Negawatt: Balancing the grid

Electricity is something we take for granted, incompetent liberals oversimplify, and an endless "why can't we" political arguments about why are we still using non-renewables when renewables "perfectly" replaces them.

The truth is to achieve clean energy requires insane engineering precision. Most people don't know that every second of every day, the power grid has to make exactly as much electricity as everyone is using.

Not close. Exactly.

Unlike other commodities you can inventory, there is nowhere to put spare electricity. You cannot warehouse it, or call back and say "we'll send it Tuesday."

If the world starts using more than the grid is making, the whole grid slows down. Make too much, and it speeds up (speed here is literal: the grid's alternating current runs at a fixed frequency -- 50 Hz in Europe, 60 Hz in North America -- and that frequency is the wheel's speed). If the frequency drifts too far, the machines have to start switching themselves off so they don't fry.

To fix this, we invented a "stock exchange" where electricity gets bought and sold ahead of time, in 15-minute chunks, sometimes a day and a half early, based on the weather forecast.

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Simulation

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Understanding the electric grid

A better way to understand the whole thing is to go through all the lectures shared in the References section. But you have little time, so I hope this one page can cover an entire year's worth of lecture.

Picture the whole grid as one enormous spinning wheel that every power plant turns together, all in sync. The speed of that wheel is called the frequency, and it is a live scoreboard of the balance between power made and power used.

Use more than you make, and the wheel slows down. Make more than you use, and it speeds up. Nobody chooses this. It is just physics.

So somebody has to stand there every second, ready to add more power in or pull some out on a moment's notice. That somebody is the system operator (the industry name is the TSO). Its tools are layers of backup power, sorted mostly by how fast they can jump in:

The important focus is: fast backups are expensive and low volume, the slow ones are cheap and high volume, and the operator is always trying to hand the problem down to the cheaper, slower ones.

Note what the fastest layer actually does: FCR does not fix anything. It arrests the fall and freezes the disaster in place so the slower, cheaper layers have time to arrive. Stabilized is not the same word as saved.

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You have 3 chances to be right about electric supply and demand

1. Day-ahead. At noon, an auction sells off every 15-minute block of tomorrow. You bid based on your forecasts, the auction hands back one price per block, and whatever you win becomes a promise to the operator: "this is exactly what I will deliver".
2. Intraday. From about three in the afternoon the day before -- right after the day-ahead results come out -- until roughly an hour before each block, there is a nonstop market that lets you fix your promise as your forecasts get better.
3. Imbalance settlement. Whatever gap is still left between what you promised and what you actually did gets settled afterward, at the imbalance price -- a number you only find out later, and one that can hurt.

Every hour that ticks by, you have fewer ways left to fix a mistake, and the price of fixing it gets harder to guess.

And "energy trading" is a phrase that tricks you to understand the wrong thing. These three are not even the same kind of market.

The day-ahead auction is not a stock exchange. Everyone hands in a secret list of "I will buy or sell this much at this price," a computer finds where all those lists cross, and everyone in a block pays one shared price.

The intraday market is more like a stock exchange -- but much thinner and exclusive. Instead of playing the "guess the price" minigame with every person in the world with an app at every second, this is more like guess the price every 15-minute, by location, mostly among the firms that own or manage plants, batteries and customers -- plus a handful of pure traders with no assets at all.

The intraday is not a power market, it is a regret market. The thing you are trading is your own broken promise -- you are paying to un-say what you said yesterday, before the operator makes you pay more for it.

The balancing layer is not traders at all. It is a single buyer -- the operator -- walking down a price-sorted list of offers because physics left it no choice. The closer you get to real time, the less it looks like finance and the more it looks like engineering.

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Bids are curves, not bets

Nobody who actually trades this wastes effort guessing tomorrow's day-ahead price. Not because it is impossible -- because they do not need to.

A day-ahead bid is not "I want 5 MW." It is a curve: at this price I want this much, at that price I want that much. In some sense, it is like a block order in equity markets (Buy 100 AAPL at $120, buy 50 AAPL at $140).

But the key difference is different people value commodities differently, and it usually comes down to their business own unit economics.

The price where running, buying, or storing is actually worth it to you is what you write inside the bid. The auction runs your rules against everyone else's, and whatever price was globall settled, you are automatically happy with what you got.

Using the crypto miner example. Suppose mining turns power into computing worth about $120 for every MWh, should the miners run at 7 tomorrow morning?

Wrong question. You hand in a curve -- buy power whenever it is $120 or cheaper -- and the auction answers how much you should buy and run your mining operations.

A "block" bidder who says "I want exactly 5 MW" has to guess the price or lose money. A curve bidder only has to know their own costs.

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Where a shortage becomes a price

When the moment of delivery arrives and the zone has a shortage of 80 MW, the operator has to buy 80 MW right now.

It buys from the stack. Think of a discount store that piles its cheapest power right by the entrance and hides the expensive stuff deep at the back.

The operator walks in, grabs from the front first, and only pushes further into the shop when it needs more. In finance terms, it is known as "drawing deeper from the liquidity pool".

It keeps grabbing until the 80 MW is covered, then pays the price on the deepest shelf it had to reach -- for the whole basket. That price becomes the imbalance price -- and everyone's leftover mistakes settle at it, not just the operator's.

The buyer here has no choice.

In the day-ahead auction, the buyers were people with options -- they would walk away if the price was bad. Here, the zone needs 80 MW at any price, because the alternative is the grid losing its balance.

There is no walking out empty-handed, and no "too expensive" -- the needle pays whatever the shelf it reaches is charging.

So why is the store sorted this way at all? Because the same electricity costs different amounts to make, depending on who makes it.

A hydro dam or an already-running nuclear plant is cheap -- the money was spent building it, and squeezing out one more unit costs almost nothing. A gas plant has to buy fuel for every single unit, so it is mroe expensive. An emergency generator, or a factory you pay to switch itself off, is even more expensive.

Line every source up by what it costs to run right now, cheapest first, and you have built a store: cheap-to-run power by the door, expensive-to-run power at the back.

If you could store electricity, the expensive back of the shop would barely matter, because you would fill a giant tank with cheap nuclear power overnight and pour it out next morning.

But you cannot keep electrons in a warehouse (batteries hold a little, but that is its own story). So at the exact second everyone wants power at once, the cheap sources are already used up, and the only thing that can jump in this instant is the pricey stuff at the back.

That is why no country runs on 100% cheap nuclear even though it looks cheaper on paper: some hours, you simply have to burn something costly to keep the wheel spinning. It is also why energy abundant countries can still complain about data centers raising their local electric bills, because it is not the abundance of electrons but rather how electrons get delivered that sets the price.

Now, you can understand why the shape matters. A normal energy deficit means people can buy their shortage from the cheap shelves by the door. But when a 300 MW plant trips, the big deficit means every operator has to restart all of their expensive generators which pushes electric prices up.

It works upside-down too. When the zone has too much -- too much wind, a blazing sunny noon -- the operator pays plants to turn down. Now the shop runs in reverse: instead of you paying to take power, it pays you to make the extra go away, and the price can go negative.

Why and how do the turn-down offers even sit below the day-ahead price in the first place? Because a plant asked to produce less is refunding power it already sold. If it banked $30 per MWh yesterday and now bids $22 to not produce, it keeps $8 -- the "cost" of turning down is a discount coupon, not a loss.

Why would anyone pay to give power away? Because for a lot of plants, stopping costs more than paying does. A nuclear plant or a heat plant cannot just flick off and on cheaply, and a subsidized wind farm that gets paid per unit will keep making electric and selling electrons at a profit even when the rest of market has announced a surplus.

When there is a surplus, the extra power physically has to go somewhere -- so the market pays whoever can soak it up. Real European markets now have hundreds of negative-price hours a year -- Germany alone logged 457 of them in 2024.¹

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Why every forecast mistake becomes a trade

When your firm promised a schedule yesterday, and reality delivered something a bit different, that difference is your imbalance, and it gets settled at the imbalance price, both directions, under a rule called single pricing. The market let you sell power you did not have yet; the balancing market is the bouncer that collects when the forecast turns out to have been a lie.

If you have a deficit, you buy the missing bit at the imbalance price. If you have a surplus, you sell the extra bit at the imbalance price.

If you had been a commodity supplier, you might assume the following business practice: "if I make too much, no big deal -- extra power just gets sold." This is a misconception because electrons is not an identical commodity to common perishables like wheat, corn, where surplus can just sit in an inventory with low risk. ²

With that out of the way, here are the arbitrage opportunities and why it happens:

1. Your mistakes are everyone's mistakes. Your solar farms and your rivals' solar farms sit under the same sky. When your output surprises you by running high, the whole zone's does too -- everyone has a surplus at the same time because of the same sunshine that gave you surplus.
2. The price comes from the zone's state, not yours. Whole zone having a cumulative surplus means the whole zone is in surplus, with cheap energy everywhere.

Put those together and it means you have the most extra to sell at the exact moment extra is worth the least, and the biggest shortfall to cover at the exact moment power is priciest.

This is also what makes balancing markets different from gambling or insurances where playing the same game repeatedly makes you profit if have an edge.

In those markets, if your forecast errors were random -- a bit high one day, a bit low the next -- they would cancel out over a month and cost you almost nothing. The technical term is errors are "random and IID". For balancing markets, your errors are not random and IID. The size of your mistake and the price you pay to fix it are driven by the same weather, so they correlate together, on the same side, every single time.

So shortages and price spikes keep multiplying -- a big error times a bad price, over and over -- and have single day losses that wipes out months of profit.

The flip side is your surplus settles at that same imbalance price too. So on the rare occasion you have extra power exactly when the whole zone is in shortage, the price is spiking -- single pricing lets you sells your extra straight into that spike.

Being off-schedule by the same amount, but in the opposite direction to everyone else means instead of paying the spike, you pocket it. That is a weird time when a forecast error makes you money, and sometimes there are traders who will try to make it happen on purpose.

The industry has names for the two cases. An imbalance that happens to push the zone back toward balance is desired; one that deepens the hole is undesired. Same act of going off-schedule, opposite verdict -- and you never know whether you were the hero or the villain until the whole grid has voted, which is after your bid is locked.

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Three ways to handle a bad forecast

Suppose one evening, your wind guess was 20 MW too high. Now you are bagholding 20MW of power you need to clear. There are three schools of thought about what to do:

Do nothing (the industry term is set-and-forget) submits the day-ahead promise and walks away. Ignore every update, let every mistake ride all the way to settlement. This is not a meme strategy -- for a tiny retail-only firm whose mistakes are rounding errors, it is the lazy choice.

Fix everything (also called the full hedge) trades every mistake away in the intraday market the second it appears. You get certainty -- for a price. By the time you know about the cloud bank, so does everyone, so the intraday price has already slid toward the bad imbalance price, and you pay the gap on every trade. Fixing does not dodge the cost of a bad forecast. It just swaps a scary unknown bill for a smaller known one. Very much like buying insurance on weather and production. But if you can buy insurance, someone smarter can sell, it is a full circle which leads us to...

Fix, then bet is fix what you know, bet on what you believe. Trade away the part of the mistake you are sure about -- then, where your model can guess the price the whole zone will price, deliberately keep a small position pointed the helpful way. That is you being wrong the opposite way to everyone else on purpose, to collect the reward single pricing pays for it.

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Getting paid for your flexibility

Everything so far cast your firm in one role -- the balance responsible party (BRP), the one that promises a schedule and pays whenever it misses. Mostly on the receiving end of the market.

The store, though, is built out of offers, and anyone who can control their own power can sell into it. That is the other role the simulation hands you: the balancing service provider (BSP), paid to stock a shelf in the store and cover the gap when the operator wants the product stocked behind the back of the shelf.

The simulation lets you play both roles at once for one reason -- to show how much option value, and how much extra profit, a plain BRP unlocks the moment it owns a battery or compute farm it can dial on demand.

The miners are your compute farm load you can switch off in seconds -- and switching off a 5 MW load is exactly the same, to the grid, as switching on a 5 MW generator. The trade even has a name for it -- a negawatt (yes, I have the same reaction when writing this).

Suppose mining earns about $120/MWh, then the miners offer to power down for $120. Whenever the stack's price beats that, mining pauses and the balancing market pays better than the mining would have.

The battery is another way of absorbing the load. Charge when the price is on the floor, discharge when everyone comes home and demand spikes.

In earn in the market mode it stocks a shelf in the shop, collecting payment each time the operator reaches deep enough to buy it. In cover our mistakes mode it quietly soaks up your firm's own errors, shrinking the leftover-gap line instead of earning visible income. The same battery cannot do both jobs at once.

The intuition will be bigger batteries or compute farms will be free money as it gives you infinite options. The simulation lets you slide the params to show few things:

1. Bigger battery pays, but ROI is not linear. Recall the electric prices are set by the stack. The first deficit you have, you can avoid buying from the expensive part of the stack. But shortages are only so deep -- pile on more battery and the extra just stands around waiting for a disaster big enough to need it, so a big capex in batteries is NOT an autowin strategy.

2. Size matters The sim pretends you never move prices. In the real world, a giant battery would flatten the very price spikes it feeds on -- the "infinite battery, infinite money" dream dies the moment you become the back of the shop.

3. Set the job to cover our mistakes under Fix, then bet and watch the money vanish. The battery cannot tell a mistake from a bet -- it cancels out your bet. And because single pricing sometimes rewards mistakes, even the sloppy strategies gain less from self-insurance than from just selling that flexibility to the market.

A flexibility asset's downside is capped: the worst case is not a giant bill, it is a reliability strike -- you fail to deliver when you are called on (the battery runs empty halfway through an outage) and the operator writes you up. In Denmark, they have a P90 rule: your reserve only has to be there 90% of the time, and if you screw up more than 1 time out of 10 you are thrown out and must re-qualify. ³

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Few rare days decide the PnL for the month

When breakdowns are zero and weather is calm, this market looks boring and makes only spreads of a few dollars, an unprofitable and unexciting business.

But when outages becomes a frequent thing, a single tripped plant can create a 300 MW shortage deep into the liquidity pool and print hours of huge spreads. The month's profit stops being a sum of days and becomes a sum of events. This makes electron trading a 'tail-end oriented' business.

In this market you do not manage the average. You manage the worst case. The expected profit an optimizer prints is a number you are mathematically guaranteed never to collect because it is the mean of outcomes, not an outcome.

The desk's actual objective has a name, CVaR: the average of your worst 5% of days. Value-at-risk tells you how likely the cliff is; CVaR tells you how tall it is, and only the second one can bankrupt you.

The flexibility strip shows the same fact from the other side: the desk that owns the batteries and miners gets those exact same events as income spikes.

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How profitable is all of this?

Great question. After all, the grid has kept the lights on for 100 years, long before anyone built a stock exchange for electricity, and it managed fine. So why, suddenly, are we paying millions for quant traders and order-book plumbing to do a job the grid did quietly for a century?

Start with why it was quiet for a century. The old grid was a few dozen big power stations an operator could basically phone. Supply was controllable -- need more, call a coal plant and turn a dial. Demand was predictable -- people boil kettles at roughly the same times every day.

Balancing was a small in-house chore, a handful of knobs the operator owned outright. There was nothing to trade, because there is only one price you get for power.

Then we wanted renewables and bolted the weather onto the grid. Wind and solar cannot be dialed up -- the sky decides, not a dispatcher -- and instead of a few dozen controllable plants there are now thousands of weather-driven ones, mostly owned by people the operator has never met.

The gaps got bigger, hit more often, and surplus or deficit errors become correlated. You cannot fix that by phoning everyone. The job stopped being an engineering chore and became a coordination problem across thousands of strangers.

A market is the cheapest way to coordinate that mess. It works out who can adjust for the least money -- the store, sorted cheapest-first -- without any central planner needing to know everyone's costs. It pays the ones who help and charges the ones who caused the gap.

The order book and the quants show up the instant real money starts flowing through that coordination. Nobody got greedy, we just made the balancing problem so painful to work with that we crowdsourced to strangers.

So who actually gets rich? Almost nobody. For a normal weather-driven firm, the balancing market is a cost you shrink, not a profit you make. You do not hire quants to strike gold. You hire them to insure your cost better than the firm across town. Remember the part when we mentioned the intraday is more like a "regret market, not a profit engine"?

And the money that does get made is mostly a transfer, with some fresh wealth ⁴. It flows from the firms that forecast badly or cannot flex, into the ones that forecast well or own a battery. The quants' salaries come straight out of that transfer.

Meanwhile, the operator still earns the boring, regulated way -- a set cut of the power delivered -- and it runs the balancing market not to profit but to buy the emergency flexibility it is legally forced to keep on hand, as cheaply as competition allows. The market is its shopping cart, not its cash register.

The alternative -- the operator building and owning a mountain of idle backup itself, or letting the frequency wander until things trip -- costs far, far more.

So, is it profitable? System-wide, it is the opposite of a gold mine. Rather than creating profit, we designed a system that avoids losses. The real profit for society is now that we have a balancing system via prices, energy producers can YOLO and produce as much power as they can without being as conservative as they used to, if they believe traders can reduce their cost of being wrong.

How is pricing set in practice?

You might be picturing a trading floor full of people shouting. There isn't one.

The day-ahead price is one computer run a day: at noon a program takes everyone's secret curves, finds where they cross, and stamps one price on each block of tomorrow. The intraday market is a matching engine pairing buyers and sellers around the clock. The imbalance price is arithmetic the operator does after the fact -- read the deepest shelf it had to buy from, print the number.

But since this is an exchange market, it means we now have to maintain a new infrastructure that runs every 15 minutes, all day, forever, because power is used every 15 minutes, all day, forever.

But that is the whole reason you bid a curve instead of manning a desk. You write your rule once -- buy under $120, sell my spare above $200 -- and the machine runs it at 3am while you sleep. The market never rests; the trader mostly does. Babysitting it by hand is the exact job the curve was invented to delete.

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Can you use price as a parameter for price forecasts?

The popular way for most price models is to run an autoregressive function (there is no shortage of Kaggle notebooks attempting this modelling effort on electric prices with bad results).

For those who don't know, an autoregression means using past price as its own prediction parameters. Can you even feed price into your decisions, when a price is really just physics of energy supply and energy demand wearing a dollar sign?

The tempting shortcut for quants it to skip the physics, feed a few years of old imbalance prices into a model, predict the next ones. The sim's poor forecast is exactly that shortcut (it literally guesses tomorrow from yesterday's prices),

The real problem with this approach is not being wrong, but the underlying physics that creates these prices keeps adapting while you are still studying it.

Balancing markets are young and get rebuilt constantly: settlement windows shrink, zones merge their backup pools, a fleet of new batteries moves into the stack and shaves every spike. Each change rewrites the relationship and margical functions between weather and price. A model that only learned old prices inherits none of how the machine works and all of its fragility.

Electric markets is very different from equity markets. Electric is a consumable and ephemeral commodity, so prices shouldn't have memory. Businesses are almost identical in the short term, so prices can have memory.⁵

This also means it is more likely to see electric prices teleporting with high volatility, while equity prices are more stable and predictable with trends and drift.

At the same time, the price is not a thermometer sitting to be read. It is also a causality trigger. Where the moment everyone can see it and react, it changes the very thing it is measuring.

A scarcity price is meant to fix the scarcity by telling everyone what to do: expensive means "come online, or stop using." But when a thousand miners and batteries obey it at once, the shortage flips to a surplus, the price craters, everyone backs off, and the shortage comes straight back. It is like a map app routing every driver down the one empty side street, which stays empty only until the app fills it. The signal built to smooth the swing may become the reason for the swing.

So is a real-time market for this even possible? Yes -- only because the grid is not perfectly efficient. The things that look like friction are the brakes for explosive feedback loops: the plant that physically cannot switch on the instant the price twitches; the imbalance penalty that punishes anyone who overreacts.

But to answer back the original question, using lagged prices for ephemeral and non-storable electron rarely works well because the physics of the commodity is wildly different from other commodity we value (perishables, social feelings to a company).

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What the simulation ignores

At the end of the day, this page is just a nerd's toy. We skipped:

• The fine detail of how intraday trades actually execute (they run at a modeled price).
• The fastest backup layer's spin up time. (the High-Frequency Trading equivalent for electric operators)
• Price differences between zones.
• Your firm's own market impact (we assume you are too small to move anything, anywhere).
• The fine print of how plants can be switched on and off (some plants legally cannot be shut off and you might have to keep feeding when prices are negative).
• What the bet knows. The sim models "what you believe about the zone" as a noisy peek at the realized imbalance -- on the good forecast the bet points the profitable way about 90% of the time, on poor about 56%, on perfect always. A real desk builds that belief from data available that morning; the sim skips the forecasting and just dials the noise. Treat the bet's payoff as "what a forecast of this quality would be worth", not as evidence that such a forecast is easy to build.
• The end of the ladder. Roughly one quarter-hour in five hundred, an outage pushes the needle past every bid in the stack. In reality that is load shedding; the sim prices it at the last bid and now says so in the "why this price?" card.
• Reserve capacity markets -- being paid per MW just to stand ready, which is where the 2024 battery gold rush above actually happened. The sim only pays for energy that gets activated.
• Price caps and floors. Europe's coupled day-ahead market has a hard floor (−€600/MWh since 28 May 2026, lowered automatically from −€500 after the April 2026 price events) and the balancing platforms cap at ±€10,000/MWh; the sim uses its own invented limits.
• The real numbers -- the shape of the stack, the size of the errors, the $120 mining value -- is just my invention, picked to sit in believable ranges.

The intention is to let people understand the business, profit opportunity, and cost incurred to civilization if not solved.

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The comic version

There's a lot of words, here is a low cortisol link. How Electricity and Compute Get Traded.

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Glossary

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References

I'm not the smartest guy in this room, most of these lessons are distilled from the following lectures: DTU course 46755 Renewables in Electricity Markets, Prof. Jalal Kazempour (2025 run, recorded):

• Lecture 1 -- Introduction to electricity markets: merit order, uniform (marginal) pricing, why renewables bid at zero or below
• Lecture 2 -- Fundamentals: actors, market sequence, Europe vs US
• Lecture 3 -- The day-ahead market and SDAC / EUPHEMIA
• Lecture 4 -- Optimization vs equilibrium (why the dual is the price)
• Lecture 5A -- The intraday market: continuous trading and the intraday auctions
• Lecture 5B -- The balancing market: BRPs, BSPs, merit-order activation, one-price vs two-price settlement
• Lecture 6 -- Ancillary services: FCR / aFRR / mFRR, PICASSO and MARI, the P90 reliability rule
• Lecture 7 -- What renewables do to the grid: forecast errors, ramps, the duck curve
• Lecture 8 -- Offering strategy under uncertainty
• Lecture 9 -- Risk: CVaR and the value of a bad day
• Lecture 10 -- Selling flexibility into reserve markets

Textbooks the course builds on: Kirschen & Strbac, Fundamentals of Power System Economics (2nd ed.); Stoft, Power System Economics; Schweppe, Caramanis, Tabors & Bohn, Spot Pricing of Electricity (1988); Morales, Conejo, Madsen, Pinson & Zugno, Integrating Renewables in Electricity Markets.

Primary sources for the specific claims on this page:

• Grid frequency and what happens when it drifts -- ENTSO-E, frequency stability evaluation criteria for the synchronous zone (load shedding from 49 Hz, generator disconnection at 47.5 Hz)
• The reserve ladder and its activation times -- ENTSO-E, aFRR process implementation guide and ENTSO-E, load-frequency control annex (FCR 30 s, aFRR 5 min, mFRR 12.5 min)
• Day-ahead at noon, 12–36 hours ahead of delivery -- Nord Pool, day-ahead market; intraday until about an hour before delivery -- Nord Pool, intraday market; the three intraday auctions -- ENTSO-E, intraday auctions on SIDC
• The switch to 15-minute blocks in the day-ahead market (30 Sept 2025) -- Nord Pool announcement
• The single European day-ahead auction and its algorithm -- ENTSO-E, single day-ahead coupling (SDAC)
• "The deepest shelf sets the price for the whole basket" -- marginal (pay-as-cleared) pricing of balancing energy: ACER, methodology for pricing balancing energy
• Single-price imbalance settlement -- Commission Regulation (EU) 2017/2195, the electricity balancing guideline, Art. 52; how a Nordic TSO derives the imbalance price from aFRR and mFRR activations -- Energinet, imbalance price design, Fingrid, changes for BSPs and BRPs (Nov 2025)
• The Baltic balancing market and its European platforms -- Elering, energy and capacity markets for balancing services; Baltic balancing roadmap 2024; the Baltic grids' synchronisation with continental Europe on 9 Feb 2025 -- Wikipedia summary with sources
• Negative prices: Germany, 457 negative-price hours in 2024; the day-ahead floor lowered to −€600/MWh -- EPEX SPOT communication, May 2026 and ACER decision 02/2026
• "Some markets have taken firms to court for being wrong on purpose" -- Bundesnetzagentur press release on breaches of balancing-group discipline (2020) and the Bilanzkreistreue proceedings
• The reliability strike in real life: Energinet's P90 rule (fail more than 10% of activations and you are out) -- Lecture 6 and Lecture 10 above
• The word "negawatt" -- coined by Amory Lovins (1989): Negawatt market
• The cobweb cycle -- Cobweb model; Poitras, Cobweb theory, market stability and price expectations, Journal of the History of Economic Thought (Kaldor 1934, Ezekiel 1938)

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Footnotes

1. Bundesnetzagentur figures reported by pv magazine, Jan 2025; up from 301 hours in 2023. The DTU lecture explains the mechanism with the same subsidy logic: a wind farm paid per MWh outside the market rationally bids negative (Lecture 1, Lecture 7 in the references). ↩

2. The electricity market is actually closer to luxury clothing brands, where you must burn off all unsold inventory by the end of the season before it costs you money. (In the case of luxury brands, the money is your "brand equity", while the grid example is to avoid costly damages to infrastructure.) ↩

3. We set lower standards to let the renewables and EV. If we demanded perfection then only fossil plants qualify. But the operator's real nightmare is not any one provider failing, it is all of them failing together: a hundred providers each dutifully P90 can still hand the grid a blackout-sized hole if their 10% fires at the same instant -- which, for anything weather-driven, it does. ↩

4. How does wealth get created from a supposed zero-sum bidding? Everyone benefits from better energy coordination, your data centers learns how to provision electric better, and there would be a net reduction in electricity prices for every person in the country because utility companies no longer need to spend more capex trying to balance the grid. If you wonder "why can't energy abundant give out free energy to citizens", it mostly have to do with the cost of coordination and not cost of production. ↩

5. When prices are 'known' to have memory, it means you can use autoregression of lagged prices as a parameter (ARIMA or ETS model). That said, if your electric price chart can run an ARIMA, it is more likely because the demand and supply of energy is predictable. NOT because the price is predictable. Very different thing to understand! ↩

6. Negawatts up? LOL. ↩