Global Energy Demand Research and Data

Global energy: supply-demand model?

This global energy supply-demand model combines our supply outlooks for coal, oil, gas, LNG, wind and solar, nuclear and hydro, into a build-up of useful global energy balances in 2022-30. We fear chronic under-supply. This is masked by economic weakness in 2023, rises to 3% shortages in 2025, and 5% shortages in 2030. Numbers can be stress-tested in the model.

Useful global energy demand grew at a CAGR of +2.5% per year since 1990, and +3.0% per year since 2000. Demand would ‘want’ to grow by +2% per year through 2030, due to rising populations and rising living standards (model here). We have pencilled in +1.75% pa growth to this model to be conservative.

Combustion energy is seen flat-lining. This includes global coal use peaking at 8.4GTpa in 2024 then gently easing to 2010 levels by 2030 (model here). It includes oil demand, rising to 101Mbpd in 2023 (data here), then plateauing (model here) as OPEC and US shale (model here) offset the decline rate impacts of conventional under-investment. It includes risked LNG supplies rising +70% from 400MTpa in 2022 to almost 700MTpa by 2030 (model here). While our roadmap to net zero would need to see global gas growing at +2.5% per year through 2050 (model here), this data-file has pencilled in flat production in 2022->30, as we think that latter scenario currently looks more likely to transpire.

Renewable energy is exploding. Our model of wind and solar capacity additions is linked here and discussed here. In our roadmap to net zero, solar more than doubles from c200GW of new adds in 2022 to 450GW by 2030, while wind doubles from 110GW of new adds in 2022 to 220GW by 2030. But in this model, we have assumed higher growth again, with 2030 supply growth approaching 900GW. We do not want to be accused of under-baking our renewables numbers in this global energy supply-demand model.

Other variables in the model include rising energy efficiency (note here), the need for a nuclear renaissance (note here) and other variables that can be flexed.

What is wrong with this balance is that it does not balance. The assumptions pencilled into the model see an under-supply of global energy of about 3% in 2025, rising to 5% in 2030. I.e., by 2050, the world will be “half a Europe” short of energy. The first law of thermodynamics dictates that energy demand cannot exceed supplies. So what would it take to restore the balance? Well, pick your poison…

(1) Slower demand growth could re-balance the model. Very high energy prices might mute demand growth to only +1.25% per year, although this would be the slowest pace of demand growth since the Great Depression, lower even than during the oil shocks (useful data here). Unfortunately, our view is that pricing people out of the global energy system in this way is in itself an ESG catastrophe.

(2) Ramping renewables faster could re-balance the model, although it would require an average of 1 TW pa of wind and solar capacity additions each year in 2024-30, and over 2 TW pa of wind and solar additions by 2030 itself, which is 3x higher than in our roadmap to net zero (discussion here). For perspective, this +2TWpa solution requires primary energy investment to quadruple from $1trn pa to at least $4trn pa, which all needs to be financed in a world of rising rates. It means that global wind and solar projects will consume over 200MTpa of steel, which is 2x total US steel production, and yet steel would not even qualify as a ‘top ten’ bottleneck, in our wind bill of materials or solar bill of materials. This scenario also requires a 3x faster expansion of power grids and power electronics than our base case estimates (see the links). Is any of this remotely possible?

(3) Continue ramping coal? The main source of global energy demand growth is the emerging world. The emerging world is more likely to favor cheap, dirty coal. Thus another way to ameliorate under-supply in our global energy supply-demand balance is if global coal continues growing, reaching a new peak of 9GTpa in 2030. Unfortunately, this scenario also sees global CO2 hitting a new peak of 54GTpa in 2030.

(4) Pragmatic gas? Another means of re-balancing the global energy system is if global gas production rises at 2.5% per year, which is the number required, and that is possible, on the TSE roadmap to net zero (model here). This scenario does see global CO2 falling by 2030. The main problem here is that pragmatic natural gas investment has become stranded in no man’s land, within a Manichean duality of fantasies and crises.

(5) Some combination? The world is complex. It is unlikely that a single lever will be pulled to resolve under-supply in our global energy supply-demand balance. In 2023, we think economic weakness will mask energy under-supply, mute energy prices, and lure many decision makers into looking at spot pricing and thinking “everything is fine”. Please download the model to stress-test the numbers, and different re-balancing solutions…

What is the energy consumption of the internet?

Powering the internet consumed 800 TWH of electricity in 2022, as 5bn users generated 4.7 Zettabytes of traffic. Our guess is that the internet’s energy demands double by 2030, including due to AI (e.g., ChatGPT), adding 1% upside to global energy demand and 2.5% to global electricity demand. This 14-page note aims to break down the numbers and their implications.

Internet energy consumption: data, models, forecasts?

This data-file aims to provide helpful numbers into the energy consumption of the internet (800TWH in 2022), the energy intensity of end-to-end internet processes (140Wh/GB of ultimate traffic) and projections of future internet energy demand (doubling by 2030?). Input assumptions to the model can be flexed. Underlying data are from technical papers.

Our best estimate is that the internet accounted for 800 TWH of global electricity in 2022, which is 2.5% of all global electricity. Despite this area being a kind of analytical minefield, we have attempted to construct a simple model for the future energy demands of the internet, which decision-makers can flex, based on data and assumptions (chart below).

Internet traffic has been rising at a CAGR of 30%, as shown by the data use of developed world households, rising to almost 3 TB per user per year by 2023. The scatter also shows a common theme in this data-file, which is that different estimates from different sources can vary widely.

Future internet traffic is likely to continue rising. By 2022 there were 5bn global internet users underpinning 4.7 Zettabytes (ZB) of internet traffic. Users will grow. Traffic per user will likely grow. We have pencilled in some estimates, but uncertainty is high.

The energy intensity of internet traffic spans across data-centers, transmission networks and local networking equipment. Again, different estimates from different technical papers can vary by an order of magnitude. But a first general rule is that the numbers have declined sharply, sometimes halving every 2-3 years.

The current energy intensity of the internet is estimated at 140 Wh/GB in our base case, and broken down in the waterfall chart below, using our findings from technical papers and the spec sheets of underlying products (e.g., offered by companies such as Dell).

Energy intensity of internet processes will almost certainly decline in the future, as traffic volumes rise. Again, we have pencilled in some estimates to our models, which can be flexed.

The electricity consumption of the internet will also include additional processing power for blockchains (crypto-currencies) and artificial intelligence engines, layering in on top of today’s core internet processes. Thus we can derive an approximate model below.

Please download the model to stress-test your own estimates for the energy intensity of the internet. It is not impossible for total electricity demand to ‘go sideways’ (i.e., it does not increase). It is also possible for the electricity demand of the internet to exceed our estimates by a factor of 2-3x if the pace of productivity improvements slows down.

Global oil demand: breakdown by product by country?

This data-file breaks down global oil demand, country-by-country, product-by-product, month-by-month, across 2017-2022. The goal is to summarize the effects of COVID, and the subsequent recovery in oil markets. Global oil demand is hitting new highs, even though several product categories are still not fully recovered.

Overall, global oil demand fell by -22Mbpd at trough in April-2020; and by an average of -9Mbpd YoY in 2020 overall. In 2021, two thirds of the lost demand recovered, but global oil demand was still -3Mbpd below 2019 levels. However, 2022 demand most likely hit all-time highs (chart above).

Comparing 2022 versus 2019. We think total oil demand was around 100Mbpd in both years. But strikingly, air travel is nowhere close to having fully recovered. Jet fuel demand remains -2Mbpd below 2019 levels, portending possible upside in 2023+. Relatedly, gasoline demand remains -0.8Mbpd below 2019, of which the decline is entirely in the developed world, and probably also linked to travel activity remaining somewhat disrupted.

All other categories are making new highs. In 2022, distillate demand was +0.6Mbpd above 2019 levels (-0.6Mbpd in the OECD, +1.2Mbpd in non-OECD, and a lot of the charts in the data-file show a trend like the one below).

Likewise, in 2022 versus 2019, naphtha use was +0.5Mbpd above, LPG use was +0.4Mbpd above and NGL use was +0.4Mbpd above (all three of these lines feed into global plastics demand). Fuel oil use was +0.4Mbpd above (chart below).

Overall this data-set confirms our fears that renewables, EVs and other new energies would all need to ramp about 3-5x faster than their likely run-rate in the 2020s to stop oil demand (and even coal demand) from continuing to rise (note here).

This matters because in 2020, many commentators were stating that 2019 would have been the all-time peak for fossil fuels, that demand would never recover to pre-COVID levels, and that the world should therefore “stop investing” in hydrocarbons. Even today, we worry that some commentators are still materially over-estimating future efficiency gains in the global energy system (note here). A lack of pragmatism worries us (note here). Long-term energy shortages worry us (note here). Our LT oil demand model is here.

However, there is some uncertainty in this data-set, as the original data-source (JODI) only covers 80% of the oil market. We estimate the remaining countries by taking a proxy from “analogous countries” (the methodology is described in our original report here). Meanwhile some of the reported data look suspect. Most notably, “other product demand” in China is a very large and erratic data-line.

Global energy demand: by region and through 2050?

This model captures global energy demand by region through 2050, rising from 70,000 TWH in 2019-22 to 120,000 MWH in 2050. Population rises 1% pa. Energy use per global person rises at 1% pa, from 9.3 MWH pp pa to 12.6 MWH pp pa. So total demand rises c2% pa. Meeting the energy needs of human civilization is crucial in the energy transition.

Total global energy consumed by human civilization has averaged 70,000 TWH over the past five years, from 2018-2022, on a useful energy basis. This comprises an average of 9.3 MWH pp pa of useful energy across 7.7bn people.

Global energy demand growth averaged 2.6% per annum from 1990 to 2019, of which 1.3% per annum is due to population growth and 1.2% per annum is due to rising energy consumption per capita.

Our outlook through 2050 is that total global energy consumption will surpass 120,000 TWH, on a useful energy basis. This represents a 1.6% growth rate.

0.8% is from population growth, as the World Bank sees global population reaching 9.7bn people by 2050. An interesting nuance in the population forecasts is that the growth rate slows over time, from 0.9% pa in the next decade to 0.6% pa in the 2040s. In turn, this suggests energy demand growth through 2050 will be somewhat front loaded.

0.9% is from rising useful energy demand per person. But these are not aggressive numbers. Small tweaks in our model of global energy demand by region and through 2050 can yield another 10-30% upside again.

Inequalities and catch-ups are a tension in the model. Today, useful energy consumption runs at 20MWH pp pa in Europe and Japan, and as much as 40 MWH pp pa in North America. Conversely, the poorest 4bn people in the world, especially in Africa, India and other Asia, consume an average of 2.5 MWH pp pa today (more here). Even by 2050, this group is only seen consuming 6 MWH pp pa of useful energy, which is 60-80% below Western levels. This sits uncomfortably with other goals for human development.

Electrification is another theme in the data-file. Total useful electricity consumption has averaged 27,500 TWH pa over the past half-decade, equivalent to 3.6 MWH of useful energy per global person, or 38% of all useful energy consumption. In other words, 62% of useful energy has been consumed directly as heating fuel or in combustion engines.

We see the growth rate of electrification doubling, from 2% pa in the past decade to 4% pa in the next decade, as part of the energy transition. Thus by 2050, we think that electricity will comprise 60% of total useful energy consumption (please see our power grids research). Our recent research explores $2trn of medium-term upside for capital goods companies as a result of electrification in the energy transition.

What share for wind and solar? Our forecasts for wind and solar step up to provide 30,000 TWH of useful energy by 2050 (note here). This would be 25% of total global energy demand. We also see nuclear re-accelerating and growing more than 2.5x. The remaining c65% will need to be sourced from somewhere, and we think the best candidate is low-carbon natural gas, combined with CCS and CO2 removals.

Different regions are represented in the data-file. China is worth a passing mention: energy demand per capita is apt to look higher than it is, because a remarkable 60-65% of all China’s energy is used for heavy industry and manufacturing, creating products that are ultimately exported and consumed elsewhere. Assumptions and growth-rates for different regions can be stress-tested in the data-file to run your own scenarios.

CO2 compression: stranger things?

CO2 is a strange gas. This matters as energy transition will require over 120 GW of compressors for 6GTpa of CCUS. This 13-page notes explains CO2’s strange properties, which helps to fine-tune appropriate risking factors for vanilla CCS, blue hydrogen, CO2-EOR, CO2 shipping, super-critical CO2 power cycles. There is also a wide moat around leading turbomachinery companies.

Energy demand: making predictions about the future?

How accurate are energy demand forecasts? I.e., what is the error of the estimate for forecasting future global energy demand, or future oil demand, a few years into the future? This data-file aggregates data in order to answer this question, across oil, coal, gas and renewables. The best rule-of-thumb is 0.6% per year.

The best data-set we have found, to assess the accuracy of energy demand forecasts, comes from the International Energy Agency’s medium term reports, which have mostly been published annually for oil, coal and sometimes gas, going back to the mid-2000s.

The adjusted error of the estimate for forecasting global oil demand is 0.6% per year. In other words, estimates of global oil demand in N-years time tend to suffer from a forecasting error of N x 0.6%. For example, the IEA’s average estimate for oil demand in 5-years time has tended to be almost 3Mbpd out in either direction.

Methodology. Note that we have excluded the totally anomalous year of 2020 from these calculations, in order to avoid a distorted result.

Overall there has been a small bias towards over-estimating future oil demand. However, this is nuanced. Our data-set covers estimates from the past 15-years, during which time, the world has endured two unexpectedly large economic shocks, one due to the global financial crisis of 2008-09 and the other due to the COVID crisis of 2020-21; and three large price shocks, including the run-up of oil prices in 2007-08, in 2012-14 and in 2021-22.

By contrast, in periods where economic activity was strong and oil prices were low/falling, such as 2010, or 2015-17, oil demand came in 2-3Mbpd higher than had been expected in forecasts from 2-5 years previously.

The data-file also contains data on medium term coal forecasts. Over the past decade, future global coal consumption has consistently been over-estimated, as there was more substitution to use gas and new energies. However, interestingly, 2021-22 appears to be the first year in over a decade where demand is actually higher than forecasts from 3-5 years prior.

Please note, we have not undertaken this analysis to criticize past forecasts. It is difficult to make predictions, especially about the future.

However, we do think that the inherent challenges of forecasting future energy demand in the world is an argument for policymakers to target an energy surplus, with ample spare capacity, in order to avoid the catastrophic impacts of persistent energy shortages. You certainly wouldn’t board a plane whose reserve fuel buffer was lower than the error of the estimate. And once you are in an energy shortage it takes a long time to build new supplies.

How accurate are energy demand forecasts? Please download the data-file to interrogate the numbers that have informed this analysis.

Energy shortage: fear in a handful of dust?

Should restoring the world’s energy surplus be seen as the most important ESG goal of the 2020s? This 12-page note outlines our top ten considerations, as our energy balances have deteriorated even further in the last year. Under-supply could persist through 2030. Shortages have cruel consequences. And unexpected ripple effects. Energy surplus also helps energy transition.

Heating-melting: how much energy is needed?

How do we quantify the minimum energy needed to heat materials and melt materials? This data-file calculates values, in kWh/ton, from first principles, based on target temperatures, specific heat capacities and latent heat capacities. A good rule of thumb is 25 kWh of useful energy to heat each ton of material by each 100ºC.

(1) Thermodynamics 101. Heating and melting materials requires energy, inducing particles to vibrate more (specific heat) and ultimately to break the bonds that hold them together as a solid or liquid (latent heat). By definition. 1 Joule can be defined as the specific heat energy needed to raise the temperature of 1 gram of air by 1ºC (see our note on energy units and conversions).

(2) Advanced thermodynamics. If you really want to get into the weeds, and quantify the minimum energy needed to heat, melt and vaporize different materials, you will find yourself entering the murky world of quantum physics. For example, the specific heat of different materials can be approximated using the well known Dulong-Petit Law. But different materials’ specific heat capacity values are not actually ‘constant’. They rise with temperature, as higher-energy particles suddenly gain the ability to spin in novel ways, requiring ever more complex physics, such as the Einstein photo-electron model. But we can ignore all of this for now.

(3) Heating a material makes it hotter. We all use this principle every day. For example, the “perfect bath” contains about 100L of water (or 0.1 tons) at 40ºC. If it is 15ºC outside, then this requires 25ºC of heating, at 4.2 J/gºC, or 10MJ of useful energy, aka 2.8 kWh of useful energy. This is the thermodynamic minimum useful energy. Including the losses in a boiler, the unintended heating of pipes and surroundings, a bath probably requires around 4kWh of input energy (conclusion: Europeans may need to take fewer baths in winter-2022).

(4) Industrial heat differs in that the volumes are larger and the temperatures are hotter. But a good rule of thumb is that heating each ton of material by each 100ºC requires a minimum of around 25kWh of useful energy. The numbers can vary widely, however.

(5) Melting metals is necessary before they can be forged or shaped. This is represented by the green dots in our chart above. Generally, metals have relatively low specific heat capacities, around 0.4 J/gºC. This is literally 10x less than water. It varies by metal. But this shows that for many metals, the energy intensive step may not be melting and working the metal, but smelting it in the first place. For more details, please see our metals research.

(6) Manufacturing heat examples. Calcium carbonate is thermally decomposed at 825ºC as an input to making cement. Ceramics are fired at 1,200ºC. Glass is produced at 1,500ºC. The minimum energy consumption here is 200-500kWh/ton. But the real-world numbers can be 2-5x higher again. For example, it is not enough to heat ceramics up in a kiln. You also have to keep the kiln hot for 10-20 hours. This is why we need to tackle total energy consumption of different products, case by case, across our c150 economic models.

(7) Mining efficiency. Mined materials are going to be crucial to the energy transition. But mining is energy intensive. And so this requires a focus on improving mining efficiency. You could argue therefore that flotation and leaching are two of the most important energy saving technologies in the future of the world. If you can concentrate ores before smelting or refining them, then you do not have to pointlessly heat up non-valuable co-associated rocks, which requires 400 kWh/ton to reach an average temperature of 1,350ºC.

(8) Silicon stands out for its ridiculously high energy intensity. We think that making solar PV silicon requires over 80,000 kWh/ton, and it is one of the most energy intensive materials we have ever looked at. The first step is melting sand at 1,700ºC (500 kWh/ton). Then there are multiple steps of re-crystallizing and then re-melting the silicon, as described in our note here. Some of these steps grow crystals very slowly, at 10-20 nm per minute, and thus they take 80 – 110 hours, with temperatures in the range of 600-1,100ºC.

(9) Fuels. If you consider that oil refining requires heating crude oils to 400-500ºC, this is going to eat up a minimum of 275 kWh/ton, equivalent to 2% of the energy in crude oil in the first place, which is why oil refining dominates the Scope 1&2 CO2 intensity of oil products, hammers oil’s EROEI, and could be enormously improved by emulating the mining industry with non-thermal separation technologies. Likewise, the energy needed to heat up coal to its maximum combustion temperature of 2,000ºC is around 600kWh/ton, or around 10% of the energy in coal in the first place, and this is going to hurt efficiency, especially from lower grade coals. Because of the constant removal of hot ashes, it is inherently harder to capture the heat from coal compared with the heat from gas. And finally, the ridiculously high energy footprint of steam — see below — explains the very high CO2 intensity of SAGD oil sands.

(10) Water and steam are weird. Finally, we should return to water. Water is weird. Water molecules love sticking together as a liquid. Their latent heat of evaporation is 2,250 J/g, which is 5x more than the next-closest material in our data-file. In other words, it takes 7x more energy to turn 100ºC water into steam than it took to bring 20ºC water up to 100ºC in the first place. This is also the reason that water will “boil” in a saucepan for long enough to make spaghetti carbonara, rather than suddenly vanishing into a particularly steamy kitchen. But the upshot is that turbines using water as a working fluid must work very hard to capture all of the energy from steam. In turn this underpins combined cycle gas turbines, combined heat and power, EGRs, and even next generation combustion technologies based around super-critical CO2, and next-generation nuclear using molten sodium or salt.

Further data on the energy needed to heat materials is broken down in the data-file, along with our underlying calculations.

Power grids: global investment?

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.

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