FEASIBILITY MODEL FOR SOLAR-POWERED CRYPTOCURRENCY MINING SETUPS

Southern Institute of Technology Journal of Applied Research - http://sitjar.sit.ac.nz

 FEASIBILITY MODEL FOR SOLAR-
 POWERED CRYPTOCURRENCY MINING
 SETUPS
 Naveed ur Rehman1*, Max Yap2, Mujaddad Afzal1, Abdul Rehman3 and Christopher
 Horasia1
1
 Department of Trades and Technology, Southern Institute of Technology, Invercargill, New
Zealand.
2
 Department of New Media Arts and Business, Southern Institute of Technology,
Invercargill, New Zealand.
3
 Department of Health Humanities Computing, Southern Institute of Technology, Invercargill,
New Zealand.

*Corresponding author:

Tel: +6439482772

Email address: naveed.urrehman@sit.ac.nz

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Abstract

This paper presents a model for assessing the financial viability of cryptocurrency mining
setups powered by off-grid solar photovoltaic (PV) systems. The model considers the features
of mining hardware, the network attributes, the price of virtual currency and the solar potential
of the installation site, to predict the payback period of the investment in months. As a case
study, the feasibility of mining using various state-of-the-art Application-Specific Integrated
Circuits (ASICs) and Graphics Processing Units (GPUs), powered by PV installed in New
Zealand has been investigated. The results show that for ASICs setups, the initial cost is very
high compared to GPU setups. However, considering the best-performing cryptocurrencies, the
payback period for ASICs is much shorter than for GPU setups. This work will help to improve
the sustainability of cryptocurrency mining businesses by reducing their dependence on
exhaustible energy resources and their impact on the environment.

Keywords: Off-grid PV; Proof-of-Work; Renewable Energy; Payback

Highlights:

 A feasibility model for solar powered cryptocurrency mining is developed.
 It considers hardware, network, cryptocurrency and solar energy-related parameters.
 The model evaluates the upfront costs and the payback periods of the setups.
 In a case study, ASICs- and GPUs-based mining setups in NZ are analyzed.
 ASICs setups have high upfront costs but have faster payback periods.

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Nomenclature:

 Cost of BOS ($)
 Cost of miner ($)
 Cost of PV panels ($)
 ̅
 Cost-per-watt of PV panel ($/W)
 Total cost of PV system ($)
 Daily energy consumed by miner (W.hr/day)
 Daily Energy to be supplied by the PV system (W.hr/day)
 Hash rate of miner (hash/sec)
 Hash rate of the network (hash/s)
 Payback period (months)
 Daily revenue in terms of coins earned (coins/day)
 Market price of coin ($/coin)
 Power demand of miner (W)
 Peak Sun Hours (hrs/day)
 Daily revenue ($/day)
 Block reward (coins/block)
 Time required to mine a single block (sec/block)
 Peak power of PV system (W)

1 Introduction
Permanently storing the creation and modification time stamp of any digital asset (e.g.,
document, picture or video) can be crucial in several real-world applications. However, if that
information is stored in some modifiable media (such as a hard drive, memory stick or the
cloud), then it can be easily tampered with. Haber and Stornetta (1990) proposed the first safe
method for such recordkeeping in the form of sequentially connected and digitally encrypted
records. Almost two decades later, a developer, working under the pseudonym Satoshi
Nakamoto, called that timestamped and encrypted record a Block and thus coined the term
Blockchain to represent a sequence of blocks (Nakamoto, 2008).

Nowadays, blockchain also refers to the whole technology that ensures the security of records
and their timestamps (Litchfield & Khan, 2021). The key concept behind this technology is
decentralization of the information, which involves the foolproof distribution of the complete
history of records on several machines (called nodes) that are not under the control of a single
entity (e.g., a person, company, or community). This way, if the record on a single node is
tampered with, the other nodes can easily recognize that by comparing the provided copy with
the stored copy of the records. Despite such a transparent mechanism, there are still some
limitations with this technology. For example, running a database on blockchain results in high
data redundancy (i.e., copies of the same records on all the nodes), slow speed of distribution
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and records querying (due to network latency) and very high energy consumption in running
multiple nodes.

While blockchain has applications in several key sectors of society (e.g. health (Kuo et al.,
2017), education (Chen et al., 2018), manufacturing (Lohmer & Lasch, 2020), and e-
government (Hou, 2017)), one of the greatest is the revolutionization of public ledgers. In
general, a public ledger holds a collection of accounts in which transactions are recorded.
Traditionally, public ledgers were always under the control of a centralized intermediary, such
as a bank. These intermediaries were responsible for recording the details of transactions; e.g.,
who has deposited what amount, who has transferred what amount to whom and so on.
However, given the issues with these intermediaries, such as trust, transparency, security,
privacy and policies, there has always been a need for a system that can safely run without
them. Putting public ledgers on the blockchain resolved the matter (Monrat et al., 2019). This
implementation may look uncomplicated but due to the inherent limitations of blockchain
technology, its immense growth has given rise to several other problems over the past decade.

At a very fundamental level, the addition of a block to the blockchain requires validation and
consensus mechanisms. In the validation mechanism, the node, if it has a full copy of up-to-
date records, confirms whether a requested transaction is valid or not. For example, in the case
of public ledger processing, the node will validate whether the sender has enough money to
send or not. Since the mechanism for disseminating the request to validate the block (hence
updating the blockchain) is peer-to-peer (i.e. it is initially sent to a couple of nodes and these
nodes disseminate it to further nodes and so on), it is highly likely that the same node will
receive the request more once from various sources. This creates a problem of double-
spending: i.e. the actual transaction is done once but due to the dissemination mechanism and
the unavoidable network latency issues, some nodes may record the transaction more than once.
Hence, it would be impossible to have exactly the same true copy of the records on all nodes.

To mitigate this problem, a consensus mechanism was developed. In this, each node receiving
a validation request is also given a challenging puzzle, whose solution is pre-requisite to adding
the block. The difficulty level of the puzzle is set such that ideally only one, or in reality, a
handful of nodes can find the correct solution. Finding this solution, also known as solving the
hashes, is not only time consuming but also requires a lot of energy to run the computations.
So, to reward the winning node, which is the one that solves the puzzle first and presents it to
the network (also known as proof-of-work), the blockchain mints some virtual coins, known as
cryptocurrency, and transfers them to the winning miner’s account (known as a virtual wallet),

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once again by means of the decentralized public ledger. The process from validation to getting
the cryptocurrency in the wallet is known as mining.

The very first, and the most famous, application of a blockchain-based public ledger is bitcoin.
It is also the name of the virtual currency awarded to the winning miners. However, at present,
there are more than 5000 alternate public ledger applications as well. The virtual currency
awarded in these systems is generally known as Altcoin. Some famous examples of altcoins
include Ethereum (ETH) and Dodgecoin (DOGE) (Li, 2019; bitFlyer, n.d.).

It is also important to note that some versions of such ledgers are operating on proof-of-stake
(rather than proof-of-work), in which the network, either randomly and/or based on the number
of coins held by the node, decides the winner; hence mining is not needed at all. Some ledgers
will move to proof-of-stake after minting the promised number of coins.

Although cryptocurrency itself has no backing, such as a precious metal (e.g., gold or silver in
the past) or government bodies behind Fiat currencies, over time it has acquired value since
businesses, especially large local and global brands such as Microsoft, PayPal and Starbucks,
started accepting cryptocurrencies (Lisa, 2021). The price of a cryptocurrency against any Fiat
currency is still based on speculation and therefore is highly volatile.

For any node owner, the whole aim of participating in a blockchain network is to get rewards.
Because of the rapidly growing number of nodes, the competition is becoming more intense
(Altman et al., 2019). In response to that, several technological advancements, in terms of
improving the speed of mining hardware, have been developed. One of these is the use of
Graphics Processing Units (GPUs) for mining since they can perform much faster than normal
Central Processing Units (CPUs). Another is the invention of Application-Specific Integrated
Circuits (ASICs), which are manufactured to perform mining. Such hardware is several times
faster compared to GPUs, but each type can mine only the coins for which it is programmed.
Cloud mining is another type of mining opportunity where one can ‘hire’ mining hardware for
a certain period of time. The user has to pay a fixed amount for beginning the contract and a
small fraction of coins on the go as a fee. Since the probability of becoming the wining node
during individual mining is almost nil, miners now prefer to join mining pools, which distribute
the workload of solving the puzzle, as well as the reward, among the participants.

With the passage of time, the speed requirements, given by hashes/sec, of the mining hardware
have dramatically increased and so has their electric power demand. According to Cambridge’s
Centre for Alternative Finances (Cambridge Bitcoin Electricity Consumption Index, n.d.), the

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bitcoin mining network power demand and annual energy consumption are estimated at around
10.33 GW and 79.73 TWh, respectively. This is more than the overall installed capacity and
production of New Zealand (Ministry of Business, Innovation and Employment, n.d.), at 9.448
GW 42.858 TWh, respectively. On the top of that, mining is also causing an alarming impact
on the environment. As a result, many sustainability activists and influencers have started
raising their voices against mining activities. In some places, governments have also started
putting legal bans on mining (Browne, 2021; Clifford, 2021).

Perhaps, if the energy demand of mining hardware could be met via renewable energy
technologies (such as solar, wind, hydroelectric, geothermal, biomass, wave, tidal and ocean
thermal), the system could survive. Of the various renewable energies, solar energy is
abundantly available almost everywhere on earth. Also, since the technology has matured
considerably, it is now fairly simple to obtain and install solar energy conversion devices,
known as photovoltaic (PV) panels, and start generating electricity (Rehman, 2018).

The major drawback of solar energy systems is their very high upfront cost. Therefore, while
planning for such projects, it is always imperative to evaluate their financial viability in terms
of payback periods. In general, a feasibility study is performed to compare the pros and cons
of off-grid solar systems and on-grid solar systems. In the former systems, all the energy
demand is met by the PV panels. However, such systems are quite expensive as they require
batteries to store energy when there is low or no solar energy available (e.g., at night or on
cloudy days). In contrast, in the latter system, the energy generated from the PV panels is sold
back to the grid, but the energy demand is still met by the grid. Such systems are cheap as they
do not require batteries. However, since the off-grid system provides complete independence
from the grid, it seems more favourable to power cryptocurrency mining using such a system.

In the literature, there is a dearth of studies related to solar-powered cryptocurrency mining.
One of the initial attempts to develop and test a solar-powered mining setup was done by
Lippman and Ekblaw (2016) at MIT. The Avalon Nano ASIC Miner was used to build a micro-
mining setup, which was powered by a 30-Watt PV panel. The setup was able to produce only
bitcoin dust, which is an untransactable amount. Then, Purnama et al. (2019) from Kumamoto
University also developed a micro-mining system based on an Asus Tinker Board CPU, GPU
miners and a Futurebit Moonlander 2 ASIC miner. This was built to mine Litecoin (LTC),
which is an altcoin. The system was powered by a 20-Watt PV panel. The authors concluded
that the profits did not justify running such small-scale setups. Govender (Govender, 2019)
performed a theoretical study on sustainable cryptocurrency mining as a concept and identified

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the potential business models that could be considered eco-innovative. The results indicated
that large-scale mining using renewable (including solar) energy has good potential but could
not come to a definite conclusion about the magnitudes of the profitability. Zhai (2019)
explored the use of solar energy to construct a sustainable and profitable business model
exclusively for commercial mining setups. It was estimated that a 2-kW mining setup, powered
by a 6.9 kW solar PV system, would have a payback period of around 7 years.

The existing research is more focused on a build-and-test approach than on formulating a
method to evaluate the viability of a project beforehand. Therefore, this paper presents a model
to perform feasibility analyses of solar-powered cryptocurrency mining, which can be used as
a design procedure.

2 Model
A typical off-grid solar-powered mining setup will consist of an array of solar PV panels, and
a Balance of System (BOS), which includes a charge controller, inverter, battery bank and
cables, and the mining hardware, as shown in Figure 1.

 Figure 1: A typical off-grid solar powered cryptocurrency mining setup

The daily energy ( , . ℎ / ) consumed by any mining hardware depends upon its
power requirements ( , ) and its operating time, which is recommended as 24 hrs, and
can be obtained using Equation 1:

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 = ∙ 24 ℎ 1

A PV system must be designed to provide not only this energy, but also to compensate for the
losses incurred by the electrical system (e.g. cables, inverters and batteries), the installation
setup (including factors such as mounting at suboptimum tilt and orientation angle, shadowing
due to nearby obstacles such as buildings and trees, and manufacturing tolerance of panels) and
operating conditions (e.g. drop of efficiency due to high temperatures and reduction in yield
due to dirt accumulation). All these losses generally escalate the requirements by 50% (Chel et
al., 2009) and therefore, if ( . ℎ / ) is the amount of daily energy to be supplied by
the PV system, then:

 = ∙ 1.5 2

The peak power to be provided by the PV system would therefore be:

 = ⁄ 3

where (ℎ / ) is the peak sun hours, equivalent to the annual average daily global
solar radiation available at the site.

The total cost of the PV system would incorporate the cost of PV panels ( , $) and the cost
of the BOS ( , $), which includes mechanical mountings, cables, inverter and batteries. If
 ̅ , $/ ) is available, can be evaluated using:
the cost-per-watt for PV panels ( 

 ̅
 = ∙ 4

whereas, for the BOS, a general rule of thumb is that its cost is around 50% of the panels’ cost
(Zeman, 2012). Therefore:

 = ∙ 0.5 5

If the cost of mining hardware is given by ($) then the total cost of the system ( , $)
will be:

 = + + 6

The revenue ( , $/ ) from running the mining hardware will depend upon the number of
coins mined in a day ( , / ) and their market price ( , $/ ), such that:

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 = ∙ 7

The number of coins mined in a day depends on factors such as the hash rate of the hardware
( , ℎ ℎ/ ), the net hash-rate of the whole network ( , ℎ ℎ/ ), time required to mine a
single block ( , / ) and the block reward to the successful miner ( , s/block). This
is given by:

 ℎ 
 3600 ∙ 24
 ℎ 8
 = ∙ ∙ 
 
Finally, the payback period ( ), in months, for this system can be calculated as:

 12 ℎ 
 = ∙ 9
 365 

3 Results and Discussion
As a case study, the feasibility of several solar powered mining setups is analyzed in this
section. A list of the mining hardware considered in this work, along with costs and
specifications, is provided in Table 1. The three ASIC miners, Antiminer E9, Antiminer and
StrongU STU-U1++ can mine ETH, DOGE and Decred (DCR), respectively. The three GPU
based miners, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3080 Ti and AMD
Radeon RX 6800 are also considered, and they can mine ETH, Ergo (ERG) and ETH,
respectively. The cost and the power requirements for the GPUs don’t include the cost and the
power requirement of the computer as this can vary a lot; also, these are just a fraction of the
cost compared to the GPUs. The hash rate and the power requirements of the GPUs are
considerably lower than those of the ASICs.

 Table 1: Mining hardware characteristics (WhatToMine, n.d.)

 Hardware Type Coin Cost Hash Power
 ( ) rate requirement
 ( ) ( )

Antiminer E9 ASIC ETH US$ 30,000 (Ganti, 3.0 2,600 W
 2021) Th/s

Antiminer E7 ASIC DOGE US$ 12,800 9.5 3,425 W
 (Bitmain, n.d.) Gh/s

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StrongU STU-U1++ ASIC DCR US$ 1,253 52.0 2,200 W
 (CoinMiningCentral, Th/s
 n.d.)

NVIDIA GeForce RTX GPU ETH US$ 3,395 114 320 W
3090 (MightyApe, n.d.c) Mh/s

NVIDIA GeForce RTX GPU ERG $US 2,639 230 280 W
3080 Ti (MightyApe, n.d.b) Mh/s

AMD Radeon RX 6800 GPU ETH US$ 2,143 64 150 W
 (MightyApe, n.d.a) Mh/s
 ̅ = 1.0 $/ ). This is slightly above
The cost of solar panels is taken as NZ$ 1.0 per watt ( 
the average cost obtained from a survey conducted online, by noting the prices from the PV
panel distributers’ websites operating in NZ, as listed in Table 2.

 Table 2: Survey of solar panel costs

 Seller Panel’s peak power Cost Cost-per-
 ̅ )
 watt ( 

 The Market Club (The Market 200 W NZ$ 199.99 NZ$ 0.9999
 Club, n.d.) per W
 (themarket.com/nz/)

 FAZCORP Solar Energy 385 W NZ$ 379 NZ$ 0.9844
 (FAZCORP Solar Energy, per W
 n.d.) (www.fazcorp.co.nz)

 Adventure Kings (Adventure 160 W NZ$ 109 NZ$ 0.6812
 Kings, n.d.) per W
 (nz.adventurekings.com)

For the PSH, the data for various cities in NZ was obtained from an online database (Boxwell,
2019). These are listed in Table 3. In this work, an average value of = 4.0 ℎ / was
used.

 Table 3: Peak sun hours of various cities of New Zealand (Boxwell, 2019)

 City Peak sun hours ( )
 Auckland 4.18 hr/day

 Christchurch 3.63 hr/day

 Dunedin 3.38 hr/day (Lowest)

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 Hamilton 3.84 hr/day

 Lower Hutt 4.01 hr/day

 Manukau City 4.18 hr/day

 North Shore 4.18 hr/day

 Tauranga 4.34 hr/day (Highest)

 Waitakere 4.18 hr/day

 Wellington 4.01 hr/day

 Average 4.00 hr/day

Finally, to obtain the prices of currencies and their network-related parameters, up-to-date
values were obtained from online monitoring databases (WhatToMine, n.d.; CoinMarketCap,
n.d.). These are listed in Table 4. For this work, it was assumed that the prices and the network-
related parameters remain nearly stable during the payback period. This also excludes the
block-halving events (the reward is halved after every few years) that may occur with some of
these currencies.

 Table 4: Cryptocurrency coins and their network statistics (WhatToMine, n.d.;
 CoinMarketCap, n.d.)

 Cryptocurrency Market Price Net Hash Block Time Block Reward
 ( ) ( ) ( ) ( )

 Ethereum (ETH) US$ 2,370 523 Th/s 13.57 s/block 2.38 coins
 (ethereum.org) per coin

 Doge (DOGE) US$ 0.1967 292 Th/s 62 s/block 10,000 coins
 (dogecoin.com) per coin

 Decred (DCR) US$ 128.91 278 Ph/s 274 s/block 7.375064 coins
 (decred.org) per coin

 Ergo (ERG) US$ 5.4 11.8 Th/s 113 s/block 67.51 coins
 (ergoplatform.org) per coin

The model explained in Section 2 was simulated to obtain the desired peak power and energy
supply of the PV system and the results for each type of mining hardware are shown in Figure
2. For the Antiminer E9, although the initial cost was the highest, because of optimized power

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consumption, it would require a smaller PV system compared to the Antiminer E7. In general,
larger PV systems would be required to power up ASICs than the GPUs setups. Among GPUs,
the NVIDIA GeForce RTX 3090 was found to need the biggest PV system.

 Figure 2: Photovoltaic (PV) system sizes for cryptocurrency mining setups

Using the assumptions laid out above regarding the initial system cost, a simple comparison of
the six sample solar-powered mining setups shows that the entry cost varies dramatically
depending on the type of setup. We can decompose this into two factors: the cost of the mining
hardware, and the PV setup required to power it. The cost of the mining hardware varies to a
large degree, with the highest being the Antiminer E9 at US $30,000, and the lowest being the
StrongU STU-U1++ at US $1,253. The cost of the PV setup then varies according to the energy
needs of the mining hardware. The three ASIC setups have a much higher energy consumption
compared to the three GPU setups.

Figure 3 shows the entry cost of each solar-powered mining setup. The Antiminer E9 and E7
mining setups have very similar entry costs of around US $120,000, with the Strong-U STU-
U1++ being approximately 55% of the cost of the Antiminer setups at US $65,000. The GPU
mining setups, on the other hand, have a much lower entry cost. The NVIDIA-powered mining
setups are in the range of US $14,000 to $16,000, whereas the AMD-powered mining setup
can be assembled for less than $10,000.
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There are other considerations with regard to initial setup cost that the reader may wish to
integrate into their own analysis. Firstly, the prices of ASIC-based mining hardware are fairly
stable, as they are specialised computing devices that cannot be easily repurposed for other
means. This implies that the prices of ASIC-based mining hardware will largely rise and fall
in sync with the price of the underlying cryptocurrency that they generate. For financially-
inclined readers who are interested in modelling the financial risk profile of the entry cost of a
solar-powered mining setup, the most relevant exogeneous variable is the price of the
underlying cryptocurrency.

In contrast, over the past three years, the prices of GPU-based mining hardware have been
volatile, and largely on an upward trend. This is largely due to the fact that GPUs are multi-
purpose hardware with other use cases, such as computer gaming, Artificial Intelligence (AI)
research, and commercial rendering. This means that as the demand for these other applications
fluctuates, the prices of GPUs will rise and fall in tandem. In addition to this, as NVIDIA and
AMD continue to experience problems with the production capacity of their suppliers during
the COVID-19 pandemic, GPUs are set to rise in price in the near future, as of the time of
writing. The greater number of relevant factors that affect the cost of GPUs makes it much
harder to model the financial risk profile of a GPU solar-powered mining setup. One final
additional consideration is the exit value (disposal or liquidation value) of each solar-powered
mining setup. Readers may wish to consider the liquidation value of each setup in the event of
a specific cryptocurrency price drop, or in the worst case scenario, in the event that a general
crash of the cryptocurrency financial market takes place. As mentioned above, every solar-
powered mining setup can be decomposed into the mining hardware and the PV setup required
to power it. The PV setup retains its value in the event of a liquidation event, as it can be used
to generate electricity. Therefore, PV setups can either be sold to interested buyers who wish
to reduce their reliance on the grid, or be used to generate a revenue stream by selling electricity
back to the main grid.

Next, we consider the exit value of the mining hardware itself. As alluded to above, the value
of ASIC mining hardware is wholly dependent on the value of the underlying cryptocurrency.
In the event of a market crash, the ASIC mining hardware has a high probability of irreversible
value impairment, with exit values at a fraction of the entry cost. On the other hand, the value
of GPU-based mining hardware is more likely to be cushioned by the alternate use cases for
GPUs. GPUs that have been used for mining have a relatively shorter lifespan due to the
constant stress of operation, but they will still hold resale value for other purposes. In that

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regard, readers who are more risk-adverse may wish to choose a GPU-based mining setup as it
provides greater financial flexibility in terms of liquidation options.

 Figure 3: Total system cost for solar-powered cryptocurrency mining setups

Figure 4 shows a simple comparison of the daily revenue generated with each solar-powered
mining setup, using the point estimates for cryptocurrency values as shown in Table 2. At a
glance, the solar-powered Antiminer E9 setup generates the highest revenue per day at close to
NZ $300. Out of the three ASIC setups, the Strong-U STU-U1++ has the weakest performance
relative to the other two, at slightly less than NZ $100 per day.

The three GPU setups perform relative to their entry cost. The highest GPU revenue stream
comes from the RTX 3090 setup, and the lowest GPU revenue stream is generated by the RX
6800 setup. This is commensurate with their relative entry costs.

Two very important considerations that aspiring solar miners should take into account is the
relative volatility of the underlying cryptocurrencies and foreign exchange conversion rates,
and how that impacts the eventual revenue stream in terms of NZ $. Within the past year, the
market for different cryptocurrencies has received several economic shocks in the form of
governmental policy (e.g. the alleged Chinese government crackdown on cryptocurrency

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mining in general), whipsawing microeconomic demand related to use cases (e.g. Tesla’s
decision to accept some popular cryptocurrencies as payment), and other general
microeconomic supply trends (e.g. the global chip shortage caused by production bottlenecks
at TSMC, Samsung, and other fabricators). Readers should take the historical volatility of each
cryptocurrency as a starting point when evaluating the attractiveness of the different revenue
streams, and further consider the possibility of specific shocks to the market of the
cryptocurrency of their choice (e.g. the upcoming changes to proof-of-stake for Ethereum will
affect the revenue stream of the RTX 3090 and RX 6800 example setups).

The second issue relates to foreign exchange conversion rates. Historically, the foreign
exchange market has been relatively stable when considering forex pairs between countries in
the Anglosphere, such as the United States and New Zealand. However, the macroeconomic
policy changes within the past two years, as sparked by COVID-19, and spearheaded by the
reserve banks of both countries, could have a marked impact on the volatility of this forex pair.
For example, the quantitative easing that was put into place by the reserve banks of both
countries has depressed denominated interest rates significantly, but that may change very
suddenly in the event that either reserve bank decides to change its policy out of lockstep with
the other.

 Figure 4: Daily revenue from the solar-powered cryptocurrency mining setups

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We now consider Figure 5, which shows the relative payback periods for the six example solar-
powered mining setups. Once again, the reader is reminded that these figures are based on a
ceteris paribus analysis, and they assume implicitly that there are no drastic changes in the
point estimates used in the analysis.

First, we discuss why we have chosen payback period as a measure of relative financial returns.
Other potential measures include the internal rate of return (IRR%) and net present value
(NPV), based on a forecasted discount rate. We have chosen payback period as it is directly
relevant to the most important macroeconomic factor: the volatility of the cryptocurrency
market. The basic Black-Scholes Merton model illustrates this simple principle. As the time to
maturity (i.e. the payback period) increases, volatility becomes a greater risk factor in
determining the economic value of each setup.

The three ASIC setups pull ahead of the three GPU setups in terms of payback period. The
Antiminer E9 has the shortest payback period at roughly 12 months, and the Antiminer E7 and
StrongU STU-U1++ take approximately 30 months to payback. In contrast, the payback period
for the GPU setups starts at 40 months for the RTX 3090 and RX 6800 setups, and tops out at
50 months for the RTX 3080 Ti setup.

 Figure 5: Payback period of solar-powered cryptocurrency mining setups

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4 Conclusion
A model for assessing the feasibility of solar-powered cryptocurrency mining setups has been
developed in this paper. The model considers the mining hardware characteristics (i.e. hash
rate, power requirements and the cost), per-watt solar panel cost, peak sun hours at the
installation site and the cryptocurrency-related parameters (i.e. market price, net hash, block
time and block reward). Then model then evaluates the monthly total upfront cost and its
monthly payback period, which investors can incorporate in their overall feasibility studies.

There are no guarantees with regard to the financial analysis set out in this paper. Prima facie,
for the case study performed for setups in New Zealand, the Antiminer E9 setup appears to be
the most attractive in terms of its payback period, which is a good measure of its relative
profitability and its exposure to the risk from volatility. However, there are several factors that
we believe aspiring solar miners should consider before embarking on a solar mining venture
in New Zealand:

1) The specific volatility of different cryptocurrencies and the impact on the volatility of the
 revenue streams generated.
2) The general volatility of the cryptocurrency market, and the potential for governmental or
 microeconomic shocks to increase its volatility.
3) The entry cost of different solar-powered setups, and the relative ease or difficulty of
 obtaining suitable financing for the venture.
4) The liquidation value of each different solar-powered setup, in the event that the venture is
 no longer financially viable.

For future work, we suggest researchers should incorporate component-level PV system design
and business financing models. We believe that this work will increase the sustainability of
cryptocurrency mining businesses by reducing both dependence on exhaustible energy
resources and impact on the environment.

5 Legal Disclaimer
There are risks associated with investing in solar-powered cryptocurrency mining. We
recommend you seek advice from your financial adviser before taking any action.

 17

Southern Institute of Technology Journal of Applied Research - http://sitjar.sit.ac.nz

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