Renewables will ramp up to 20% of global energy consumption by 2050, on our models for a fully decarbonized energy system. This is a vast achievement. But many commentators ask why renewables’ share is not higher. One reason is that renewables operate at low utilization rates (around 35% of installed capacity) while industrial demand requires higher utilization rates.
This data-file tabulates the utilization rates of different industries over time, based on a variety of data sources. Average US manufacturing utilization rates ran at almost 80% prior to the COVID crisis, to sustain c10% operating margins, with many commoditized industries running above 90%.
Utilization matters. A 5pp reduction in utilization rates (e.g., due to over-reliance on volatile renewables) could cut manufacuting profits by 35%. At 35% utilization, no manufacturing facility with >20% fixed costs is likel to turn a profit. This matters as manufacturing industries comprised $2.4trn of US GDP in 2019 (11% of the total) and c25% of energy consumption.
This data-file compiles all of our insights into publicly listed companies and their edge in the energy transition: commercialising economic technologies that advance the world towards ‘net zero’ CO2 by 2050.
Each insight is a differentiated conclusion, derived from a specific piece of research, data-analysis or modelling on the TSE web portal; summarized alongside links to our work. Next, the data-file ranks each insight according to its economic implications, technical readiness, its ability to accelerate the energy transition and the edge it confers on the company in question.
Each company can then be assessed by adding up the number of differentiated insights that feature in our work, and the average ‘score’ of each insight. The file is intended as a summary of our differentiated views on each company.
The screen is updated monthly. At the latest update, in July-2020, it contains 167 differentiated views on 87 public companies.
What are the top technologies to transform the global energy industry and the world? This data-file summarises where we have conducted differentiated analysis, across c80 technologies (and counting).
For each technology, we summarise the opportunity in two-lines. Then we score its economic impact, its technical maturity (TRL), and the depth of our work to-date. The output is a ranking of the top technologies, by category; and a “cost curve” for the total costs to decarbonise global energy.
Download this data-fileand you will also receive updates for a year, as we add more technologies; and we will also be happy to dig into any technologies you would like to see added to the list.
This data-file looks through all of our different power models, and summarizes their sensitivity to capital costs and CO2 prices. Specifically, we tabulate what power price is require, in c/kWh, to earn specific unlevered WACCs, on gas, coal, nuclear, wind, solar and hydrogen.
From conversations with investors, we suspect many wind and solar projects are being financed at lower WACCs (c5%) than conventional gas projects (at c10%). The sensitivity of wind and solar projects is also 4.5x higher.
It is interesting to thinkhow clear CO2 prices or varying interest rates in the future might change the relative attitudes toward these technologies. You can flex the CO2 price in the model, which changes the economics accordingly.
This data-file aggregates 20 different TSE patent screens, to assess the pace of progress in different energy technologies. Our short, 3-page summary note on the findings is linked here.
Lithium batteries are most actively researched, with 8,300 patents filed in 2019 ex-China. Autonomous vehicles and additive manufacturing technologies are accelerating fastest, with 10-year patent filing CAGRs of 22% and 53% respectively.
Wind and solar remain heavily researched, but the technologies are maturing, with patent activity -36% and -76% from peak, respectively. The steepest deceleration of interest has been in fuel cells and biofuels, declining at -10% pa and -7% since 2009.
It remains interesting to compare the pace of progress within sub-industries; for example, more supercapacitor patents were filed in 2019 than nuclear patents; while hydraulic fracturing patents remain the most intense focus area within conventional oil and gas.
This data-file models the economics of a new renewable diesel plant, converting waste oils into green diesel. It is based on technical papers and cost estimates from past projects.
A strong, c25% IRR isattainableif renewable diesel maintains a $1.0/gallon pricing premium to conventional diesel, as has been historically supported by the blenders tax credit.
The IRR is obliterated and falls to zero if this premium is lost, for example, due to emerging competition from carbon offsets. Please download the model to flex our input assumptions and stress test the economics.
This data-file aggregates the labor intensityof different energy sources: wind, solar, oil, gas, coal and nuclear, based on data from the United States and from underlying projects.
Direct labor intensity tends to vary between 75-150 workers per TWH of useful energy. The gas industry is among the most efficient power sectors, providing 100 jobs per TWH of useful energy. Oil-fired transportation is less efficient at 135 workers per TWH, rising to 730 per TWH if you include service station staff.
Renewables have a jagged profile. A typical wind and solar project creates 250-500 jobs per TWH during the construction phase, but only just 20-30 during the operational phase. So in the short-run, jobs may be creatd by expanding renewables but in the long-run, they may be destroyed.
This data-file tracks over 6,000 patents filed into battery recycling technology, focusing in on 1,800+ post-2010, Western-filed patents. This matters as annual battery disposal requirements will ramp up to over 250kTpa over the next decade. Hence the pace of patent developement has been escalating at a 15% CAGR.
18 technology leaders are profiled ex-China, based on their patent filings and public disclosures. We tabulate the size, likely battery recycling revenues and recent commercial progress.
The leaders include 6 larger-cap listed companies (two in Japan, two in the US, one in Korea, one in Europe) and 10 private companies, including some exciting, early-stage concepts to improve material recovery and costs.
The final tabsof the file include all of the patents, with summaries, and our notes from recent technical papers.
This data-file models the economics of green hydrogn production via the electrolysis of water, powered by renewable energy. IRRs and NPVs are calculated incorporating our best estimates of capex costs, opex costs, power prices, CO2 prices, utilization rates and conversion efficiencies.
A base case hydrogen price of $7.5/kg (over $60/mcfe) is required to earn a 10% unlevered return on a green hydrogen project. The most challenging input is not cost or efficiency, but utilization rate, if a green hydrogen project is to be truly green, and fully powered by renewables.
The full model contains a short summary of our conclusions, and allows you to flex our input assumptions to stress-test the economics. Sensitivity analyses are also included, varying capex, utilization, H2 prices and electricity costs.