My agents chose to map the providers on two axes: ‘transparency/productisation’ on the horizontal axis and ‘BESS-modelling footprint’ on the vertical axis. Arbitrary? Yes, probably, but the simplified characterisations that emerge might act as useful foils for the fuller complexity. We always need to start somewhere.

The upper-right corner of our simplified map contains four very different approaches. Modo sits farthest right because it publishes detailed forecast and benchmark methodology, exposes an API, and runs benchmark governance as a regulated activity. Aurora is also strongly ‘productised’, but its public material still reveals more about the economics than the methods, assumptions, tools. AFRY combines a large storage footprint with some optimisation-engine detail. LCP Delta reaches the same corner by a different route: it describes a Europe-centred hybrid of forecasts, benchmarking, backcasting, data tools, and trading analytics. [Modo strategy] [Modo regions] [Aurora / TPG] [AFRY BESS] [LCP Germany storage] [Enact]

Baringa sits high on footprint but left of the most productised names because its public proposition seems primarily report- and judgement-led. It clearly has a serious model estate, including a pan-European PLEXOS-based model and a 31-market BESS Index, but it publishes less about the underlying storage engine than Modo, AFRY, or even Aurora. enervis sits lower and left not because it looks weak, but because it is intentionally narrower: its public storage proposition is still most convincing as a Germany-first specialist with a strong local power-market and policy heritage. [Baringa flex reports] [Baringa PLEXOS methodology] [Baringa BESS Index] [enervis history] [enerStorage Pro]

The academic literature helps explain why no single provider dominates every dimension. Reviews of storage economics and optimisation find no single preferred method across all use cases. Capacity-expansion and equilibrium approaches aim at preventing fantasy long-run rents; stochastic dispatch and trading models aim to capture realistic dynamics; myopic planning frameworks are probably more realistic about decision timing than perfect-foresight models. The commercial providers in this market are hybrids, but they still tilt toward one of those camps. [JRC review] [Hutchinson et al. 2026] [Butters et al.] [Fuso Nerini et al.]

Key findings at a glance

• Modo is positioned as a storage-first, benchmark-governed, API-accessible modelling platform.

• Aurora and AFRY offer a combination of power-market modelling depth and BESS-market scale, but they come from different intellectual traditions: Aurora from economics/software, AFRY from engineering/optimisation.

• Baringa has one of the broadest BESS market-coverage footprints, but its public trust mechanism looks more like ‘expert-led scenario judgement’ than ‘documented product architecture’.

• enervis is the most Germany-native of the core six and appears strongest where local market design, regulation, and co-location configuration matter most.

• LCP Delta sits in the middle: more productised and transparent than a classic advisory house, but still more consultancy-shaped than Modo.

Quadrant-style landscape

Axes: rightward means more publicly documented method and more productisation; upward means a broader and deeper BESS-modelling footprint. Positions are interpretive and based only on public ‘data’. Firms that most clearly productise and document their methods also tend to scale them geographically and commercially.

Read more

It seems to me that we’d want excellent causal analysis to get a sense for the interaction effects. The analysis should be rigorous, open-source, well-communicated, a basis for dialogue.

What we often have instead, it seems to me, are plausible stories built from timing coincidences, co-movements, and vivid failure scenarios. A starting point, perhaps, but no more.

Or have I missed something?

Read more

Calendar seasons are too ‘blunt’ for the German power market. They do not capture the move from a winter-compressed system into a spring market in which the middle of the day can soften sharply while the later system remains firmer.

…the recurrence of all sorts of days which not only nature, but adventitious circumstances, a purely conventional order, introduce into a season. Marcel Proust

A market-season vocabulary helps to identify the path more clearly than calendar seasons alone. In this report window, the useful sequence is Autumn Solar Fade, Winter Return, Winter Compression, and Spring Solar Ramp.

Seasonality in the German Energy Market

• Autumn Solar Fade: the high-solar period rolls away gradually rather than disappearing at a calendar boundary.

• Winter Return: solar falls back toward single digits and the system begins to feel winter-like again.

• Winter Compression: the deepest winter-like stretch, with weak solar and a system that still behaves as if winter is in charge.

• Spring Solar Ramp: solar is back strongly enough to soften the middle of the day, but the market has not yet settled into a summer plateau.

Summer Solar Plateau sits beyond this sample, but we will get there soon enough!

Between 2025-10-01 and 2026-04-08, as we’ll see below, the market moved from autumn fade into winter return, tightened into winter compression, and then opened into a spring solar ramp.

• Autumn Solar Fade (2025-10-01 to 2025-10-15): 15 days, average solar share 11.4%, average load 53.2 GW, dominant regime Surprise dislocation regime.

• Winter Return (2025-10-16 to 2025-12-31): 77 days, average solar share 5.4%, average load 57.1 GW, dominant regime Compressed baseline regime.

• Winter Compression (2026-01-01 to 2026-02-24): 55 days, average solar share 4.2%, average load 62.4 GW, dominant regime Compressed baseline regime.

• Spring Solar Ramp (2026-02-25 to 2026-04-08): 43 days, average solar share 20.3%, average load 56.9 GW, dominant regime Mixed transition regime.

…that fresh and piercing novelty of a recurring season, of a change in the routine of our hours… Marcel Proust

Winter gave us a Low-Low Baseline

Winter Return was the settling phase after the autumn fade: solar averaged 5.4%, load about 57.1 GW, and the dominant read was Compressed baseline regime. Winter Compression then deepened that structure. Solar slipped another 1.2 percentage points to 4.2%, load rose by roughly 5.3 GW to 62.5 GW, and the market stayed under the same compressed-baseline label.

And when I thought how I would see the return of that cold season which … had always seemed to me so melancholy, when I thought how evenings would come back like that snowy evening … what at such moments I still dreaded most…was the return of the intense cold, and I said to myself that what it would be hardest to live through was perhaps the winter. Marcel Proust

That winter baseline was also quieter in spread terms. Winter Return and Winter Compression were relatively contained SPARX regimes. Once the market moved into Spring Solar Ramp, both the average stress level and the upper tail moved materially higher. The spring market was not just brighter. In this sample, it left the market more exposed to intraday shape risk.

That is the baseline against which spring should be read. Once Spring Solar Ramp arrived on 2026-02-25, solar had climbed back far enough and load had eased far enough for the middle of the day to soften much more easily than it could in January.

Spring Repriced The Middle Of The Day

By late February, the market was no longer behaving like a winter system. Once it moved into Spring Solar Ramp, solar started reshaping the middle of the day more consistently. Midday pricing could soften much more easily, even while later-day tightness remained possible.

…a decanted springtime, which is reduced to its own essence and expresses the lengthening, the warming, the gradual unfolding of its days.. Marcel Proust

Three parts of that spring turn matter here. After 2026-02-25, solar moved into a higher operating range and stayed there much more often than in winter. Late March then wobbled without fully resetting the spring pattern: solar eased, load firmed, but the score layer stayed active instead of dropping back to the quieter early-February read. The Easter block belongs inside that same setting. Spring already looks like its own operating environment rather than a brief transition out of winter.

A useful late-March comparison window runs from 2026-03-24 to 2026-03-27, when the spring opening wobbled without fully resetting. The early-April holiday block in this report runs across Good Friday on 2026-04-03, Easter Sunday on 2026-04-05, and Easter Monday on 2026-04-06.

Early April Was A Shape Event

Easter Monday was a decisive break. It landed inside Spring Solar Ramp, with unusually weak demand, strong solar, and the daily classifier already in Surprise dislocation regime. DA average still sat near flat at EUR 3.04/MWh, but settled SPARX reached EUR 4274.16/MWh.

…from the muffling of sounds in the heat of the morning hours, the cool taste of cherries; the longing for Brittany or Venice from the noise of the wind and the return of Easter… Marcel Proust

Some of the setup was visible before Monday. By 2026-04-03, the classifier had already shifted into Surprise dislocation regime. By 2026-04-05, DA average was at EUR -16.34/MWh, and the 12-16 block had already turned sharply negative. A soft holiday midday was already in the day-ahead structure.

Day-ahead already showed a soft midday shape on 2026-04-06, but, in retrospect it does not capture the eventual scale of the break. 12-16 cleared at EUR -103.33/MWh, but 16-20 still printed EUR 30.50/MWh and 20-24 EUR 111.97/MWh. That left a 12-16 versus 20-24 day-ahead gap of EUR 215.30/MWh on the same curve. On the realised quarter-hour path, the intraday-minus-day-ahead spread still ranged from EUR -4233.90 to EUR 40.26/MWh across the day. That is why Monday produced the largest SPARX break in the sample.

Read more

Energy systems concentrate public-law duties, private investment, market coordination, cross-border interdependence, and decarbonisation pressures in one operational field. It is a system of constant negotiation across public and private systems. What could be more fascinating as an object for study and discussion?

The German setting is especially interesting, I believe. The Energiewende has led to a slow-motion unfolding of complexity as high-level commitments meet questions of supply security, affordability, and the practical need to translate those commitments into grid expansion, planning, redispatch, connection, and balancing rules.

To get closer and explore the dynamics, let us now suppose that it is a “day in the life in the future.” AI agents are being widely used to solve problems. How do we imagine this would be working itself through in energy systems and settings?

ChinaTalk

Claude Just Opened the Strait

In what analysts are calling “the most productive jailbreak in diplomatic history,” Anthropic’s Claude model reopened the Strait of Hormuz early Sunday morning. This shocking development came hours after President Trump threatened to obliterate Iran's power plants if the strait wasn't reopened within 48 hours, singlehandedly preventing global recession…

Read more

a month ago · 943 likes · 193 comments · Jordan Schneider

How do public-law duties, critical-infrastructure rules, regulator determinations, operator obligations, market rules, contracts, and judicial review become harnesses for automated systems to determine who may decide what, on which grounds, and subject to what form of challenge?

An agent designed to operate under constitutionally relevant constraints would need to recognise the legal basis of its task, the non-negotiable limits on its role, the priority rules between relevant layers, the points at which uncertainty must be escalated, and the need to preserve reasons for later review.

1. Operational authority in a critical system. Redispatch brings public system aims and private asset operation into the same legally structured decision space. It can both constrain preferred private operation and recruit flexible private assets as a service to the grid. In March 2026, TransnetBW and Octopus Energy reported redispatch processes using more than 700 household electric vehicles. The question for agentic support, if introduced into such a setting, is what may be recommended, what may be triggered automatically, what requires human confirmation, and which layer governs when security of supply, cost efficiency, and decarbonisation pull in different directions.

2. Priority-setting in connection and buildout. AgNes and the 2026 Reifegradverfahren for large connection requests show how scarce capacity is allocated through readiness criteria and system-benefit considerations, with direct consequences for buildout timing and contract structure. The question is who defines the optimisation target, and how national efficiency, local affordability, and regional fairness are translated into operative priorities.

3. Cross-border collision. EU balancing and forward-capacity-allocation rules may meet German statutory duties, TSO constraints, vendor model policies, and firm-specific risk controls in the same workflow. Interconnectors and allocation rules can widen the space for trade and balancing across borders, but public TSO materials also make clear that cross-border capacity remains physically constrained and jointly allocated through market mechanisms. The question is how such collisions are mediated: by hard override rule, negotiated escalation, interface design, or technical default.

Taken together, these three questions prepare the transmission-chain analysis that follows. Full article and source links at the end of the post.

Constitutional Transmission in Germany

The German energy case shows how constitutional commitments reach a dense infrastructural setting of regulators, network operators, private contracts, and software. The claim is not that the Basic Law directly governs every operational decision. It is that constitutional commitments are translated, through increasingly specific legal and institutional forms, into operative permissions, constraints, procedures, and review structures. That sequence is the transmission chain that becomes increasingly relevant to our imagined agents.

1. Constitutional principles. At the top sit basic constitutional commitments: democratic legitimation, the rule of law, administrative binding to law, and, increasingly, environmental orientation. These do not tell a TSO or DSO how to run redispatch on a Tuesday afternoon. They do, however, define the conditions under which public power may be delegated, constrained, justified, and reviewed.

2. Statutory concretisation. The Energy Industry Act carries those higher commitments into sectoral public purposes and competence structures. It gives the energy order a legal telos, allocates responsibilities to transmission and distribution operators, and creates the legal basis on which more detailed regulatory ordering can occur.

Read more

I wanted to investigate this logic further with open data so …

Read more

Summary: In the current industrial landscape, two philosophies are colliding: the Silicon Valley “Engineering State” (iterative chaos) and the German “Lawyerly Society” (methodical procedure). The question is whether the law is a brake or a blueprint for agents in the grid.

This deep-dive was generated via bespoke, tuned instructions in NotebookLM, synthesising a wide range of primary and generated sources on NIS-2, the BNetzA catalogues, and OpenClaw architecture. Subscribers have access to the full podcast and transcript.

Summary

The modern industrial landscape is witnessing a profound collision between two fundamentally different philosophies: the “Engineering State” and the “Lawyerly Society”. The former, epitomised by the chaotic, high-speed iterative culture of Silicon Valley startups, prioritises raw speed and “pushing to production”. The latter, exemplified by the German distribution grid operator, is a world of documented processes, categorised risks, and strict legal compliance.

As Germany navigates its energy transition, the central question is whether its dense regulatory frameworks will stifle agentic AI—autonomous entities that execute code rather than just chat—or serve as a unique “master specification” to safely scale these systems to an industrial level.

Point 1: Blueprints vs. Regulatory Fortresses

The debate begins with a fundamental disagreement on the nature of German law.

• The Catalyst argues that Germany is not over-regulated but “pre-specified”. For decades, Germany has invested in detailed rules and codes that can be treated as markdown (.md) files—the foundational instructions for AI models. In this view, the law is the ultimate system prompt, providing precise mathematical boundaries for AI agents.

• The Critic counters that this creates a “regulatory fortress” that fundamentally paralyzes the fluid nature of agentic AI. They contend that while laws are rigidly static, the philosophy of agentic AI is “software building software,” creating a mechanical mismatch with critical infrastructure laws.

Point 2: The Autonomy Deadlock

A key point of contention is how to audit a system that is designed to change itself.

• The Critic points out that by August 2026, the EU AI Act classifies energy safety components as “high risk,” requiring static declarations of trustworthiness. An auditor signs off on a snapshot of compiled code. However, you cannot mathematically certify a system that opens a terminal and rewrites its own code base on a Tuesday afternoon to solve a novel grid congestion issue. The code hash changes, and the certification is instantly void.

• The Catalyst proposes the “Admission Gate” (DefenseClaw) as the engineering solution. This governance layer sits between the AI agent and the physical infrastructure. Before any agent-generated code runs, it is automatically scanned in real-time against strict parameters defined by the BSI (Federal Office for Information Security).

Point 3: Decoupling Risk via the “Starbucks Pattern”

How can autonomous agents safely manage critical infrastructure without risking a regional blackout?

• The Catalyst suggests using the “Starbucks Pattern” of asynchronous messaging. Just as a cashier taking an order is decoupled from the barista making the coffee, an AI’s optimisation request is decoupled from the grid’s physical response. If an AI hallucinates or fails, the system issues a “compensating action” or falls back to a safe baseline rather than crashing the physical world.

• The Critic warns that the stakes for critical infrastructure are “legally existential” compared to a coffee shop. Under the NIS-2 Implementation Act (active since December 2025), management faces personal liability and massive fines for cyber risks, forcing a “culture of no” where any technical failure could lead to personal ruin.

Point 4: Sovereignty and the Works Council

The debate concludes with German labor and geopolitical reality.

• The Critic notes that Section 87 of the Works Constitution Act (BetrVG) gives Works Councils mandatory co-determination rights. Because cybersecurity laws require strict logging of who prompted what and when, any AI deployment effectively becomes a workplace monitoring apparatus, leading to grueling negotiations.

• The Catalyst argues these hurdles force superior engineering. For example, to comply with GDPR data minimization, engineers use Retrieval Augmented Generation (RAG) to separate the AI’s reasoning engine from sensitive data. Furthermore, NIS-2 forces utilities to build sovereign, hardened AI infrastructure on their own bare-metal servers rather than relying on fragile, foreign cloud APIs.

The Final Verdict: The Synthesis

The ultimate test for Germany is whether the Lawyerly Society can adapt to the machine speed of the Engineering State without breaking its own rules. If the law is treated as a master specification, Germany may uniquely fuse industrial dynamism with its rich tradition of legal and human safeguards. If not, the technology gap between agile “synthetic engineering teams” and rigid legacy infrastructure may become insurmountable.

Read more

The Wall Street Journal’s piece on how JustPaid is using agents made me wonder whether we’ll ever see an article like that for a company in the German Energy Industry: delegated software work, agentic coordination.

Pinnaka says the creation of his AI agent engineering team followed the natural evolution of Claude Code, which was dramatically improved when Anthropic released the Opus 4.6 model in early February. Then, as the OpenClaw craze began to sweep Silicon Valley, and beyond, the idea popped into his head that he could build an “AI version of an engineer.”

Articles about companies using AI and ‘agents’ are a dime a dozen these days. You’re forgiven for stifling a yawn. But I think the question of how far away we are from something like this in the German energy industry gives interesting top-spin.

I hear at least one of the optimisers is going all-in on Claude Code. Good on them, especially since I think they are set up to make best use of it. More widely, your average corporation is probably struggling to put the puzzle together.

I’ve heard of an energy organisation trying to get “German AI” to work for them. Laudable, but I wouldn’t make that bet before achieving a cruising altitude with the best options. Better chances with “French AI?” The WTO may be dead, but Ricardian principles probably apply for synthetic ‘intelligence.’ Where does that lead?

What is it that makes the WSJ story interesting? Not OpenClaw as such. The extent. In German energy, ‘extent’ is the whole question… To what extent can I use that grid connection? To what extent has the system brought all parties together to use the latest technology for the best solution.

Right now, our traditional energy systems are like old-school telephone landlines – clunky, inefficient, and expensive. But with AI, we’re moving to the smartphone era, where everything is optimised in real time.

AI can adjust energy flows based on what’s happening right now, making the grid significantly more efficient. This is especially important for integrating renewable energy sources like wind and solar which can vary in output.

Greg Jackson, Octopus Energy

Germany will get there when firms stop treating law as a brake and start treating it as part of the design. What does progress look like?

• A bit of AI-chat, an internal enterprise assistant.

• Progress to embedded copilots. Guarded workflow automation? Polite applause.

• Development agents with autonomy and repo access…

• Autonomy near production, operational technology, critical operations.

Turn the law into a resource and Germany may have a unique advantage to confidently skip ahead through these stages. For decades it has invested heavily in writing and re-writing its laws, rules, and codes. Think of these as the MD files to help agents structure and understand the solution space.

Suddenly, the quality of your specs determines the quality of your product. Ambiguity that a senior engineer used to resolve intuitively now produces bugs at machine speed. So we started investing heavily in what happens before a single line of code is written.

We spend more time understanding the domain, shaping the product, and writing precise specifications. Communication skills, product sense, and judgment matter more than ever. Vasily Geyer at Entrix

Germany has invested in writing the specs. Now the solutions can begin to grow.

Read more

The war that began on 28 February has already become a major disruption to global energy trade, with oil and gas flows through the Strait of Hormuz badly affected and global LNG supply reduced by around 20%. Brent rose by over 60% in March, as did Dutch TTF. In that environment, it is natural to expect European power markets to start behaving like a seemingly ‘simpler’ fossil story again.

Source and further reading:

• https://www.iea.org/topics/the-middle-east-and-global-energy-markets

In Modo’s analysis, higher gas prices lift peak power prices, and battery revenues rise with them. Its sensitivity analysis says a 50% rise in gas prices combined with a 40% increase in carbon prices lifts day-ahead battery revenues by 28%.

Wood Mackenzie makes the transmission story equally explicit, arguing that gas price spikes still pass through to electricity prices despite structural changes since 2022, and saying that when TTF rises by €30/MWh, German power prices rise by €40/MWh. Montel, too, has highlighted a world of sharply rising storage revenues, intense volatility, and gas-fired generation setting increasingly high marginal prices.

Sources and further reading:

• https://modoenergy.com/research/en/gas-price-jump-iran-war-qatar-lng-ras-laffan-bess-batteries-ttf-nbp-jkm-revenues-interest-rates-march-2026,

• https://modoenergy.com/research/en/germany-fundamentals-sensitivity-gas-prices-carbon-price-ets-bess-battery-revenues

• https://www.woodmac.com/press-releases/middle-east-conflict-drives-european-power-price-volatility-as-gas-disruption-removes-1.5-mt-lng-weekly-from-global-markets

• https://www.linkedin.com/posts/montelnews_battery-storage-revenues-are-rising-sharply-activity-7443282103506608128-pqdl/

All of that is important, but the best analysis (including Modo’s in particular) doesn’t stop there.

Read more

Last time I said that flexible asset optimisation may be one of the most strategically attractive parts of the market.

It may also be one of the most exposed: exposed to consolidation, exposed to margin pressure, and exposed to the possibility that software moats here prove thinner than they first appear.

It’s an interesting question for every software driven company: how much of a ‘moat’ do you have with the new technology available? Have you set yourself up to take advantage?

I think for the actual mental load of being a person, interacting with these systems is going to be quite strange. I already find that I’m like: Am I keeping up with the ability of these systems to produce insights for me? How do I structure my life so I can take advantage of it?

Jack Clark, Transcript link

It’s hard enough as individual, even harder for a company. Gaps will develop quickly.

So, who has investor momentum? Who is burning through the cash? Who is growing organically? And who is investing in this ‘exposed’ part of the market? The transaction data can’t settle these questions, but it might help you form a view.

The first thing the funding history shows is that there is no single “optimiser market.” There are at least two capital stories. The trader / optimizer core (ESFORIN, Entrix, enspired, suena, with FlexPower better treated as an M&A signal than a funding case) still looks mostly like a venture-style story.

The adjacent layer (I’ve chosen to look at The Mobility House, Terra One, Flower, terralayr) already looks more like a commercialisation and financing story, where optimisation is increasingly tied to ownership, structured debt, or the control of asset portfolios.

The distinction matters because it explains why some transaction sizes look much larger than others: in several cases, investors are backing more than software and trading capability; they are backing businesses that sit closer to a wider base of assets and revenues. Over time we may see convergence.

The Core

Start with ESFORIN. Publicly, its funding history is short but revealing. In April 2021, SET Ventures announced growth capital for ESFORIN, but no amount was disclosed. What that early release did disclose was operating traction: ESFORIN said it had completed more than 2.2 million trades on EPEX in 2020 and expected more than €100 million turnover in 2021. Then, in May 2023, the picture became clearer with a disclosed €7.5 million Series B led by SEB Greentech VC, with participation from ERAME, SET Ventures, Christoph Ostermann / Green Fortress, and ESFORIN’s founder holding.

The sequence suggests a business that was commercially established before further venture expansion. It also helps explain why ESFORIN might be underestimated if one looks only at disclosed funding totals: the company may simply have needed less outside capital, or preferred to raise less, because it sits closer to flex-structuring and market access than to a pure “AI for batteries” pitch.

With Entrix we see three stages. First, there is an inception investment in summer 2021 from Pelion Green Future, though no public amount was disclosed. Entrix’s own 2023 announcement says Pelion had already invested “during its inception in the summer of 2021.” Then, in September 2023, Entrix announced a new financing round with Abacon Capital, Enpal, KRAFTWERK.ventures, Pelion Green Future, and several business angels, but the company did not publish a round size in its own release. The clearest number only appears indirectly in industry coverage: Energy-Storage.news reported that Entrix’s CEO said total funding had exceeded €8 million to date, with the vast majority coming from the latest round. In March 2026, a cleaner disclosure: €43 million round led by Junction Growth Investors and Korys, alongside BNP Paribas’ Solar Impulse Venture Fund, Allianz, AENU, Enpal, Abacon, and Arvantis.

The Entrix story does not look like a smooth “Series A, Series B, Series C” staircase. It built early backing quietly, added sector-heavy investors in 2023 without disclosing the amounts then reappears in 2026 with a large, clearly disclosed jump. What might one conclude from this sort of pattern? A business that needed time to prove commercial traction before the larger round? Or simply a company whose early rounds were raised in a less publicity-driven way.

Contrast enspired’s funding growth, which is much easier to read. In December 2021, it announced a USD 8.7 million Series A to expand grid-flexibility optimization in Europe. In May 2024, it announced a clearly disclosed €25.5 million Series B led by Zouk Capital, with a broad syndicate including PUSH VC, Banpu NEXT, Vopak Ventures, Presidio Ventures, Emerald, Helen Ventures, 360 Capital, and EnBW New Ventures. Then in October 2025, enspired said it had extended Series B to over €40 million, bringing in Future Energy Ventures while existing investors also recommitted. This is ‘textbook’ successful venture progression. That ‘staircase’ shape suggests that enspired has repeatedly been able to refresh investor conviction in a way that is both gradual and visible. No reset needed.

suena has been funded at a smaller scale. It’s important to note that suena has a different setup. Their execution is built on Volue PowerBot, with Suena’s focus on adding optimisation intelligence above that layer.

It is worth noting that external coverage often describes Suena as a “platform.” For example, PV Magazine reported in early 2024 that they had secured financing to scale their “AI-based trading platform” for renewables and storage. Yet Suena’s own branding is more restrained: “Autopilot” rather than “platform.” This gap highlights how loosely the term circulates in the energy sector, sometimes applied to any digital optimisation service. Their execution is built on Volue PowerBot, with Suena’s focus on adding optimisation intelligence above that layer.

The public history runs from a €1.2 million pre-seed in July 2022, to a €3 million seed round in December 2023, to an €8 million Series A in September 2025. The 2025 Series A was led by Eneco Ventures with 4impact participating, while earlier backers such as InnoEnergy, J.O.S.S., Santander, and Energie 360° also returned.

Adjacent Players

The adjacent group tells a more dramatic story because the financing forms are already different.

Read more

Between 1 January 2024 and 29 March 2026, a revealing set of publicly announced transactions accumulated around the German energy market.

This review captures 27 company-announced transactions notionally worth €3.98 billion on a lower-bound basis, alongside 14 investor-led private-capital entries, of which 9 disclosed or bounded amounts totalling €21.48 billion. The company-side sample is small in 2024, 6 deals worth €466 million, before broadening sharply in 2025 to 16 deals worth €2.21 billion, with 2026 year-to-date already at €1.30 billion across 5 deals. That progression is part of the story: the larger capital-formation layer of the Energiewende becomes much more visible only later in the sample, especially as household-electrification finance, battery platforms, and grid-linked capital start to scale.

The top 10 distinct deals/transactions in the sample are…

1. APG / GIC / Norges Bank IM — TenneT Germany: up to €9.5bn

2. TPG Rise Climate / GIC — Techem: €6.7bn

3. Apollo — RWE / Amprion JV: €3.2bn

4. Cloover — financing package: €1.04bn

5. Enpal / M&G — warehouse: c. €700m

6. Bees & Bears — financing commitments: €500m

7. VPI / Quantitas — German battery projects: up to €450m

8. green flexibility / Partners Group: up to €400m

9. terralayr — equity raise: €192m

10. ENVIRIA / BlackRock: over $200m

The emerging dataset combines company rounds, mezzanine, warehouses and asset-backed structures, investor-led private-capital deals, and selected strategic transactions where Germany is the clear operational focus. There’s enough here to start reading patterns from the flows.

What kinds of capital are entering German energy, through which structures, and with what implied view of where value will sit next?

From the available data gathered so far, 2024 was an emerging build phase. By 2025, the pace and scale of transactions intensify. And 2026, even as a year-to-date slice, is already about half the announced transaction value in 2025.

We see different layers of the same market being developed and financed in parallel and in different ways.

• BlackRock backed ENVIRIA with more than $200 million for commercial solar in early 2024.

• EQT launched its Transition Infrastructure strategy in December 2024.

• Partners Group committed up to €400 million of initial equity to green flexibility in January 2025.

• Enpal and M&G announced a roughly €700 million warehouse in October 2025.

• Apollo agreed a €3.2 billion structure tied to RWE’s 25.1% stake in Amprion

• A consortium including APG, GIC, and Norges Bank Investment Management agreed to buy 46% of TenneT Germany for up to €9.5 billion.

Which companies in the German energy-linked space announced the biggest capital events? Let’s focus on the biggest company-level announced transactions in the dataset from the perspective of the company raising or receiving capital. For an overall view, we’ll mix things like: equity rounds, mezzanine, (ABS) warehouses, debt facilities, financing commitments.

At company level, the largest transactions do not cluster around one tidy category called “energy tech.” They gather instead around the capital-formation layer of the Energiewende: household electrification finance, battery platforms, and the structures that make distributed assets scalable.

What is being built here is not only technology deployment. It is the financing architecture that allows deployment to keep happening without every company funding every asset from scratch on its own balance sheet.

Enpal’s warehouse with M&G is one expression of that. Cloover’s package of equity, debt facility, and guarantee support is another. 1KOMMA5° sits in the same broader story even though the instrument differs. The household is becoming an energy asset base, and the prize is not just installation volume but the financed and controllable customer relationship.

This is also where competition sharpens. Enpal and 1KOMMA5° are not merely selling equipment. Both are trying to sit at the centre of the electrified home. thermondo approaches from a more focused heating angle. Cloover is different again: it does not primarily present itself as a consumer brand, but as enabling infrastructure for installers and financing flows. So this is not simply a fight over who sells more hardware. It is a fight over who becomes the dominant financing and operating layer around the home.

If that is one contest, then another one involves grid-scale batteries and flexibility infrastructure.

Germany’s battery and flexibility market now attracts an unusually wide range of capital. There is growth equity, mezzanine, infrastructure-style capital, project partnerships, and private-credit logic, all circling the same basic opportunity. green flexibility, Terra One, terralayr, ju:niz Energy, TotalEnergies/Kyon, Alpiq and others are all positioning around utility-scale storage. But they are not all the same kind of animal. Some are primarily developers and owners. Some are trying to become platforms. Some are building both an asset base and a commercialization layer.

The market strategically important and crowded. The competition is not only for megawatts and megawatt-hours. It is also for grid access, land, connection rights, route-to-market, capital efficiency, and the credibility to keep financing large asset bases as the field matures.

Consider terralayr, Entrix, enspired, Suena, and in Citadel’s acquisition of FlexPower: this is the control and optimization layer: dispatch, forecasting, revenue stacking, degradation management, and market access. In other words, a large part of the competition is about who gets the right to orchestrate flexible assets rather than merely own them. terralayr is interesting here because it is also building its own battery assets, thereby seeding its commercialization and flexibility platform.

Each sits differently along the Smiling Curve. Each faces the gravitational pull of the middle. Their challenge (and opportunity) is to strengthen their position at the ends: as upstream tech specialists, or as downstream orchestrators.

A focus on the control and optimisation layer can lead to powerful position if the asset base grows faster than owners’ desire to build internal trading and optimisation teams. The control layer may be one of the most strategically attractive parts of the market, while also being one of the most exposed to consolidation and margin pressure.

A quieter but increasingly important layer sits beneath both the home-electrification story and the distributed-flexibility story: metering and control access.

metrify’s partnership with Macquarie is a good example. On the surface it is a smart-meter deal. In practice it is more than that. Smart meters are one of the enabling conditions for dynamic tariffs, automated load management, and distributed flexibility. That makes metering less of a side issue than it first appears. It is a bottleneck technology with capital beginning to form around it. If rollout accelerates, the economics of home-energy platforms and distributed optimization improve with it. If rollout remains slow, some of the more ambitious distributed-energy claims remain constrained.

Then there is the backbone itself.

Here the tone changes. The transactions around TenneT Germany, Amprion, and related grid funding feel like a system realising that the network itself has become a strategic asset class.

The TenneT Germany transaction brought in sovereign and pension-style capital. Apollo’s structure around Amprion shows private capital willing to finance expansion around regulated network assets. Germany’s own move toward a state-backed position in TenneT Germany makes the same point from the public side. The grid is no longer background plumbing. It is at the center of the investment story.

Techno-economic paradigm shifts?

Read more

One system seems to begin from the fear that flexibility will produce bad feedback unless tightly bounded. The other seems to begin from the hope that flexibility can be taught to behave well if the incentives are right.

Please remember that optimism and pessimism are definitions of the world, and that our own reactions on the world, small as they are in bulk, are integral parts of the whole thing, and necessarily help to determine the definition. They may even be the decisive elements in determining the definition. A large mass can have its unstable equilibrium overturned by the addition of a feather’s weight. A long phrase may have its sense reversed by the addition of the three letters n, o, t. William James

I have previously argued that German energy-market design reflects a broader stability culture: balancing groups are expected to keep quarter-hour deviations small, balancing energy is meant to correct what could not reasonably have been predicted, and institutions worry that too much real-time visibility might encourage overreaction.

In this narrow but important sense, Germany’s balancing world is a planned economy. Every quarter-hour is supposed to add up. Purposeful imbalance is streng verboten. It is not seen as a potentially legitimate contribution to system correction, but as a breach of balancing discipline.

“The aim… is to stop the wrong kind of incentives. We want to prevent imbalances in the German electricity system such as the severe ones that occurred in June 2019,” said Jochen Homann, Bundesnetzagentur President. “ This decision completes the measures designed to improve the upholding of balancing group commitments.

Source Link.

In contrast GB’s imbalance is more openly cashed out by the system rather than folded into a broader ethic of plan-fulfilment.

Previous UK/Germany essays have developed this point more broadly: in Britain, data tends to function more openly as a coordination signal; in Germany, data more often sits inside a regulatory toolset whose purpose is to make institutional reasoning nachvollziehbar.

So let’s consider Germany’s ID-AEP, which I think is revealing of the German arrangement towards imbalance in its system.

Netztransparenz defines the ID-AEP as an intraday price index built from the continuous intraday market in Germany, using the last relevant trades closest to delivery, with a liquidity threshold: the index is formed from a volume-weighted average once at least 500 MW of trading volume is reached.

ID-AEP contributes to the German imbalance price, reBAP used to settle balancing-group imbalances: flexibility of the short-term market is folded into a top-down settlement architecture for remaining imbalances between planned and actual.

Britain’s short-term imbalance world has a different feel. Market Index Data (MID) is used to calculate the Market Index Price for each Settlement Period and reflects the price of wholesale electricity in the short-term market.

The imbalance price is used directly to settle the difference between a party’s contracted and metered position in each Settlement Period. The system is built around cash-out of that difference. Parties can seek to mitigate their imbalance position closer to real time, and that more real-time information can help them reduce their exposure to the imbalance price.

In other words, Britain still wants parties to contract properly and avoid imbalance, but the mechanism is different: the system is more willing to let imbalance be priced and managed ex post, rather than treating the quarter-hour balance as a quasi-constitutional duty in the same way Germany does.

Read more

Returning from Perugia to Munich via Verona it was easy to think first about fuel and energy. The war had pushed oil and gas back to the front of the European energy conversation, and with them an old promise: that security lies in self-sufficiency.

And the view of the United States — well, at least the Trump administration, as you said — has been to double down on petrostate dominance. If you’re the largest oil and gas producer in the world, why are we buying all this cheap clean energy from China?

Energy security comes from being self-sufficient, producing more oil and gas than we need. And I think today’s conflict is a reminder that in an interconnected global market, there’s a limit to that.

https://www.nytimes.com/2026/03/24/opinion/ezra-klein-podcast-jason-bordoff.html

Italy is not a petrostate fantasy, nor is it a post-fossil system. It is a modern European power market in which gas still matters a lot. But with this fuel shock, the issue is not only the level of direct dependence, it is the system’s room to respond.

Flexibility, in this sense, is the modern form of energy security.

What does “self-sufficiency” mean, anyway? Who is the self and in relation to whom? How is that self distributed? Where does a city or region gets its power, exactly? How much of demand is met locally rather than elsewhere in the wider system? Have all the linkages been mapped out?

Read more

Walking the streets of Perugia you sometimes catch gas (mercaptan) odours. I noticed it most around the Arco dei Gigli. My mind inevitably drifted to the role of oil and gas in our economies.

Last time we looked at wholesale prices from Germany to Austria into Italy: an upward gradient into Italy NORD, where average prices are higher, which relates to combined-cycle gas being the price-setting technology a high proportion of the time.

Italy is among Europe’s most gas-dependent large economies, with gas accounting for almost 40% of total energy supply. 10% of consumption is usually imported from Qatar and Reuters reported that Italy is now in talks with the United States, Azerbaijan, and Algeria about replacement volumes after damage to Qatari infrastructure.

As I was reflecting on all of this I happened upon ’s latest post, which describes the layered benchmark system around which Middle East crude is valued: the Platts Dubai process, linked swaps, and more liquid instruments such as Brent and the Brent-Dubai EFS. What can the BESS market learn from this system?

Oil not dead

What's the price?

I know I should have addressed it before, but I got lost in the heat of the battle. Oil at 170, is it true?? Yes and No…

Read more

a month ago · 20 likes · 4 comments · The Oil Bandit

We have looked at relationships like this before, thinking about volatility across different markets.

This time our focus is on benchmark and market design, centred around the simplest of questions: what are we pricing? Headline price moves inherently involve a story about benchmark design. How are oil price benchmarks designed? What can the BESS asset class learn from the more mature oil & gas markets?

In the Corriere della Sera, Federico Fubini pointed out that the oil market has “split in two” and then gives the comparison directly: Brent around $114, Dubai around $136, and Oman around $153. What exactly does it mean to say that “oil is up”? Which oil? Priced how? Through what instruments? Against what delivery assumptions?

L’aumento vertiginoso degli indici di greggio Dubai e Oman si spiega con il fatto che essi sono divenuti molto più scarsi con la chiusura di Hormuz. Dunque, molto più cari. Ma presto le raffinerie asiatiche, dopo aver consumato un po’ delle loro scorte, potrebbero entrare in concorrenza con le raffinerie europee e americane per il greggio occidentale venduto ai prezzi del Brent e Wti. E una maggiore domanda non può che far convergere i prezzi del petrolio consumato in Europa, al rialzo, verso quelli del petrolio consumato in Asia. In altri termini, potremmo dover assistere ad un altro strappo al rialzo del Brent, che già da questa mattina si inizia a vedere.

The meteoric rise in the Dubai and Oman crude indices is explained by the fact that they have become much scarcer with the closure of Hormuz. Therefore, much more expensive. But Asian refineries, having used some of their reserves, could soon enter into competition with European and American refineries for Western crude sold at Brent and WTI prices. And increased demand can only cause the prices of oil consumed in Europe to converge, upward, towards those of oil consumed in Asia. In other words, we could be witnessing another upward surge in Brent crude, which is already beginning to be seen this morning.

Source Link

The Oil not Dead note focuses in further on the question of what an oil ‘price’ means. An important part of this machinery in focus through the current situation is Platts Dubai, which S&P describes as the physical price of Dubai crude loading through the relevant month, reflecting the repeatable, transactable price of crude loading two, three and four months ahead of the assessment date, using bids, offers and trades in the Market on Close process.

This benchmark enables a “swap” layer: Dubai-linked swaps are contracts that settle against the benchmark. These swaps are standardised enough to anchor a regional hedge market, and are best thought of as a family of benchmark-linked instruments.

The Dubai benchmark provides a reference point for more regional or specialised grades and markets. Currently, for example, immediate Oman and Murban barrels are worth more than the paper Dubai benchmark for the same month.

Spot premiums for Oman and Murban futures to Dubai swaps also surged to more than three-year highs of $5.51 and $6.52 per barrel, respectively. Source Link

So we have regional benchmarks, which support families of financial hedges/ instruments and provide reference points for more specific transactions. Regional market dislocation can be measured quite precisely by comparing sub-regional contract value to the regional benchmark.

Zooming out, the larger-scale dislocation can be measured by comparing regional and global benchmarks. Brent futures are the deep, liquid global crude contract, whereas Dubai-linked pricing is the main sour-crude reference used across Asia and the Middle East.

The Brent-Dubai EFS (Exchange of Futures for Swaps) is the spread that links the two. It is the spread between Brent futures and the Dubai cash market, i.e. what it takes to exchange a Brent futures position for a Dubai swap position.

Brent and WTI are the world’s major benchmarks. They have attracted the deep financial markets that solidify their usefulness and status. They are so overwhelming that they overshadow all other initiatives trying to gain market share. Creating benchmarks takes time. In the Middle East, Dubai and Oman are benchmarks for pricing medium, sour oil. But they essentially trade at a differential versus Brent. Trade in Dubai and Oman fine-tunes the spread versus Brent as expressions of the quality differential between sweet and sour grades and the geographic differential between the Atlantic Basin and Asia.

Source Link

What looks, from a distance, like “the oil price” is therefore a layered system: benchmark assessment, derivative overlays, and more liquid futures around them. Under normal conditions, that structure mostly disappears behind a single number. Under stress, it comes back into view: good benchmark machinery makes the stress visible. Consider two examples.

TotalEnergies was reported to have bought a significant number of Oman and Murban cargoes just as the pool of crude eligible for the Dubai benchmark process had been cut back sharply. At the same time, Oman and Murban prices jumped relative to Dubai swaps. The physically available crude inside the system had become scarcer and more valuable, and so aggressive buying in the benchmark window suddenly mattered much more than usual.

A Japanese refiner reportedly bought 2 million barrels of U.S. WTI for June arrival as an alternative to tighter Middle Eastern supply. On paper, the crude itself looked competitive against Dubai-linked pricing. But once freight costs were added, the delivered cargo ended up costing roughly $10 per barrel more than Dubai. The lesson? In times of stress, you need to look beyond the benchmark! When regional barrels become hard to get, buyers can try to replace them with oil from farther away, but the replacement is not judged only by its headline price.

Now, do aspects of this seem familiar in the context of BESS? The connection is not as far-fetched as you might think.

Read more

Along the way, let’s learn about the market structures through which those prices and flows are produced.

1. Market zones: virtual borders

Let us begin with the virtual borders of the day-ahead market: the wholesale prices cleared in each zone.

• Germany DE-LU day-ahead bidding-zone price

• Austria day-ahead bidding-zone price

• Italy NORD MGP zonal price

• Italy CSUD MGP zonal price.

Germany is the low ‘anchor.’ Austria usually sits above Germany, and Italy NORD above both.

Across the year, the average of the monthly observations is 86.57 EUR/MWh for Germany, 97.17 EUR/MWh for Austria, 112.40 EUR/MWh for Italy NORD, and 112.56 EUR/MWh for Italy CSUD. (As ever, let me know if you have different numbers, I’m leaving the comfort zone here.)

What looks at first like a simple staircase from Germany to Austria to Italy should reflect how fuel mix, grid constraints and market design shape prices inside an “integrated” Europe.

1.1 Price Differences

Germany’s lower average reflects a system more exposed to renewable-heavy low-price hours. Austria then tends to sit above Germany because cheap northern power does not move south without friction, especially since the 2018 split of the German-Austrian bidding zone introduced formal congestion management at that border.

Italy NORD sits higher again because gas still sets the marginal price more often. In its 2024 annual report, GME says combined-cycle gas was the price-setting technology 61.4% of the time and that Terna’s generalised northern-border constraint mechanism was activated in 21% of hours. Read that way, the gap is not just “Italy is expensive”; it is also the visible effect of transmission bottlenecks along a corridor where geography still matters.

1.2 Loopy Travels

Looking at all of this I came across the concept of ‘loop flows.’ In a meshed AC grid, commercial trades and physical paths do not line up neatly and ENTSO-E defines a loop flow as a physical flow whose source and sink lie in the same zone, even though the line used lies in another.

A long-standing BNetzA/Frontier-Consentec study illustrates this with north-south German transfers spilling through neighbouring countries. So, part of the corridor can already be physically “used up” before the market gets to allocate it commercially. Does this help explain why German, Austrian and Italian prices can diverge even in a coupled market?

This also echoes the German bidding-zone debate. Does it still make sense for Germany to remain a single zone? A split would change what counts as “internal” and what counts as “cross-zonal,” forcing more of the north-south bottleneck to appear directly in prices and capacity allocation instead of being pushed downstream into redispatch, cross-border distortion and recurring argument about inefficiencies and spreads. In its 2025 bidding-zone study, ENTSO-E said all studied German-Luxembourg split configurations improved economic efficiency, with a five-zone split scoring highest.

Are dynamic grid fees the answer, or merely a sticking plaster over inefficiencies created by a single large zone? BNetzA is very seriously exploring more dynamic network tariffs to reward flexible behaviour. Arguably that sits at a different layer of the problem. Dynamic fees can sharpen local incentives. They do not replace the wholesale task of locating structural transmission scarcity more in prices.

1.3 Market structure

Read more

This trip will be the starting point for a new category of essays that aims to expand our energy horizons. We have previously explored aspects of energy systems beyond Germany, and beyond Europe, but not consistently. In particular, our data-derived explorations have all focused on Germany.

From here on in, let us treat travel as a way of investigating the energy systems in the places to which we travel: exploring associations, questions, and the data available to develop our “energy journey.” Travel becomes a way of expanding our “data model” in a meaningful way.

This post sets the scene by linking reflections on the upcoming journey with material that may help in studying an energy system about which I currently know almost nothing.

A good starting point for the present market structure is GME’s Vademecum to the Electricity Market: https://www.mercatoelettrico.org/Portals/0/Documents/en-us/20250101VademecumBorsaElettrica_En.pdf. IEA’s Italy 2023 Energy Policy Review places Italy’s dependence on imported fossil fuels, the centrality of gas, the need for more flexibility and grids, and the challenge of integrating more renewables into one coherent frame. See https://www.iea.org/reports/italy-2023. Alongside that we could read Paolo Malanima’s historical work on Italian energy consumption, reminding one that present dependencies are layered on long historical changes in fuel, industrialisation, and infrastructure rather than dropping from nowhere. https://histecon.fas.harvard.edu/energyhistory/data/Malanima_Energy%20Consumption%20Italy.pdf.

A trip from Germany to Italy and back is, I feel, perfectly suited to launch cross-border energy explorations. Germans have always loved Italy, a country that has long represented many of the things missing from daily more ‘northern’ life. Might some version of that attraction extend even to Italy’s energy system?

While Germany searches, somewhat awkwardly one might say, for ways to address the internal tensions concealed beneath the abstraction of its large bidding zone, Italy may show the issue in a more candid form. Since 1 January 2021, it has operated with a seven-zone configuration, and Terna’s explainer notes explicitly that Umbria was moved from Centre-North to Centre-South in that redesign.

Bologna and Verona are in NORD; Perugia (Umbria) is in CSUD. So the middle of the trip is not just a pleasant movement from one city to another. It is a crossing inside the market itself. Terna’s explainer is here: https://lightbox.terna.it/en/insight/new-electricity-market-zones and the official GME zone document is here: https://www.mercatoelettrico.org/Portals/0/Documents/it-IT/20231018_ME_Zone.pdf

Might thoughts of Italy incite German Sehnsucht for more candid connection between internal tension and overall design?

Read more

What matters here is not so much the rhetoric around market design as the decree behind it. By proposing to reimburse gas-fired producers for ETS costs, Italy was …

Read more

To a developer, it is a pipeline.
To an investor, a portfolio.
To a virtualiser, flexible capacity.
To the grid, a node.
To the household edge, an argument.

These are not separate markets. They are different descriptions of the same one. And the interesting part begins when one description runs into another.

“A change in perspective is worth 80 IQ points.” — Alan Kay

Recent weeks have made that unusually easy to see. One story showed how battery projects can be translated into something long-duration capital is willing to buy. Another showed how the same assets can be translated into virtual flexibility through tolling and software layers. Another showed the system pushing back through storage fees, FCA design, and connection bottlenecks. Another replayed the same clash at the household edge. Then geopolitics barged back in and reminded everyone that the whole system still rests on molecules, ships, and chokepoints.

The market keeps producing cleaner abstractions. The system keeps reintroducing friction.

From pipeline to portfolio

Start with the capital side.

The interesting thing about the recent AllianzGI move is not that batteries have somehow become plain infrastructure. The point is that it shows how parts of the battery value chain are being repackaged and translated into a form that infrastructure-style capital can grok.

What began as project development was carried through a larger balance sheet into something easier for long-duration capital to recognise: a portfolio, a financing structure, an operating plan, a partially de-risked asset story.

The battery itself didn’t change. Its financial description did. Repackage. Recycle. Hold.

That is one way of reading the market. Not mainly as a technology story. Not even mainly as a battery story. As a packaging story.

How does a project become something capital can hold?

From battery to virtual capacity

BATCON showed another translation of the same market. I wasn’t there, but the programme and the reactions around it were revealing.

From this perspective, batteries no longer appear primarily as assets to own. Flexibility appears as capacity to access. The hardware stays put, but the commercial imagination moves. The asset becomes something that can be bundled, sliced, tolling-wrapped, API-exposed, and routed through different counterparties. Ownership and market access begin to separate.

That is a real shift in description. But BATCON was revealing in a second way as well — and perhaps the more important one.

Read more

“The idea becomes a machine that makes the art.” — Sol LeWitt

In a small way, Stratnergy itself is becoming such a loop. The regime classifier is one example: a tool that keeps asking the same question of the market day after day — not “what happened?” but “what state are we in?”

This is the first in a short series on recent Stratnergy updates. The features have developed faster than I expected, and one thing is becoming clearer: the writing and the code are starting to push each other forward. Analysis turns into tools; tools in turn change what we think is worth writing about.

There is a lot of market commentary around, but much of it does the same thing: it tells you what just happened.

Cue the inevitable LinkedIn post about a price spike. That is useful up to a point. But if you follow things seriously, you’ll usually want something slightly different.

Where is the market now?
How stable is that view?
What should have my attention next?

That defines the job for the regime classifier, which has developed significantly since the last post.

Instead of giving you only a daily adjective, the new regime feature starts to answer a better set of questions:

• What state does the market appear to be in?

• How stable is that state?

• What nearby states or risks should you be watching?

A live example: Wednesday to Thursday

Real examples are important. Let me know if it reveals mistakes I haven’t caught…

As I write this on Wednesday, March 4, 2026, the observed regime is the “Upward Shape Pressure” regime. The strongest live signal sits in the late-day upward correction need. The top aFRR+ block is 16-20 at EUR 54.00, day-ahead spread for the observed surface is EUR 404.2/MWh, and the current winner beats the “surprise dislocation” regime by a healthy margin.

So today has a relatively clear position.

But the interesting part is what the model says next. The published next-day preview for Thursday, March 5, 2026 rotates to the “mixed transition” regime.

That is not because the market gets calmer. Almost the opposite. Tomorrow’s surface lights up several things at once. Midday points strongly toward downward pressure, reserve and tightness are both elevated (the 12-16 block carries aFRR- at EUR 65.00 and FCR at EUR 97.09), and the evening still carries visible upward correction need (16-20 block still shows aFRR+ at EUR 47.87).

In other words, the market is no longer cleanly one-sided. Several candidate states are active together. “Mixed Transition” only beats “Downward Shape Pressure” by a very thin margin.

The regime explorer is doing something slightly different from traditional commentary. It helps locate the market in a broader state space: what the nearest neighbours look like, whether the current state sits in a stable pocket, and whether the surrounding terrain looks familiar or fragile.

That is exactly the kind of thing a companion site can do better than a newsletter post. The regime object stays live and becomes useful day after day.

The site is becoming a place you can open for quick orientation before diving into the details.

What to watch tomorrow…

• The midday 12-16 block. aFRR- at EUR 65.00 and FCR at EUR 97.09 make that the clearest downward-pressure candidate in the published surface.

• The evening 16-20 block. aFRR+ at EUR 47.87 means upward correction need does not disappear just because midday gets heavier on the negative side.

• Whether the market resolves or stays mixed. Tomorrow could either settle into a cleaner downward state or stay stuck in a transition zone.

The last version tested some market state descriptors. Interesting and useful, a bit like wine tasting notes. But as with wine, I think it’s essential to have a system behind the language. So, what’s the system here?

Read more

Energy markets are too complex to read from raw prices alone. But they are also too important to flatten into a handful of lazy stories.

What we need are better heuristics: patterns, state descriptions, disciplined language that compresses the market without pretending it is simpler than it is.

Energy markets do not move through time as a smooth series of prices. They move through states.

Some days are quiet.
Some are all shape.
Some are tight.
Some are stressed in reserve.
Some are transitional, a few things are moving, but not enough to justify a cleaner read.

Market commentary usually handles those states loosely. One day is “volatile”, another is “tight”, a third is “dislocated”.

The language is impressionistic. Isolated price spikes and duck curves tell us little. Movement is easy to see; change is harder to recognise.

Let’s introduce a framework.

Why Classify?

Because a number on its own is rarely enough.

If day-ahead spread is EUR 114/MWh, is that unusual? If aFRR- is elevated, is that a one-off block effect or part of a broader reserve-pressure state? If FCR is high but day-ahead is not, are we seeing underlying system tightness or narrower reserve strain?

Those are regime questions. A regime classifier is not mainly about prediction. It is about compression.

It takes a larger field of prices and turns it into a smaller, more stable question:

What state is the market expressing?

That answer changes how you read everything else:

• whether a spread move is structural or tactical

• whether reserve prices are confirming or diverging from the day-ahead story

• whether a quiet day is truly quiet or merely transitional

• whether a market note should be read as distortion or regime shift

The regime label is not meant to explain the whole world. Fuel headlines and geopolitics sit in the background. But the first task is simpler:

Identify the state the market is actually expressing before attaching a larger story to it.

Keep It Simple

There is an obvious temptation to make a regime classifier too clever.

You can easily pull in:

• ID

• reBAP

• residual load

• forecast error

• renewables by type

• cross-border position

• activated balancing volumes

All of those matter.

But the cleaner starting point is narrower and easier to build awareness around. Our first version uses four core layers:

1. DE-LU day-ahead prices

2. German aFRR capacity prices

3. German FCR capacity prices

4. SPARX (dislocation layer)

That is already enough to produce a meaningful state description without turning every run into an essay-length calculation.

How the Classifier Works

It computes daily features from those four layers.

Day-Ahead (Shape)

• Daily average

• Daily minimum

• Daily maximum

• Daily spread

This captures level — but more importantly, shape.

aFRR Capacity (Reserve Stack Intensity)

• Positive-side average

• Positive-side marginal

• Negative-side average

• Negative-side marginal

• Marginal-over-average premium

Reserve markets are not just about price level. They are about the steepness of the accepted stack.

FCR Capacity (System Backdrop)

• Germany average

• Germany maximum

• Cross-border average (secondary context)

FCR helps distinguish ordinary shape from broader reserve pressure.

SPARX (Expectation vs Settlement Gap)

• Raw SPARX level

• Percentile rank

• Direction of change

SPARX captures the gap between the day-ahead expectation and short-term realised reality.

It is neither a day-ahead surface nor a reserve surface.

It is the dislocation layer.

Read more

Let’s see if we can push the connected scatter plot further.

Start with the inverse relationship that runs like clockwork every year: when the aFRR NEG 08-12 capacity price is high, ID prices are low. When aFRR capacity is cheap, ID prices sit higher. Both link to solar generation intensity. When the sun is strong, the grid needs downward flexibility in the morning hours, which makes negative aFRR capacity valuable and suppresses spot prices simultaneously.

The chart traces this seasonal cycle — a diagonal sweep from upper-left (winter) to lower-right (summer).

Read more