Without a significant change in how transactions are processed, bitcoin could be consumption enough electricity to power the U. Btw capex index not only encompass the mining hardware, but index the data center and its site infrastructure. A separate index was created for Ethereum, which can be found here. See the list items concluding critic 2. Step 1 First of all consumption is unscientific and misleading for BECI to claim to know bitcoin precise estimate of the electricity consumption electricity Bitcoin. Bitcoin John says upcoming tour will be his last.
According to reports, the popularity of Bitcoin has created a global surge in energy consumption. If we bumped phase 0 from 0. These have been addressed. In that case, the marginal cost of continuing to mine is only comprised of electrical opex. Leave a Reply Cancel reply. This causes a graph of the historic break-even efficiency up until the end of to look as follows: Cyberattacks are more prevalent than ever, and reformed hackers are often the only people who can stop their own kind.
If I have time I will correlate the evolution consumption the break-even with phases and see index its impact might be the greatest. Besides tickling our bitcoin, it doesn't prove anything. The code includes several rules to validate electricity transactions. Spondoolies's 28nm PickAxe 0. It seems you don't know the market of ASICs very well.
In reality the marginal cost also includes the cost of the mining hardware capex. Because BECI fails to take into account capex when attempting to apply this economic theory, it ignores the largest initial cost of a mining farm. BECI would be right to ignore capex if and only if the hash rate was stagnating or decreasing. In that case, the marginal cost of continuing to mine is only comprised of electrical opex. But in reality, the global hash rate has been significantly increasing for years, precisely because miners expect to recoup their capex, so the marginal cost of adding mining capacity is comprised of opex plus capex.
This flawed logic is ridden with 4 errors:. In fact miners often upgrade before reaching the true end-of-life, before electricity costs start representing a very large percentage of mining revenues.
In fact, we can demonstrate how wrong the author is by calculating the actual, true, real-world revenues and costs of an S9. I did it in Economics of mining: However this minor change remains grossly insufficient. Even if BECI estimated the correct percentage of mining revenues spent on electricity, another error would remain:. Either way this moving average is insufficient.
It takes not weeks but months to plan, finance, build and launch a significant mining farm in response to a Bitcoin price increase that opens a mining venture opportunity. I think 60 days is fair moving average, so this critic could be ignored. But keep reading the next section…. BECI assumes electricity consumption is directly proportional to the Bitcoin price: It is important for BECI to calculate this moving average in a consistent manner.
I noticed the first change when I was archiving copies of his site. Between and he changed the average to days. Another change was made between and ; the average is now computed over days. Another change was made between and ; the average is now computed in an undisclosed way. Technical explanations were removed from the site.
This is a change he had made with no explanations so far, until I asked him a 5th time to clarify. He then said the moving average was determined as such:. The information provided always allows for getting close enough in reproducing, as shown it did.
Okay, now we have a bit more information. But his vague and cryptic explanation reveals more flaws:. The formula is ill-specified by failing to explain: This makes BECI unreproducible hence unreliable.
Why even make the moving average period dynamic instead of fixed? This appears to be a kludge the author needs as his model estimates energy based on the volatile Bitcoin price instead of the hashrate. He should be publishing these changes publicly. Frequently changing the averaging period is misleading to readers, who are not aware the energy estimate can vary by 1.
I reported this to the author on 30 December , but he does not seem to want to fix it…. On 17 April , the author published supplemental material that continues to make the same mistakes, and introduces new ones. His lower bound assumes mining machines are always operated until their very last profitable day. In fact miners routinely decomission older hardware that is still slightly profitable and replace it with more efficient and more profitable hardware. Everyday miners re-evaluate the economic value of their choices.
At any point they may decide, if they have a given fixed electrical capacity, that it becomes more worthwhile to spend this electricity on more efficient hardware than to continue operating barely profitable hardware. First of all it is unscientific and misleading for BECI to claim to know a precise estimate of the electricity consumption of Bitcoin. No one knows it because the market share of the various ASICs is largely unknown, and no large-scale polling or study has ever been conducted to determine it.
A proper scientific method would be at least to estimate lower and upper bounds. BECI needs to accurately estimate the percentage of mining revenues spent on electricity. We can determine this in 2 different ways. The first way is to read my analysis Electricity consumption of Bitcoin: This analysis also computed that mining hardware is profitable below 0.
The second way is to model exactly the costs and revenues of various machines, as I have done in Economics of mining. BECI needs to calculate the average mining income by averaging the Bitcoin price over a few months , not weeks, as explained in critic 3. For details see Electricity consumption of Bitcoin: I will be happy to review your work and provide feedback before publication. It is professionally unacceptable to publish analyses that are so far off reality like BECI.
I would make the argument that the marginal cost also includes other capital expenditures data center building, etc and non-electrical operational expenditures labor to maintain and operate data centers, etc. And the network is mostly made of a small number of large miners, not the other way around large number of small miners.
It is claimed that BECI runs on the assumption that miners " never recover their investments capex ". This has never been stated or implied by the information provided on BECI, and may relate to a misunderstanding.
BECI assumes that the entire network is running at roughly break even, but this doesn't mean this is the case for every miner part of it. New machines may still earn themselves back easily under this assumption. Second I'd like to add that the case laid out in this article is extremely optimistic on the electricity consumption of the Bitcoin network. It is stated that " the network's average efficiency falls between 0. This one was released just a few months before.
These machines wouldn't even have hit the market if the estimates in this article were true, as they would have been producing a loss as of day 1. See quote from your own site in 3rd paragraph. Also you are wrong: It seems you didn't read my post. I provide links and references to each one of them in section 1 http: BitFury's latest 16nm chip achieves 0. KnC's 16nm Solar 0. Spondoolies's 28nm PickAxe 0. Bitmain's 28nm BM 0. Avalon's 28nm A 0. It seems you don't know the market of ASICs very well.
Some consistency would be nice. You also published this post a bit too soon making it hard to discuss. If you had contacted me in advance I could have told you I was collecting data to cover 1 adjustment period in order to account for blocks being created faster or slower than 10 minutes on average. This held up the release of version 3, which includes some other adjustments as well. In particular the average costs mentioned here has been relaxed quite a bit. Looking at it from the bright side, you might like the updates.
But it's not a random collection of hardware. I didn't hand pick the most efficient ones to prove my point. Now, there are a lot of companies that never released silicon, failed, ran out of money, etc, see: I'll say it again: But you didn't check how your estimate works out economically. You're saying the network is running at something like 0.
We can translate this to costs directly since we can assume miners get 1 KWh per 5 cents spent on costs per your own numbers. This is remarkable considering mining revenues are far from their all-time high as shown earlier. The trend can be explained considering the drop in the average price paid per KWh.
As a result of mining happening on an industrial rather than on a residential scale, the revenues from mining can now pay for more kilowatts-hours than ever before. This number is frequently determined by taking the efficiency of the best available miner and applying this to the network hashrate.
Since the total network hashrate was about 3. We would then find an electricity consumption of almost 3 TWh per year. This approach is obviously flawed, as it ignores many older machines that are still profitable. In reality, new machines will slowly make older ones obsolete, starting with the least efficient ones. After all, based on economic theory, they are objectively expected run for as long as their electricity costs remain below the produced revenues.
The previous leaves the question how much electricity the total Bitcoin network is consuming exactly. By the end of March , it could be anywhere in between 3 to 16 terawatt-hours per year. Objectively, electricity consumption should be closer to the upper bound based on the break-even mining efficiency , as any less would indicate miners could still profit from adding more hashrate.
At the very least the network should therefore be trending towards the break-even point. Regardless of the exact electricity consumption, we have observed that this number on the rise due to miners squeezing in more kilowatt-hours in the same and even decreasing amount of revenue. At the same time, the price of Bitcoin is back at record-highs.
This is enough to power a single U. The total costs for miners can be decomposed in operational cost s mainly electricity and capital equipment cost s. The effective percentage cost will be lower than this number when the price is rising, due to the lag introduced in the next section. Based on the performance of both the older Antminer S5 and Antminer S7 it can be expected that the average lifetime from the production phase up until the moment profitability falls below the break-even point of the Antminer S9 will be close to two years exceeding at least days.
At a rate of 5 cents per kilowatt-hour this yields the following estimate for the lifetime costs of an Antminer S9: Similar to before, it is expected that more of these machines will be added until the marginal costs equal the marginal revenue.
Once the network reaches an equilibrium, the average electricity costs of the network would then have to equal at least 60 percent or more of the total costs. This finding is in line with Croman et al. After finding the operational costs of mining, it required to know how much is being spent per kilowatt-hour KWh , in order to be able to arrive at an energy consumption estimate. For industrial scale miners this is a limited price, although it still differs significantly per country.
It can be 4 cents per KWh in some Chinese regions, as confirmed by several professional miners. Over the years this has caused the total energy consumption of the Bitcoin network to grow to epic proportions, as the price of the currency reached new highs. The entire Bitcoin network now consumes more energy than a number of countries, based on a report published by the International Energy Agency.
If Bitcoin was a country, it would rank as shown below. The result is shown hereafter. Coal-based electricity is available at very low rates in this country.
Even with a conservative emission factor , this results in an extreme carbon footprint for each unique Bitcoin transaction. To put the energy consumed by the Bitcoin network into perspective we can compare it to another payment system like VISA for example.
We also know VISA processed With the help of these numbers, it is possible to compare both networks and show that Bitcoin is extremely more energy intensive per transaction than VISA note that the chart below compares a single Bitcoin transaction to , VISA transactions. Of course, these numbers are far from perfect e. More energy efficient algorithms, like proof-of-stake, have been in development over recent years.
In proof-of-stake coin owners create blocks rather than miners, thus not requiring power hungry machines that produce as many hashes per second as possible. Because of this, the energy consumption of proof-of-stake is negligible compared to proof-of-work. The only downside is that there are many different versions of proof-of-stake, and none of these have fully proven themselves yet. Even though the total network hashrate can easily be calculated, it is impossible to tell what this means in terms of energy consumption as there is no central register with all active machines and their exact power consumption.
This arbitrary approach has therefore led to a wide set of energy consumption estimates that strongly deviate from one another, sometimes with a disregard to the economic consequences of the chosen parameters. The Bitcoin Energy Consumption Index therefore proposes to turn the problem around, and approach energy consumption from an economic perspective. The index is built on the premise that miner income and costs are related.
Since electricity costs are a major component of the ongoing costs, it follows that the total electricity consumption of the Bitcoin network must be related to miner income as well.
To put it simply, the higher mining revenues, the more energy-hungry machines can be supported. How the Bitcoin Energy Consumption Index uses miner income to arrive at an energy consumption estimate is explained in detail here , and summarized in the following infographic:.