Industry: Energy Product: ModelRisk Application: Fundamental Price-Formation Analysis
The PJM RTO settled day-ahead at an average $43/MWh in 2023 and at an average $62/MWh in 2022 — a 44% inter-annual swing driven primarily by gas. Forward-curve forecasts that take a single $4.00/MMBtu gas view and feed it through a deterministic dispatch produce a single $48/MWh power forecast. The fundamental Monte Carlo model on the same dispatch stack produces a mean forecast of $52/MWh with a P10 of $43 and a P90 of $63 — and tells the trader, the developer, and the policy analyst something the deterministic forecast cannot: which input is driving which percentile.
A commodity-trading and asset-development group used ModelRisk to rebuild its fundamental price-formation model for a US power market, replacing single-input scenario runs with a full probabilistic dispatch that prices each hour against the stochastic distribution of fuel, load, and renewable output. The annual-average price the desk publishes is the projection of that whole distribution onto one number — and the distribution sits visibly to the right of the deterministic $48 view:
The annual average power price for 2026 comes out at mean $51.9/MWh, P10 = $43.0, P50 = $50.4, P90 = $62.7, P99 = $81 — right-skewed by the gas stress regime in a way a single $4.00/MMBtu gas view cannot reproduce.
The fundamental model orders generators by marginal cost, intersects the supply curve with hourly demand, and reports the marginal unit's variable cost as the locational price. The deterministic version uses point inputs; the probabilistic version uses distributions for each:
For an annual simulation the model evaluates 8,760 hours × 50,000 paths, then aggregates to monthly and annual price distributions — the distribution shown above.
Comparing the fundamental Monte Carlo's monthly price percentiles to the traded forward curve is what makes the model commercially valuable:
The forward sits at roughly the mean in shoulder months but trades below the model's mean in winter (a winter risk-premium that the dispatch model says is rational) and above the model's mean in mid-summer. The trading desk took two positions on this read: long power calls in January and short power in late August. The simulation supplied the strike, the size, and the confidence interval on the expected P&L.
Gas price dominates — a $3.0 to $4.5/MMBtu mean swing moves expected annual price by $14/MWh. The winter-stress probability is third, and load growth fourth. The model's coal price hardly matters at the annual level because coal is largely off the margin in this RTO; that finding alone retired three deterministic coal-scenario runs the team had been performing weekly.
A 280 MW peaker proposal was evaluated against the simulated 2026 hourly price distribution. The deterministic NPV said the peaker clears $19M at an 8% discount rate; the Monte Carlo said the NPV distribution has a mean of $24M but a P10 of −$22M, with the P10 driven by the cluster of low-summer-volatility paths. The decision was a go on the peaker — but with a 15% sized gas hedge layered alongside, because the simulation showed that the project's NPV was most sensitive to the gas price percentile in which 2026 lands, not to its annual average.
A power-price forecast is the projection of a distribution onto a single number. Monte Carlo gives you the distribution back — and once you have the distribution, the trades and the investments that pay off in the tails become priceable.