toddmedema / electrify

Take Charge of the Power Market
http://electrifygame.com
MIT License
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Solar + wind's build cost and expected output should reflect local weather forecast #103

Closed toddmedema closed 2 months ago

toddmedema commented 2 months ago

It's currently based on a single hardcoded capacity factor, obviously not correct

  1. DONE: Update solar output calculation in updateSupplyFacilitiesFinances in Game.tsx to account for lat/long (add lat/long to LOCATIONS in constants) AND month of year...
  2. Build facilities menu should reflect full output calculation (incl weather and lat long) in average output and $/MWh for wind + solar

For simplicity in determining "average output", can use the weather for the full upcoming year as a model year, e.g. don't need to simulate/forecast every year of service life uniquely

toddmedema commented 2 months ago

Perhaps "capacity factor" is the best way to estimate this

Thought: How much would I expect the climate to meaningfully change in a way that would impact solar/wind capacity factor? Uhhh, without getting into complex climate change modeling, minimally... so, then, I could argue that capacity factor could just be locally-calculated once

Which would also work well since that particular logic of generating facilities isn't used much - only in BuildFacilities and InitGame, so it's ok if it works a bit to actually forecast out.

So, basically, expand the export function GENERATORS in Facilities.tsx to take in (location? weather?) and calculate custom capacity factors for solar and wind — and then, of course, verify that the updates flow through and make sense.

For the record, existing values on master when starting SF 2020 scenario, 200MW: wind: 62MW/year, $27.4/mwh, capacityFactor: 0.31 solar: 44MW/year, $25.1/mwh, capacityFactor: 0.22

Okay, so we made this change, and wind looks good... but solar's capacity factor plummeted to 0.05; why? Just checked and it does look like the irradiance average for 2020 SF is actually that low. 6% in PIT, 9% in puerto rico. But the US average is 16-28% depending on the state... https://www.eia.gov/todayinenergy/detail.php?id=39832

Even removing cloudiness from the equation, that only bumps it up to 11% SF / 13% puerto rico

Removing the recently added compensation factor for latitude gets it up to 17% and 20%, so I think that was redundant with the existing day length modifier. Still not super accurate / could use work, but way closer than it was. Good enough for MVP.