a load profile study and hybrid power system …...tribal travel murdoch university regen power a...
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Tribal Travel
MURDOCH UNIVERSITY REGEN POWER
A LOAD PROFILE STUDY AND HYBRID POWER SYSTEM
DESIGN FOR REMOTE INDIGENOUS COMMUNITIES
Acknowledgements
I would like to take this opportunity to thank a few people involved in this project.
Firstly David Parlevliet, for always being available WHen I was in need of guidance and also giving me
the freedom to work independently WHen I needed to. David has been a great and calming
supervisor, WHen I was stressed he was calm.
I’d like to thank Srini, head Engineer at Regen Power. Not every student gets the opportunity to
complete an internship, especially one that includes a solo mission to the stunning Kimberley. WHen
I first told Srini of plans for Broome it was originally for family business, he saw an opportunity and
instead of myself having to defer the internship he changed it a little for me. I am deeply
appreciative for that as this has been one of the most interesting projects of my academic career.
I would like to thank Kelly Antonia, previous head coordinator of events at Murdoch University. Kelly
was the person that first put me in contact with and recommended me to Srini and Regen Power.
I would also like to thank Gareth Lee, for always having great advice on the subject at hand as well as
being an understanding and a fair part of the Academia. For always making time for meetings even if
they are unscheduled.
I would like to thank Steve Holdsworth for trusting in the project and inviting me to the amazing
community of Jarlmadangah. Steve allowing me to do my research was probably the most important
segment of the entire project.
I would like to thank Andy Greig for his ongoing commitment to the betterment of life, skills and
treatment of Indigenous people in the Kimberley and for his direction given toward the community.
I went up to Broome blind with no contact and couldn’t have done it without you Andy.
And finally I would like to thank Murdoch university school of engineering for always being open to
ideas of sustainability and renewable energy.
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Contents Acknowledgements .................................................................................................................................. i
Table of figures ...................................................................................................................................... iv
1 Project Goals ........................................................................................................................................ 1
1.1 Deliverable A ................................................................................................................................. 1
1.2 Deliverable B ................................................................................................................................. 1
1.3 Deliverable C ................................................................................................................................. 1
2 Scope .................................................................................................................................................... 2
3 Background .......................................................................................................................................... 2
3.1 Motivations ................................................................................................................................... 4
3.2 Ethics ............................................................................................................................................. 4
4 Similar projects .................................................................................................................................... 5
4.1 Arenas solar to power more than 30 communities ...................................................................... 5
4.2 The remote Indigenous Energy program (RIEP)............................................................................ 5
4.3 AllGrid energy ............................................................................................................................... 6
5 Surveying and creating load profiles .................................................................................................... 7
5.1 Data analysis ................................................................................................................................. 8
5.2 Overall base load ........................................................................................................................... 8
5.3 Loads with averages added ........................................................................................................... 9
5.4 Loads with best case scenario ....................................................................................................... 9
5.5 Loads with worst case scenarios added ...................................................................................... 10
5.6 diesel consumption checking against load profile model ........................................................... 11
5.7 Load profile checking .................................................................................................................. 11
5.8 Peak sun hours ............................................................................................................................ 14
5.9 Cyclone protection and history ................................................................................................... 15
6 basic component choice .................................................................................................................... 16
6.1 panels .......................................................................................................................................... 16
6.2 Battery storage............................................................................................................................ 17
6.3 Inverter choice ............................................................................................................................ 21
6.4 Diesel generators ........................................................................................................................ 22
6.5 back of the envelope calculations ............................................................................................... 23
7 HOMER simulation ............................................................................................................................. 25
7.1 HOMER inputs ............................................................................................................................. 25
7.2 Component inputs ...................................................................................................................... 27
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7.3 HOMER simulation results .......................................................................................................... 30
8 economics .......................................................................................................................................... 32
8.1 capital cost .................................................................................................................................. 32
8.2 diesel inflation ............................................................................................................................. 34
8.3 payback period ............................................................................................................................ 35
9 safety .................................................................................................................................................. 36
10 conclusion ........................................................................................................................................ 37
10.1 implementation in the future ................................................................................................... 37
10.2 Deliverables ............................................................................................................................... 38
11 Appendices ....................................................................................................................................... 39
11.1 Correlation tests........................................................................................................................ 39
11.2 load profile surveys in order (average, best, worst) ................................................................. 40
12 Bibliography ..................................................................................................................................... 44
iv
Table of figures
Figure 1: Map of Looma communty [2] .................................................................................................. 3
Figure 2: example of individual survey ................................................................................................... 7
Figure 3: Average load profile vs hours of the day ................................................................................. 9
Figure 4: best case load profile vs hours of the day ............................................................................. 10
Figure 5: worst case load profile vs hours of the day ........................................................................... 11
Figure 6: Diesel usage email from Janine .............................................................................................. 12
Figure 7: Average diesel consumption chart [5] ................................................................................... 13
Figure 8: Comparison of predicted diesel usage to actual .................................................................... 13
Figure 9: Solar irradiation figures from bureau of meteorology [5] ..................................................... 14
Figure 10: Cyclone occurrences in Australia from bureau of meteorology (citation above) ............... 15
Figure 11: Price comparison of PV panels ............................................................................................. 16
Figure 12: Specification sheet of chosen panel from clean technical [5] ............................................. 17
Figure 13: Study from cleantechnica on battery technology comparison in USD [8] ........................... 18
Figure 14: Life cycle comparison of battery technologies [11] ............................................................. 19
Figure 15: Battery cost comparison[10] [11] [12] [13]. ........................................................................ 20
Figure 16: Sunny island configurations from sma [10]....................................................................... 22
Figure 17: SMA sunny island specifications .......................................................................................... 22
Figure 18: Summary of basic components for base model .................................................................. 25
Figure 19: Diesel input window from HOMER ...................................................................................... 26
Figure 20: Solar irradiation window from HOMER ............................................................................... 26
Figure 21: Load profile window from HOMER ...................................................................................... 27
Figure 22: Inverter window from HOMER ............................................................................................ 28
Figure 23: Battery window from HOMER ............................................................................................. 28
Figure 24: PV input window from HOMER ............................................................................................ 29
Figure 25: Diesel Generator input window from HOMER .................................................................... 29
Figure 26: Optimized results from HOMER ........................................................................................... 30
Figure 27: Electrical production results from HOMER .......................................................................... 31
Figure 28: Battery state of charge results from HOMER ...................................................................... 31
Figure 29: Diesel generation results from HOMER ............................................................................... 32
Figure 30: Estimated capital cost before industry check ...................................................................... 32
Figure 31: Estimates for cost of PV systems from APVI [21]................................................................. 33
Figure 32: Email confirming industry standard prices .......................................................................... 33
Figure 33: Average diesel cost per year from AIP [20] ......................................................................... 34
Figure 34: Diesel inflation model .......................................................................................................... 34
Figure 35: Payback period graph .......................................................................................................... 36
1
1 Project Goals
The main purpose of this project is to research power usage and sources in remote area
communities. To find correlations between household statistics and power usage. To design a day in
advance load prediction model and design an overall hybrid power GENERATION system that could
replace an existing diesel generator and reduce costs for power on a long term basis.
Designing of the hybrid system will be done using the program HOMER and load prediction models
are too be designed with a combination of Microsoft excel and Matlab.
1.1 Deliverable A My primary deliverable was to move to a remote area initially and make contact with a remote
aboriginal community that consists of 30-70 homes.
Once contact has been made it was important to explain in detail the research and privacy
boundaries that I will be taking note of and gain written permission so to safe guard the company.
Once at the community the first stage of my research will be collecting data in the form of surveys
for each household. The entire survey can be found in appendix 1 in the appendices section.
The survey will consist of devices in the house, their rating, how old they are and how often they are
used per day and When. It will also be taking note of members of each household, their gender,
their age and whether they are working or not.
It will need to do this for each individual household and then each of the public use buildings.
Please see figure 3 for a sample of the survey that will be used to survey each individual member of
the community.
This is the second goal for the project, the first being the collection of data. Regen Power has asked
me to create day ahead load prediction profile as a starting point for the overall project. This will
allow us to then size the components for a given community and enable us to extrapolate data for
other various sized communities.
Deliverable A will also include an entire hybrid system design for the community and a finance
report testing whether a new system for this community is potentially viable for a community of this
size.
1.2 Deliverable B Deliverable B involves the documentation of all research, programming, problems encountered and
discoveries made. It is to be in a thesis format consisting of 3 documents. A project plan of no more
than 1500 words, a project progress report of no more than 2000 words and a final thesis document
of 12,000 to 15,000 words.
1.3 Deliverable C Deliverable C is the preparation and delivery of a small 15 minute presentation in front of other
thesis and industry project students and their supervisors detailing the completed project, the
research and the discoveries made.
2
2 Scope This thesis has been researched and written over an entire year (2 semesters). The first three
months (August-November 2015) were spent scouting and making contacts in Broome looking for a
suitable indigenous community to use as a model.
During this period a visit to the chosen community was also achieved as well as data gathering to
build a base load to base our load predictions on and give an idea of the end system that could be
implemented.
From December 2015 until February 2016 the data was sorted and put in a format that could be
read by a program to create an overall hourly base load profile for the entire community.
The rest of the time was then spent building various models that will be explored further on in this
document, namely a day ahead load prediction model written with Matlab that takes weather and
fluctuating populations within the community into account, a HOMER analysis to help decide on the
hybrid system design and then the thesis document itself.
It addresses the problem of diesel consumption being the main source of power generation in
remote communities and the high cost associated with the diesel consumption.
Limitations will be the number of participants in the survey and the human error in estimating daily
power usage.
3 Background In the first few weeks of scouting in Broome one of the key people involved and spoken to was Andy
Greig, the CEO and founder of Agunya. [1]
We started discussing possible communities that would suit the project. Regen had specified that
they would prefer the community to have 30 buildings at least.
Andy mentioned that there was a community 200km east from Broome called Jarlmadangah that
was small but might suit the study as they had applied to have solar installed before.
Andy was good enough to provide details of the CEO of Jarlmadangah Steve Holdsworth. We started
communicating via email and I prepped an introduction document that can be found in appendix 1
to be sent through as an outline of the research I wanted to complete and its purpose.
Regen was able to offer a full proposal for the community that was to partake in the research that
they could then use to pitch to other organisations. Steve was very eager to take part in the research
project as they have been applying to get funding for solar for years and have not yet succeeded. He
realised that the proposal would be a useful tool.
3
The community of Jarlmadangah is a small off-shoot community of Looma.
Figure 1: Map of Looma communty [2]
It has been in operation for 30 years and is independent from the government drawing most of its
income from a cattle station they own and a strong tourism program in the dry season.
The community itself is located 200km eats of Broome city, WA. It is a relatively small community
having a total of 17 homes, a school, a woman’s centre, a workshop, medical building, offices and
basketball courts.
Recently the green army have set up a shaded permaculture area as a start-up program to
encourage the rehabilitation of native plants as well as the growth of food for the community to
help implore self-sustainability. “The Green Army is a hands-on, practical environmental action
program that supports local environment and heritage conservation projects across Australia.” [3]
The entire community runs off a diesel generator of which specific details and exact annual fuel use
is being collected but estimated by Steve, the CEO as a total diesel cost of $200,000AUD per annum.
There are very few trees around the community, especially tall ones and the sun shines bright for
most of the year. This makes it a perfect location for a possible solar plant. It should also be noted
that in the wet season very high winds usually travel through the area in the afternoon making it
possible for individual wind power for each home.
Recently the community, in an effort to reduce its power use, has switched to a pre-paid power
tariff, much like that of prepaid sim cards.
Before this new system was introduced, power was charged at a flat rate to gain access and no
further charge per unit, this resulted in excess power being used.
Although introducing a prepaid system may have reduced usage it is not a solution, due to the
remoteness and nature of the surroundings diesel use is still unbelievably high for a community of
17 homes.
It should also be mentioned that a few years ago before funding was pulled a government initiative
had an engineer come to survey for a possible solar plant to be installed but there was no further
progress after the initial survey.
4
3.1 Motivations For the past few years the Barnett state government has been forcing the closure of
aboriginal communities under the premise that they are “too expensive”. In order to ensure
the survival and improvement of these communities it is important to consider alternative
means to reduce operating costs and at the same time take away reliance on the
government and increase the self-sustainability of these communities.
Oil and diesel fuel are only becoming increasingly depleted and therefore more expensive.
With most of the communities in Western Australia primarily, if not completely, running on diesel
generators for electricity production it becomes obvious that this is one of the main costs and
therefore, threats to remote communities.
There is however a cheaper, cleaner and quite obvious solution: solar power. In locations that have
some of the highest solar radiation and lots of space with low lying vegetation it is the ideal scenario
for implementing solar power production in combination with battery storage and backup diesel
generators to generate if solar power and batteries cannot cover the load. “On the north-west coast
around Port Hedland, Western Australia, where average daily global radiation is the highest for
Australia (22–24 megajoules per square metre), average daily sunshine is also highest, being
approximately ten hours.” [4]
3.2 Ethics Anything surrounding indigenous communities and outreach can be a sensitive subject especially
with the surrounding issues in the past and today. With the forced closure of many communities
already and the desire of the government to close more and of course the documented failure in
certain communities that include alcohol abuse, domestic and drug abuse it is important to carry out
this project in an ethical nature as not too jeopardise either party. There are many aspects of ethics
to take into consideration.
Privacy and consent was an extremely important part of the site visit. As I was visiting representing
both Murdoch University and Regen Power it was important before beginning the survey that each
member understood what the purposes of the survey were, what the information would be used for
and whom it would be shared with. Srini from Regen Power was good enough to supply me with a
consent document that was created by the Regen Power lawyers that could be signed by each
individual member that stated the purposes of the survey were clearly explained and how the
information would be used.
In negotiating a site visit to Jarmadangah, Srini mentioned that it may be a good idea to offer the
community something in return for the valuable information being provided. Although we did not
have much funding to offer monetary compensation we could offer information. I came up with the
idea of offering part of a hybrid power design and full documentation to be used as a proposal for
investors and NGO’s in return for the visit and full access to the population of Jarlmadangah as well
as accommodation for a week.
The delivery of this document could possibly result in the community gaining a much more
sustainable and cheaper power option in the future.
The last ethical obligation that should be mentioned is the obligation to provide Regen Power with
the load prediction model they desire. Although this is only part of the thesis this is the most
5
important deliverable to Regen Power. It should be extensive and as accurate as possible with the
given data.
4 Similar projects
4.1 ARENA’s solar to power more than 30 communities The Australian Renewable Energy Agency, a department of the Australian Federal government has
released a project proposal that aims to power over 30 remote Northern Territory communities in
collaboration with the Northern Territory power and Water Corporation investing 27.5 million-
dollars AUD each.[1]
It is a solution aimed at lowering the increasing costs of diesel fuel consumption in remote
communities.
The project aims to create 10 mW of solar PV constructed over 30 communities in the NT.
“ARENA is very pleased to be partnering with Indigenous Essential Services – a subsidiary of PWC –
to deliver this exciting project, Which will see a total of 10 MW of solar PV constructed at more than
30 remote communities in the NT. This project will open the door to a more diverse, secure energy
mix for off-grid communities, and will also create local jobs and boost skills during construction and
operation.” ARENA CEO Mr Frischknecht said. [1]
The installations are not of high solar penetration with the aim for most communities being around
15% with a single community having a displacement of 50% at Nauiyu (Daly river). “A 1MW solar
facility will be built at Nauiyu and will incorporate advanced technologies to allow clean energy
production to meet 50% of the community’s annual electricity needs.” [6]
ARENA’s outlook on the project and goals seem to be aimed at creating awareness and prove
economic viability for renewable integration into existing diesel gen power production.
“Not only does this project have the potential to catalyse further renewable energy investment in
other isolated communities, it also sets up each of the participating communities to plug in more
renewables as costs continue to decline.”[1]
The model differs slightly as it seems the design will encompass a larger solar array with distribution
networks rather than individual power production per community however it is still renewable
integration.
4.2 The remote Indigenous Energy program (RIEP) In 2012 the government released the remote indigenous energy program which was a part of the
clean energy future plan. “Remote Indigenous Energy Program will primarily provide reliable 24-hour
power in up to 50 smaller remote Indigenous communities across Australia through the installation
of fit-for-purpose renewable energy systems. RIEP will also provide energy efficiency education and
training in basic system maintenance to community members and repairs and maintenance to
existing systems.” [7]
It is aimed towards closing the gap between indigenous and non-indigenous Australians.
6
The funding (40 million dollars AUD) over four years was to be provided by the government.
The pre-requisites for eligibility of the program were the communities had to be:
“dependent on diesel generators for power (off-grid), have an ongoing permanent population, have a demonstrated social or economic need for reliable power such as employment or education and have a capacity to assist in basic maintenance.” [2]
Research shows that projects are still being completed under the RIEP program with a 29.5 kW PV
system being installed in Miniyalini in 2015 which was installed by Sunwiz solar power, a major
industrial PV installer that stated an expected annual saving of 43,070 kWh (approx. $7,753 AUD) [3].
The RIEP program not only has been retrofitting communities with renewable power systems but
have also been helping to maintain previous programmes from 2002’s bushlight program.
4.3 AllGrid energy Another company worth mentioning is the aboriginal owned AllGrid that is said to be the new rival
of Tesla. They first came into the spotlight with their design of the Wattgrid, a 10kW solar/battery
storage unit that is comprised of lead acid gel batteries, a 5kW solar inverter with a solar array
included and was available at an earlier date than Tesla’s Powerwall.
“Aboriginal-owned company AllGrid is providing a solar energy system that is 30 percent cheaper per
kilowatt-hour (kWh), it told NITV News.
"We believe AllGrid Energy’s WattGrid systems are currently the most cost-effective storage entry
point in the market today," said CEO Ray Pratt.” [9]
More exciting and relevant though is an invention by the same company called the Porta grid.
The unit designed for remote area power comprises of a solar array on the roof of a shipping
container like housing, battery storage, UPS, an inverter and outlets.
The actual outputs and sizing of the Porta grid has not been released yet but could be a viable
solution for smaller communities.
“The PortaGrid product is already attracting interest, Deborah Oberon said, with the company
in discussions with National Parks about supplying the units for remote sites that currently rely
on diesel generators.”[4] Head of AllGrid Deborah Oberon says.
Commercial-scale systems that can power an entire remote Aboriginal community and replace expensive and high-emissions diesel generators are also on the horizon.
“This would create energy wealth and energy autonomy for those remote Aboriginal communities,” Ms Oberon also said. [4]
With such a positive outlook and clever designs AllGrid is a promising leader in remote area power production.
7
5 Surveying and creating load profiles
The primary purpose of going out to visit Jarlmadangah was to collect load profiles from the leader
of each household. Regen Power provided me with an excel spread sheet as well as a questionnaire
to gather load data for each household.
The spreadsheet focused on the hourly use of main devices such as stoves, refrigerators, air
conditioners, fans, lights, televisions, microwaves, any smaller devices were deemed negligible.
The spread sheet was a good tool for building base load profiles, however it is only an estimate as
these values were only taken verbally and not actually collected with a meter. It should also be
noted that average power ratings for devices and appliances were applied as collecting individual
power ratings for every building would be extremely time consuming and also possibly invasive. It
seems that most of the power usage actually can be put down to air conditioning and refrigeration
with many household having 2-3 fridges and multiple air-conditioning units. In terms of population
per households most homes were found to have children with some houses having more than 2 or 3.
Individual surveys can be found in the appendices. Winter values have been left blank intentionally
as it was stated by all participants that usage was the same in summer as winter.
Figure 2 shows the overall base load for the community.
Figure 2: example of individual survey
The questionnaire focused more on the usage and spending of resources. It covered what kind of
energy each house used to power devices. It was found that most of them would use gas for cooking
and electricity from the diesel generator on which they use a prepaid power card system in order to
maintain the costs of power.
There is also quite a high use of wood for cooking as a lot of traditional cooking techniques are still
employed. The wood is gathered from surrounding bush though and is not bought from town.
In terms of employment surveying found that at least 50% of adult inhabitants were employed
either within the community, as a ranger or by the nearby cattle station.
8
The households were quite surprising in terms of the devices and amount of power actually being
used. Some houses have up to 4 air conditioning units and 3 televisions with air conditioners running
all day in many cases.
There were a few problems using such a small window in which to extract data. Firstly as
aforementioned, the data is only an estimate as the residents themselves would find it hard to be
exact with actual usage. The other problem being the fluctuation of population within the
community. During the dry season some families mentioned their household increasing by 5-10
members, this could potentially increase power usage during these times. If permitted by the CEO a
further listing of daily diesel usage, population of the entire community and weather patterns would
greatly enhance the predictions and correlations of this study and make the load prediction model
much more accurate.
5.1 Data analysis The data collected from Jarlmadangah was helpful in compiling a base load profile, however there
were a few problems. Firstly the data provided by the leader of each household would only be an
estimations due to human error and assumptions made. The second being at the given time of the
visit not the entire population of the community was present, in fact only 8 households were able to
be surveyed (plus the public buildings). This means that another 9 households were unaccounted for
in building an entire load profile. This initially caused problems in designing a hybrid system, building
a daily load profile prediction model and completing a finance report on viabilities on the new power
system. However a few options were devised. For the HOMER analysis at least we could take an
average of existing load profiles for homes and multiply by the number of unaccounted homes, or
could do a base load for both worst case and best case scenarios (i.e. Take the household with least
power usage and most power usage and undertake two separate HOMER analyses to find a best
case and worst case scenario for a power system).
It was decided to do both the average and best case and worst case and see how vastly different
they are. For the day ahead load prediction model this would not be enough data to complete a day
ahead prediction model as three aspects would be needed for comparison. The weather (which
would be easy to obtain). The history of daily or weekly power usage and a daily or weekly history of
population).
As it is not possible to gather records of individual power usage for each home if the records of
diesel usage from the generator were available and the corresponding population and weather then
correlation could be made between temperatures and current populations and an average of the
previous diesel use and given the rating of the generator and losses in the lines the actual power use
of the overall community.
5.2 Overall base load One of the main problems faced with the collection of data from Jarlmadangah was the allocated
time window and the ever moving population. The result of the visit being in a time period when
some of the population were away was a complete load profile was not able to be completed. To
overcome this it is fair to complete 3 models for load profiles, a best case, a worst case and an
average.
This was completed by simply taking the worst household (most power used), the best household
(least power used) and the average (an average of the existing houses) and respectively added to
make up for the missing households for each case.
9
Each of these load profiles will then be used in HOMER simulations along with weather data and,
available PV systems, battery banks and existing diesel to help design and decide on the hybrid
power system. Note: The entire load profile sheets from Excel can be found in the appendices.
5.3 Loads with averages added Figure 3 shows the overall base load for the community with an added 9 “average” household
profiles. In this particular load profile there is a peak power spike around 7pm that reaches over 90
kW. There is a trend between 7am and 6pm in which the loads vary and hit the lowest point at
around 5pm.
The daytime also sees a “W” shaped trend of power usage with the usage dropping around 8 or
9am, climbing back up around midday and then back to a low again at 5pm.
From the pictured load profile it seems that a base PV system of 70 kW would be suitable as it
maintains this load through a majority of hours of the day. Batteries could be charged in the middle
of the day where usage is at a low and help keep the systems running throughout the peak hours at
7 and the night with a diesel gen as backup.
Figure 3: Average load profile vs hours of the day
5.4 Loads with best case scenario
The best case scenario seems to be the one that is least useful, usually in design an average or worst
case scenario will be used to encompass peak periods and growth of the community, essentially to
leave room for growth and error. But for the sake of the exercise and comparison it has been
calculated here to see how large the differences in worst and best case scenarios are.
0
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Load (W)
Time(Hours)
Total base loads(Average)
10
In the best case scenario the same “W” trend is seen but the peak power spike moves to midday.
The overall average operating load is around 60 kW which is lower than the average scenario as
expected and the peak is around midday at 76 kW. Figure 4 shows the best case scenario base load.
Figure 4: best case load profile vs hours of the day
5.5 Loads with worst case scenarios added As the worst case household used A considerately higher amount of energy than the other
households with the load staying fairly stable during the night at 120 kW, again the “W” trend is still
visible with the low points of consumption still being at 8am and 5pm and the peak still taking place
at 7pm. The system stays around 100 kW for most the night after the peak at 7pm.
As the low usage periods are still during the day in this model it would still be acceptable to include
battery banks in the system design as the PV system would easily be able to store energy during the
day to help offset diesel usage during the night.
It seems that as expected the average load profile will be the best for system design as to not “over”
or “under” engineer the system.
The Pattern for the homes could possibly be due to the working nature within the community. The
residents work or are in school during the mornings and late afternoons returning home for the
hottest hours of the day. This could account for the power spike in the middle of the day as most of
the community will be in their homes presumably running air conditioners. Figure 5 shows the base
load for the worst case scenario.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Base load (w)
Time(Hours)
Total Base loads (best case)
11
Figure 5: worst case load profile vs hours of the day
5.6 Diesel consumption checking against load profile model As the data collected is only based on interviews which leaders of each household and the
community leader for the public buildings there is the possibility of human error in estimating
household power usage. This is where checking against diesel consumption will be useful. Right now
Jarmadangah is running purely off a diesel generator. In a perfect design with large resources
invested in power meters could be fitted to monitor the exact usage of power on a daily basis but as
this is not available a more cost effective solution is to first gather the diesel consumption from the
CEO of Jarmadangah as well as the power rating and consumption of the generator itself. Power loss
factors and wastage also needs to be factored in and then power usage per day/week/month can be
calculated. That can then be compared to best case, worse case and average load profiles and this
will indicate which the closest load profile to the actual data is.
5.7 Load profile checking Steve Holdsworth provided an introduction to Mick from KRSP(Kimberley regional service providers).
“Kimberley Regional Service Providers (KRSP) provides a range of quality services including
maintenance, repair and capital works that improve the quality of life for Indigenous people living in
the Kimberley Region of Western Australia.” [10]
KRSP is the power provider for Jarlmadangah. KRSP are a part aboriginal owned service in the north
west of Australia, they are the company in charge of providing the community with the diesel
generators being used as well as the diesel.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Base(w)
Time(Hours)
Hourly loads (worst case)
12
Upon first contacting KRSP via telephone the employee seemed resistant to give load profile details,
generator information and diesel usage. Understandably so, any information gathered by third
parties on indigenous community costs can be used as weapons against the cause and are therefore
very sensitive.
I reassured the people of KRSP that I was indeed a Murdoch University student and was only
interested in the information for personal and academic use.
However unfortunately after consulting with the manager at KRSP, Mick, he replied to the email
stating the KRSP is in no position to share that information with third parties, even if the information
was for educational use. Mick suggested that contacting the housing commission would be best as
they hold the rights to make such a decision and grant permission.
Another avenue was to contact Janine King(suggested by Steve). Janine reports fuel usage of various
communities. The only reports available from her are for each quarter and are just litres used and
expenditure.
Steve was not able to provide daily usage for more than a month so the information was deemed
invalid. Figure 6 shows the expenditures on diesel in an email from Janine King.
Figure 6: Diesel usage email from Janine
The above email is the quarterly spending on Jarmadangah for diesel fuel. The usage actually varies a
large amount, this may be due to the varying population throughout the year. This limited data
makes it hard to check against the collected load data.
The only option for using this data to check is to average over 2 years and compare the power that
might be produced to the power on average consumed and find the profile (best case, worst case or
average) that is the closest match.
The total litres of diesel used from September 2014 to March 2016 according to the diesel usage
report from Janine is 233,042 litres. This is only for 7 quarters so then the average consumption per
13
quarter becomes 33,292 litres (rounding up) then multiplying by the four quarters in a year the
annual diesel consumption is 133,166 litres.
For comparison to the amount of power used by the community in a year the diesel curve for
Cummins generators (70kW or 110kW, the two existing diesel generators at Jarmadangah) are
needed.
Due to the dynamic nature of consumption verses loading this will be a very simple and roughly
accurate calculation. Figure 7 shows the average consumption rates for multiple sizes of diesel
generators.
Figure 7: Average diesel consumption chart [5]
The above is an image of average diesel generator consumptions. The publisher of this site rates
Cummins as one of their top 4 manufacturers.
If on average 33,292 litres (or 8,794 gallons) are being used per quarter and it is assumed that the
100kW generator (closest to 110kW) is running at 75% then it would result in 1516 hours of the
generator running at an average of 75kW which makes the overall power usage for a quarter
113,715,517 WH.
If the daily totals the average load profile is multiplied by 91 days it will be easy to compare how
close the surveys are and help determine how accurate the model is. Figure 8 shows energy usage of
diesel generators.
Case Energy over a day (mWh)
Power over a quarter(mWh)
Average usage according to usage reports(mWh)
Percentage error
Average 1.63
148 113.71 23%
Figure 8: Comparison of predicted diesel usage to actual
Considered the simple nature of this usage comparison and the average non dynamic behaviour of
the generator assumed for it 77% is relatively accurate.
14
This confirms that on average the survey load profile collected at Jarlmadangah is a good launching
point for the system’s overall base design.
5.8 Peak sun hours In order to correctly estimate the size of the PV array the peak sun hours at the proposed site is
needed. However no data as such has ever been directly collected at Jarlmadangah, so the closest
site must be used.
The two closest major towns/communities to Jarlmadangah are Derby and Looma, however Fitzroy
could also be used failing the previous two proving unusable.
The Bureau of Meteorology has statistics for the last 15 years of solar irradiation for Curtin aero
station which is approximately 26km from Derby and relatively close to Jarlmadangah and much
closer than Fitzroy. Figure 9 shows solar irradiation figures per month in Peak sun hours.
Figure 9: Solar irradiation figures from bureau of meteorology [5]
The above values show the mean, the highest and lowest monthly solar irradiation in kWhm^-2
(PSH) for the last 15 years.
This information will be extremely valuable in calculating and sizing the system.
The above information (averages of PSH) is extremely helpful in designing an on-average system, but
it is also important to examine what the longest amount of days in a row were that did not meet
4.9kWHm^-2. This will help decide the days of autonomy needed for the battery design.
The last 10 years were tested, examining daily PSH values for each month and the worst cases picked
out.
Complete data sets are listed in the appendices section.
To design the solar array the lowest monthly average PSH is considered over a 10 year period. The
system is then designed to be able to run on the month with the lowest peak sun hour values. Days
of autonomy must also be considered. That is, how many days in a row can the system keep running
if the PSH is lower than the average for multiple days in a row? This depends on how large the
battery bank is.
In the past 10 years the worst case where 4.9 PSH is not reached was 5 days in a row, however
almost all the other years there are no more than 4 days in a row. To alter the design the worst case
scenario for battery design will be 4.1PSH. This will bring down the days of autonomy to an
acceptable number of three with diesel generation for the outlying years where more than 3 days
with PSH values less than 4.1.
In the case that funding must be cut, days of autonomy will be brought down to one and the diesel
generator will serve to make up the load.
15
5.9 Cyclone protection and history
For designing a system that can withstand the elements, especially in the wild north Kimberley it is
important to research cyclone occurrences close to Jarlmadangah. The reason being some PV panels
are cyclone rated for areas that are prone to such catastrophes.
The Bureau of meteorology advises for Derby (the closest large town) that cyclones are of very low
risk and there has only ever been one incident that caused serious damage.
“The main impacts of tropical lows and cyclones in the Derby region are heavy rainfall and
associated flooding. Derby's cyclone risk with respect to wind is much lower than Broome and
coastal Pilbara towns. The reduced risk is related to several factors including that there are less
cyclones and less severe cyclones occurring in this region (see figure 10) and cyclones move over
land and weaken before reaching Derby. For example Chloe in April 1995 crossed the coast to the
north northeast of Derby as a category 4 cyclone but weakened rapidly before reaching Derby.
Certainly those communities in more exposed coastal locations such as Beagle Bay and Cape
Leveque have a much greater risk of a cyclone impact.
Since 1910 there is only one identified system, in March 1935, that has had at least a category 2
impact on the town. This cyclone caused significant property damage around the town.
Nevertheless there is still the risk that a severe cyclone will impact Derby. The threat of a major
impact lies from a strong system moving south either across the Dampier Peninsula as in March
1935 or down King Sound.” [6] Figure 10 shows cyclone occurrences, the black noting minimum damage
and the red representing higher damaged areas.
Figure 10: Cyclone occurrences in Australia from bureau of meteorology (citation above)
16
The above figure is also evidence of cyclones damage on coastal regions but not so much inland. The
black dots on the map indicate medium damage cyclones whereas the red indicate highly damaging
occurrences.
The latitude and longitude of Jarlmadangah are 18 degrees south and 124 degrees east. If the map is
examined at these coordinates there is no recorded cyclone incidents.
Cyclone rated panels and mounting frames are therefore not to be included in this system design as
the expenditure for the system would not be justifiable. Jarmadangah seems to be inland enough
that the cyclones tend to lose power over large land masses and will usually die down before
reaching it.
6 Basic Component Choice Before inputting data into HOMER for sizing of the system itself it is important to select certain basic
components so the size of panels and batteries available can be selected.
6.1 panels Various solar modules were researched from online wholesalers taking note of price, size and
efficiency. Most of the data was collected from sol distribution an online Australian wholesaler with
great reviews. [5] Figure 11 shows prices and power ratings in AUD of various solar panels.
Figure 11: Price comparison of PV panels
The green light cell represents the number one in either price or efficiency, the yellow indicates the
second best. The highest efficiency goes to BenQ’s new 325w panels. [15] However the price is
almost double that of the holder of the second best efficiency which also holds the lowest price so
this will be the obvious choice for the system design as it holds a decent efficiency with a low price
per watt at 0.82$/w.
Advantages listed on the site include
- Superior performance under low light conditions and hence its output is less hindered by
overcast conditions.
- Utilises a 4 busbar technology to enable higher efficiency.
17
Figure 12 shows the specification sheet for the Talesun M280 solar panel.
Figure 12: Specification sheet of chosen panel from clean technical [5]
The string configuration will be determined by the inverters chosen to be used on site by the rated
current needed.
6.2 Battery storage
There have been leaps and bounds in battery technology over the last decade, especially with the
general population now more interested and aware of the possibilities of energy storage in everyday
life. This is especially good news for standalone systems.
Creating batteries that have a larger capacity at higher voltages and better permitted depth of
discharge is good not only for residential use but also for standalone systems.
10 years ago the only real option that was not super expensive was deep cycle lead acid batteries,
now there are larger options for lithium ion batteries and even saltwater batteries offering
comparable prices for storage.
One of the most interesting and new battery designs is one that is taking it back to basics only using
a salt water electrolyte and non-heavy metals for anodes or cathodes. “Aquion Energy’s M100-LS82P
Battery Module is a modular building block for clean energy storage systems. The M100-LS82P is
composed of twelve S20-P08F Battery Stacks connected in parallel and comes prewired as a plug-
and-play battery bank. Designed for years of hassle-free operation in stationary, long-duration
applications, AHI batteries are optimized for storing solar energy for residential, off-grid, and
microgrid applications. The M100-LS82P delivers an unmatched combination of performance, safety,
and environmental sustainability in a cost-effective battery platform.”[7]
“CleanTechnica is the number one cleantech-focused news & analysis site in the world” [17]
A study from clean technical comparing the cost for Tesla’s Powerwall, Aquions m100 and another
lithium battery showed that the cost per kWh is comparable to the other batteries in its class
however it does have a slightly lower life time there are definitely benefits of being safer (due to the
lack of heavy metals and only using saltwater as an electrolyte).
18
Figure 13 shows a costing analysis of multiple batteries from Cleantechhnica’s study.
Note: all derating factors and depth of discharge were included in the analysis
Figure 13: Study from cleantechnica on battery technology comparison in USD [8]
These prices are from a US site so it is just an interesting comparison for the time and these prices
will not be used in the final capital cost calculation.
The Aquion salt battery is obviously a more expensive choice with the larger model producing
around 65 mWh for approximately $15,000. It also has less cycles (which is assumed at 100).
From a design perspective and the need for safer environmentally friendly batteries, including these
batteries in the design would be an ethical decision but on such a large scale, with increasing
pressure on use of funds in aboriginal communities a more economical choice will need to be made.
Problems could also arise as in connection with certain inverters may not yet be approved, however
SMA sunny boys[9] are able to be connected to both deep cycle lead acid batteries and most lithium
batteries. “Sunny Island inverters are compatible with all lead-acid and many lithium-ion batteries
from a range of manufacturers. “ [9]
Tesla’s Industrial size Powerpack will be on the market within the next year. “The system also
includes a $65,000 Bi-Directional 250 kW Inverter as well as the cabling and site support hardware
for $3,000. Without installation, the cheapest Powerpack system you can buy costs a total $162,000
for 200 kWh of energy and 100 kW of peak power.” [10]
This price comes out at $38.88/Ah which is 65 times the cost of lead acid batteries so it begs the
question, how big are the benefits of lithium batteries vs lead acid and are they worth the
massive investment.
19
A study from alternative energy magazine shows the capacity retention vs cycle number for
multiple depth of discharges of lead acid batteries and a lithium battery. Figure 14 shows cycle
life of different battery technologies.
Figure 14: Life cycle comparison of battery technologies [11]
“As cycle life is influenced by depth of discharge, the figure shows multiple DOD percentages
for the lead acid. It can be seen that the AGM(competing model of battery) pack must be limited
to a 30% depth of discharge to get comparable life to a lithium-ion that is at 75% depth of
discharge. This means that the AGM battery must be 2.5 times larger in capacity than the
lithium ion to get comparable life.” [11]
Even though there is higher capacity retention over longer life cycles of lithium ion batteries it is
not a large enough difference to warrant 65 times the cost on such a large scale project.
Figure 15 displays costs in AUD for multiple batteries of similar sizes and includes prices per
Amp-hour.
20
Figure 15: Battery cost comparison[10] [11] [12] [13].
At first all voltage sizes were considered but 2 volt cells were more economically viable and had the
added benefit of being able to connect 24 batteries in series, reducing the number of parallel strings
which is recommended.
The most cost effective Battery in the 2 volt range is Suncycles 1200 amp-hour 2 volt gel sealed
battery costing just below $0.60/Ah of storage.
The manufacturer states:
“Made in Australia for Australian sunshine. The Battery Energy Suncycle is carefully designed to
satisfy the special needs of solar and remote area power systems. All models come with a 3-year full
warranty. Users of solar and remote systems need reliability, low levels of maintenance, excellent
cycling capability especially during low input periods when demand tends to be highest.
Suncycle batteries, properly maintained, should deliver a working life well in excess of 10 years.
Cycle life is consistent with design, with at least 5,000 cycles expected with the typical daily usage in
a solar system. Improvements have continued in recent years, with changes to the active material to
ameliorate charging from the discharged state, a frequent problem with solar batteries. Battery
Energy has designed Suncycle to deliver reliability and performance, using ultra thick grids for long
21
life, very high 100 hour performance and a large electrolyte reservoir for both safety and ease of
maintenance.” [16]
Although there are exciting new technologies in battery storage that result in longer life spans at
higher temperatures and the reduction of heavy metal use the prices are not yet cost-effective and
as a result this power system will use Suncycle’s 1200 amp-hour 2 volt gel batteries.
6.3 Inverter choice Inverter choice is extremely important when designing a system. You want maximum efficiency
while keeping costs low but not cutting on reliability.
From years of studying Renewable energy engineering and also working for Regen Power as a solar
consultant it is noticeable that most companies were using the SMA “Sunnyboy” inverters. They
come a range of sizes and have high efficiencies and longer warranties compared to their Chinese
counter parts. SMA designs and creates inverters especially for hybrid system designs and are the
primarily used inverter in RAPS even here at Murdoch. “The RAPS 2 system at Murdoch University
was selected for an overhaul early in 2010. The system was redesigned to include new inverter
technology from SMA.” [26] They also boast a lifespan of twenty years.
The other aspects to take into account are efficiencies and life spans, although life spans are not
easily obtained and could just be best case scenarios it is more viable to consider the warranties that
are given with the inverters by the manufacturers themselves, this is a better indication of WHat to
expect as a life span. From previous experience at Regen chinese made inverters usually only offer a
5 year warranty while the Sunny boys offer a 10 year warranty, hinting that they may be more
reliable.
SMA inverters offer large scale inverting system solutions (up to 300kW) stating that costs have
dropped for large scale systems this year.
“The average price of a fully installed commercial-scale solar system changed little between March
and April 2016 – holding steady at about $1.33 per watt. WHile there were slight increases in
10kW and 30kW system prices. This was offset by decreases in 50kW and 100kW system prices.”
[9]
From back of the envelope calculations it can be seen that the inverter size need is approximately
112kW. This is based on peak value seen in any hour with an added 25% to be safe.
SMA offers housing cabinets for inverter “clusters”. These are clusters of three inverters that can
be connected in parallel in order to achieve different ratings. The figure below shows combinations
for the higher scale systems. Figure 16 shows SMA multiple inverter configurations.
22
Figure 16: Sunny island configurations from sma [10]
The solution for creating any sized system larger than 100kW (see the figure above) is to use
multiple SMA sunny island 8.0h inverters in clusters of three. In this case as each is approximated at
10kW each we would use 11 in SMA’s Multicluster box to achieve a maximum AC input power of
122kW (11*11.5kW) . To save on installation costs the multicluster boxes come prewired and are
safe AS approved housing for the inverters. Figure 17 shows the SMA sunny island specifications.
SMA SUNNY ISLAND 8.0H
Rated input frequency 50Hz
Maximum AC input power 11,500W
DC input range 48V-63V
Max efficiency 95%
Max input current 50A Figure 17: SMA sunny island specifications
The cost per unit from Sol-distribution is $4376 AUD per unit. [11] A quote has been requested for
the 11 unit multi-cluster box complete but for now calculations can be made for individual units.
6.4 Diesel generators
23
Jarlmadangah runs completely on diesel generators. There are currently three diesel generators on
site at Jarlmadangah. From conversations with Jarlmadangah’s CEO Steve Holdsworth all three
generators can be run at the same time for peak periods.
There is a slight problem with disparity in information on the ratings given by Steve and the ratings
on datasheets for the corresponding model numbers.
The generators are as listed in the appendices along with the ratings from the data sheet and as
specified by Steve. The disparity could be due to human error reading the generators or the rating is
at half load or includes derating factors. For the purpose of this thesis we will be using data from the
manufacturers’ data sheets but further investigation of the generators before would be useful.
As the main purpose of this system design is not just to create an economically viable system but
also a system which has deep solar penetration it would be wise to just keep the smallest diesel
genrator and sell the rest as extra capital funding.
As the design model aims to keep diesel generator use to a minimum and only as a backup the
smallest diesel generator will be used as it will have lower start up costs.
The smallest generator as stated by Steve is a Cummins 70kW generator however it would be in the
designs best interest to use one of the generators that could handle the peak load which is around
90kW so the next size up shall be used, the Cummins 110kW generator.
6.5 Back of the envelope calculations
Most back of the envelope calculations include seasonal data but all interviewees insisted that due
to the year round hot weather the load profiles did not change between the seasons. Air
conditioners, lights and fridges were all run at relatively the same amount of time.
For the purpose of this study the same load profile has been considered for both seasons.
As mentioned in section 5, the peak sun hour data was found from the Bureau of meteorology, a
government run climate and weather data organization. The lowest worst case month was June in
which the PSH value is 4.1 PSH.
For the purposes of design the average load profile will be used. The total mWh used by the
community in Jarlmadangah is 1.63mWh based on an average of collected data.
This is due to the communities 17 homes with high population and constant use of multiple air-
conditioning units.
It is recommended from Leonics that about 30% energy will be lost in the system [7]. So multiplying
the total mWh by 1.3:
1.3 ∗ 1 .63 𝑚𝑊ℎ = 2.11𝑚𝑊ℎ
It is then needed to divide the overall KWH/day by the peak sun hours of the worst month
24
2.11𝑚𝑊ℎ
4.1𝑃𝑆𝐻= 515.692𝑘𝑤
Now this gives an idea of the type of system we need to find how many panels we simply divide the
above figure by the peak rating of each panel which is 280 watts
515.692𝑘𝑊
0.28𝑘𝑊= 1,842 𝑝𝑎𝑛𝑒𝑙𝑠
Although the initial value seems staggeringly high, the initial capital cost of just purchasing the
panels would be approximately $420,491 AUD plus O&M, installation, and transport. At this point it
is important to remember that the community spends over a quarter of a million dollars on diesel
fuel alone per annum.
For inverter sizing the inverters need to adhere to multiple requirements. The ratings of the
inverter/ inverters should never be lower than the total number of appliances running at the same
time. WHen designing for use within standalone systems it should be designed at a size of 25-30%
larger.
From the load profile previously collected in section 5 the peak watts in any hour is approximately
90.1 kW.
Therefore to find the total size of inverters
90.1𝑘𝑊 + (0.25 ∗ 90.1) = 112.625𝑘𝑊
For battery sizing multiple aspects also need to be accounted for including losses, DOD (depth of
cycle) to ensure the battery is not discharged at a lower rate than that of its rating as discharge
below this level can cause long term damage to the battery and possibly cause a need for
replacement and also increases the risk of chemical fires/explosions.
The assumptions are made below and can be changed once a final, appropriate battery is chosen.
Battery losses will assumed as 15% i.e. 0.85
Depth of discharge will be 0.6 (so the battery does not discharge below 40%)
Nominal battery voltage will be assumed at 48V as this is a large scale system.
The assumption will also be made as discussed previously that 3 days of battery backup are needed
as although the location has very good PSH in each year there is at least one incident and a backup
diesel generator to run base loads in the worst case scenario. Although this will not result in a
completely self-sufficient system, the cost to design for higher days of autonomy will be extravagant
and especially as there is existing diesel generation for backup when the odd cases occur.
𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦(𝐴ℎ) =𝑡𝑜𝑡𝑎𝑙 𝑤𝑎𝑡𝑡 ℎ𝑜𝑢𝑟𝑠 𝑝𝑒𝑟 𝑑𝑎𝑦 ∗ 𝑑𝑎𝑦𝑠 𝑜𝑓 𝑎𝑢𝑡𝑜𝑛𝑜𝑚𝑦
0.85 ∗ 0.6 ∗ 48
25
=1 .63 𝑚𝑊ℎ ∗ 3
24.48= 199,314 𝐴ℎ
Figure 18 summarises basic component sizes and number of modules needed according to back of
the envelope calculations.
Component Capacity Number of modules
PV panels 515.692𝑘𝑤 1,842
Batteries 199,314 𝐴ℎ 182
inverters 112.625kW 11 Figure 18: Summary of basic components for base model
7 HOMER simulation HOMER is a useful tool, a piece of software that can perform thousands of permutations of varied
sizings of renewable and non-renewable power systems.
It takes into account solar irradiation data, diesel fuel costs and load profiles to optimise WHatever
micro grid is being built, in this case a hybrid solar, diesel generator and battery system.
“HOMER is the global standard for microgrid optimization. Avoid costly mistakes by focusing on
optimal hybrid power systems that meet your needs.” [22]
The purpose of using HOMER in this study is to find the optimum system design, it is something a
little more capable and for in depth when comparing to back of the envelope calculations. HOMER is
also an extremely helpful tool in examining the economics of a system, especially for its NPC (net
present value calculation) function which returns a net present value, that is the entire cost of the
system over the projects lifespan. This in turn will help determine if a project is viable or not.
The following section explains how the appropriate data was entered into the HOMER simulation
and then examines the results.
7.1 HOMER inputs
The non-design based inputs in HOMER that will be useful for simulating this project are mainly
diesel fuel cost, load profile and solar resource. These are the inputs that will govern the system but
are not chosen, the constraints. Figure 19 shows the diesel input dialog box on HOMER.
26
Figure 19: Diesel input window from HOMER
The diesel cost was the current price at is entered at $1.40 p/litre. The diesel inflation listed in
section 10.3 was also entered as a percentage which can be seen in figure 20.
Figure 20: Solar irradiation window from HOMER
The solar resource was actually gained through an in-built HOMER function in which it uses the
latitude and longitude results to import solar irradiation and clearness indexs straight from the NASA
website. See Figure 21.
27
Figure 21: Load profile window from HOMER
The above load profile was taken directly from the average load surveys performed earlier in the
year with a scaled average of 1625 kWh per day. As aforementioned, the locals of Jarlmadangah
stated that their power usage did not differ given wet or dry season and therefore for the purpose of
the study this load profile was used for the entire year as an average load profile.
7.2 Component inputs
All the costs and sample sizes of components needed for the system are to be carefully entered into
the HOMER model, that is PV array, inverters, diesel generators and batteries. The main problem
encountered here was the O&M costs. An assumption for the diesel generator was made based on
an answer on the HOMER support page stating “For diesel generators, I typically assume an O&M
cost of about 2 US cents per kWh at rated output. That would be $1/hr for a 50 kW diesel. HOMER
assumes that the O&M cost per hour is independent of the power output, so that 50 kW diesel
would cost $1 per hour of operation whether idling or running full blast.” [23] The O&M value for
diesel generators were then entered as 2$/hour/100kW. O&M for PV panels and other
miscellaneous costs were accounted as $5000 per annum.
Figure 22 shows the inverter window from HOMER.
28
Figure 22: Inverter window from HOMER
Although back of the envelope calculations were performed it was important to understand that
those are just a basis for the base system, the starting point. Therefore although 112kW was the size
of the inverter deemed necessary other sizes were considered from 70kW all the way to 200kW and
higher. In Figure 23 the battery inputs for HOMER’s battery component is showed.
Figure 23: Battery window from HOMER
As the batteries were 2V batteries 24 batteries were needed per string. The data sheet for batteries
desired in the original design were not available so a similar lead acid battery with a nominal
capacity of 1000Ah was chosen and a price per kWh used that was courtesy of a quote received from
Kieren Peters, electrical engineer and previous student. The costing was calculated directly from
company spreadsheets he had designed that use current updated prices that are downloaded
straight from wholesalers price lists online. Figure 24 shows the PV inputs that were used for the
simulation.
29
Figure 24: PV input window from HOMER
The PV was also tested for multiple sizes for 0 to 600 kW, Pricing again courtesy of Kieren which also
accounted for the panels chosen as well as installation, switches and cabling, DC inverters (SMA) and
thus added more to the capital cost but was an industry level current price which would be a much
more accurate representation.
Figure 25 shows the inputs for the generator module for the simulation.
Figure 25: Diesel Generator input window from HOMER
30
The remaining component for the system was the diesel generator. As mentioned previously the
capital investment for these generators were obviously $0 as they are already on site. The O&M was
entered as $2/hour/100kW and a large lifetime given (replacement will not be needed in the project
lifetime, ignore replacement cost). The sizes of generators considered were the three generator sizes
on site (70kW,110kW and 150kW) as well as combinations of the multiple generators running at the
same time.
7.3 HOMER simulation results
The HOMER simulation, with all the varied input sample sizes, ended up having over 14000
simulation scenarios to calculate. The optimisation scenarios came out as below. Note: the
simulation below is for a daily random load variation of 1%. This was used instead of the normal
assumed 15% due to the prediction that loads would not be increasing but more likely would be
dropping slightly in the near future with the introduction of power cards. A simulation with a bigger
varying load will be included but design choices will be made from the former rather than the latter.
Figure 26 shows HOMER’s output from the simulation.
Figure 26: Optimized results from HOMER
These are the categorized results, a summary of the different component scenarios that are
possible.
HOMER picks the most economically viable system to be a hybrid system of all components, made
up of 400kW of PV, 70kW of inverters on the AC side, the existing 70kW generator and 960 batteries.
This would result in a total NPC of $2,341,409 WHich WHen compared to the $4,348,043 in the fifth
scenario (purely diesel generator) it is almost half the cost over the 25 year life of the project.
what is even more interesting, especially from an ethical and renewable standpoint, is that for less
than $100,000 more a system that did not rely or consume any diesel fuel at all could be achieved
with 100kW more of PV. Now obviously this is only an accurate representation of the mathematical
model and does not account for anomalies, however it is a positive to know that the system (if some
control and load shedding were to be programmed into the inverters) that this system could in fact
run purely on renewables. This could be highly advantageous in the near future with the
exponentially increasing use of fossil fuels and the many predictions of it becoming scarcer and
scarcer as civilisation steams forward.
If subsides for running a completely renewable power station were in effect it would definitely be
advantageous to run the second scenario and claim rebates and incentives.
31
Figure 27: Electrical production results from HOMER
Figure 27 shows the electrical production throughout the year. The PV penetration is an impressive
97.4% producing 813,477 kWh throughout the year. Surprisingly the diesel is actually used more in
the summer months, but as this is in a sub-tropical region the clearness index actually improves mid-
year and accounts for the lesser production from the diesel generator during those months. It should
be also noted that there is an excess electricity of 17% per year, this could be due to batteries being
fully charged at certain times of the year. This also shows promise as the excess power could be used
for electric vehicles in the near future, saving further diesel.
Figure 28: Battery state of charge results from HOMER
Figure 28 (above) shows the battery state of charge results.The battery bank ends up being made up
of 960 units, 40 strings of 24 battery strings resulting in 1,344 kWh of usable storage (assuming a
depth of discharge of 60%). The battery bank has 19.8 hours of autonomy (more than enough to
make it through each night, possibly even two nights). If the histogram is examined the batteries
reach below 60% DOD for only 5% of the year with the average staying well above 40% DOD with an
expected lifetime of 8.29 years.
32
Figure 29: Diesel generation results from HOMER
Figure 29 shows that the diesel generator (70kW) starts up 26 times throughout the year running a
total of 445 hours producing 21,398 kWh per year. The low amount of running time will extend the
diesel generator’s lifetime and result in lower replacement cost.
8 Economics
8.1 Capital cost The capital cost will act as a negative cost and the money the system saves from diesel will be
subtracted from that figure and this will be the payback period.
Most of the costs listed are from wholesale providers, however given the size of the system
discounts may apply and improve the economics of the system more so.
Component Capacity Number of modules
Cost per unit ($)AUD
Total cost ($) AUD
PV panels 515.692𝑘𝑊 1,842 228.28 420,491
Batteries 199,314 𝐴ℎ 182 715 130,130
inverters 112.625kW 11 4376 48,136
Installation 515kW 515000 0.5 257500 Figure 30: Estimated capital cost before industry check
Figure 30 lists costs per module and total costs for the system. For the estimation of transport a
report from the Australian PV institute for 2014 estimates the cost for large scale solar systems in
remote areas.
33
Figure 31: Estimates for cost of PV systems from APVI [21]
Assuming the system includes batteries and inverters if the overall cost so far is calculated then the
remainder can be estimated for the rest of the system. The total cost of the system so far comes out
at 1.16$AUD/W. From figure 31 it can be seen that for a grid connected solar farm the cost is
approximately 1.80$AUD/w this means the cost of mounting, installation and transport should be
around 0.64$AUD/W. This means the remaining cost is
0.64 ∗ 515,620 = $329,996.80
This makes the overall system cost $845,617
The costs were worth double checking and confirming especially if the simulation was to cover
multiple sizings an industry standard for pricing would be helpful purely for the HOMER simulation
Figure 32: Email confirming industry standard prices
The costs listed in Kierens email were of similar values to the researched wholesale prices in this
study. It was found that PV prices through Kieren were slightly cheaper than researched prices. The
actual cost of Sunny Island inverters were higher than the value obtained from research. Battery
prices were comparable To the researched values. The HOMER file originally containing researched
prices was updated to include the industry prices.
34
Once DC inverters cabling, installation and all the extra associated costs were accounted for the
initial cost now topped 1.4 million dollars which seems more reasonable and accounts for all aspects
of the system.
8.2 Diesel inflation Diesel inflation must be included in the HOMER model and system design as the cost for diesel can
change over the years and what may be cheaper to run now could be more expensive in the long
run. It will also need to be taken into consideration for calculating payback periods as the negative
gearing of costs saved on diesel need to be adjusted annually to account for inflation.
Diesel inflation information for Australia is not readily available but there were some historical
average yearly costs available for the last 10 year period from AIP.
Figure 33: Average diesel cost per year from AIP [20]
From the values in figure 33 of average diesel costs per annum a graph was able to be created as
well as a trend line (linear fitted).
Figure 34: Diesel inflation model
35
The equation of the line of best fit seen in figure 34 suggests that on average the cost of diesel fuel is
increasing by 0.83 cents per annum, which as a percentage of the average cost for diesel over a 10
year period which is 146.2 $/L is 0.5678% increase per annum.
This is the closest value discoverable for the purposes of this report. The inflation percentage of
0.5678% will be used for the HOMER simulation model.
8.3 Payback period
The payback period determines whether a project is financially viable, the basic question being, is it
going to pay itself off within the lifetime of the project? And, how much cost is it going to save?
To calculate this, the capital cost is subtracted from zero at the start of the lifetime of the project
and each year the money saved on diesel or buying power from the grid is essentially added. Each
time a replacement component is needed due to its lifetime ending then that cost is also subtracted.
The payback period is reached when the cost leaves the negative region and crosses zero.
In industry for commercial power stations it is recommended that payback should be within 5 years
otherwise the project may be deemed unviable. However this is not a commercial project, the
project will be deemed successful if cost is saved over the project, the aim is to create a renewable
source that will be an increasingly cheaper and viable option over the years, create jobs and skills
and awareness of using resources that are so readily available in remote Australia.
“In the past solar panels have been an expensive investment with a financial payback period that
many would have considered too long.
Due to dramatically increasing electricity prices in recent years and falling solar panel prices
commercial installations have now become more than viable.
In 2010 a 50kW solar system would have cost in the region of $150,000 or $3,000 per kW of solar
panels installed. In 2014 prices were seen as low as $60,000 or $1,200 per kW of solar panels
installed.” [26]
36
Figure 35: Payback period graph
From figure35 (above) the payback period of this project will be 6 years. The model used has
allowed for the aforementioned diesel inflation price per annum as well as replacement costs for
batteries. That cost can be seen as a small dip in year 10 and year 18. All operating diesel costs for
the hybrid system were also included in the calculations and a screenshot of the spreadsheet will be
included in the appendices.
A 6 year payback period for this community means an easier possible approach to funding, it means
that the project is profitable and a low risk for any entities looking to fund the project. It also makes
the project highly attractive to the government due to projected savings of over 2 million dollars
with a short pay-back period.
9 Safety As the design still requires further research before implementation, broad safety requirements will
be touched on and are to be considered at a greater depth later in the final implementation and
installation of the project
Australian standards require that a system adheres to certain aspects of design to ensure the safe
operation and maintenance of the project.
In general safety requirements for PV, batteries, cabling, inverters and housing should be adhered to
and will be briefly summarised below.
The clean energy council states “It is essential that Clean Energy Council-accredited installers own
and use the relevant standards for design and installation of solar photovoltaic (PV) systems.” [25]
For installation and final design clean energy council accredited installers will be used and it is
essential that they follow the following Australian standards upon installing and designing the
system.
AS 4509 for stand-alone power systems, AS 4086 for batteries and AS 5033 (amended version) for
the installation of PV arrays.
AS 3000 should also be used for electrical wiring, AS 1768 for lightning protection and AS 4777 for
inverter design.
-2000000
-1000000
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Cash flow vs year of project
Year Nominal cash flow
37
It is imperative that these standards are followed very closely for the safe operation of the system
and protection of those in the community and those installing the system.
10 Conclusion
This thesis has been a helpful study on load profiling and has provided both practical and theoretical
work. When first embarking on this project almost a year ago the aims and purpose of the task were
very different to what they have evolved into. This is mainly due to a lack of information in the
Kimberley or when the information is present it not being readily available due to privacy issues.
However valuable load data was collected and when compared to quarterly figures can prove to be
relatively accurate. It should be mentioned that seasonality and number of people living in the
houses could possibly affect the load profiles even though members of this community stated that
the seasonality did not.
For the sake of the thesis an average load profile was used for system design. The average profile
seemed to be the closest option to the quarterly averaged data.
Many components and their correlating prices were researched and then compared to industry
standard prices. This provided a good base for the system’s overall capital cost which was important
in simulating the system and calculating economics for the system.
The base system was then calculated using simple back of the envelope calculations and this would
serve as a basis or starting point for the simulation in HOMER.
All inputs were then entered into HOMER and analysed. This resulted in a hybrid system consisting
of the smallest of the diesel generators, 400kW of PV, 180kW of inverter (AC) and 960 batteries.
The initial capital cost being just above 1.4 million dollars (AUD) but with a saving of $270,000 AUD
per year on diesel the system reaches payback within 6 years. For such a large non-commercial
system this payback period is very acceptable and attractive and shows promise in gaining funding or
subsides for this project.
10.1 Implementation in the future If the project gains funding there are a few recommendations before the system would be designed.
This is a good preliminary design and points towards the project being viable, however if that
amount of capital was to be invested it would be worth doing further research on the load profiles. It
would be the recommendation of this engineer that a meter be installed at the generator for at least
an entire year before implementation takes place.
This is for two reasons. The first being that this will settle whether the seasonality up in
Jarlmadangah affects the load as although the population stated that it didn’t and as it was relatively
hot all the time it should still be checked to avoid a potentially large design flaw.
The second being that the introduction of the power card came in to action only a few months prior
to my visit and will continue to encourage smarter and more conservative use of power. That means
that power usage could drop dramatically as the inhabitants now have to pay for the power they use
whereas before power was free. Obviously the new habits can take a little while to come to fruition.
38
Another aspect of further research that should be implemented before final design and construction
would be keeping a daily list of populations within the community. A correlation test performed
early in the project (see appendices) showed the number of members in the household had a high
correlation with amount of power used. Originally part of this project was to collect population
records and cross reference with the loads used to create a prediction model but unfortunately
there was no records of populations at Jarlmadangah and daily load profiles were not available from
KRSP due to new privacy acts which only allowed personnel of the company to access such
information.
Keeping a record of the population throughout a year and then cross referencing to the loads of
those days would help in system prediction, allowing inverters to ramp up and down accordingly and
diesel generators to charge batteries in advance if there was to be a spike in power usage that PV
couldn’t account for.
This prediction model would also help in designing systems in the future giving a basic model for
usage that could be purely based on the population of the community.
Work will continue if need be to ensure the completion of this model for Srini and Regen Power.
I have also been contacted by an engineer that works for a company (intentionally unnamed here)
that completes hybrid systems in remote aboriginal communities. Steve Holdsworth recommended
him. The company is interested in installing a PV system for Jarlmadangah and was going to conduct
a survey of its own. However Steve mentioned I may be able to help. Part of this thesis will serve as
preliminary research and a possible tender to this company. Already saving Jarlmadangah a fee of
$5000 for surveying alone.
10.2 Deliverables At the start of this project almost a year ago 3 deliverables were mentioned. The success of this
thesis is based on whether these deliverables were in fact delivered.
The primary deliverable was to make contact with a small indigenous community and collect load
data to create and simulate a hybrid power system and to also create a day ahead prediction model
based on correlations of education, members of household, employment.
The first was hugely successful with a deeply involved and researched system design that had a
successful payback period of 6 years, saving over 2 million dollars over the lifetime of the project,
however the latter was not able to be completed due to the aforementioned lack of information,
however it would be easily achievable with further research using electricity meters and
implementing daily records of populations.
Deliverable B and C were to deliver a thesis paper between 12,000 to 15,000 words that documents
the research, discoveries and results of this study. C being a presentation presenting a summary of
all discoveries made. Both B and C were completed successfully and within the given time limit.
Overall apart from the inability to complete the load prediction model this thesis was a huge success
and led to a deeper understanding of power consumption in the remote Kimberley and proves that
renewable hybrid systems will play a huge part in the future not just from an ecological viewpoint
but economically as well.
39
11 Appendices
11.1 Correlation tests
The prediction model will use historical power usage and match it with known variables that
occurred on that same day, the variables could be temperature, humidity, population, and public
holidays.
In order to know just what variables to include within the prediction model it is a good idea to do
some correlation tests on the data. This was achieved using a program called Matlab. “MATLAB is a
high-performance language for technical computing. It integrates computation, visualization, and
programming in an easy-to-use environment where problems and solutions are expressed in familiar
mathematical notation.” [37] The correlation test is designed to find which variables (number of
members in a household, number of rooms, education, and employment) are most related to the
power usage. This will give an indication on what most influences power usage.
The program is very simple and small for calculating correlations, it uses an inbuilt function within
Matlab that compares two vectors and finds the correlation between them.
A vector was constructed for each variable to be tested against the load vector. The four variables
listed above were to be tested.
The correlation tests yielded the following results.
TEST CORRELATION TO AMOUNT OF POWER USED
MEMBERS IN HOUSEHOLD 95.06% ROOMS IN HOUSEHOLD 30.42% EDUCATION 92.60% EMPLOYMENT 87.80% MONTHLY INCOME 87.80%
The correlation test yields as expected that the number of members of the household has the
highest correlation to the amount of power so this can possibly be used in the prediction model as
long as there are records of the overall populations at any given time. The aim here would then be
being able to use the weather forecast as well as a known population for the community of that day
40
and then use historical data to compute the likely power usage of that day by cross referencing
historical days of similar events and then averaging them.
11.2 load profile surveys in order (average, best, worst) The complete load profile surveys were omitted from the main report as they take up a relatively
large amount of space. Please find the average scenario, best case and worst cast below.
41
42
43
44
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