power-market-trading-docs/primers/grid/04_market_mechanics_companion_en.md

# Power Market Mechanics: A Deep-Dive Companion

*Bidding, price formation, and settlement in the US and China — a structured capture of the questions the primers raise once you start pulling threads: how offers actually work, where prices mathematically come from, how contracts and spot markets interlock, and who does what inside China's market machinery.*

*This companion assumes the three primers (the grid, US markets, China markets) as background.*

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## Part I — Bidding

### 1.1 What a US generator actually submits

Plants bid with both price and quantity — and considerably more. A day-ahead submission is a **multi-part offer**:

- **An energy offer curve**: up to ~10 price-quantity segments. A 500 MW gas plant might offer 200 MW at $32/MWh, the next 150 MW at $38, the next 100 MW at $45, the last 50 MW at $60. The upward slope reflects real physics (efficiency falls off away from the design point) plus margin. Segmentation allows *partial* clearing: at an LMP of $40, this unit is dispatched to 350 MW — its in-the-money segments only.
- **Start-up cost**: the fuel and wear of firing up — tens of thousands of dollars for a large steam unit.
- **No-load cost**: the hourly cost of being synchronized before producing the first useful MW.
- **Operating parameters**: min/max output, ramp rate, minimum run time, minimum down time.

The commitment optimization weighs all parts jointly — paying a start-up cost may be worthwhile for a six-hour evening run but not a one-hour peak. If a committed unit's energy revenues fail to cover its as-offered costs (it was committed for reliability but prices stayed low), it receives a **make-whole payment** — the "uplift" of the settlement chapter. The demand side mirrors the structure with price-quantity bids, though much load still bids as fixed quantity regardless of price.

### 1.2 China: the same engine, three differences

Chinese provincial spot markets imported the clearing architecture — centralized day-ahead and real-time markets, security-constrained dispatch, segmented price-quantity offers, 15-minute granularity. Three differences distinguish the bidding process:

1. **Who bids.** US markets are two-sided: generation offers meet demand bids. Most Chinese markets launched **single-sided** — generators bid, while demand enters as the dispatch center's load forecast; users pay the resulting price without participating in forming it (changing under the 2025 reforms, but demand-side bidding remains the immature half). On the supply side there is a formal tiering: conventional units 报量报价 ("report quantity and price" — full offers), while renewables and typically nuclear participate 报量不报价 ("report quantity, not price") — declaring expected output and clearing as price takers at the front of the stack.
2. **What's in an offer.** The Chinese offer is closer to an energy-only curve; start-up costs, no-load costs, and detailed parameters play less of a role in the market optimization, with commitment leaning more on the dispatch center's engineering and administrative processes, and start-up/must-run compensation often handled outside the market.
3. **What the bid is for.** In the US, the day-ahead market sets most physical positions. In China, the MLT contract book covers the large majority of volume, and spot bidding largely determines the settlement of *deviations* — the commercial outcome is mostly decided in annual and monthly contract negotiations, with spot trimming the edges. As spot volumes grow and contracts become hourly-shaped financial instruments, the gap closes.

### 1.3 The sequence: prices are outputs, not inputs

A common misconception is that generators see the day-ahead price and then bid quantities against it. The order is the reverse — **the day-ahead price does not exist until after everyone has bid**:

1. Morning of D−1: offers submitted for every interval of tomorrow (full curves from conventional units; quantity-only from price takers). Load forecast and network model finalized.
2. Midday of D−1: the clearing optimization runs. Day-ahead prices come into existence as its solution.
3. Afternoon of D−1: schedules and prices for all 96 intervals are published.

Nobody bids against an observed outcome; bidding is the mechanism by which the price is discovered. Two features feed the contrary intuition: price takers do submit "quantity only," but they are committing to accept whatever price emerges, not reacting to one; and bidders see abundant price *information* beforehand (yesterday's results, historical patterns, published indicative forecasts) — expectations, not the actual number. The one place where participants genuinely act against known prices is the operating day: by then day-ahead prices are published and real-time prices stream continuously, and deviation decisions are made against visible numbers. The two-tempo structure — blind auction to set the reference, visible prices to steer the physics — is the same in Shanxi as in PJM.

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## Part II — The financial layer (US)

### 2.1 How big a role pure financial players play

Larger than commonly assumed — in some corners, financial players *are* the market:

- **Day-ahead energy**: virtual transactions (INCs/DECs) routinely run at volumes on the order of 10–20% of physical load in markets like PJM and MISO, dominated by specialized proprietary trading firms, and concentrated exactly where day-ahead and real-time prices are likely to diverge — the marginal arbitrageur at the seams.
- **FTR markets**: the majority of positions in most RTOs are held by banks, funds, and specialist congestion traders rather than by the physical parties the instrument nominally hedges. The perennial controversy — whether FTR auctions systematically underprice congestion, transferring ratepayer-funded value to traders — flared with the **GreenHat default** (PJM, 2018): a three-person firm amassed one of the market's largest FTR portfolios on minimal collateral, defaulted, and socialized ~$180M of losses, forcing a rework of credit rules.
- **Futures/OTC**: financial institutions supply most liquidity in hub-settled power futures; the population shifted from banks toward hedge funds and commodity specialists after Dodd-Frank and FERC enforcement actions.

The verdict is genuinely double-sided: measurable benefits (better day-ahead/real-time convergence, deeper FTR auction competition) alongside real costs (centrality in marquee manipulation cases — JP Morgan's $410M settlement, the classic scheme of virtual bids at illiquid nodes moving prices that FTR positions profit from — plus uplift contribution and credit risk). The US response has been to tighten plumbing, not remove players. Note the design stance: "pure financial player" is a *designed-in* role with dedicated instruments; China currently has no equivalent — no virtuals, no FTR analog, physical participants only.

### 2.2 FTR vs. the day-ahead market

Different layers entirely. The day-ahead market trades energy — MWh for delivery tomorrow at full LMP. An FTR is a financial contract on the **congestion-component spread** between a source and sink node, acquired in RTO auctions months or years ahead, paying out mechanically against each day's day-ahead results for its whole term. No energy, no losses component, no electrons.

Purpose: FTRs solve a problem locational pricing creates — a generator in cheap-land selling to a buyer in expensive-land bleeds the congestion spread every congested hour; the FTR pays exactly that spread back, converting unpredictable congestion exposure into a known upfront auction cost. Funding closes elegantly: congestion splits prices so load pays more than generators receive; that surplus (congestion revenue) accrues to the RTO and is precisely the pot that funds FTR payouts, with auction proceeds returned via ARRs to transmission customers.

Worked example: buy a June FTR, 100 MW, node A→B, at $2/MWh. In a given June hour, A's congestion component is −$5, B's +$15: the FTR pays (15−(−5))×100 = $2,000. If June congestion averages above $2/MWh, the position profits; if the constraint barely binds, it expires worthless. A physical A→B seller holding the FTR is simply made whole — for a hedger the point is cancellation, not profit. Mental model: the day-ahead market is the casino floor where prices are made daily; the FTR is a side contract whose payout is computed from what happens on that floor — which is why FTR trading is really congestion *forecasting*.

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## Part III — How US prices are generated

### 3.1 The pipeline

Both day-ahead and real-time prices come from optimization engines, not order books:

1. **Inputs** (morning D−1): multi-part offers, demand bids, virtuals; load/renewable forecasts; network model with line ratings and outages.
2. **Day-ahead SCUC**: security-constrained unit commitment — a mixed-integer program with millions of variables choosing which units run and at what level, minimizing total as-offered cost subject to nodal energy balance, all transmission limits under normal and post-contingency (N-1) conditions, reserve requirements, and unit physical envelopes. A companion **pricing run** (the dispatch LP with commitments fixed) produces hourly day-ahead LMPs — financially binding, published in the afternoon.
3. **Reliability check (RAC/RUC)**: if the RTO's own forecast says the financial market cleared short of expected real load, additional units are committed out-of-market (a source of uplift).
4. **Operating day**: the **state estimator** converts thousands of live measurements into the actual system state; every five minutes **SCED** — now a pure linear program, commitments fixed — re-solves dispatch against actual load, renewables, and flows, issuing setpoints and fresh real-time LMPs.

### 3.2 Where the price mathematically comes from

An LMP is not set by anyone: it is the **shadow price (Lagrange multiplier) of the energy-balance constraint at that node** — the marginal change in total system cost if demand there rose by 1 MW — computed as a byproduct of the optimization's dual solution. All structure falls out automatically: unconstrained, every node equals the marginal unit's offer; when a line binds, its shadow price propagates through shift factors into nodal differences — the congestion component. Nobody decides prices at 10,000 nodes; the solver's duals *are* the prices.

Three refinements: **co-optimization** (energy and reserves clear jointly, so reserve prices embed foregone energy profit); **scarcity adders** (reserve demand curves inject administrative scarcity value into the duals when reserves run short — how $1,000+ prices form without anyone offering that high); **fast-start pricing** (block-loaded peakers aren't "marginal" under strict duals, so most RTOs relax constraints in the pricing run to let them set price — theoretical purity traded for investment signals).

### 3.3 Optimization vs. equation-solving, precisely

Both markets are optimizations; the distinction is the *kind*. Day-ahead SCUC is a **mixed-integer program** — on/off commitment decisions are discrete, making it fundamentally hard. Real-time SCED is a **linear program**: by the operating day the discrete layer is fixed (steam plants don't materialize in five minutes), leaving only continuous dials, solvable in seconds. And because MIPs don't yield clean duals, day-ahead prices actually come from an LP pricing run with commitments fixed — so, precisely, *both* price sets come from linear programs; the day-ahead just requires a monster MIP first to decide which plants exist in that LP. Pure equation-solving does appear in the pipeline — the state estimator and power-flow calculations that reconstruct the grid's physical state — but as the *input* to the optimization, not the source of prices. Summary: optimization generates every price; equations tell the optimizer where the grid is.

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## Part IV — How China's prices are generated

### 4.1 Price generation is plural: four layers

Where the US answer is "everything comes from SCUC/SCED duals," China's depends on which price you ask about:

1. **Spot provinces — the same engine, modified.** Centralized day-ahead and real-time clearing, security-constrained optimization, 15-minute prices from the solution. Modifications: mostly **single-sided** (demand = the dispatch center's forecast, entered as fixed quantity); the **pricing asymmetry** (locational prices for generators, one uniform provincial price for load); renewables and nuclear clearing as **price takers**; tight administrative **caps and floors**; and the whole computation running inside the grid company's dispatch center rather than an independent ISO, with limited public visibility into the model.
2. **Contract prices — negotiated and auctioned around the benchmark.** The majority of settled volume takes its price from MLT negotiations and exchange listing/matching sessions, within the mandated ±20% band around the provincial coal benchmark. In spot provinces these contracts settle as differences against spot, so spot increasingly *disciplines* contract pricing without *generating* it.
3. **Administered prices — set, not discovered.** Transmission-distribution tariffs from cost audits; residential/agricultural catalog prices; time-of-use ratios from provincial price bureaus; the coal capacity payment; pumped-hydro two-part tariffs.
4. **Mechanism prices — annual auctions.** Document 136's provincial reverse auctions discover the CfD strike price for new renewables — genuine competitive price discovery, but of an annual administered contract, not an operational price.

Non-spot regions have no operational price generation yet: contracts plus regulated tariffs, with administrative balancing. The reform's trajectory is for layer 1 to become the reference that disciplines all others — the role day-ahead LMP plays in America.

### 4.2 The uniform provincial load price, in depth

The design: the optimization computes locational prices; generators settle at them; but consumers pay a single provincial purchase price — conceptually a load-weighted average of the locational results — uniform across the province though fully varying by time (users see the 15-minute peaks and valleys; they don't see place).

Why: intra-provincial locational retail prices are politically near-untouchable (price-as-fairness is the inherited philosophy); the demand side is administratively immature (most users entered the market only in 2021, via thin retailers, without bidding); and it descends structurally from the single-buyer era's uniform catalog prices.

Money consequence: the congestion surplus — which in PJM funds FTR payouts — is collected in provincial settlement and socialized through the uniform price. With no locational basis risk on the demand side, an intra-provincial FTR would have nothing to hedge; hence no FTR analog.

Cost: half the market receives no locational signal. A data center siting next to stranded northern wind vs. in the congested southern load pocket sees identical energy prices; storage earns locational prices discharging but faces the flat price charging; demand response can answer time signals but not place signals — a real cost in a country whose central problem is renewables in the wrong place relative to demand.

Fair comparison: the US isn't symmetric either (generators nodal, most load zonal) — but US zones are smaller, sophisticated users can opt into nodal settlement, and zonal averaging is a settlement convenience atop a nodal market rather than a policy commitment. Europe is symmetric the other way (one price both sides, zone-wide, congestion managed by redispatch). China's asymmetric design is a middle path: locational where investment responds most directly (generation), suppressed where politics are hardest (consumption). Whether demand ever gets locational granularity — even two or three load zones per province — is a quiet design question to watch.

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## Part V — Contracts and the settlement chain

### 5.1 MLT contracts as contracts-for-differences

Once a spot market exists, dispatch follows offers, not contracts — so a contract cannot be a literal delivery obligation. It becomes purely financial, settled in two layers: (1) everything physical settles at spot — every injected MWh paid the locational spot price, every consumed MWh charged the provincial purchase price; (2) for the contracted volume in each interval, the parties exchange the difference between contract price and the spot reference. Spot below contract: buyer tops the seller up; spot above: seller refunds the excess. Net result: each party achieves exactly the contract price on contracted volume regardless of spot.

Worked interval: contract 10 MWh at ¥420/MWh; spot ¥360; generator produces 12 MWh, factory consumes 9. Spot layer: generator receives 12×360 = ¥4,320; factory pays 9×360 = ¥3,240. Difference layer: factory pays generator 10×(420−360) = ¥600. Net: generator earned contract price on 10 MWh plus spot on its extra 2; factory paid contract price on 10 minus spot value of the 1 MWh unconsumed. Contracted positions perfectly hedged; only deviations face spot.

The discipline mechanism: once contracts settle against spot, signing at ¥0.42 when spot is expected to average ¥0.36 is a ¥0.06 gift — so every MLT negotiation becomes a negotiation about expected spot plus a risk premium, exactly as gas and oil forwards relate to their spot markets. Before spot, MLT prices were anchored to benchmark and bargaining power with no operational truth to check them; after, a contract is a forward on spot. Contract *shape* therefore matters: a flat block is a poor hedge for a profiled consumer — hence the reform push decomposing MLT from flat monthly blocks into time-of-use and hourly-shaped curves, converging on the hub-settled power swap. Caveats: trial-settlement and non-spot provinces remain messier than pure CfD logic; and mandated hedge ratios plus the ±20% band mean the discipline operates within a corridor.

### 5.2 The three-layer settlement chain: where day-ahead fits

The precise chain in the mainstream design:

**MLT contract → settles differences against the day-ahead price. Day-ahead position → settles differences against the real-time price. Real-time → settles against metered physics.**

Worked example across all layers: contract 10 MWh at ¥420; day-ahead cleared 12 MWh at ¥360; actual production 11 MWh; real-time price ¥300. Settlement: day-ahead 12×360 = ¥4,320; real-time buys back the 1 MWh shortfall: (11−12)×300 = −¥300; contract difference: 10×(420−360) = +¥600. Total ¥4,620 for 11 MWh — decomposing exactly into: contract price on 10 contracted MWh (¥4,200), day-ahead price on 2 surplus scheduled MWh (¥720), real-time charge for the 1 MWh delivery miss (−¥300).

The day-ahead price is therefore the system's most important single price, playing three roles: the **hedging reference** (the entire MLT book is economically a strip of forwards on the day-ahead price); the **scheduling instrument** (positions are managed a day early, converting physical risk into priced financial risk); and the top of the **risk gradient** (contracts absorb slow price risk; day-ahead absorbs forecastable daily structure; real-time carries only residual surprises — each layer more volatile but smaller in volume; a well-hedged participant might sit 90% contract / 8% day-ahead / 2% real-time). Design footnotes: provinces vary on the CfD reference (day-ahead, real-time, or blends; day-ahead is mainstream because settling contracts against real-time weakens scheduling incentives), and since demand doesn't bid, the day-ahead price this edifice settles against is generated with one side of the market a spectator — tightening that loop is a central reform goal.

### 5.3 What factors go into the day-ahead price

Four buckets: **Supply curve** — fuel prices (offers ≈ heat rate × fuel + VOM; gas-heavy US regions make day-ahead power nearly a gas derivative; coal plays the role in China; carbon where it binds); the available fleet (outages, maintenance, deratings; hydro conditions with opportunity-cost offering); renewable forecasts (near-zero-priced volume at the front of the stack — the biggest day-to-day driver, with forecast shape setting the midday trough and evening ramp); start-up/no-load lumpiness; bidding behavior (opportunity costs, risk premia, margin where mitigation permits). **Demand** — weather above all; calendar (weekends, holidays — Chinese New Year craters industrial load for weeks); in the US, price-responsive bids and virtuals embedding real-time expectations; in China, the dispatch center's forecast with no expectations channel yet. **Network** — transmission limits and outages (a line out can split a market for a week); interchange (US: expected flows between markets; China: rigid inter-provincial schedules acting as pre-set supply shifters). **Rulebook** — reserve requirements and scarcity mechanisms; caps, floors, bands truncating the distribution; in China the coal-benchmark band plus price-taking renewable volume compressing how much of the supply curve can express itself.

Compression: day-ahead price ≈ marginal fuel cost of the expected marginal unit ± congestion at your location + scarcity adders if tight — where the marginal unit is determined by load forecast × renewable forecast × available fleet. Day-to-day these factors set level and shape; across years, the fleet itself (investment, retirement, fuel mix) moves the whole curve.

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## Part VI — Institutions and the real-time layer in China

### 6.1 Dispatch center vs. power exchange

Formally separate entities; practically, separate desks of the same family. The **dispatch center** (调度中心) is an internal department of the grid company (national/regional/provincial/local hierarchy) running physical operations *and the spot clearing engines* — the closest analog to an RTO operations floor, but on the grid company's org chart. The **power exchange** (电力交易中心) is a distinct legal entity from the post-2015 reform — Beijing and Guangzhou centers for inter-provincial trade, one exchange per province — running the commercial layer: registration, MLT platforms, green power trading, settlement calculation. Shareholding reform has diluted grid-company ownership of the exchanges ("relatively independent," 相对独立 — the word "relatively" carrying great weight), but the grid company typically remains dominant, and the dispatch/clearing function has not been separated at all. The governance issue: the grid company is simultaneously transmission monopolist, dispatch operator, dominant exchange shareholder, settlement counterparty, default supplier, and (through trading arms) a market participant — the standing question being whether a unified national market eventually requires something ISO-like, independent of both grid companies.

### 6.2 How real-time prices are generated, and what drives them

Mechanics: a rolling SCED-style clearing every 15 minutes inside the provincial dispatch center, fed by the actual system state (SCADA/state estimation), ultra-short-term load and renewable forecasts, current topology — and generator offers **carried over from day-ahead**, with limited or no intraday re-declaration. Prices emerge as the solution's marginal values (locational for generation, uniform provincial for load), bounded by caps and floors, with AGC executing between runs.

Factors, in rough order: **renewable forecast error** (the headline driver — price-taking renewables put the entire miss onto the priced stack; over-delivery pushes real-time toward the floor or negative, under-delivery up); **load forecast error** (doubly important in a single-sided market, where the forecast *is* the demand side); **contingencies** (unit trips, UHV/line outages — repriced within minutes off pre-submitted curves); **inter-provincial schedule adjustments** (lumpy, administratively adjusted flows acting as sudden supply shifts — a bigger real-time factor than inter-market flows in the US); **flexibility scarcity** (ramp and range, not energy: sunset ramps spike prices; holiday-noon solar floods against inflexible coal at technical minimums drive floors and negative prices — Shandong's Labor Day negative-price stretches being the canonical case); **reserve coupling and administrative bounds** (tails clipped by design). Exposure is structurally small — contracts and day-ahead positions insulate most volume — but marginal incentives are large: real-time is where forecast accuracy becomes a revenue skill, storage earns intra-day arbitrage, and flexible units capture ramp scarcity. The pattern of real-time prices is the reformers' clearest empirical readout of what the physical system needs.

### 6.3 "Real-time" is minutes-ahead — and in China, nothing is bid at that stage

No market prices the literal present. The real-time clearing runs shortly before each interval, using ultra-short-term forecasts, issuing setpoints and the price *for the upcoming interval* — ex-ante. The price for 14:00–14:15 was computed around 13:45–14:00. Inside the interval, the second-by-second residual is absorbed by AGC regulation, compensated as an ancillary service (capacity + mileage), not priced as energy. The temporal ladder: contracts (months–years) → day-ahead (12–36 h) → real-time (minutes ahead, 15-min resolution; 5-min in the US) → AGC (continuous, a service not a price). Most designs, China's included, settle on ex-ante prices — forecast noise accepted as the cost of actionable signals.

And in China's mainstream design, the 15-minute price involves **no live bidding at all**: conventional offers are frozen from the day-ahead submission; renewables are represented by output forecasts; demand is a forecast. The engine re-runs the dispatch each interval against updated conditions, walking yesterday's frozen curves — an auction mechanism with no live auction participation, closer to a computed scarcity index than a traded price. The US contrast is partial, not total: US offers are also largely set day-ahead, but intraday updates are allowed under rules, storage re-optimizes continuously, and border transactions are effectively bid every interval — live edges China mostly lacks. The consequence: China's real-time price can reveal stress but almost nothing can respond within the day — the market screams, and only the dispatch engine is listening. Opening intraday re-declaration, admitting storage and VPPs as active real-time bidders, and giving C&I users independent declaration and settlement (the 2025 push) is precisely the program of growing live participants around the clearing engine, so the 15-minute-ahead price graduates from diagnostic readout to genuinely traded price.

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## One-page synthesis

- A US offer is multi-part (curve + start-up + no-load + parameters); a Chinese offer is mostly an energy curve, with renewables as formal price takers and demand as a forecast.
- Prices are never bid or set — they are the dual solution of dispatch optimizations: a MIP-then-LP at day-ahead, an LP every 5/15 minutes in real time; equations (state estimation) locate the grid, optimization prices it.
- The US has one price-generation mechanism feeding everything; China has four layers (spot optimization, banded negotiation, administration, annual CfD auctions), with spot designed to gradually discipline the rest.
- China's signature asymmetry: locational prices for generators, one provincial price for load — deleting the demand side's locational signal and, with it, any need for FTRs.
- Contracts in spot provinces are CfDs settling against day-ahead; day-ahead positions settle against real-time; real-time settles against meters — a risk gradient from slow/large to fast/small exposure.
- "Real-time" everywhere means minutes-ahead ex-ante; in China it is additionally bid-frozen — the near-term reform frontier is precisely adding live participants (re-declaration, storage, VPPs, bidding demand) around the clearing engine.

*End of companion.*