Cheap or clean? How do you weigh cost against emissions?
Spot the plan nobody should pick, slide a carbon price, and trace the frontier with a solver
- Analyst · L2
- Lesson 12 of 14
- 15 min
- After lesson 11
- Completed
Six plans for Prairie Town: yearly estimates from seven representative weeks of 2025
| Plan | Cost a year | CO₂ a year | Note |
|---|---|---|---|
| A · Gas only | $103.9M | 815 kt | cheapest at no carbon price |
| B · Gas + 300 MW wind | $119.4M | 521 kt | wins between $53 and $64 a tonne |
| C · Gas + 500 MW solar | $131.4M | 488 kt | not dominated, but no carbon price picks it |
| D · Gas + 600 MW wind | $136.8M | 249 kt | wins between $64 and $166 a tonne |
| E · Gas + 800 MW solar | $159.6M | 433 kt | dominated: D costs less and emits less |
| F · Wind, solar, battery and gas backup | $159.1M | 115 kt | wins above $166 a tonne |
Plan F: 600 MW wind, 200 MW solar, a 100 MW / 400 MWh battery, and 300 MW of combined-cycle gas plus 80 MW of peakers as backup.
With JavaScript on, you pick the dominated plan, slide a carbon price and trace the frontier with a solver.
Model: lesson 13's; it estimates each plan's year from seven representative weeks, and a full-year check is separate.
Data: real 2025 hourly shapes of the Southwest Power Pool grid (EIA-930).
Costs: EIA's and NREL's, dated in lesson 13's sources.
Price year: 2025 dollars throughout; NREL's 2024 battery costs are converted with BEA's GDP implicit price deflator (×1.0263).
Plans: illustrative, not recommendations; Prairie Town is fictional.
Need a refresher? Toolbox K3 (how a building cost becomes a cost a year).
What you just did, as diagrams
- Dominated plan
- Another plan costs no more and emits no more, and is better on one count: nobody should pick it.
- Weighted sum
- Score each plan by cost plus a carbon price times its CO₂; the lowest score wins.
- Epsilon-constraint
- Cap the CO₂ and find the cheapest plan under the cap; sweep the cap to trace the frontier.
- Frontier
- The plans that cannot get cheaper without getting dirtier, or cleaner without getting dearer.
- Shadow price
- Used as a carbon price, the cap's shadow price makes the cap's plan one of the cheapest choices.
Go deeper · AnalystThe limits of weighted sums
- Dents. Plan C ($131.4M, 488 kt) lies above the straight line from B to D, so no carbon price picks it, though no plan beats it on both counts. Frontiers built from yes-or-no choices, such as building a plant or not, often have such dents.
- Nearly straight pieces. Between 500 and 400 kt the slope barely changes ($43.4 to $44.0 a tonne), so prices from $43 to $45 move the plan from 541 kt to 389 kt.
- Uneven spacing. Even steps in price give uneven steps along the frontier: up to $45 a tonne moves the plan from 792 kt to below 400 kt; from $45 to $220 it moves only to 100 kt.
- Weights carry units. The weight in cost + w × CO₂ is a price in dollars per tonne; measure CO₂ in kilotonnes and the same number means something a thousand times larger.
Das and Dennis (1997) showed these drawbacks for weighted sums in general. The epsilon-constraint method avoids the first two by fixing one goal and optimizing the other.
Go deeper · ModelerThe cap's dual as a carbon price
The epsilon-constraint problem: the cheapest plan under a CO₂ cap.
\[\min_x \; c(x) \quad \text{subject to} \quad e(x) \le \varepsilon \;\; (\lambda), \;\; x \in X.\]
| Symbol | Meaning |
|---|---|
| \(x\), \(X\) | a plan (what to build and how to run it), and every plan that meets the other rules |
| \(c(x)\), \(e(x)\) | its yearly cost ($) and its CO₂ (tonnes) |
| \(\varepsilon\) | the cap, in tonnes a year |
| \(\lambda\) | the cap’s multiplier, or dual: its shadow price, in $ per tonne |
| \(\lambda^*\), \(c^*(\varepsilon)\) | that multiplier at the best plan, and the best cost for cap \(\varepsilon\) |
- Duality. For a linear program, strong duality (a theorem that pairs every LP with a “dual” LP of prices) guarantees a \(\lambda^* \ge 0\) for which the cap’s best plan also minimizes the weighted sum \(c(x) + \lambda^* e(x)\). Other plans may tie with it, and a solver may return one of them.
- Slope. Where the frontier is smooth, \(\lambda^* = -\,\mathrm{d}c^*/\mathrm{d}\varepsilon\); at a kink, \(\lambda^*\) lies between the slopes on either side.
- Here. A 200 kt cap has \(\lambda^* = \$85.2\) per tonne; a $85.2 price with no cap lands at 199 kt and $129.4M.
- Ties. On an exactly straight piece every plan ties at its slope; with integer decisions there is no such guarantee at all.
Mavrotas (2009) shows how to sweep \(\varepsilon\) efficiently. Next: A22 (five goals at once); M6 (carbon in models).
Check yourself
Myth or fact? “The cheapest plan is always the right choice.”
- Myth
- Fact
Answer
Myth. Here plan A stays the pick only while CO₂ is priced below $53 a tonne. The frontier shows what each tonne avoided costs; people decide what that is worth.
Myth or fact? “A carbon price and a CO₂ cap can lead to the same plan.”
- Myth
- Fact
Answer
Fact. A 200 kt cap has a shadow price of $85.2 a tonne; that price, with no cap, lands at 199 kt, next to the cap's plan.
Myth or fact? “Every plan that is not dominated can be picked by some carbon price.”
- Myth
- Fact
Answer
Myth. Plan C is not dominated, yet it sits in a dent between B and D, so no price picks it.
Plan B costs $119.4M a year and emits 521 kt; plan D costs $136.8M and emits 249 kt. Above what carbon price does D score lower than B?
- About $64 a tonne
- About $17 a tonne
- About $273 a tonne
- D never scores lower
Answer
About $64: D costs $17.4M more and emits 272 kt less, and 17.4 million ÷ 272,000 tonnes ≈ $64 a tonne.
Numbers, sources and what’s next
Numbers to remember
| Number | What it means | Source |
|---|---|---|
| 52.91 kg | CO₂ released by burning one million Btu (MMBtu) of natural gas. | EIA, CO₂ emissions coefficients · released September 2024 |
| 0.33 t/MWh | CO₂ per MWh from a new combined-cycle plant (6,226 Btu per kWh); a peaker emits 0.48. | EIA, AEO2026 assumptions, Table 3 (PDF) · April 2026 |
| $3.85/MMBtu | Average cost of natural gas to U.S. power plants in 2025. | EIA, Electric Power Annual, Table 7.4 · 2025 data |
Next on the starter path
In the real world
Both routes exist: some places tax CO₂ (a price); others cap it and trade allowances, so the market finds the price. Planning studies trace frontiers like yours; lesson 13 lets you plan the town yourself.
Case file CF6 (average and marginal emission factors, and when moving electricity use to cleaner hours lowers CO₂).
Sources and further reading
- Das, I. and Dennis, J. E. (1997). A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. Structural Optimization 14.
- Mavrotas, G. (2009). Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems. Applied Mathematics and Computation 213.
- EIA. Carbon Dioxide Emissions Coefficients.
- EIA (2026). Assumptions to the Annual Energy Outlook 2026: Electricity Market Module (PDF), Table 3; other costs as listed in lesson 13.
Spotted an error, or stuck? Write to hlli@ksu.edu. Corrections are made in place and dated here.
Text licensed CC BY 4.0, code MIT: teachers and students may reuse and adapt it, with credit to Honglin Li.