Category: Report

This 12-page note studies gas power plant generation profiles, across 10 of the largest gas plants in Australia, at 5-minute intervals, comparing 2024 versus 2014, amidst the rise of wind and solar. Ramping renewables to c30% of Australia’s electricity mix has not only entrenched gas-fired back-up generation, but actually increased the need for peakers?

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Australia’s electricity demand has increased at 0.9% per year in the past decade, reaching 273 TWH in 2023. 46% is still powered by coal, while 17% comes from gas.

Australia’s renewables generation has increased. Wind power generation has ramped 3x from 4% of Australia’s grid in 2013 to 12% in 2023, while solar has ramped 8x from 2% to 16%. For the data, please see our overview of each country’s grid mix.

So, what has happened to gas power plant generation profiles amidst the rise of renewables? To answer this question, we have tabulated 5-minute by 5-minute generation data, from AEMO, for ten of the largest gas power plants in Australia, in 2014 and 2024.

Gas is clearly backstopping the volatility of solar, per pages 2-4.

Hence, we have drawn five conclusions about the utilization rates of gas turbines, generation in MWH and capacity requirements in MW on pages 5-9 of the report (1-2 key charts support each conclusion).

Utilization rates have fallen at baseload gas generation facilities, which is inflationary. But utilization rates have increased at peaker plants.

It looks challenging to fully replace the flexibility of these gas turbines with grid-scale batteries, for the reasons on pages 9-10.

Conclusions, predictions and implications are summarized on page 11.

Power grids are truly amazing in their complexity, but tend to get over-simplified in energy transition roadmaps. In the words of Ludwig Wittgenstein, “don’t think, but look”.

Wittgenstein was probably not talking about gas power plant generation profiles. Yet our data show how ramping renewables have entrenched pre-existing gas turbines in the grid in Australia — similar to other analysis we have conducted in California, the UK and Europe — and arguably require c30% more peaker plants than a decade ago.

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This 13-page note summarizes the key conclusions across all of our research from 1H24, concisely, for busy decision-makers. We highlight 101 companies exposed to AI, which have come up in our recent work, to enable the rise of AI, and debottleneck its electricity supplies, out of 1,500 companies that have now crossed our screens overall.

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1,500 companies have been mentioned 2,500 times in our research since 2019, and our energy transition research now includes over 1,400 research notes, data-files and models. Hence this report is part of a quarterly series summarizing the key conclusions across our work.

In 1H24, the #1 theme that has excited the entire energy world has been the rise of AI. We estimate 150GW of AI data centers will be built by 2030. 40% will be in the US. This will underlie the largest period of new generation capacity growth in history.

Companies exposed to AI have thus featured heavily in our 1H24 research, as we tried to unravel the bottlenecks across capital goods, more capital goods, energy, utilities, infrastructure and materials.

In particular, we reached 15 thematic conclusions, and specific companies stood out alongside each conclusion, as outlined on pages 3-8.

We are less worried about materials bottlenecks biting in 2024 than we have been at other points in the past, but still excited by advanced materials, for the reasons on page 9.

Our energy outlook is more balanced than at other points in the past, albeit we think LNG will surprise to the upside and there is growing value in volatility, per page 10.

The most mentioned companies in our research in 1H24, and from 2019-2024 more broadly, are profiled on pages 11-13. Fourteen companies stand out, with angles that may be interesting to explore further.

The downside of a concise, 13-page report, is that it cannot possibly do justice to the depth and complexity of these topics. A TSE subscription covers access to all of the underlying research and data.

We are also delighted to elaborate on our energy transition conclusions from 1Q24, and discuss them with TSE clients, either over email or over a call.

Solar ramps from 6% of global electricity in 2023, to 35% in 2050. But could any regions become Solar Superpowers and reach 50% solar in their grids? And which regions will deploy most solar? This 15-page note proposes ten criteria and ranks 30 countries. The biggest surprises will be due to capital costs, grid bottlenecks and pragmatic backups.

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We are amending our solar growth forecasts in this research note, using ten criteria to rank the long-term competitiveness of solar in different nations, then screening 30 different nations globally.

Solar Superpowers could be capable of ramping solar to 50% of their power grids by 2050, but we think this would require meeting ten criteria…

Criteria #1-2 relate to solar insolation, and are explored on pages 3-4.

Criteria #3-4 relate to costs, impacting both the absolute levelized costs of solar, and the cost relative to other regional power prices.

Capital costs are among the most overlooked variables. Solar projects in Switzerland can be lower cost than in the sunny Sahara. See pages 5-6.

Criteria #5-6 are linked to solar siting. Further away from major demand centers, land is more available, and at lower costs. But this is counterbalanced by the cost to move power over longer distances, especially amidst grid bottlenecks. See the charts on pages 7-8.

Criteria #7-8 relate to grid integration and backups. These challenges present the greatest risks that could cause developed world countries to fall short of their solar ambitions, per pages 9-10.

Criteria #9-10 relate to incentives and competition, per pages 11-12.

Solar Superpower Scores are calculated for 30 countries, which comprised 75% of global electricity demand in 2023, and derived an average of 6% of their total power generation from solar over 2023. Results and surprises are discussed on pages 13-14.

The ultimate share of solar might reach 50% for Solar Superpowers, but we do not see any countries reaching this threshold. Australia and California come close. Different regions are discussed on page 15.

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Could renewables increase hydrocarbon realizations? Or possibly even double the value in flexible LNG portfolios? Our reasoning includes rising regional arbitrages, and growing volatility amidst lognormal price distributions (i.e., prices deviate more to the upside than the downside). This 14-page note explores the upside for energy trading in the energy transition. What implications and who benefits?

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Global energy markets are growing increasingly volatile, as argued in our January-2024 quantification of energy market volatility. Key reasons are the volatility of wind and solar, which are gaining share in the global energy system, as re-capped on pages 2-3.

In order to assess commodity price volatility, we have tabulated the statistical distributions of commodity prices, for a dozen major commodities, over the past 50-years. More volatile commodities generally have higher mean average prices, as shown on pages 4-5.

In order to model the impacts of rising volatility upon commodity prices, we need to fit a statistical distribution onto the commodity prices. Lognormal distributions provide a beautiful fit. Our confidence intervals for oil prices, gas prices and coal prices are outlined on pages 6-7.

How are commodity price realizations impacted by rising volatility? Mean outcomes exceed median-basis forecasts by a wider margin! The impacts of rising volatility on gas prices, coal prices and oil prices are quantified on pages 8-9.

How are the commodity price realizations available to energy trading businesses impacted by rising regional volatility? We argue that arbitrage potential will widen most in global LNG markets. Energy trading profits are often treated as one-offs. But they are one-offs that will tend to recur every quarter. We have quantified the growing value of diverting flexible LNG contracts to higher value markets on pages 10-13.

Global LNG: offtake contracts and spot market development?

LNG portfolios are most likely to benefit from rising volatility in the global energy system, as price spikes become more frequent, and higher prices are also required to mobilize a limited number of truly flexible LNG cargoes. 25 companies’ LNG portfolios are assessed on page 14.

We think this report should be required reading for anyone with commodity-exposed interests. Commodities are volatile. But as the energy transition progresses, there is value in volatility.

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High-temperature superconductors (HTSs) carry 20,000x more current than copper, with almost no electrical resistance. They must be cooled to -200ºC. So costs have been high at 35 past projects. Yet this 16-page report explores whether HTS cables will now accelerate to defray power grid bottlenecks? And who benefits within the supply chain?

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Superconductivity is a form of quantum magic, where particular materials show almost no resistance to electrical currents, once their temperature drops below some critical transition temperature.

Hence these materials can theoretically carry infinite quantities of current. The weird quantum effects that give rise to superconductivity are briefly described on page 2.

Hundreds of materials have been shown to demonstrate superconductivity, since the effect was first discovered in mercury in 1911. Some of the key materials, such as Nb3Sn, NbTi, BSCCO and YBCO (REBCOs), are summarized on pages 3-4.

The reason for writing this report is our growing fear over power grid bottlenecks as the biggest bottleneck in energy markets and for energy transition. We have already explored advanced conductors to debottleneck the overhead transmission network.

Yet one of the biggest unsolved challenges is expanding the distribution network in space-constrained urban environments. We outline how high-temperature superconductors could help on pages 5-7.

Superconductors have already been piloted in global power grids, with 35 past projects going back to 2000. So what costs and other details from past superconductor projects stand out on pages 8-9?

The costs of HTS cables are compared with costs of transmission and costs of distribution at conventional projects — both on a top-down and bottom-up basis — on pages 10-12.

Material implications of high-temperature superconductors are also explored, for materials such as silver, superalloys, yttrium, helium and for displacing copper on page 13.

Leading companies in superconductors include six large global producers, including leaders listed in Europe, the US and Japan, plus interesting private companies scaling up capacity. Conclusions from our superconductor company screen are reviewed in pages 14-16.

Finally, there are reasons to wonder whether higher-temperature or even room-temperature superconductors might be developed in the future, from the multi-billion member state space of possible candidates across materials science. We have predicted that AI will ultimately earn its keep by ‘figuring out’ state spaces too complex for human brains.

But in the mid-late 2020s, the most interesting angle is that we think YBCO HTSs will play an increasingly large role helping to debottleneck the distribution network, especially in space-constrained urban environments. Could project activity accelerate by 5-50x by 2030?

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This 16-page report appraises 30 different options for low-carbon, round-the-clock power generation. Their costs range from 6-60 c/kWh. We also consider true CO2 intensity, time-to-market, land use, scalability and power quality. Seven insights follow for powering new grid loads, especially AI data-centers.

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Today we are increasingly receiving questions from clients looking to self-generate electricity, for large new loads, while also avoiding power grid bottlenecks. There is especially sharp demand to power new data-centers amidst the rise of AI.

Hence this report aims to compile the most extensive cross-comparison we have attempted to-date, into different sources of low-carbon baseload. We assessed 30 options across 20 different dimensions, in our LCOE database. Our methodology is described on pages 2-3.

The costs of low-carbon baseload range from 6 – 60 c/kWh. Numbers, sensitivities, capex costs, true CO2 intensities, construction times, transmission requirements, land intensity, scalability, ramp rates and reliability are all cross-plotted in the charts on pages 4-8.

Gas value chains are lowest-cost overall in the US, especially when developed directly in shale basins. Observations, discussion points and US gas market conclusions are summarized on pages 9-10.

Pure wind and solar value chains cost an order of magnitude more, when they are required to generate round-the-clock power (defined as having 3 days of battery coverage on cloudy/non-windy days). Observations and discussion points are on pages 11-13.

There are also options that use zero-hydrocarbons. They include blending wind and solar with pre-existing hydro, incubating next-generation nuclear, or housing AI data-centers alongside Iceland’s geothermal hotspots and then moving the data (!). See pages 14-15.

There is no perfect solution, however, on the quest for rapidly scalable low-carbon baseload. Hence, we close by considering whether this will delay the rise of AI, or even entrench high-carbon generation sources that would otherwise be phased out. Different options for generating low-carbon baseload reward careful consideration.

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New AI data-centers are facing bottlenecked power grids. Hence this 15-page note compares the costs of constructing new power lines, gas pipelines or fiber optic links for GW-scale computing. The latter is best. Latency is a non-issue. This work suggests the best locations for AI data-centers and shapes the future of US shale, midstream and fiber-optics?

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One of the biggest questions in energy markets this year concerns the rise of AI. Specifically, how is the world going to electrify a possible 150GW of new AI data-centers by 2030, amidst bottlenecked power grids and bottlenecked gas grids?

This 15-page note considers the options for moving molecules, electrons and information to and from AI data-centers. Ultimately, the best locations for AI data-centers will offer the best service, at the lowest cost, and after some acceptably low lead-time.

Mostly moving electricity to an AI data-center requires constructing new AC transmission lines, or possibly even HVDCs. This turns out to be the most costly option and has the highest lead-time. Capex costs (in $M/km), total costs (in c/kWh) and logistical conclusions are on pages 2-3.

Mostly moving gas to an AI data-center requires constructing new gas pipelines, but has the advantage of alleviating power grid bottlenecks, by self-generating power on site. This is a high-cost option in $M/km terms, but a low cost in c/kWh terms, and must also overcome logistical challenges, as discussed on pages 4-5.

Mostly moving data from an AI data-center requires constructing new fiber optic links, but has the advantage of alleviating power grid bottlenecks and gas infrastructure bottlenecks, by siting the data-center within a US shale basin. This has by far the lowest costs in $M/km terms and c/kWh terms, plus other logistical advantages, per pages 6-9.

Latency myths. The pushback we are anticipating is that an AI data-center needs to be close to end-consumers, because otherwise the latencies on AI query responses will be overly high. This is simply untrue. Data and counter-arguments are outlined on pages 10-12.

Locations for AI data-centers may largely be determined by the locations of upstream gas. Further help may come from a cooler, wetter climate, lowering the energy and financial costs of data-center cooling.

There is a strange symmetry bringing the shale and AI industries together: the former suffering bottlenecks in energy demand and export infrastructure; the latter suffering bottlenecks in supply and import infrastructure. Conclusions for shale and midstream are on pages 13-14.

The fiber optic industry also sees large growth, hence we end by noting the market size, growth, material usage and leading companies on page 15.

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Transformers are needed every time voltage steps up or down in the power grid. But lead times have now risen from 12-24 weeks to 1-3 years. And prices have risen 70%. Will these shortages structurally slow new energies and AI? Or improve transformer margins? Or is it just another boom-bust cycle? Answers are explored in this 15-page report.

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Three years ago, we wrote an overview of transformers, which are used every time voltage steps up or down in the world’s power grids. As examples at both extremes, efficient power transmission requires high voltages at 200-800kV, while the sockets in your home power electrical appliances at a low, safe 120V (in the US, or 230V in Europe).

The central argument in our 2021 report was that the total capacity of transformers would double or more, and the number of transformers needed in the power grid could rise by 30x as part of the energy transition. The rationale is re-capped and updated on page 2.

Transformer shortages are biting by 2024. Lead times have risen from 12-24 weeks to 1-3 years. Prices have risen by 70%. We are concerned about power grid bottlenecks, powering the rise of AI, long interconnection times for wind and solar, and delays to power electronics order books, per pages 3-4.

Hence in this report, we have attempted to break down the bottlenecks across the transformer supply chain, to see which ones might be persistent; or conversely, which ones might resolve, covering design considerations (page 5), transformer materials (pages 6-7), specialized labor requirements (pages 8-9), the capex costs of new facilities (page 10) and ultimately IRR sensitivities for the costs of transformers (page 11).

Transformer market: companies and costs?

If we follow other materials that matter in the energy transition — e.g., lithium, solar modules — then we can clearly see evidence for boom-bust cycles. Hence what are the risks of a boom-bust cycle for transformer manufacturing? Evidence is reviewed on pages 12-14.

Conclusions into transformer shortages, and companies across the supply chain, are summarized on page 15.

Reconductoring today’s 7M circuit kilometers of transmission lines may help relieve power grid bottlenecks, while avoiding the 10-year ordeal of permitting new lines? Raising voltage may have hidden challenges. But Advanced Conductors stand out in this 18-page report. And the theme could double carbon fiber demand?

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Power grids are shaping up to be one of the biggest and most imminent bottlenecks in the energy transition, for the reasons in our note here, having the consequences in our note here, and one of many reasons why new AI data-centers will need to build their own dedicated generation capacity per our note here.

A key challenge for constructing new transmission lines is the long development times, as permitting can take over 10-years. Hence what opportunities exist to raise the capacity of today’s 7M circuit kilometers of existing global transmission lines, e.g., via reconductoring.

The carrying capacity and the cost of a power line are built up from first principles on pages 2-4. Raising capacity requires raising voltage or raising current, ideally without inflating the costs of transmission.

(For more theory, please see our overview of energy units, overview of electricity and/or overview of power transmission, reactive power and harmonic distortion).

The simplest option to increase the capacity of a power transmission line might be to increase the voltage, by upgrading the transformers. Doubling voltage, all else equal, might seem to double the power. But we think material voltage increases may be more challenging than indicated in other recent commentaries, with negative net NPVs, per pages 6-8.

Raising the current through each conductor is the other way to increase power ratings. Usually there are technical and economic issues. But they can be economically addressed with Advanced Conductors, which replace steel strands at the center of Aluminium Conductor Steel Reinforced (ACSR) with composites such as carbon fiber. Properties of Advanced Conductors versus ACSR and economic costs are on pages 9-13.

Advanced Conductors versus ACSR: costs and companies?

Materials implications? Carbon fiber is a miracle material, which is 3-10x stronger than steel, but 70-80% lighter. Could Advanced Conductors effectively double global demand for carbon fiber by 2030, taking the carbon fiber market from recent oversupply into bottleneck territory? Forecasts for aluminium and copper are also revised on pages 14-15.

Leading producers of Advanced Conductors are profiled on page 16. One large public conglomerate and three private companies are gearing up. Overall, Advanced Conductors are among the best antidotes we have seen for power grid bottlenecks, based on the cost-modelling in this note.

In September-2024, we have added further details into the note, screening Prysmian’s E3X technology that dovetails with advanced conductors and achieves many of the same benefits (page 17) and tabulated evidence that advanced conductors are accelerating (page 18).

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Does defence displace decarbonization as the developed world’s #1 policy goal through 2030, re-allocating $1trn pa of funds? Defence versus decarbonization? Perhaps, but this 10-page note also finds a surprisingly large overlap between the two themes. European capital goods re-accelerate most? Some clean-tech does risk deprioritization?

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One of the catalysts for starting Thunder Said Energy, back in 2019, as a research firm for energy technologies and energy transition, was the sense that decarbonization was becoming the largest priority in the world.

Yet today, news headlines would suggest that a different theme is becoming the largest priority. The theme is defence. Comparisons between decarbonization in 2019 and defence today are drawn on page 2.

Defence spending is a deterrent against war, and may increase from $2.4trn in 2023, rising by +$1trn to $3.4trn in 2030, and then by a further +$1trn to $4.4trn in 2050, per our breakdowns of global GDP by region, and discussed on pages 3-4.

If the world allocated $1trn pa more for defence by 2030, and $2trn pa more by 2050, then how would these vast sums compete with energy transition expenditures? For an answer, we turn to our roadmap to net zero, and the costs/capex needed for wind, solar, gas, power grids, efficiency, CCS and nature-based solutions, on pages 4-7.

Winners and losers? The most important part of the note speculates as to winners and losers — by theme, by sector and by company. There is potential for more pragmatism and reindustrialization in Europe. Beware of watermelons. Our key conclusions are distilled on pages 8-10.

Ultimately all military expenditures do go somewhere, and what surprised us most is the overlap between defence versus decarbonization. This is most true for critical infrastructure and some energy technologies.

We have already watched the energy transition become the very hungry caterpillar, encompassing $15trn of market cap across a dozen sectors. Including defence. For example, we have written on super-alloys, Rare Earths and carbon fiber. And new technologies such as power-beaming, military drones and thermoelectrics.

More of our upcoming research will focus on the overlap between decarbonization and strategic infrastructure and technologies. For now, some further reading is the energy history of WWII. And our key conclusions on decarbonization versus defence are in this 10-page note.

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Oil and War: ten conclusions from WWII?