Billion Electric is a global leading broadband networking provider for more than 42 years. We provide a complete portfolio of M2M, 3G, 4G LTE, and DSL networking for SOHO/SMB users. Through our dedication to providing customer-oriented innovation and trusted partnerships, we are committed to creating optimal values for our current telecom operators, enterprises partners and future consumers. Billion Electric provides a complete portfolio of M2M, LTE, and DSL networking for SOHO/SMB users. (M2M/LTE/Wireless/Industrial /In-Vehicle/Outdoor/Enterprise Routers, LED Driver, Power Supply). Boost your high-speed wireless network at home or office! The Billion BiPAC 3011N is ideal for home and office users to upgrade their wireless capability of noteb ook, handheld or desktop PC to a wireless-N network a t blazing-fast Wireless-N speeds, with 6 times data rate and 3 times wireless coverage of an 802.11g network device.
With state-of-the-art DSP technology and mixed-mode signal technology, the RTL8153 offers high-speed transmission over CAT 5 UTP cable or CAT 3 UTP (10Mbps only) cable. Functions such as Crossover Detection and Auto-Correction, polarity correction, adaptive equalization, cross-talk cancellation, echo cancellation, timing recovery, and error correction are implemented to provide robust transmission and reception capabilities. The RTL8153 features embedded One-Time-Programmable (OTP) memory that can replace the external EEPROM (93C46/93C56/93C66/TWSI).
What's New:
- Windows 10 version 10.10
- Windows 8 version 8.31
- Windows 7 version 7.24
- Windows Vista version 6.13
- Windows XP version 5.9
The RTL8153 features USB 3.0 to provide higher bandwidth and improved protocols for data exchange between the host and the device. USB 3.0 also offers more advanced power management features for energy saving.
Advanced Configuration Power management Interface (ACPI)—power management for modern operating systems that are capable of Operating System-directed Power Management (OSPM)—is supported to achieve the most efficient power management possible. In addition to the ACPI feature, remote wake-up (including AMD Magic Packet and Microsoft Wake-Up Frame) is supported in both ACPI and APM (Advanced Power Management) environments.
The RTL8153 supports Microsoft Wake Packet Detection (WPD) to provide Wake-Up Frame information to the OS, e.g., PatternID, OriginalPacketSize, SavedPacketSize, SavedPacketOffset, etc. WPD helps prevent unwanted/unauthorized wake-up of a sleeping computer.
The RTL8153 supports ‘RealWoW!’ technology to enable remote wake-up of a sleeping PC through the Internet. This feature allows PCs to reduce power consumption by remaining in low power sleeping state until needed.
Note: The ‘RealWoW!’ service requires registration on first time use.
The RTL8153 supports Protocol offload. It offloads some of the most common protocols to NIC hardware in order to prevent spurious wake-up and further reduce power consumption. The RTL8153 can offload ARP (IPv4) and NS (IPv6) protocols while in the D3 power saving state.
The RTL8153 supports the ECMA (European Computer Manufacturers Association) proxy for sleeping hosts standard. The standard specifies maintenance of network connectivity and presence via proxies in order to extend the sleep duration of higher-powered hosts. It handles some network tasks on behalf of the host, allowing the host to remain in sleep mode for longer periods. Required and optional behavior of an operating proxy includes generating reply packets, ignoring packets, and waking the host.
The RTL8153 supports IEEE 802.3az-2010, also known as Energy Efficient Ethernet (EEE). IEEE 802.3az-2010 operates with the IEEE 802.3 Media Access Control (MAC) Sublayer to support operation in Low Power Idle mode. When the Ethernet network is in low link utilization, EEE allows systems on both sides of the link to save power.
The RTL8153 is fully compliant with Microsoft NDIS5, NDIS6 (IPv4, IPv6, TCP, UDP) Checksum features, and supports IEEE 802 IP Layer 2 priority encoding and IEEE 802.1Q Virtual bridged Local Area Network (VLAN). The above features contribute to lowering CPU utilization, especially benefiting performance when in operation on a network server.
The RTL8153 is suitable for multiple market segments and emerging applications, such as desktop, mobile, workstation, server, communications platforms, docking station, and embedded applications.
Features:
- Hardware
- Integrated 10/100/1000M transceiver
- Auto-Negotiation with Next Page capability
- Supports USB 3.0, 2.0, and 1.1
- Supports CDC-ECM
- Supports LPM (Link Power Management)
- Supports pair swap/polarity/skew correction
- Crossover Detection & Auto-Correction
- Supports Wake-On-LAN and ‘RealWoW!’ (Wake-On-WAN) Technology
- Supports ECMA-393 ECMA ProxZzzy Standard for sleeping hosts
- XTAL-Less Wake-On-LAN
- Supports power down/link down power saving
- Transmit/Receive on-chip buffer support
- EEPROM Interface
- Embedded OTP memory can replace external EEPROM
- Built-in switching regulator and LDO regulator
- Supports Customizable LEDs
- Supports hardware CRC (Cyclic Redundancy Check) function
- LAN disable with GPIO pin
- Supports 25MHz or 48MHz external clock (from oscillator or system clock source)
- SPI Flash Interface
- 48-pin QFN ‘Green’ package
Download Previous Versions:
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- 10.6 MB
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The Bitcoin Energy Consumption Index provides the latest estimate of the total energy consumption of the Bitcoin network.
NEW: Study reveals Bitcoin’s electricity consumption is underestimated and finds the network “represents close to half of the current global data centre electricity use” (August 2020).
Download data.Annualized Total Footprints
36.95 Mt CO2
Comparable to the carbon footprint of New Zealand.77.78 TWh
Comparable to the power consumption of Chile.11.19 kt
Comparable to the e-waste generation of Luxembourg.Single Transaction Footprints
309.26 kgCO2
Equivalent to the carbon footprint of 685,438 VISA transactions or 51,544 hours of watching Youtube.651.08 kWh
Equivalent to the power consumption of an average U.S. household over 22.32 days.93.72 grams
Equivalent to the weight of 1.44 'C'-size batteries or 2.04 golf balls. (Find more info on e-waste here.)*The assumptions underlying this energy consumption estimate can be found here. Criticism and potential validation of the estimate is discussed here.
**The minimum is calculated from the total network hashrate, assuming the only machine used in the network is Bitmain’s Antminer S9 (drawing 1,500 watts each). On February 13, 2019, the minimum benchmark was changed to Bitmain’s Antminer S15 (with a rolling average of 180 days), followed by Bitmain’s Antminer S17e per November 7, 2019 and Bitmain’s Antminer S19 Pro per October 31, 2020.
***Note that the Index contained the aggregate of Bitcoin and Bitcoin Cash (other forks of the Bitcoin network have not been included). The latter has been removed per October 1, 2019.
Did you know Bitcoin runs on an energy-intensive network?
Ever since its inception Bitcoin’s trust-minimizing consensus has been enabled by its proof-of-work algorithm. The machines performing the “work” are consuming huge amounts of energy while doing so. Moreover, the energy used is primarily sourced from fossil fuels. The Bitcoin Energy Consumption Index was created to provide insight into these amounts, and raise awareness on the unsustainability of the proof-of-work algorithm.
A separate index was created for Ethereum, which can be found here.
What kind of work are miners performing?
New sets of transactions (blocks) are added to Bitcoin’s blockchain roughly every 10 minutes by so-called miners. While working on the blockchain these miners aren’t required to trust each other. The only thing miners have to trust is the code that runs Bitcoin. The code includes several rules to validate new transactions. For example, a transaction can only be valid if the sender actually owns the sent amount. Every miner individually confirms whether transactions adhere to these rules, eliminating the need to trust other miners.
The trick is to get all miners to agree on the same history of transactions. Every miner in the network is constantly tasked with preparing the next batch of transactions for the blockchain. Only one of these blocks will be randomly selected to become the latest block on the chain. Random selection in a distributed network isn’t easy, so this is where proof-of-work comes in. In proof-of-work, the next block comes from the first miner that produces a valid one. This is easier said than done, as the Bitcoin protocol makes it very difficult for miners to do so. In fact, the difficulty is regularly adjusted by the protocol to ensure that all miners in the network will only produce one valid block every 10 minutes on average. Once one of the miners finally manages to produce a valid block, it will inform the rest of the network. Other miners will accept this block once they confirm it adheres to all rules, and then discard whatever block they had been working on themselves. The lucky miner gets rewarded with a fixed amount of coins, along with the transaction fees belonging to the processed transactions in the new block. The cycle then starts again.
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The process of producing a valid block is largely based on trial and error, where miners are making numerous attempts every second trying to find the right value for a block component called the “nonce“, and hoping the resulting completed block will match the requirements (as there is no way to predict the outcome). For this reason, mining is sometimes compared to a lottery where you can pick your own numbers. The number of attempts (hashes) per second is given by your mining equipment’s hashrate. This will typically be expressed in Gigahash per second (1 billion hashes per second).
Sustainability
The continuous block mining cycle incentivizes people all over the world to mine Bitcoin. As mining can provide a solid stream of revenue, people are very willing to run power-hungry machines to get a piece of it. 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. If Bitcoin was a country, it would rank as shown below.
Apart from the previous comparison, it also possible to compare Bitcoin’s energy consumption to some of the world’s biggest energy consuming nations. The result is shown hereafter.
Carbon footprint
Bitcoin’s biggest problem is perhaps not even its massive energy consumption, but the fact most mining facilties in Bitcoin’s network are located in regions (primarily in China) that rely heavily on coal-based power (either directly or for the purpose of load balancing). To put it simply: “coal is fueling Bitcoin” (Stoll, 2019).
Thinking about how to reduce CO2 emissions from a widespread Bitcoin implementation
— halfin (@halfin) 27 januari 2009
Locating miners
Determining the exact carbon impact of the Bitcoin network has been a challenge for years. Not only does one need to know the power requirement of the Bitcoin network, but one also need to know where this power is coming from. The location of miners is a key ingredient to know how dirty or how clean the power is that they are using.
Just like it’s not easy to find out what machines are active in the Bitcoin network, determining location isn’t an easy feat either. Initially the only information available to this end was the common belief that the majority of miners were located in China. Since we know the average emission factor of the Chinese grid (around 700 grams of carbon dioxide equivalent per kilowatt-hour), this can be used for a very rough approximation of the carbon intensity of the power used for Bitcoin mining. Assuming that 70% of Bitcoin mining is taking place in China, and that 30% of mining is completely clean, this yields a weighted average carbon intensity of 490 gCO2eq/kWh. This number can subsequently be applied to a power consumption estimate of the Bitcoin network to determine its carbon footprint.
A more detailed estimate
Later on, more granular information became available in the Global Cryptocurrency Benchmarking Study by Garrick Hileman and Michel Rauchs from 2017. In this study, they identified facilities representing roughly half of the entire Bitcoin hash rate, with a total (lower bound) consumption of 232 megawatts. Chinese mining facilities were responsible for about half of this, with a lower bound consumption of 111 megawatts. This information can be used to get a more accurate idea of the carbon emission factor in grams of carbon dioxide equivalent per kilowatt-hour (gCO2eq/kWh) that applies to the electricity used for mining.
The table below features a breakdown of the energy consumption of the mining facilities surveyed by Hileman and Rauchs. By applying the emission factors of the respective country’s grid, we find that the Bitcoin network had a weighted average carbon intensity of 475 gCO2eq per kWh consumed. (This number is currently applied to determine the carbon footprint of the Bitcoin network based on the Bitcoin Energy Consumption Index.)
| Location | Power consumption (megawatts) | % of surveyed facilities | Carbon intensity (gCO2eq/kWh) |
|---|---|---|---|
| China | 111 | 47.60 | 711 |
| Georgia | 60 | 25.80 | 231 |
| United States | 27 | 11.60 | 489 |
| Canada | 18 | 7.70 | 158 |
| Sweden | 10 | 4.3 | 13 |
| Iceland | 5 | 2.1 | 0 |
| Estonia | 2 | 0.90 | 793 |
| Total / Weighed Average | 233 | 100.00 | 475 |
Breakdown of regional carbon intensity
One can argue that specific locations in the listed countries may offer less carbon intense power. In 2018 Bitcoin company Coinshares suggested that the majority of Chinese mining facilities were located in Sichuan province, using cheap hydropower for mining Bitcoin. Subsequent studies have, however, never been able to support this claim and/or found the opposite. Confronted with this evidence, the lead author of the Coinshares paper had to admit “mistakes” were made.
The main challenge here is that the production of hydropower (or renewable energy in general) is far from constant. In Sichuan specifically the average power generation capacity during the wet season is three times that of the dry season. Because of these fluctuations in hydroelectricity generation, Bitcoin miners can only make use of cheap hydropower for a limited amount of time.
In a study titled “The Carbon Footprint of Bitcoin” (Stoll et al. 2019) properly account for these regional differences (while also introducing a new method to localize miners based on IP-addresses), but still find a weighted average carbon intensity of 480-500 gCO2eq per kWh for the entire Bitcoin network (in line with previous and more rough estimations).
Using a similar approach, Cambridge in 2020 provided a more detailed insight into the localization of Bitcoin miners over time. Charting this data, and adding colors based on the carbon intensity of the respective power grids, we can reveal significant mining activity in highly polluting regions of the world during the Chinese dry season (as shown below). On an annual basis, the average contribution of renewable energy sources therefore remains low. When Cambridge subsequently surveyed miners (also in 2020), respondents indicated only 39% of their total energy consumption actually came from renewables.
Key challenges for using renewables
It is important to realize that, while renewables are an intermittent source of energy, Bitcoin miners have a constant energy requirement. A Bitcoin ASIC miner will, once turned on, not be switched off until it either breaks down or becomes unable to mine Bitcoin at a profit. Because of this, Bitcoin miners increase the baseload demand on a grid. They don’t just consume energy when there is an excess of renewables, but still require power during production shortages. In the latter case Bitcoin miners have historically ended up using fossil fuel based power (which is generally a more steady source of energy).
Further substantiation on why Bitcoin and renewable energy make for the worst match can be found in the peer-reviewed academic article “Renewable Energy Will Not Solve Bitcoin’s Sustainability Problem” featured on Joule. With climate change pushing the volatility of hydropower production in places like Sichuan, this is unlikely to get any better in the future.
Comparing Bitcoin’s energy consumption to other payment systems
To put the energy consumed by the Bitcoin network into perspective we can compare it to another payment system like VISA for example. According to VISA, the company consumed a total amount of 740,000 Gigajoules of energy (from various sources) globally for all its operations. This means that VISA has an energy need equal to that of around 19,304 U.S. households. We also know VISA processed 138.3 billion transactions in 2019. 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 100,000 VISA transactions). The difference in carbon intensity per transaction is even greater (see footprints), as the energy used by VISA is relatively “greener” than the energy used by the Bitcoin mining network. The carbon footprint per VISA transaction is only 0.45 grams CO2eq.
Of course, VISA isn’t perfectly representative for the global financial system. But even a comparison with the average non-cash transaction in the regular financial system still reveals that an average Bitcoin transaction requires several thousands of times more energy. One could argue that this is simply the price of a transaction that doesn’t require a trusted third party, but this price doesn’t have to be so high as will be discussed hereafter.
Alternatives
Proof-of-work was the first consensus algorithm that managed to prove itself, but it isn’t the only consensus algorithm. 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. Bitcoin could potentially switch to such an consensus algorithm, which would significantly improve environmental sustainability. The only downside is that there are many different versions of proof-of-stake, and none of these have fully proven themselves yet. Nevertheless the work on these algorithms offers good hope for the future.
Energy consumption model and key assumptions
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). In the past, energy consumption estimates typically included an assumption on what machines were still active and how they were distributed, in order to arrive at a certain number of Watts consumed per Gigahash/sec (GH/s). A detailed examination of a real-world Bitcoin mine shows why such an approach will certainly lead to underestimating the network’s energy consumption, because it disregards relevant factors like machine-reliability, climate and cooling costs. 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 (also in peer-reviewed academic literature here), and summarized in the following infographic:
Billion Electric Network Map
Bitcoin miner earnings and (estimated) expenses are currenly as follows:
$17,355,327,868
Total value of mining rewards (including fees) per year.$3,889,109,037
Assuming a fixed rate of 5 cents per kilowatt-hour.22.41%
Estimated ratio of electricity costs to total miner income.Note that one may reach different conclusions on applying different assumptions (a calculator that allows for testing different assumptions has been made available here). The chosen assumptions have been chosen in such a way that they can be considered to be both intuitive and conservative, based on information of actual mining operations. In the end, the goal of the Index is not to produce a perfect estimate, but to produce an economically credible day-to-day estimate that is more accurate and robust than an estimate based on the efficiency of a selection of mining machines.
Criticism and Validation
Even though critics like Marc Bevand and Jonathan Koomey have long argued that the estimates provided by the Bitcoin Energy Consumption Index are “seriously flawed”, the launch of the Cambridge Bitcoin Electricity Consumption Index (CBECI) in 2019 managed to prove the opposite. The latter index was based on the alternative methodology provided by Bevand (which is strongly advocated by Koomey), but failed to produce significantly different estimates. In fact, the Bitcoin Energy Consumption Index and the Cambridge Bitcoin Electricity Consumption Index are mostly in perfect agreement with each other.
Apart from the energy consumption estimates, the resulting environmental impact (in the form of carbon footprint) has also been strongly contested by critics like Robert Sharratt and the company Coinshares. Specifically, Sharratt used the Coinshares mining report to argue that the network has limited environmental impact. Interestingly, the Coinshares mining report only implies that the network has limited environmental impact due to a large share of renewable energy usage, but doesn’t contain the words “carbon footprint” at all. This is an important omission, as it ignores that the carbon intensity of electricity bought in Sichuan (China), where miners are primarily located according to Coinshares, is nowhere near as low as one might expect. The Technical University of Munich (TUM) independently studied the environmental impact of the network while properly accounting for this, and concluded that “coal is fueling Bitcoin”. Their weighted emission factor for the whole Bitcoin network matched the one that is used to calculate the network’s carbon footprint, based on the Bitcoin Energy Consumption Index.
Forecasting
Of course, the Bitcoin Energy Consumption Index is also very much a prediction model for future Bitcoin energy consumption (unlike hashrate-based estimates that have no predictive properties). The model predicts that miners will ultimately spend 60% of their revenues on electricity. At the moment (January 2019), miners are spending a lot more on electricity. On January 22, 2019, the Bitcoin Energy Index was estimating that 100% of miner revenues ($2.3B) were actually spent on electricity costs. This can happen after a significant drop in mining revenues where mining becomes generally unprofitable. In this situation machines are removed from (rather than added to) the network. Since machine investments can be considered sunk costs (no longer relevant to the decision to continue mining), miners will continue to run their machines up until the point where the electricity costs exceed the amount of mined income (approaching 100%).
Based on 100% of revenues already being used to cover electricity expenses, the Energy Consumption Index would thus predict little change in Bitcoin’s energy consumption.