could you elaborate, sounds like an interesting argument

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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, โ€œwell letโ€™s just take the weighted average of mix of miners on site and use that as our single $/MWh curtailment hurdle rate.โ€ Bad idea ๐Ÿ˜‚

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 youโ€™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

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 you๐Ÿ’ฏ

Thank you for the mercy, friend ๐Ÿซ‚๐Ÿค™๐Ÿป

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.

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. ๐Ÿ”ฅ๐Ÿค™๐Ÿป