Global energy: supply-demand model?

global energy supply-demand

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 2023-30. We fear chronic under-supply if the world decarbonizes, rising to 5% shortages in 2030. Another scenario is that emerging world countries bridge the gap by ramping coal. 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 in our net zero scenario. 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 102Mbpd in 2024 (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 c220GW of new adds in 2022 to 500GW by 2030, while wind rises from c100GW of new adds in 2022 to 150GW by 2030.

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 2030, 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. Or worse, deforestation for firewood. 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…

Global energy demand: nervous breakdown?

We have attempted a detailed breakdown of global energy demand across 50 categories, to identify emerging opportunities in the energy transition, and suggesting upside to energy demand forecasts? This 12-page note sets out our conclusions and is intended as a useful reference.

Global energy demand by end use?

Breakdown of global useful energy demand across 50 categories. The largest are electric motors and residential heat, followed by steel, general manufacturing, and plastics.

This data-file is a breakdown of global energy demand by end use, drawing across our entire research library, to disaggregate the global energy system across almost 50 applications. Such as transportation, heat, electricity, materials and manufacturing. Numbers, calculations, efficiencies and heating temperatures are in the data-file.


Primary global energy demand runs at 160,000 TWH pa. Useful global energy demand (net of efficiency losses) runs at 80,000 TWH pa. Per our global energy supply models, it is relatively easy to disaggregate energy supply, by summing across oil, gas, coal, nuclear, hydro, wind and solar, biomass and other.

A breakdown of global energy demand is more challenging. But we have slowly been building up a library of economic models and supply-demand models, looking theme-by-theme, material-by-material, market by market. Hence we have attempted a full granular breakdown of global energy demand by end use here.

As simple rules of thumb, electricity generation absorbs almost 40% of primary energy, heat is 30%, transportation is almost 25%, and 10% is feedstocks for materials. However, some of the categories overlap. Materials and manufacturing absorb c35% of global primary energy to make 60GTpa of stuff, drawing upon electricity, heat and feedstocks.

A breakdown of primary global energy demand by category is plotted below. The largest categories are electric motors (15%), passenger cars (13%), residential heat (10%), manufacturing processes (6%) and other electrical appliances (5%). Although note that this is also because these are some of the broadest categories in the data-file.

The database of global energy demand also allows us to quantify the most and least efficient value chains. For example, passenger cars comprise c13% of global primary energy in the chart above but only c5% of global useful energy, due to the relatively low efficiency in internal combustion engines. Conversely, residential heat is highly efficient, comprising c10% of primary energy above but 13% of useful energy.

The breakdown of global energy demand by end use also allows us to disaggregate global heat, which comprises 30% of primary global energy. 50% is used residentially or commercially at temperatures below <100◦C. Conversely, at the other end of the spectrum, 20% is ultra-hot industrial heat >1,000◦C (chart below).

Breakdown of total global heat demand by temperature and category. Residential heat is low temperature but makes up a large fraction of total demand. Materials production requires temperatures up to a few thousand Celsius.

The full data-file includes estimates of global energy demand across almost fifty end uses: agriculture, air conditioning, air separation, aluminium, ammonia, asphalt, aviation, bleach, buses, cement, chlor-alkali, coal production, commercial heat, cooking, copper, desalination, electric motors, electrical appliances, glass, graphite, heavy trucks, hydrogen, industrial acids, internet, lighting, lithium batteries, LNG liquefaction, manufacturing, methanol, oil & gas E&P, oil refining, other metals, paper & pulp, passenger cars, pipelines, plastics, polysilicon, refrigeration, residential heat, shipping, solar modules, steel, trains, transmission, two-wheelers and wind turbines.

India: electricity demand and power grid over time?

India’s electricity demand is growing by 6-8% per year (+100-140 TWH per annum). But 75% of India’s power still comes from coal, which has itself grown at a 5% CAGR over the past half-decade, and by +9% YoY in 2023. Wind and solar would need to grow 4x faster than 2023 levels for thermal generation to flatline. What do India electricity demand data mean for global energy markets?


India is now the largest country in the world by population, with 1.4bn people (18% of the global total), $3.5 trn of GDP, and GDP per capita of $2,500 pp pa. However, India only uses 6% of total global energy, 6% of total global electricity and emits 6% of global CO2. What implications for energy markets and energy transition as India grows? And could India’s energy demand move global energy markets in the late 2020s as China’s moved global energy markets in the mid-2000s?

This data-file has tabulated, cleaned and estimated India’s electricity demand data, and power grid capacity data, monthly, by generation source, back to 2015, using data from India’s Ministry of Power.

We think emerging world countries are going to prioritize energy security over energy shortages, as discussed in our outlook for 2024. And the data from India seem to support this conclusion, strengthening the conclusions published in the original note.

Electricity consumption in India grew by 8% in 2023, rising +120 TWH YoY, to surpass 1,700 TWH. The growth rate exceeded its trailing 5-year rate of +6% pa, but slowed from 2021-22 levels (chart below).

75% of India’s total power generation comes from combusting coal, which is even higher than China’s 60% share for coal in China’s power mix. Coal-fired power generation in India grew by 9% YoY in 2023, exceeding a trailing 5-year growth rate of 5% per annum (chart below).

Russia’s invasion of Ukraine has not helped, as Europe’s sudden thirst for LNG has pulled gas away from emerging world geographies. India’s total gas-fired power generation in 2023 was 40% lower than in 2019, which has required ramping up coal instead.

India’s total power grid has grown by 15GW per annum over the past half decade, of which 10 GW pa has been from solar (at an average availability factor below 20%), while 3GW pa has been from coal (at an average availability factor of 60%). This implies that new capacity additions have added solar and coal-fired electricity in equal proportions.

But the shift to coal is higher, as the utilization rates of coal plants also stepped up from 53% in 2019 to 68% in 2023. Thus coal fired generation has grown at a 1.5% pa CAGR over the past five years. If anything, high utilization rates at existing coal plants may augur for a step-up in construction for coal-fired generators, per our coal outlook. Mathematically, wind and solar would need to be growing 4x faster than in 2023 to have kept total thermal generation flat.

Another opportunity to improve CO2 credentials in India’s power grid would be strengthening the efficiency of transmission and distribution, where losses are estimated as high as 20% of electricity that is generated, or 3x higher than in the developed world. Some of this is due to climate, as power losses are amplified in hot and wet conditions, as covered in our overview of power transmission.

A final stand-out feature of India’s power grid is extreme seasonality. Hydro availability is 20% in the dry season (December-January) but exceeds 50% after the monsoon season (August-September). Wind’s availability profile is similar (chart below). While the call on thermal generation is highest in December-January.

Wind and solar availability also vary +/- 3-6% each year, hence demand for backups, as per broader energy markets, will be volatile.

This data-file has tabulated, cleaned and estimated India electricity demand data, and power grid capacity, monthly, by generation source, back to 2015, using data from India’s Ministry of Power. Please download the data for granularity on the numbers.

Peak commodities: everything, everywhere, all at once?

Commodities needed for energy transition

This 15-page note evaluates 10 commodity disruptions since the Stone Age. Peak demand for commodities is just possible, in total tonnage terms, as part of the energy transition. But it is historically unprecedented. And our plateau in tonnage terms is a doubling in value terms, a kingmaker for gas and materials. 30 major commodities are reviewed.

MOSFETs: energy use and power loss calculator?

MOSFETs are fast-acting digital switches, used to transform electricity, across new energies and digital devices. MOSFET power losses are built up from first principles in this data-file, averaging 2% per MOSFET, with a range of 1-10% depending on voltage, switching, on resistance, operating temperature and reverse recovery charges.


MOSFETs and other power transistors matter, as they are the basis for solar inverters, wind converters, electric vehicle traction inverters, AC-DC rectifiers, other DC-DC converters, the power supplies to data-servers, AI and other digital devices.

Transistors are digital switches made of semiconductor materials, which allow one circuit to control another. Our overview of semiconductors explains how a transistor works, from first principles, by depicting a bipolar junction transistor (BJT), which is driven by current.

However, it is better to control a transistor using voltage than current. Ambient electrical fields induce currents that can cause current-driven transistors to misfire. Hence MOSFETs and IGBTs are driven by voltage.

MOSFETs were invented at Bell Labs in 1959 and are now the most used power semiconductor device in the world. Something like 2 x 10^22 transistors have been produced across human history by 2023.

MOSFETs: how do they work?

We are sorry to say it, but it is simply not possible to understand how a MOSFET works, without a basic understanding of voltage, current, conduction band electrons, valence band holes, N-type semiconductor, P-type semiconductor and Fermi Levels. Do not despair! To help decision-makers understand these concepts, we have written an overview of semiconductors and an overview of electricity.

MOSFET stands for Metal Oxide Semiconductor Field Effect Transistor. Actually this is something of a misnomer. The eponymous ‘metal oxide’ is referring to an oxide of silicon metal, or in other words, a highly pure layer of silicon dioxide. It is oxidized to create an insulating layer. In turn, the reason for creating this insulating layer is so that a Field Effect can be induced by a potential difference (voltage) across the gate.

Why can’t current flow through a MOSFET in the off-state? A simplified diagram of an N-channel enhancement MOSFET is shown below. Ordinarily, electrons cannot flow from the source to the drain, due to the PN junction between the body and the drain, which is effectively a reverse-biased diode. A negative voltage at source draws in the mobile holes from the P-type semiconductor. A positive voltage at the drain attracts the mobile electrons in the N-type layer. And this creates a depletion zone where no current can flow, just like in any other diode.

How can current flow through a MOSFET in the on-state? The ‘Field Effect’ occurs when a positive voltage is applied to the gate, raising the Fermi level of the P-type semiconductor. Remember the Fermi Level is the energy level likely to be exceeded by 50% of electrons. A large enough voltage raises the Fermi Level above the lower bound of the conduction band. Suddenly there is a sea of mobile electrons, forming an N-channel, so that electrons can flow from source to drain.

What power losses in a MOSFET?

Resistive losses occur when a current flows through a semiconductor, proportional to the on-resistance of the semiconductor, and a square function of the current. The on resistance of different MOSFETs is typically in the range of 0.1-0.6 Ohms, at power ratings of 1-20kW, based on data-sheets from leading manufacturer, Infineon (as profiled in our screen of SiC and MOSFET companies).

Hence a better depiction of an N-channel enhancement MOFSET follows below. In the chart above, the N-channel through the P-layer is very long and thin, which is going to result in high resistance. Hence in the chart below, the NPN junction is slim-lined, and the on resistance from source to drain is going to be lower, which helps efficiency.

Raising voltage is also going to reduce I2R conduction losses, because less current is flowing. However, voltage is limited by a MOSFET’s breakdown voltage. Above this level, the PN junction will fail to block the flow from source to drain, and the MOSFET will be destroyed (avalanche breakdown). The voltage ratings of different MOSFETs are tabulated in our data-file. A clear advantage for silicon carbide power MOSFETs is their higher breakdown voltage, which allows them to be operated at higher voltages across the board, reducing conductive losses.

Switching losses are also incurred whenever a MOSFET turns on or off. When the MOSFET is off, there is a large potential difference (voltage) between the source and the drain. When the MOSFET turns on, current flows in while the voltage is still high, which dissipates power. And then the voltage falls when current flow is high, which dissipates power. The same effect happens in reverse when the MOSFET is switched off. These losses add up, as the pulse width modulation in an inverter will often exceed 20kHz frequency. And the latest computer chips run with a clock speed in the GHz. Minimizing switching losses is the rationale for soft switching, being progressed by companies such as Hillcrest.

Hillcrest Technology Review

A reverse recovery loss is also incurred by a MOSFET, because every time the MOSFET switches on, the body diode needs to be inverted from reverse bias to forward bias. This physically requires moving charge carriers, or in other words, requires flowing a current. The reverse recovery loss can often be the largest single loss on a MOSFET.

Transistors: IGBTs vs MOSFETs?

IGBTs stand for Integrated Gate Bipolar Transistors, which is another transistor design that has been heavily used in solar, wind, electric vehicles and other new energies applications.

An IGBT is effectively a MOSFET coupled with a Bipolar Junction Transistor, to improve the current controlling ability.

IGBTs are generally more expensive than MOSFETs, and can handle higher currents at lower losses. However when switching speeds are high (above 20kHz), MOSFETs have lower losses than IGBTs, because IGBTs have slow turn off speeds with higher tail currents.

Finally, in the past, it was suggested that IGBTs performed better than MOFSETs above breakdown voltages of 400V, although this is now more nuanced, as there are many high-performance MOSFETs with voltages in the range of 600-2,000 V.

The very highest voltage IGBTs and MOSFET modules we have seen are in the range of 6-12 kV. This explains why so much of new energies requires generating at low-medium voltage then using transformers to step up the power for transmission; or conversely using transformers to step down the voltage for manipulation via power electronics modules.

Formulae for the losses in a power MOSFET?

This data-file aims to calculate the power losses of a power MOSFET from first principles, covering I2R conduction losses, voltage drops across the diode, switching losses and reverse recovery losses, so that important numbers can be stress tested.

Generally, the losses through a MOSFET will range from 1-10%, with a base case of 2% per MOSFET. These numbers consist of conduction losses, voltage drops across the diode layer, switching losses and reverse recovery charges.

Losses add. Many circuit designs contain multiple MOSFETs, or layers of MOSFETs and IGBTs (example below). Roughly, flowing power through 6 MOSFETs, each at c2% losses, explains why the EV fast-charging topology depicted below might have losses in the range of 10-20%.

Power losses in a MOSFET rise as a function of higher switching speeds, as calculated in the data-file, shown in the chart below, and for the reasons stated above. High switching speeds produce a higher quality power signal, but are also more energetically demanding.

Power losses in a MOSFET fall as a function of Voltage, as calculated in the data-file, shown in the chart below, and for the reasons stated above. Although lower voltage MOSFETs face less electrically demanding conditions and are less expensive.

Overall, our model is intended as a simple, 30-line calculator to compute the likely power flow, electricity use and losses in a MOSFET. This should enable decision makers to ballpark the loss rates of MOSFETs, and power electronic devices containing them.

However, interaction effects are severe. Drain current, breakdown voltage, gate voltage, temperature, on resistance, reverse recovery charges and all of the switching times depend on one-another. Hence for specific engineering of MOSFETs it is better to consult data-sheets.

Semiconductor manufacturers also stood out in our recent review of market concentration versus operating margins.

Jevons Paradox: what evidence for energy savings?

Using a commodity more efficiently can cause its demand to rise not fall, as greater efficiency opens up unforeseen possibilities. This is Jevons’ Paradox. Our 16-page report finds it is more prevalent than we expected. Efficiency gains underpin 25% of our roadmap to net zero. To be effective, commodity prices must also rise and remain high, otherwise rebound effects will raise demand.

Average home sizes: living space per person?

Average home sizes

Average home sizes matter for overall residential energy demand, heating and cooling demand. Hence the purpose of this data-file is to aggregate average home sizes by country, then translate the data into living space per capita. A good rule of thumb is that each $1k pp pa of GDP translates one-for-one into 1m2 pp pa of useful living space. The trend towards ever larger homes challenges the notion of peak energy demand?


On a global average basis, the average home is 70m2 in size and shared between 3.5 inhabitants, which equates to an average of 20m2 of living space per capita.

There is a direct linear relationship between income per capita and living space per capita. A good rule of thumb is that each $1k of GDP per capita equates to 1m2 per capita of living space.

In wealthy countries, the average home is 130-200m2 in size, shared between 2-2.5 people, for an average of 60-80m2 of living space per person, which is 3x the global average. This is large, but still not that large. A mansion is 800m2 and above. The largest houses in the US are catalogued here. And the largest house in the world, belonging to the Sultan of Brunei, is 200,000m2.

In the least wealthy countries, the average home is 20-40m2 in size, shared between 3-5 people, and thus living space per capita is 5-10m2, 50-75% below the global average. This is staggeringly low. For example, a recent press article highlighted that the average living space per capita in a dwelling in India is “less than the recommended size of a prison cell”.

Average home sizes have been increasing in substantively every country we surveyed. For example, the average new single-family home being built in the United States in 2022 is 223 m2, up 45% since 1980, up 2.5x since 1900. Household sizes have fallen from 4.8 people in 1900 to 2.5 people in 2022. Hence overall, total living space per American in these newly built homes has risen by 60% since 1980 and 5x since 1900 (charts below).

Average home sizes
US average home sizes have risen 2.5x since 1900 and space per household member has risen 5x

In my adopted homeland of Estonia, I have also seen my fair share of boxy 30-40m2 concrete monstrosities, dating back to the fifty year period of Soviet occupation. No one really wants to live in them. The average size of a new dwelling constructed in 2023 has jumped to 83 square meters.

Urbanization patterns are another driver of average home sizes. A typical urban apartment is about half the size of a typical ‘house’. However another demographic trend is that wealthier urbanites tend to move out of apartments and ‘out into the suburbs’ which also adds energy demand in the form of commuting.

Overall we think that rising home sizes are another example of a rebound effect severely challenging the idea of ‘peak energy demand’. Improved living standards, building materials, efficiency, insulation, heating and cooling, will almost invariably result in people choosing to live in larger houses, which in turn consume more energy.

The data in this file are the best aggregation we could find from technical papers, national records, internet searches, and data-based triangulation. As far as we are aware, there is no aggregated source of home sizes released by global statistical agencies.

Countries covered in the data-file include Argentina, Australia, Bangladesh, Bolivia, Brazil, Canada, China, Colombia, Congo, Denmark, Egypt, Estonia, Finland, France, Germany, Greece, Hong Kong, India, Indonesia, Italy, Japan, Korea, Mexico, Netherlands, New Zealand, Nigeria, Norway, Poland, Portugal, Romania, Russia, South Africa, Spain, Sweden, the United Kingdom, the United States and Vietnam.

Residential energy consumption over time?

US residential energy consumption runs at 3,000 MWH per annum, equivalent to one quarter of total US energy consumption. Total demand has run sideways since 1980 as rebound effects and new demand sources have offset underlying efficiency savings?


This data-file compiles a time-series of US residential energy consumption over time, based on periodic surveys conducted every 3-7 years by the US EIA.

US residential energy consumption is around 3,000 MWH per annum, equivalent to 9 MWH per person per year, up on 1980 in absolute terms, but down 30% since 1980 in per capita terms.

US residential electricity consumption has increased from 3 MWH pp pa in 1982 to 4 MWH pp pa in 2022.

Efficiency gains are visible in categories such as refrigeration, where electricity consumption has fallen from 0.7 MWH pp pa in 1982 to 0.3 MWH pp pa in 2022.

On the other hand, new categories of demand, such as air conditioning and other appliances, have more than offset the efficiency improvements in individual devices such as refrigerators.

Heating demand for houses has halved from 120 kWh per m2 of living space per annum in 1980 to 60 kWh per m2 of living space per annum in 2022, due to improving insulation.

However, rebound effects are also visible in this category, as new single-family homes have become 60% larger over the same timeframe.

Finally, the data-file contrasts residential electricity consumption in the US versus other geographies. Statistically, a hot tub in the Alps consumes more electricity per annum than an African village of 40 people.

Data are aggregated in the Excel file as a useful reference running back to 1980. For more, please see our research into rebound effects and Jevons Paradox and our overall US energy supply demand model.

LEDs: seeing the light?

Outlook for LEDs

Lighting is 2% of global energy, 6% of electricity, 25% of buildings’ energy. LEDs are 2-20x more efficient than alternatives. Hence this 16-page report is our outlook for LEDs in the energy transition. We think LED market share doubles to c100% in the 2030s, to save energy, especially in solar-heavy grids. But demand is also rising due to ‘rebound effects’ and use in digital devices. We have screened 20 mature and (mostly) profitable pure plays.

Copyright: Thunder Said Energy, 2019-2024.