Subnostr

could you elaborate, sounds like an interesting argument

We have a couple projects that have a mix of different miner types. Each ASIC machine has a different $/MWh breakeven power cost. I had a [wrong] thought recently of, “well let’s just take the weighted average of mix of miners on site and use that as our single $/MWh curtailment hurdle rate.” Bad idea 😂

Say you have 5 inefficient miners who mine profitably up until $1/MWh and you have 1 miner who is extremely efficient and mines profitability until $5/MWh. Thus, the weighted average would be $1.67/MWh. If you put that at your curtailment hurdle rate then you’d be running the inefficient miners beyond their profitable power cost range, and not utilizing the efficient miners effectively. All bad, really terrible idea on my part. Total brain fart

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Discussion

bedair81 1y ago

ohhhh I see I see, well the good news is 1) you are able to reason about the pros and cons of your own idea and 2) you are critically thinking which is seems 95% of people do not these days.

keep up the innovation brother, we need people like you💯

Garrettstr 🌸 1y ago

Thank you for the mercy, friend 🫂🤙🏻

Jestopher 1y ago

I don't think you're far off here from making something useful. You could arrange a Cumulative Density Function of Hashrate versus $/MWh which would indicate the remaining profitable Hashrate as electricity prices fluctuate.

Garrettstr 🌸 1y ago

a CDF of Hashrate versus $/MWh showing how much of the total mining hashrate remains profitable at various electricity prices is a great idea. Thanks for the suggestion. Right now we just have a tiered model ramping down miners at their respective breakeven points, so only the portion of miners unable to mine at the current price will turn offline. A CDF tool would be a neat way of visualizing that strategy. 🔥🤙🏻