the research consultancy for energy technologies
Our renewables research and data-files capture broader opportunities for renewables in the energy transition. This might include opportunities to integrate or debottleneck renewables. Or, going beyond wind and solar, which are categorized separately, it might involve additional renewables categories, such as hydro power, next-generation geothermal, or some forms of biomass energy.
Other renewables research covers growth trajectories, capex levels, physics of how renewables work, power volatility, inter-correlations of different renewables technologies, maintenance costs and decline rates.
Looking across all of our work in the energy transition, our roadmap to net zero sees renewables providing over 25% of all global energy by 2050.
This 17-page report revisits our roadmap for the world to reach ‘net zero’ by 2050, after integrating over 1,000 pieces of research from 2019 through 2022. Our updated roadmap includes large upgrades for renewables and energy efficiency; less reliance on new energies breakthroughs; but most of all, simple, pragmatic progress is needed as bottlenecks and shortages loom.
Reaching net zero requires building wind, solar, grid infrastructure, energy storage, electric vehicles and capturing CO2. Energy is needed to build all of these things. The total energy costs of energy transition reach 1% of total global primary energy in 2025, 2% in 2030, 4% in 2050 and 6.5% in 2050. In other words, energy transition is materially easier to achieve from a period of energy surplus. You can stress-test numbers in this simple model.
We want to achieve an energy transition, by ramping wind and solar to 25% of the world’s total useful energy by 2050 (note here), building a global fleet of over 2bn efficient electric vehicles, constructing power grid and storage infrastructure, and capturing over 6GTpa of CO2 via various forms of CCS.
This data-file compiles our estimates for each category, quantifying (a) how many units do we want to build? (b) what is the energy cost per unit? (c) by simple multiplication, what are the total energy costs of each category in TWH and as a percent of global primary energy.
However, building all of these things absorbs energy. There are energy intensive materials in a solar plant. There are energy intensive materials in a wind-turbine. And in electric vehicles. Around two-thirds of the energy costs for expanded power grids is embedded in the aluminium of power cabling. Finally, energy storage consumes energy in the form of round-trip efficiency losses, while CCS consumes energy in regenerating amines.
By 2025, around 1,500 TWH of primary energy, or 1.0% of total global primary energy, will be needed specifically to construct these energy transition technologies. The near-term is most heavily weighted to solar, then wind, then electric vehicles.
The numbers grow ever larger as we extrapolate out into the future. The energy transition itself will consume 2% of the world’s primary energy by 2030, 4% by 2040 and 6.5% by 2050.
These are simply enormous numbers. The 2025 number is equivalent to the total primary energy consumption of a country such as Spain or Australia. While the 2050 number is equivalent to two Saudi Arabias worth of oil production.
It is clearly going to be easier to build the important assets and infrastructure needed in the energy transition from a position of energy surplus, and it is going to be more difficult (even, inflationary) if the world is suffering from sustained energy shortages. This is why we think restoring the world’s energy surplus is the most important ESG goal of the 2020s.
The data-file also contains energy balances for each theme in the energy transition. Wind is already in a position of large energy surplus, because wind plants require 50-70% less up-front energy to construct than solar plants (per unit of ultimate generation, e.g., in kWh). The solar chart below is also more finely balanced through the mid-2020s, because solar additions are still accelerating sharply (note here). EV growth is seen accelerating so sharply that building ever more EVs will absorb more energy than they save through the mid-2030s (note here).
The technology that looks most challenged on this roadmap is green hydrogen. Converting useful, rateable electricity into green hydrogen generates no energy savings. There are simply efficiency losses, due to entropy increases, over-voltages at the anode, storage, transport, fuel cells, etc. Our chart above has <0.1% of the world’s useful energy in 2050 coming from green hydrogen. But if the number were 10%, then the total energy requirements of the energy transition would literally double.
The technology that looks least challenged on this roadmap is natural restoration (note here). Nature based solutions may create a 20GTpa CO2 sink with long-term pricing around $50/ton. But planting trees is not an energy intensive activity. There is even an argument that it generates energy, although consuming this energy has varying CO2 credentials.
A key objective for the new energies industry is going to be deploying new technologies that can improve efficiency and lower the energy intensity of energy transition. Hence our own research is also delving into opportunities in energy efficiency.
What are the energy costs of the energy transition? You can stress test numbers in the data-file, flexing total wind and solar installations, total EV deployment, CCS deployment, grid storage, green hydrogen, and the energy intensity factors of each technology.
Electrification is the largest, most overlooked, most misunderstood part of the energy transition. Hence this 10-page note aims to explain the upside, simply and clearly. Electricity rises from 40% of total useful energy today to 60% by 2050. Within the next decade, this adds $2trn to the enterprise value of capital goods companies in power grids and power electronics.
Some of the top public companies in energy transition are aggregated in this data-file, looking across over 1,000 items of research into the energy transition published to date by Thunder Said Energy.
The data file should be useful for subscription clients of Thunder Said Energy, if you are looking for a helpful summary of all of our research to-date, how it reflects upon public companies, and links to explore those companies in more detail, across our other research.
Specifically, the file allows you to filter different companies according to (a) listing country (b) size — i,e., small-cap, mid-cap, large-cap, mega-cap (c) Sector — e.g., energy, materials, capital goods, OEMs (d) TSE research — and whether the work we had done made us incrementally more optimistic, or cautious, on this company’s role generating economic returns while advancing the energy transition.
A back-up tab then reviews all of our research to date, going back to 2019, and how we think that specific research conclusion might impact upon specific companies. This exercise is not entirely perfect, due to the large number of themes, criss-crossing a large number of companies, at a large number of different points in time. Hence the observations in this data-file should not be interpreted as investment recommendations.
The screen is updated monthly. At the latest update, in September-2022, it contains 285 differentiated views on 148 top public companies in energy transition.
The purpose of this data-file is to review supercapacitor case studies, to see if they are being used to back up renewable-heavy grids? Our conclusion is that super-capacitors are well-suited to backstopping short-term wind and solar volatility, and their deployment will gradually surprise to the upside, in combination with other power-electronics.
The motivation for this work is that we recently evaluated the second-by-second volatility of solar and wind output, which incur 80-100 volatility events per day, of which c70-80% last less than 60-seconds. In turn, this volatility profile is well suited to be backed up by super-capacitors, directly, or in combination with other batteries such as lithium ion. So do case studies show increasing deployment of super-capacitors?
The build-up in our data-file has aggregated a dozen recent examples of super-capacitor deployments, based on the disclosures from leading companies, such as Skeleton, Eaton, Vinatech. Many companies endorsed the logic above (quoted in the data-file). Installations typically range from 10kW to 10MW, with 5 – 30 seconds of energy storage (chart below-left), and costs of $30/kW.
Advantages of super-capacitors, cited in many of the case studies, are very rapid responses (20 milliseconds), up to 1M charge-discharge cycles over 15-years (i.e., very low degradation) and safe functionality across wide-temperature ranges (-40ºC to +65ºC). Again, details are in the data-file.
Uses of super-capacitors are broadening. Short-term volatility events may cause $100bn pa of damage to electrical equipment. Around 100,000 wind turbines now use super-capacitors to feather their blades. Many industrial machines also have jagged power demand profiles (example above right, a servo-press used to stamp metal plates in auto-manufacturing). Peak power draw can be reduced over 80% with ultracapacitors. This matters as ‘peak power use’ can explain 50% of industrial power bills.
At grid scale, progress is slowly accelerating. One excellent case study from Eaton highlighted how a data-center could earn €50k per year by providing 1MW of demand-smoothing, kicking in within <1-second to prevent frequency drops in an increasingly renewable-heavy grid. Vinatech also noted a MW-scale super-capacitor in Korea, deemed to be more cost-effective and safe than other grid-scale batteries.
Our conclusion from these supercapacitor case studies is that this market will likely surprise to the upside. Ultracapacitors are particularly well-suited to back up the short-term volatility of renewables. But the trend is opaque, as many of the super-capacitor installations overleaf are small, not subject to the fanfare of large press releases, and integrated alongside other power electronics.
Scope 4 CO2 reflects the CO2 avoided by an activity. This 11-page note argues the metric warrants more attention. It yields an ‘all of the above’ approach to energy transition, shows where each investment dollar achieves most decarbonization and maximizes the impact of renewables.
The solar energy reaching a given point on Earth’s surface varies by +/- 6% each year. These annual fluctuations are 96% correlated over tens of miles. And no battery can economically smooth them. Solar heavy grids may thus become prone to unbearable volatility. Our 17-page note outlines this important challenge, and finds that the best solutions are to construct high-voltage interconnectors and keep power grids diversified.
Can large-scale power transmission smooth renewables’ volatility? To answer this question, this horrible 18MB data-file aggregates 20-years of hour-by-hour solar insolation arriving at four cities in the US (Los Angeles, San Francisco, Phoenix and Houston). This is our starting point to assess volatility and intermittency.
For example, San Francisco receives an average annual insolation of 2,100 kWh/m2/year, however the hour-by-hour standard error is 141% of the hourly average, day-by-day standard error is 50% of the daily average, month-by-month volatility is 30% of the monthly average and year-by-year volatility is 9% of the annual average. Solar insolation is volatile.
It would be helpful for a stable grid to smooth each of these different time-periods of volatility. Hence the data-file models the impact of constructing large inter-connector transmission lines. The model uses a very simple rule: minimize the difference in solar output in the two inter-connected regions. For example if Region A has 10GW of output and region B has 5 GW (e.g., because it is cloudy that day), you could export 2.5 GW from Region A to Region B, and both would now have 7.5 GW.
Can power transmission smooth renewables volatility? Inter-connectors can have a phenomenal impact. Returning to our example of San Francisco, we find that a 2.5 GW inter-connector between 10 GW solar hubs in both San Francisco and Phoenix would smooth San Francisco’s volatility considerably: With the inter-connector, the hour-by-hour standard error is 124% of the hourly average level (down from 141%), day-by-day standard error is 36% of the daily average (down from 50%), month-by-month volatility is 24% of the monthly average (down from 30%) and year-by-year volatility is 4.4% of the annual average (down from 9%).
This is interesting and helpful because we think batteries may find it harder to smooth year-by-year volatility (it requires an enormous battery that only gets to discharge once every 2+ years). These arguments are laid out in our 17-page research report here. Workings are in the different tabs of the data-model linked below, including scripts we have used to manage the gargantuan data-sets, and apologies in advance for the large file size.
This simple model integrates estimates the global investment in power grids that will be needed in the energy transition, as a function of simple input variables that can be stress-tested: such as total global electricity growth, the acceleration of renewables, and the associated build-out of batteries, EV charging, long-distance inter-connectors and grid-connected capital equipment for synthetic inertia and reactive power compensation.
Global investment into power networks averaged $280bn per annum in 2015-20, of which two-thirds was for distribution and one-third was for transmission. This is a good baseline.
Our base case outlook in the energy transition would see total global investment in power grids stepping up to $400bn in 2025, $600bn in 2030, $750bn in 2035 and $1trn pa in the 2040s.
Our scenario is also not particularly aggressive around renewables, which are seen accelerating by 10x to provide around 20-25% of all global energy in 2050. You can realistically reach $2trn pa of global power network investment in a scenario that relies more heavily upon renewables and batteries.
Amazingly, these numbers can actually become larger than the total spending on producing all global primary energy. Whereas in the past, transmission and distribution were a kind of side-show, equivalent to c30% of total primary energy investment, the energy transition could see them become comparable, at 50-100%.
Definitions. By ‘power networks’ we are referring to the grid, which moves electrical energy from producers to consumers. Please note that our classification of power grids excludes (a) investments in primary energy production, such as renewables, nuclear, and hydro (b) investments in large conventional power-generating plants (c) downstream investments made by customers, such as in switchgear, power electronics and amperage upgrades.
The model can be downloaded to stress-test simple numbers, inputs and outputs. Please contact us know if the work provokes any questions, or further numbers that we can helpfully pull together for TSE clients.
The purpose of this data-file is to summarize the main challenges in power electronics, products offering solutions, and how their deployment will evolve amidst the ramp-up of renewables and electrification. Hence we have attempted to quantify power electronics’ market size, product by product. Spending ramps from $360bn pa to over $1trn pa by 2035 as part of the energy transition.
We describe c15 problems that are incurred by power consumers, all of which will be amplified amidst the build-out of renewables, some more than others.
In turn, this means we expect c$100bn pa growth in the market for compensatory power-electronics solutions by 2030 (this number excludes grid-scale batteries). Different devices, examples, market sizes and costs are summarized in the equipment tab.
Increasing electrification, safely, reliably, amidst the build-out of renewables is going to require ramping up the use of power electronics commercial and industrial customers. We think a $360bn pa market for power electronics in 2021 could expand to around $1trn pa by 2035. Our numbers are also broken down in this data-file.
Categories of equipment covered in the data-file include switchgear, variable frequency drives, inverters, batteries, meters, logic controllers, harmonic filters, sensors, surge arresters, EV charging, capacitor banks, STATCOMs, other voltage regulators, synchronous condensers, and other categories that matter in commercial and industrial power.
Power electronics is a complex topic. To help decision-makers save time and quickly gain a good understanding, we have published a primer into energy, a primer into electricity, a primer into power quality, and an overview of renewables volatility.
Back-up data follows from technical papers in the final tab.