Power grid research for Energy Transition

Power grids: opportunities in the energy transition?

power grid opportunities in the energy transition

This article summarizes our conclusions into power grids and power electronics, across all of Thunder Said Energy’s research. Where are the best power grid opportunities in the energy transition?

Power grids move electricity from the point of generation to the point of use, while aiming to maximize power quality, minimize costs and minimize losses. Broadly defined, global power grids and power electronics investment must step up 5x in the energy transition, from $750bn pa to over $3.5trn pa. This theme gets woefully overlooked. This also means it offers up some of the best opportunities in the energy transition.

(1) Electrification is going to be a major theme in the energy transition, a mega-trend of the 21st century, as the efficiency and controllability of electrified technology is usually 3-5x higher than comparable heat engines. It is analogous to the shift from analogue to digital. 40% of the world’s useful energy is consumed as electricity today, rising to 60% by 2050 (note here — our best overview of the upside in grids) propelling the efficiency of the primary global energy system from 45% today to 60% by 2050 (note here). Power demands of a typical home will also double from 10kW to 20kW in the energy transition (data here). Electricity demands of industrial facilities are aggregated here.

(2) Electricity basics are often misunderstood? If we have one salty observation about power markets, it is that many commentators seem to love making sweeping statements without understanding much at all. It is the energy market equivalent of wandering in off the street to an operating theater, and without any medical training at all, simply picking up a scalpel. This is a little bit sad. But it also means there will be opportunities for decision makers that do understand electricity and power systems. As a place to start, our primer on power, voltage, current, AC, DC, inertia and power quality is here.

(3) Power generation costs 5-15c/kWh. But variations within each category are much wider than between category (note here). So generation will not be a winner takes all market, where one “energy source to rule them all” pushes out all the others. This view comes from stress testing IRR models of wind, solar, hydro, nuclear, gas, coal, biomass, diesel gensets and geothermal. And from 400-years of energy history. The average sizes of power generation facilities are here, and typical ramp rates are here.

(4) Transmission is becoming the key bottleneck on renewables and electrification in the energy transition. Each TWH pa of global electricity demand is supported by 275km of power transmission and 4,000km of distribution (data here). Connecting a new project to the grid usually costs $100-300/kW over 10-70km tie-in distances (data here). But bottlenecks are growing. The approval times to connect a new power plant to the grid have already increased 2.5x since the mid-2000s, averaging 3-years, especially for wind and solar, which take 30% and 10% longer than average (data here). Avoiding these bottlenecks requires power grids to expand. Spending on power grids alone will rise from $300bn pa to over $1.2trn pa, which is actually larger than the spending on all primary energy production today (data here).

(5) Power transmission also beats batteries as a way of maximizing renewable penetration in future grids. Rather than overcoming intermittency — solar output across Europe is 60-90% inter-correlated, wind output is 50-90% inter-correlated — by moving power across time, you can solve the same challenge by moving them over a wider space. A key advantage is that a large and extensive power grid smooths all forms of renewables volatility, from a typical facility’s 100 x sub-10-second power drops per day to the +/- 6% annual variations in solar insolation reaching a particular point of the globe. By contrast, different batteries tend to be optimized for a specific time-duration, while at long durations, the economics become practically unworkable. A new transmission line usually costs 2-3c/kWh per 1,000km (model here). Additional benefits for expanded power grids accrue in power quality, reliability and resiliency against extreme weather. These benefits will be spelled out further below…

(6) Upside for transmission utilities and suppliers? Our overview of how power transmission works is here. Operating data for high voltage transmission cables are here. Leading US transmission and distribution utilities are screened here. Leading companies in HVDCs are here. Offshore cable lay vessels are screened here. We have also screened Prysmian patents here. But the opportunity space is also much broader, which becomes visible by delving into how power grids work…

(7) Cabling materials. As a general rule, overhead power lines are made of aluminium, due to its light weight and high strength. Conversely, HVDC cables and household wiring are made of copper, which is more conductive. HVDCs are also encased in specialized plastics. New power transmission lines add 3-5MTpa of demand to aluminium markets, or 5-7% upside (note here). But we are more worried about bottlenecks in copper (where total global demand trebles) and silver.

(8) Transformers and specialized switchgear are needed to step the voltage up or down to a precise and prescribed level at every inter-connection point in the grid. The US transmission network operates at a median voltage of 230kV, which keeps losses to around 7%. Energy transition could double the transformer market in capacity terms and increase it by 30x in unit count (note here, costs and companies screened here), surpassing $50bn pa by 2035. Downstream of these transformers, the power entering industrial and commercial facilities will often remain at several kV, which requires specialized switchgear to prevent arcing. We see the MV switchgear market trebling to over $100bn pa by 2035.

(9) AC and DC. Wind and solar inherently produce DC power, but most transmission lines are AC. Hence they must be coupled with inverters and converters. At the ultimate point of use, AC power also usually needs to be rectified back to DC and bucked/boosted to the right voltage for each machine or appliance. The same goes for EV charging and EV drive trains. DC-DC conversion, AC-DC rectification and DC-AC inversion are effectively consolidating around MOSFETs. And we think one of the most interesting incremental jolts for the energy transition is the 1-10pp higher efficiency and rising market share of SiC MOSFETs. Leading companies in SiC and MOSFETs are screened here.

(10) Inertia and frequency regulation. All of the AC power generators in the grid are running in lockstep, ‘synchronized’ at around 50 Hertz in Europe and 60 Hz in the US. But the frequency of all the power generators in the grid changes second by second. If there is a slight under-supply of power, then what prevents the grid from collapsing is that energy can be harvested from the rotational energy of massive turbines weighing up to 4,000 tons and spinning at 1,500 – 6,000 rpm, as they all slow down very slightly. This sorcery is called ‘inertia’. Wind and solar do not inherently have any inertia (no synchronized spinning). But there are ways of partially mimicking inertia or adding synthetic inertia to the grid through flywheels, supercapacitors, synchronous condensers, batteries, smart energy. Our grid models reflect growing demand for infrastructure in all of these categories.

(11) Reactive power compensation. Apparent power (in kVA) consists of two components: real power (in kW) and reactive power (in kVAR). Inductive loads consume reactive power as the creation of magnetic fields draws the current behind the voltage in an AC wave. This lowers power factor in the grid, amplifies the current that must flow per unit of real power, and thus amplifies I2R losses. Large spinning generators have historically provided reactive power to energize transmission lines and compensate for inductive loads. Again, wind and solar do not inherently provide reactive power compensation and have historically leaned on the rotating generators. Renewable heavy grids will need to add reactive power compensation, expanding this market by a factor of 30x. The best opportunities are in STATCOMs and SVCs (leading companies screened here), capacitor banks at industrial facilities and Volt-VAR optimization at the grid edge.

(12) Electric vehicle charging: find the shovel-makers? Each 1,000 EVs will likely require 40 Level 2 chargers (30-40kW) and 3 Level 3 fast-chargers (100-200kW), so our numbers ultimately have $100bn pa being spent on EV charging in 2025-50. But we wonder whether EV chargers will ultimately become over-built, and the best opportunities will be in supplying components and materials to these chargers, rather than owning the infrastructure itself. Our best single note on this topic is here. Economics of EV charging stations and conventional fuel retail stations make a nice comparison.

(13) Motor drivers are another huge efficiency opportunity. There are 50bn electric motors in the world, consuming half of all global electricity. But most motors are inefficient, rotating at fixed speeds determined by the frequency of the AC power grid, rotating faster than they need to, which matters as power consumption is a cube function of rotating speed. One of the best efficiency opportunities in the grid expands the role of variable frequency drives to optimize motors (note here). Economics are screened here and leading companies are covered here. All of our work into electric motor efficiency and reliability is linked here.

(14) Without reliable and high-quality power grids, frankly, things will break. This is a statement made in patents and technical papers, again and again, discussing how lagging power quality enhances maintenance and breakage costs of expensive equipment. Fundamentally, this is why we think that commercial and industrial power consumers will increasingly invest more in power electronics, and there are so many hidden power grid opportunities in the energy transition.

(15) Power electronics is the broad category of capital goods that encompasses effectively everything discussed on this page. And this summary has hardly even scratched the surface. We think pure power electronics spending trebles from $300bn pa to $1trn pa by 2035 (model here). It is the same group of companies coming up again and again in this space (best note here). For example, we have attempted to break down Eaton’s revenues across 10,000 SKUs in 200 different categories here. We do think that the complexity in power grids and power electronics creates opportunity for decision makers that can grasp it.

All of our research — PDF research reports, data-files, economic models and company screens — into power grid opportunities in the energy transition is summarized below, in chronological order of publication.

Power grids: down to the wire?

Power grid circuit kilometers need to rise 3-5x in the energy transition. This trend directly tightens global aluminium markets by over c20%, and global copper markets by c15%. Slow recent progress may lead to bottlenecks, then a boom? This 12-page note quantifies the rising demand for circuit kilometers, grid infrastructure, underlying metals and who benefits?

Global electricity prices vs. CO2 intensities?

This data-file compares electricity prices (in c/kWh) vs power grids’ CO2 intensities (in kg/kWh), country-by-country. Retail electricity prices average 11c/kWh globally, of which 50-60% is wholesale power generation, 25-35% is transmission and 10-20% covers other administrative costs of utilities. The CO2 intensity of the global average power grid is 0.45 kg/kWh. Variations are wide. And there is a -35% correlation between electricity prices vs CO2 intensities in different countries globally.

Electricity Prices and CO2 Intensity Data

Retail electricity prices average 11c/kWh globally, across 28,500 TWH of global electricity demand in 2021, which is mostly composed of electricity consumption in 80 larger countries. The lower quartile is 7c/kWh and the upper quartile is 17c/kWh. The lower decile is 4c/kWh and the upper decile is 22c/kWh.

Some countries and regions do report retail, commercial and industrial electricity prices, such as the US EIA, Eurostat, or gov.uk, And we have aggregated some useful indices in our data-file. However, we think there are also data-challenges here.

Data challenges. Electricity prices are a minefield because they vary region-by-region within each country. They can also increasingly vary season-by-season, day-by-day or hour-by-hour. Prices for residential and commercial customers are usually around 2x higher than industrial customers. Tax regimes differ. There is often a ‘fixed charge’ plus a ‘variable tariff’, which means that total costs fall as usage rises. And finally, the end cost paid by consumers often reflects other variables such as their specific location and power factors.

We think the best data sources for electricity prices globally are therefore found via the tariffs actually charged to end customers. There are numerous price comparison websites that aggregate the data. For example, cable.co.uk is an excellent resource, comparing prices by country.

Good data on the CO2 intensity of different grids can also be found from sources such as Our World in Data. We have calculated CO2 intensity of different power grids directly, in other work, but for our cross-plot above, we want to avoid being accused of manipulating the data-sets, so we will take the average numbers from this independent resource. The average electricity generation globally has a CO2 intensity of 0.45 kg/kWh, with a lower quartile of 0.21 kg/kWh and upper quartile of 0.51 kg/kWh.

Correlation between electricity prices vs CO2 intensities?

Across our entire data-set, there is -35% correlation between retail electricity prices in different countries and their CO2 intensities. However, the correlation jumps to -50% if we exclude certain outliers.

Hydro-heavy countries. The global average is that 15% of all electricity in 2021 was generated from hydro. But four countries are unusual, because they generate the majority of their electricity from hydro, which has almost no embedded CO2 intensity. They are Norway (91% hydro), Canada (59%), Brazil (55%) and Sweden (45%). Electricity prices in these countries are just below the global average. Thus if we strip out these four countries from the analysis, then the correlation coefficient is -39%.

Nuclear-heavy countries. The global average is that 10% of all electricity in 2021 was generated from nuclear. But three countries are unusual, because they generate the majority of their electricity from nuclear, which has almost no embedded CO2 intensity. They are France (69%), Ukraine (55%) and Slovakia (52%). Remove these three countries as well, and the correlation coefficient is -41%.

Oil-heavy islands. Many islanded grids lack the size and scale for conventional power infrastructure, and thus rely heavily on diesel generators, with high costs above 20c/kWh and high CO2 intensity of 0.6 kg/kWh (data-file here). If we also exclude Caribbean Islands from our cross-plot, then the correlation coefficient is -45%.

Germany is another outlier on the chart. Its grid has the same CO2 intensity as Russia’s or Pakistan’s, yet its retail electricity prices are 5-7x higher. Or stated another way, Germany’s retail electricity prices are similar to Denmark’s — a nation that famously has the highest electricity prices at around 35c/kWh and the highest share of wind power of any country in the world at c50% — yet Germany’s CO2 intensity is over 2x higher. Remove Germany from our cross-plot, and the correlation coefficient is -46%.

Conclusions: what do the data mean?

We want to draw out important conclusions from our data-set. But we also want to do this objectively. There is no agenda. We are simply trying to interpret data here.

Our first interpretation is a simple rule-of-thumb. Energy prices get cheaper when countries invest in low-cost resources, especially domestic resources; while energy prices inflate when they cannot, or do not.

For example, the countries with the lowest cost electricity in the world, which is often below 6c/kWh on a fully-loaded retail basis, include OPEC countries running oil-heavy grids (e.g., Saudi Arabia, Kuwait, Libya), gas-rich countries running gas-heavy grids (Qatar, Russia, Algeria, Kazakhstan), and coal-rich countries running coal-heavy grids (e.g., Poland, South Africa).

Conversely, countries with the most expensive electricity seem to lack low-cost domestic resources, are highly reliant upon imports, or worse, have historically shut down low-cost domestic resources, and failed to invest enough in energy infrastructure.

Resist over-simplification. We often hear over-generalizations in energy, as though there will ultimately emerge “one energy source to rule them all”. This seems unlikely. The most economical energy sources very often depend upon context (note here).

Another interpretation is that countries with larger, more complex and more diversified energy systems tend to have higher electricity costs than countries that focus on simple domestic resources. This might seem surprising. But consider how ‘rate of return regulation’ works in the utility industry (note here). Consumers clearly have to pay more when a utility is earning 10% statutory returns on a large and low-utilization asset base, compared to a small and high-utilization asset base (power grid research here).

Generation opportunities? Generally, as global electricity prices are high, and there is reason to fear they may rise even further, some decision-makers may be increasingly interested in energy generation, or even self-generation to meet their own demand needs. This may augur favorable for rooftop solar, gas turbines, CHPs, storage or diesel gen-sets.

These interpretations also present a challenge in the energy transition, which is that price-sensitive countries may choose not to shut down low-cost but high-carbon domestic resources (coal deep-dive here). Hence, in turn, we expect more border tax adjustments to be introduced from countries seeking to encourage global decarbonization (note here).

We also remain worried about under-investment in energy (note here), resultant leakage of industrial activity to geographies with low energy prices (note here), or even outright backsliding in countries where energy prices become overly expensive (note here).

Our research remains focused on the best opportunities to achieve an energy transition. The best antidote to the challenges above will be if new technologies can lower the costs and expedite the deployment of wind, solar, power grids, efficiency, CCS and nature based solutions.

Power cuts: how frequent are grid disruptions?

Are US power cuts becoming more frequent data by disruption cause and duration

This data-file aggregates significant US power grid disruptions, based on data from the DOE. On average, there are 250 power cuts per year in the United States, lasting for a median average of 5-hours, and affecting a median average of 80,000 customers. 20% of the power cuts last longer than 1-day. 15% affect more than 1M customers. What implications?

Power grids are a wonder of the modern world, and crucial enabler of the energy transition (TSE overview here). But how reliable are power grids? To answer this question, we have aggregated and cleaned-up data into 3,000 significant power disruptions, from the US Department of Energy.

How frequent are power cuts? The United States incurs an average of 250 power cuts per year, each impacting an average of 80,000 customers, for an average of 5-hours. Note that a “customer” can range from a studio apartment to a 400-bed hospital, but our guess from the data is that c20% of the US population endures a serious power cut each year.

What are the causes of power cuts? Over the past decade, 40% of US power cuts can primarily be attributed to weather events, such as storms or heatwaves, 35% can be attributed to physical incidents, vandalism or sabotage, and 25% can be attributed to failure of grid infrastructure itself.

Different outages have different characteristics. The median sabotage event impacts 2,000 customers and is remedied within 1-hour. The median average grid failure impacts 20,000 customers and is remedied within 2-hours. The median average weather issue impacts 90,000 customers and is remedied within 1-day.

The worst power cuts can occur in the aftermath of major weather events such as hurricanes, leaving “millions” of customers without power for 5-30 days. The database contains 27 power cuts (i.e., >2 per year) that impact more than 1M customers, and 97 that last longer than 5-days (i.e., 8 per year). The impacts of such power cuts have been poignantly dramatized in Apple TV’s recent series Five Days at Memorial.

Seasonality also contributes. There are 30% more disruptions than average in August, which is prone to heatwaves and hurricanes, and 13% more than average in February, which is prone to winter storms. Conversely, there are 30% fewer disruptions than average in November, amidst mild autumn weather.

Are US power cuts becoming increasingly prevalent? The DOE’s power grid disruption database saw a trough of 141 incidents in 2016, rising to a new peak of 390 incidents in 2022. This is all the more remarkable because 2022 was a year with fewer weather-related disruptions than average.

What is causing the uptick in power grid disruptions? Grid disruptions attributed to the grid itself (i.e., not directly caused by weather or physical incidents) have increased from 36 incidents per year in 2012-17 through to 125 per year in 2020-22 (below).

Implications? This suggests increasing investment is needed in power grid infrastructure, and possible upside for transmission utilities and companies constructing power transmission. It may also create rising demand for backup solutions, from batteries to CHPs to diesel generators. Finally it illustrates the need for smart grid and power electronics technologies.

Our cleaned-up interpretation of the raw data, some analytics, averages, and charts are available in the data-file. Our best ideas in power grids are linked here.

Diesel power generation: levelized costs?

Levelized costs of diesel power generation

A multi-MW scale diesel generator requires an effective power price of 20c/kWh, in order to earn a 10% IRR, on c$700/kW capex, assuming $70 oil prices and c150km trucking of oil products to the facility. Levelized costs of diesel power generation can be stress-tested in this economic model.

A diesel genset includes an engine, power generator, switchgear, control systems, fuel supply systems, coolant and lubrication systems, a foundation, powerhouse civil works and wiring towards the connected load.

In the fuel cycle, air is drawn into the cylinder, compressed by 14-25x so its temperature reaches 700-900ºC, then a metered quantity of injected diesel spontaneously ignites, which provides the power to turn a rotating shaft, usually at 1,500-3,000 rpm (gas comparison here).

Total CO2 intensity is 0.6 kg/kWh for a diesel generator, at 40% average electrical efficiency, and including Scope 1, Scope 2 and Scope 3. This creates a rationale for expanding power grids and hybridizing diesel generation with solar and wind.

Some sensitivities are that each $10/bbl on the oil price translates into a 2c/kWh variation in power costs. For remote locations, each 100km of trucking distance adds another 0.2 c/kWh to the power price.

Capex costs can vary +/- 50%, especially depending on the emissions clean-up downstream of the generator (e.g., Diesel generators tend to be Tier 4, which emit 94% less NOx and 91% less particulate than Tier 2).

Another context where diesel generators are used is as a back-up power solution. Federal regulations require critical infrastructure, such as hospitals, care homes, airports, to have backup generators with 48-96 hours of fuel supplies. While facilities with risks of product spoilage might also have on-site generators to protect against grid failures, hence a typical super-market maintains a 250kW generator with 36 hours of fuel. When regulators talk of banning fossil fuels, it is not entirely clear what alternative is envisaged for these contexts.

The effective power price can be calculated for back-up generation systems, and might translate into around 100-200 c/kWh, depending on how frequently they are used. Although strictly, back-up generators exist to avoid much larger costs associated with power failures, rather than connoting a general willingness to pay 100-200c/kWh for electricity.

Companies with leading market share in diesel generators include Caterpillar, Generac, Cummins, Atlas Copco, AKSA, Aggreko.

Please download the economic model, to stress test the levelized costs of diesel power generation. The model allows for some easy flexing of power prices (c/kWh), capex costs ($/kW), oil prices ($/bbl), delivered diesel costs ($/gal), O&M costs ($/kW/yr) and CO2 prices ($/ton).

Power grids: transmission and distribution kilometers by country?

This data-file aggregates power transmission and distribution kilometers by country, across 30 key countries, which comprise 80% of global electricity use. In 2023, the world contains 7M circuit kilometers of power transmission lines and 110M kilometers of power distribution lines. Useful rules of thumb follow below.

What are circuit kilometers? One ‘network kilometer’ of power transmission lines may carry one circuit kilometer, two circuit kilometers or sometimes (rarely) three circuit kilometers, suspended from the same towers. In turn, each circuit kilometer may contain two large conductors (e.g., an HVDC), three conductors (3-phase AC) or sometimes (rarely) six conductors where the 3-phase AC is disaggregated to promote transmission efficiency. This makes the ‘length’ of a transmission line a somewhat debatable concept. But we have aimed to aggregate data on circuit kilometers in this data-file, as we think it is the most meaningful and comparable metric.

Power transmission per TWH of electricity? A good rule of thumb from the data-set is that each TWH pa of electricity use globally is supported by 225 km of power transmission lines, with an interquartile range of 175-275 km per TWH pa.

Power distribution per TWH of electricity? Another rule of thumb is that each TWH pa of electricity use is supported by almost 4,000km of distribution lines. The cut-off between transmission and distribution is a little bit blurry, but generally we are defining >100kV lines as transmission and <50kV as distribution.

Ratio of distribution to transmission kilometers? The global average country in our sample has 16 km of distribution lines per km of transmission lines, with an interquartile range of 12-24x. Generally, large, developed world countries tend to have a higher share of large-scale transmission, due to greater availability of financing for larger and more efficient grid infrastructure.

How much transmission is needed to build out wind and solar? Using our rules of thumb above, each 1 GW of new, utility-scale renewables might warrant constructing or upgrading around 500 km of transmission lines and 8,000 km of distribution infrastructure? Although the requirements will clearly vary case by case and depend on regional backlogs. A far-offshore wind project clearly has different network impacts from rooftop solar.

Overall, the build-out of renewables and electrification are transformational for power grids (TSE research summary here). And it pulls on the demand for copper and aluminium conductors.

Countries tend to have longer power transmission networks per unit of delivered electricity when (a) population density is lower (b) GDP per capita is lower and (c) average voltages of the transmission system are lower. Correlations are available in the data-file.

We think the best explanation for (b) and (c) is that wealthy countries may have constructed higher voltage lines, which carry more power. Although another theory is that low-income countries are bottlenecked not in transmission, but in distribution?

Countries lying above the trend lines on our charts are most at risk of having ‘over-saturated’ grids and requiring grid upgrades; especially where their position on the charts cannot be explained by a more dense supply-demand base or a higher-voltage network.

Power transmission circuit kilometers by country-region and power distribution kilometers by country-region are also estimated in the data file, including future projections for the energy transition (chart below, data in the file).

The full data-file contains our best estimates of the transmission infrastructure by country, and distribution infrastructure by country, aggregated from different public sources, company reports and technical papers.

US electric utilities: leading companies in transmission and distribution?

This data-file is a screen of US electric utilities, with a focus on transmission and distribution. The data-file covers a dozen companies, which control around 30% of US generation capacity (in GW), transmission (in miles), distribution (in miles) and electricity sales (in million MWH). We wonder whether there is increasing upside for transmission and distribution as part of the energy transition?

A key conclusion from our research into the energy transition is the upside in the grid, with total investment accelerated from around $1trn pa to $3-4trn pa. The reasons are summarized here. We wonder if this creates hidden upside for utilities that control transmission and distribution infrastructure?

Regulated utilities are “the opposite” of conventional energy companies, which the market has tended to punish for increasing their capex. Regulated utilities earn a pre-agreed rate of return on equity, usually 9-11%. Thus higher spending translates into higher future earnings.

Our data-file shows several companies planning 20-50% step-ups in T&D spending over the coming half-decade. The average company is trading at a 3.5% dividend yield today and targeting 6.5% annual earnings growth, as its rate base expands.

Who are the largest companies in US power transmission and distribution? We have aggregated data below. We think this sample comprises 35% of all the transmission infrastructure and 25% of the distribution infrastructure in the US.

The full data-file contains details on each company. The average company has been in operation for 80-years, employs 18,000 people, has over 25 GW of generation assets, 15,000 transmission miles, 100,000 distribution miles, 8M customers, $20bn pa of revenues, c10% net margins, 8.5% ROE and 3.5% dividend yields.

We have also written a 4-7 line summary of each company. Common themes for these US electric utilities include rising capex, especially for renewables, the phase out of coal, building out electric vehicle infrastructure and a target of reaching net zero by 2050 or before.

DC-DC power converters: efficiency calculations?

DC-DC power converters are used to alter the voltage in DC circuits, such as in wind turbines, solar MPPT, batteries and digital/computing devices. This data-file is a breakdown of DC-DC power converters’ electrical efficiency, which will typically be around 95%. Losses are higher at low loads. We think there will be upside for increasingly high-quality and efficient power electronics as part of the energy transition.

What are DC-DC converters and why do they matter?

DC-DC converters are used to alter voltage and current in DC circuits. The global market is $15-20bn per year and growing at 12% per year. These devices are used seemingly everywhere as the world electrifies. From IT equipment and smartphones, to the MPPT in solar, to wind turbines, to charging and discharging batteries, such as in electric vehicles.

DC-DC converters invariably contain one or more MOSFETs, diodes, inductors and capacitors. Think about the MOSFET as a fast-acting switch, the inductor as resisting change in current (voltage fluctuates instead, as energy is stored in an expanding and collapsing magnetic field) and the capacitor as resisting change in voltage (current fluctuates instead, as energy is stored in an expanding and collapsing electric field).

In a buck converter, voltage is lowered. The MOSFET turns the entire circuit on and off. Power can only flow from the source to the load for a fraction of the time. But the inductor and capacitor keep the output voltage and current relatively stable. It follows that the delivered voltage will be some fraction of the input voltage, depending on the percent of time that the MOSFET is on (aka the duty cycle).

In a boost converter, voltage is raised. When the MOSFET switches on, it short-circuits the inductor. A spike of power flows into the inductor, creating an electromagnetic field. Then when the MOSFET turns off, this electro-magnetic field collapses, creating a sharp burst of higher voltage. Again the capacitor keeps the output current relatively stable.

What determines DC-DC power converters’ efficiency?

But what is the efficiency of a DC-DC converter? We think a good base case is around 95%, which is an optimized balance across a dozen different input variables. We think value will accrue to leading semi-conductor and power-electronics companies, that can improve the efficiency of electrification technologies. Recent examples include Silicon Carbide (SiC) semi-conductors, Zero-Voltage Switching.

Step-up or step-down ratio. In our model, we have captured a buck converter, where in the base case, the voltage is being stepped down by 50%. This is what underpins our 95% efficiency calculation. However, the efficiency falls to only 90%, if we step-down by 75%, as effectively all of the losses rise proportionately.

Power output. We also optimized our device for a nominal 1.0 Amps of current. At 10x lower current, efficiency falls to 87% as reverse recovery losses in the diode become disproportionately large. At 10x higher current, efficiency falls to 77% as inductor losses become disproportionately large.

Switching frequency. We optimized our device for 1MHz switching frequency. At 0.1MHz, efficiency falls to 89% and the losses are dominated by resistance in the MOSFETs and inductors. At 10MHz, efficiency falls to 78% and is dominated by the switching loss and reverse recovery loss on the diode.

Renewables: how much time to connect to the grid?

Is the power grid becoming a bottleneck for the continued acceleration of renewables? The median approval time to connect to the grid for a new US power project has climbed by 30-days/year since 2001; and has doubled since 2015, to over 1,000 days (almost 3-years) in 2021. Wind and solar projects are now taking longest to inter-connect, due to their prevalence, lower power quality and remoteness. This data-file evaluates the data, looks for de-bottlenecking opportunities, and wonders about changing terms of trade in power markets.

Accelerating wind and solar are a crucial part of our roadmap to net zero. But we have also been worrying about bottlenecks, especially in power grids. Project developers are increasingly required to fund new power transmission infrastructure, before they are allowed to interconnect, usually costing $100-300/kW, but sometimes costing as much as the renewables projects themselves (data here). If there is one research note that spells out the upside we see in power grids and electrification, then it is this one. We also see upside in long-distance transmission, HVDCs, STATCOMs, transformers, various batteries.

Other technical papers have also raised the issue of rising interconnection times and power grid bottlenecks for wind and solar. And the US’s Lawrence Berkeley National Laboratory has also started tracking the ‘queue’ of power projects waiting to inter-connect. We have downloaded their database, spent about a day cleaning the data (especially the dates), and aimed to derive some conclusions below.

Methodological notes. The raw LBL database contains a read-out of over 24,000 US power projects that sought to inter-connect to a regional power grid, going back to 1995. However, 13,000 of these applications were withdrawn, 8,000 are still active/pending and 3,500 are classed as operational. 2,500 of the projects have complete data on (a) when they applied for permission to inter-connect to the grid and (b) when they were ultimately granted that permission, allowing us to calculate (c) the approval time (by subtracting (b) from (a)). But be warned, this is not a fully complete data-set. And some States, which have clearly constructed large numbers of utility-scale power projects, seemed not to report any data at all. Nevertheless, we think there are some interesting conclusions.

The median time to receive approval to inter-connect a new US power project to the grid has risen at an average rate of 30-days per year over the past two decades and took over 1,000 days in 2021, which is 2.8 years. This has doubled from a recent trough level of 500 days in 2015 (chart below) and a relatively flat level of 400-days in the mid-2000s.

Renewables projects now take longer to receive approval to connect to the power grid. Wind projects have always taken longer to receive approvals. And recent wind projects continued taking 30% longer than the total sample of approved projects in 2019-21. More interestingly, however, solar projects have gone from taking 50% less time to receive grid connection approvals in the mid-2000s to taking 10% longer than average, especially in 2020 and 2021. Why might this be? We consider five factors…

#1. Project quantity is probably the largest bottleneck. The numbers of different projects receiving permission to connect to the grid are tabulated below. A surge in wind projects in 2005-2012 correlates with the first peak in inter-connection approval times on the chart above. And a more recent peak in utility-scale solar, battery and wind projects correlates with the recent peak of approval times in 2020-21. This suggests a key reason it is taking more time to approve new inter-connections is that grid operators are backlogged. It would be helpful to resolve the backlog. And we wonder if the result might be a change in the terms of trade: favoring grid operators more, favoring capital goods companies more, and requiring project developers to be more accommodating?

#2. Project sizing does not directly explain inter-connection approval times. The average utility-scale solar project has become larger over time (now surpassing 150MW). But wind projects have always been larger than the average power project seeking approval to connect to the grid. And there are many small gas, coal and nuclear projects that take longer to receive connection approval than large ones. So we do not think there is a direct link between power project size and the time needed to approve an inter-connection. However, there may be an indirect link. It is clearly going to take longer to study the impacts of connecting 10 x 100 MW solar projects (in 10x separate locations), than 1 x 1,000 MW nuclear plant, even though both have the same nameplate capacity.

#3. Connection voltage does not explain inter-connection approval times. The median project in the database is connecting into the grid at 130kV. The median wind project is at 145kV. The median gas project is at 135kV. The median solar project is at 110kV. The median battery project is connecting at 140kV. Although we do think that moving power over longer distances is increasingly going to favor higher voltage transmission and also pull on the transformer market.

#4. Power quality seems to explain relative approval times and increasingly so. Another interesting trend is the difference in interconnection approval times between different types of power projects. Wind and solar projects now take 30% and 10% longer than average to receive approvals. Whereas gas, batteries and hydro now take 15%, 50% and 90% less time than average to receive approvals. We think this is linked to power quality. On a standalone basis, wind and solar may tend to reduce the inertia, frequency regulation, reactive power compensation and balancing of power grids. Whereas gas power plants, batteries and hydro typically help with these metrics (each in their own way). We think this adds evidence in support of our power grids thesis.

#5. Remote projects take longer to approve, as they will likely require more incremental transmission lines. The shortest interconnection times across all power projects were in Texas, which already has a very large power grid, arguably the best energy endowment and infrastructure in the world. But other more densely populated states (Michigan, Illinois) tended to have 50% lower times to approve inter-connections than some of the least densely populated states (the Dakotas, Iowa, Montana), where we think new power generation likely needs to be moved further to reach demand centers. Location matters for levelized cost of electricity. Again, we think this evidence also supports our power transmission thesis.

Overall the data suggest that there are growing bottlenecks to inter-connect renewables to power grids; especially in areas with a surge of activity, where power quality is increasingly important, and in more remote areas that require new transmission infrastructure. We think this trend will continue. It would be helpful to debottleneck the bottlenecks, to sustain the upwards trajectory of wind and solar. But we do think the terms of trade are shifting in favor of grid operators, power electronics, transmission infrastructure, developers that can use their own power and consumers that can demand shift.

Goldwind: frequency response from wind turbines?

Goldwind is one of the largest wind turbine manufacturers in the world, having delivered over 50,000 turbines by early-2023. The company was founded in 1998, headquartered in Beijing, it has 11,000 employees, and shares are publicly listed.

The wind industry is increasingly aiming to mimic the inertia and frequency response of synchronous power generators. Goldwind has published some interesting case studies, boosting power by 6-10%, within 1-2 seconds, for 5-6 seconds. Hence this data-file reviews Goldwind frequency response patents to look for an edge?

Synchronous power generators have ‘inertia’. If the grid suddenly becomes short of power, due to a large new load switching on, or a large power source disconnecting, then all of these synchronized machines will slow down very slightly, and in unison. Harvesting their rotational energy provides more power to the grid. But it also lowers the ‘frequency’ of the grid. At least for a few seconds, until firing rates can be ramped up. Generally, the larger the synchronous power generators, the higher their ‘inertia’, the more power that can be drawn out as they slow down, and the less grid frequency will drop per unit of incremental power. This is all crucial to the functioning of a modern power grid.

Wind turbines do not inherently provide any inertia or frequency response. Interestingly, they have about the same amount of angular momentum as conventional power generators, as they spin. But it is not synchronized with the grid. A wind turbine spins at 15-20 revolutions per minute, whereas a typical grid at 50 Hz (or 60 Hz in the US) is completing 50 full AC cycles per second.

An increasing goal for the wind industry is to ‘mimic’ some of the inertia and frequency responses of synchronous generators. Recently, Goldwind has published interesting case studies at wind farms, e.g., in Australia, boosting power by 6-10%, within 1-2 seconds, for 5-6 seconds (chart below).

The goal of this patent screen is to evaluate whether Goldwind’s frequency response algorithms give it an edge over other wind turbine manufacturers. We were unable to de-risk this idea from reviewing the patents, for the reasons explained in the data-file.

There are three key challenges for implementing frequency responses, as a form of ‘synthetic inertia’ and wind power plants, which are also borne out by the patent analysis. It takes time to implement the response (certainly longer than a battery, capacitor bank or conventional generator). Second, it is challenging to coordinate the responses of dozens of turbines, each with a different operating state. Third, there is always a danger that the wind drops at the precise moment you want to implement your frequency response, due to natural wind volatility.

Goldwind frequency response? Goldwind discusses possible solutions to each of these challenges in its patents. The bright spot is that we think many of the solutions are software-side, which will lower their implementation cost, and not pull too hard on already-bottlenecked power electronics. However, as usual, we find it harder to de-risk algorithm-heavy patents.

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