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Search results for: “aluminium”

  • Energy economics: an overview?

    Energy economics: an overview?

    This data-file provides an overview of energy economics, across 175 different economic models constructed by Thunder Said Energy, in order to put numbers in context. This helps to compare marginal costs, capex costs, energy intensity, interest rate sensitivity, and other key parameters that matter in the energy transition.

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  • Battery recycling: the economics?

    Battery recycling: the economics?

    This data-file models the economics of recycling spent lithium ion batteries, taking in waste cells, and recovering materials such as cobalt, nickel, manganese, copper, aluminium, lithium and steel. It currently looks challenging to generate acceptable IRRs without charging a disposal fee in the range of $1,700-2,000/ton. This could change through more automated processes.

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  • Carbon leakage: China versus the West, 1999-2019

    Carbon leakage: China versus the West, 1999-2019

    The purpose of this data-file is to assess how ‘industrial activity’ has changed, in China and in the West (US and Europe), from 1999-2019, as a proxy for ‘carbon leakage’. We find heavier industrial activity is down 12% in the West over this 20-year period, and up 6.5x in China.

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  • Vehicle mass: what opportunities to improve fuel economy?

    Vehicle mass: what opportunities to improve fuel economy?

    Steel comprises c50% of the volume and c80% of the weight of materials in a vehicle. Each 1% reduction in mass yields a 1% improvement in fuel econome. Carbon fiber repays its extra costs after 30-70k miles, while hybridisation repays its extra costs after 10-30k miles.

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  • Energy transition: top commodities?

    Energy transition: top commodities?

    This data-file summarizes our latest thesis on ten commodities with upside in the energy transition. The average one will see demand rise by 3x and price/cost appreciate or re-inflate by 100%. The data-file contains a 6-10 line summary of our work into each commodity.

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  • Electrochemistry: battery voltage and the Nernst Equation?

    Electrochemistry: battery voltage and the Nernst Equation?

    What determines the Voltage of an electrochemical cell, such as a lithium ion battery, redox flow battery, a hydrogen fuel cell, an electrolyser or an electrowinning plant? This note explains electrochemical voltages, from first principles, starting with Standard Potentials and the Nernst Equation.

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  • High voltage transmission cables: power parameters?

    High voltage transmission cables: power parameters?

    This data-file aggregates technical parameters of ultra high-voltage power lines. The average one transmits 6.5GW, at 800-1,000kV and 4,000 Amps, over a distance of 1,500 km. Every 500 meters, there is a 70m tall tower. The power lines have total mass of 200 tons/km, 2-3% losses per 1,000km and c$3M/mile costs.

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  • Electrical conductivity: energy transition materials?

    Electrical conductivity: energy transition materials?

    Electrical conductivity of energy transition materials is tabulated in this data-file. ‘The action’ takes place in the range of 10^-8 to 10^-3 Ohm-meters, including silver in solar cells, copper in renewables and EVs, aluminium transmission lines, batteries, and solar semiconductors.

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  • How do commodities perform during recessions?

    How do commodities perform during recessions?

    How do commodities perform in recessions? Industrial metals are usually hit hardest, falling 35% peak-to-trough. Energy price spikes partly cause two-thirds of recessions, then typically trade back to pre-recession levels. Precious metals, mainly gold, tend to appreciate in financial crises. Data are compiled in this file, across recessions back to 1970.

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  • Solar: energy payback and embedded energy?

    Solar: energy payback and embedded energy?

    What is the energy payback and embedded energy of solar? We have aggregated the consumption of 10 different materials (in kg/kW) and around 10 other energy-consuming line-items (in kWh/kW). Our base case estimate is 2.5 MWH/kWe of solar and an energy payback of 1.5-years. Numbers and sensitivities can be stress-tested in the data-file.

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