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Hendra
4 hours ago
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My Insight
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arman
4 hours ago
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This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics
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3
5 hours ago
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My Insight
5 hours ago
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Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

SEIRD 01: COVID-19 spread
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ecossystem model
First insight
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TCC 2
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Clone of Muizen
5 hours ago
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My Insight
5 hours ago
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финал
5 hours ago
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A growing grid can only build what its permitting system lets through each year. This model asks what that does to prices and to fossil fuel generation when you speed the process up, leave it slow, use it to block gas plants, or wait for a better deal.

How it works. Two stocks, clean capacity and the fossil fleet, in average gigawatts delivered. Demand compounds. Each year the grid wants to build for demand growth, replace retiring plants and keep a 15 percent reserve margin, but it can only build what the rules allow (a pace that scales with the grid), and about 80 percent of what gets built is clean. Fossil plants supply whatever clean power can't, so the fossil power needed (our emissions proxy) is demand minus clean output. When the grid runs short, prices rise and old plants that were due to close stay open.

What it shows.

  1. Blocking a gas plant only cuts fossil power if something clean gets built in its place. Otherwise it changes nothing except the reserve margin: higher prices, older plants.
  2. Build pace matters until it covers demand growth plus retirements, about 19 GW a year here. Past that, extra pace buys nothing.
  3. A gas ban is a price policy. Across every setting we tried it raises prices by 2 to 20 percent. For emissions it does nothing while the bottleneck binds and gains a few percent once the bottleneck is cleared, because a slightly short grid keeps building clean. What costs emissions is delay.
  4. Holding the bill hostage to get the ban is a bad bet. If you win, emissions end 1 to 3 percent lower than the deal and prices 4 percent higher. If you lose, you get no reform: 11 percent more fossil power and 9 percent higher prices. On emissions alone you need to be 80 to 90 percent sure of winning to break even, and prices lose in every branch. The ban's value comes from a cleared bottleneck, so if you want it, pass the bill first and fight for the ban after.

Premises and limits. The model assumes the bottleneck binds today, which five-year queues, tightening margins and deferred coal retirements suggest. Capacity is in effective gigawatts, so the reserve margin is a stylized slack index, not NERC's number. Demand doesn't respond to price. Coal and gas are lumped together, which understates the climate cost of keeping old coal open. Numbers are stylized, roughly the US in 2026. Rhodium's full energy-system model of the bill finds prices 3 to 5 percent lower and power emissions up to 18 percent lower by 2040; this toy lands at 7 and about 20 percent by 2046, for a bill that lifts the pace to 18 to 20.

Built by Second Order Lab around Datta and Amarnath's "Energy isn't just about climate change" (The Argument, Nov 6, 2026).

Blocking vs. Building: a growing grid behind a permitting bottleneck
5 hours ago
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Финальная версия с людьми
5 hours ago
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My Insight
5 hours ago
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اب معدنی
5 hours ago
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ecosystem model
Clone of first insight
5 hours ago
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Tuberculosis in China: Epidemiological Situation and Population Dynamics (2023)
6 hours ago
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日内波动
6 hours ago
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Tuberculosis in India | Agent model
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FÁBIA Clone of Clone of DS - Natural gas market in Brazil
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ecosystem model
First Insight
6 hours ago
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Agent-Based Disease Model
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Tuberculosis in India