both facts call for clean copper production. The present work addresses the greenhouse gas emissions of this industry and focuses on designing the future electricity supply of the main copper mines around the world, from 2020 to 2050, using distributed solar photovoltaic energy, storage, and a grid connection. We also consider the increasing energy demand due to ore grade decline. For the design, we use an optimization model called LEELO. Its main inputs are an hourly annual demand profile, power-contract prices for each mine, cost projections for energy technologies, and an hourly annual solar irradiation profile for each mine. Our findings show that it is attractive for the mines to have today a solar generation of 25% to 50% of the yearly electricity demand. By 2030, the least-cost solution for mines in sunny regions will be almost fully renewable, while in other regions it will take until 2040. The expected electricity costs range from 60 to100 €/MWh for 2020 and from 30 to 55 €/MWh for 2050, with the lower bound in sunny regions such as Chile and Peru. In most locations assessed, the low cost of solar energy will compensate for the increased demand due to declining ore grades. For the next steps, we recommend representing the demand with further detail, including other vectors such as heat and fuels. In addition, we recommend to include the embodied emissions of the technologies to get a more complete picture of the environmental footprint of the energy supply for copper production. [ABSTRACT FROM AUTHOR]