SOLA9103
RE System Modelling and Analysis
School of Photovoltaic and Renewable Energy Engineering
Assignment 2: Resource and Energy Production Assessment
Due Date: Week 7, Friday, 5pm
Assignment Brief:
You have been employed as a consultant for a solar firm. Your client requires you to (1) undertake a
resource assessment of a site for PV deployment; (2) recommend an appropriate set of weather data
for use in the clients PV system modelling; (3) undertake an energy production assessment of the
client’s proposed solar farm; and (4) provide a detailed report outlining the methodology,
assumptions and outcomes of the solar resource and energy production assessment.
Context:
The process of being able to undertake, understand and interrogate resource and energy production
assessments is a key skill for any Engineer who plans on working within the commercial or utility
scale renewable energy industry. The methodology used, assumptions made, and outcomes of
resource and energy production assessments are used by various parties in research and industry
such as prospective renewable energy (RE) developers, financiers, EPC companies, owners’
engineers and regulatory bodies. These parties use resource and energy production assessments to
undertake a range of activities. For example, EPC engineers can use them to bid for and negotiate
contracts, whilst an owner’s engineer might use them to justify, negotiate and set guaranteed
performance targets.
Learning Outcomes:
Coursework Related Outcomes:
• Apply appropriate data cleaning and data visualisation techniques to manage, query, explore
and communicate information from large weather and energy data sets.
• Use modelling to undertake a resource assessment, predict short- and long-term renewable
energy system performance and appropriately describe the uncertainty of the prediction.
• Use data analysis and modelling techniques to understand, describe, interrogate and
challenge assumptions in RE modelling.
General Skills:
• Handling large datasets, data exploration and data visualisation
• Basic statistics and evaluating uncertainty
• PV system modelling
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Assignment Resources:
The Clients Proposed Solar Farm
The client has proposed the following specifications for their Solar Farm:
Table 1: Specifications of the clients proposed solar farm
Azimuth & Tilt Angle Horizontal single-axis tracker N-S axis
0°/0°
Tracker Rotation -60°/+60° backtracking included
Mounting Arrangement Rows of 1 panel in portrait* orientation
Row Spacing (m) 5.0
Inverter Type SMA 4200 kW Sunny Central 4200 UP
Number of inverters 25
Total inverter power PAC (MW) 105
PV module type Canadian Solar (CSI) CS3W-450MS 1500V
PV module capacity (Wp) 450
Number of PV modules 260,400
Total rated power PDC (MWp) 117.18
Modules per string or in series 28
Strings per tracker 3
Number of trackers 3100
* For PVsyst versions prior to version 7.0, PVsyst considers this to be landscape
Your Assignment 2 Location
For this assignment, you will be required to undertake a resource and energy production assessment
for a specific location based on the dataset you were assigned in Assignment 1.
Your assigned location for Assignment 2 can be determined by referring to Table 2 and by following
the instructions below:
1. Using Table 2, under the Assignment 1 header, locate the row which contains the BOM
Station Name and Station ID that corresponds to the dataset you were assigned in
Assignment 1.
2. Under the Assignment 2 header, read off the Location, Latitude and Longitude which
corresponds to the same row as the row you identified in Step 1.
3. This is your assigned location for Assignment 2.
Students who fail to undertake the assignment for their assigned location for Assignment 2 will
receive a 30% penalty on the maximum possible grade.
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Table 2: Relationship between the BoM AWS data you were assigned in Assignment 1 and your assigned location for
Assignment 2.
Site
Assignment 1 Assignment 2
BOM Station Name BOM Station ID Location Latitude Longitude
1 Blackall Airport 036034 Barcaldine -23.548 145.32
2 Broken Hill Airport 047048 Broken Hill -31.987 141.39
3 Georgetown Airport 030124 Kidston -18.891 144.14
4 Goulbourn Airport 070330 Gullen Range -34.61 149.47
5 Griffith Airport 075041 Griffith -34.319 146.12
6 Moree Aero 053115 Moree -29.57 149.87
7 Parkes Airport 065068 Parkes -33.118 148.08
8 Swan Hill Aerodrome 077094 Gannawarra -35.729 143.78
9 Trangie Research Station 051049 Nyngan -31.557 147.08
10 Tuggeranong 070339 Royalla -35.49 149.14
Recommended Data Sources
For the resource and energy production assessment, you can make use of any of the following data
sources, or other similar resources that you manage to track down:
• The data you were asked to assess in Assignment 1.
• The Australian BOM Climate Data Online http://www.bom.gov.au/climate/data/
• The National Map web portal (formally known as AREMI) https://www.nationalmap.gov.au/
• The NASA POWER Data Access Viewer https://power.larc.nasa.gov/data-access-viewer/
• Annual and monthly statistics of irradiation, air temperature and wind speed from
Meteonorm and NASA SEE – Access available through PVsyst.
• The World Bank Group’s Global Solar Atlas and Global Wind Atlas
o http://globalsolaratlas.info/
o https://globalwindatlas.info/
• The International Renewable Energy Agency’s (IRENA) Global Atlas for Renewable Energy.
https://irena.masdar.ac.ae/gallery/#gallery Multiple layers of data are available on this
resource including:
o Vaisala solar and wind maps
o Meteotest Solar Map
o Hint: use search for key words ‘solar’ and ‘wind’
• The TMY and RMY weather files available for Australia: – Access via the U.S. DOE EnergyPlus
Weather website:
https://energyplus.net/weather-region/southwest_pacific_wmo_region_5/AUS
• TMY weather files for Australia from Climate.OneBuilding.Org
http://climate.onebuilding.org/default.html
• The IWEC2 weather files – Part of the assignment resources available to download from the
course website.
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Assignment Tasks:
Task 1: Undertake a Resource Assessment of the Clients Specified Site
The client has asked you to undertake a detailed resource assessment for their specified location,
with the aim of determining the suitability of the site for the installation of a Photovoltaic solar farm.
The client has requested that the resource assessment considers the long-term characteristics and
variability of the solar resource and temperature. In addition, the client requests that you undertake
a rainfall soiling analysis and make a recommendation for an appropriate weather file/dataset for
use in modelling their proposed solar farm.
The assessment must include:
1. An analysis of the long-term annual and monthly averages of Global Horizontal and Direct
Normal Irradiation in units of kWh/m2.year and kWh/m2.month, and a measure of
uncertainty of the estimates.
2. An analysis of the long-term annual and monthly averages of air temperature in units of °C,
and a measure of uncertainty of the estimates.
3. An analysis of the interannual variability of Global Horizontal Irradiation.
4. The determination of the best and worst solar resource years for the specified location.
5. An assessment of the available hourly weather files/sources for the specified site or from
nearby locations, including how well the weather files/sources reflect (a) the long-term
averages for GHI, DNI and air temperature; and (b) the long-term distribution of direct
normal irradiation.
6. An assessment of the monthly soiling rate via a rainfall soiling analysis.
7. A recommendation for an appropriate hourly weather file/source for use in modelling the
performance of the client’s proposed solar farm.
NB: You can make use of your data visualisations from Assignment 1 as part of your Assignment 2
submission if they are relevant to the tasks listed above.
Task 2: Undertake an Energy Production Assessment of the Clients
Proposed Solar Farm
The client has asked you to model their proposed solar farm in PVsyst, requesting the calculation of
the P50 and P90 probability of exceedance statistics of the predicted average annual energy
production over the first year of operation, over the first 10 years of operation and over the first 25
years of operation.
For this task you will need to:
1. Develop a model of the client’s proposed solar farm in PVsyst.
2. Report the P50 and P90 probability of exceedance statistics for the predicted average annual
energy production over the first 1, 10 and 25-years of operation.
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Task 3: Putting it All Together
Put together a detailed report (maximum of 15 pages) in Microsoft Word outlining the methodology
and outcomes of the resource (Task 1) and energy production (Task 2) assessments. The client has
requested that your report include a discussion of the methodology used, the assumptions made,
and the uncertainty of, the assessments provided.
Your report must include:
1. All items listed in Task 1.
2. All items listed in Task 2.
3. A discussion of the methodologies, assumptions and uncertainty of the assessments
provided.
4. An introduction and conclusion, summarising the results or key findings/recommendations
from the resource and energy production assessments.
Your final report must be written and submitted in Microsoft Word (.docx) format. Microsoft
Word, and other Microsoft applications, are available to all UNSW students via Microsoft Office 365.
You can learn more about Microsoft Office 365 for UNSW students here.
The body of the report should have a maximum of 15 pages plus any appendices. Appendices will
not be marked, hence you as the Engineer need to ensure that the most important and relevant
information is contained within the body of your report, and only supplementary information is
provided in any appendices. If your report includes a title page, it will be excluded from the page
limit.
Do not include a copy of your PVsyst report as part of your detailed report or as an appendix to
your report. You will be required to upload a copy of your PVsyst report as a separate item as part of
the assignment submission process in Moodle.
NB: Simply uploading a copy of the PVsyst report to Moodle will not be considered as an adequate
description of your PV modelling methodology. You need to outline all your assumptions and
modelling methodology in the body of your report.
Task 4: Complete the Excel Answer Sheet
In order to aid the marking process, you will also need to fill out and submit a copy of the Excel
Answer sheet as part of your assignment submission. The Excel Answer sheet is the Excel workbook
titled ‘zID_LastName_FirstName_Answers.xlsx’ available to download from Moodle. Instructions on
how to complete the Answer sheet are provided within the Excel workbook.
Please ensure you rename your answer sheet using the following name convention:
zID_LastName_FirstName_Answers.xlsx. For example a student named John Smith with zID
z1234567, would label their file: z1234567_Smith_John_Answers.xlsx
NB: The Excel Answer sheet does not capture all the requirements of Tasks 1 and 2 outlined in this
assignment brief. Hence, you are advise to carefully read the assignment brief to ensure you include
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all requested elements in your final report. The provided answer sheet should not be treated as a
check list for the tasks required in this assessment task.
Submission
This assessment is to be done individually. Submit a copy of your final report, your Excel Answer
sheet and your PVsyst report to the ‘Assignment 2 Submission’ drop box on Moodle by the date
specified.
Your final report must be written and submitted in Microsoft Word (.docx) format. Pdf
submissions of the final report will attract a 30% penalty.
Your PVsyst report can however be a pdf submission.
Work submitted late without an approved extension by the course coordinator or delegated
authority is subject to a late penalty of 30 percent (30%) mark reduction on the first day and an
additional 10% per day thereafter, consistent with other SPREE courses. The late penalty is applied
per 24 hour period (including weekends and public holidays) that the assessment is overdue. There
is no pro-rata of the late penalty for submissions made part way through a day.
Work submitted after the ‘deadline for absolute fail’ (see the course outline) will not be accepted
and a mark of zero will be awarded for that assessment item.
Academic Honesty and Plagiarism
UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity.
All UNSW students have a responsibility to adhere to this principle of academic integrity. Plagiarism
undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using
the words or ideas of others and passing them off as your own.
Plagiarism is a type of intellectual theft. It can take many forms, from deliberate cheating to
accidentally copying from a source without acknowledgement. UNSW has produced a website with a
wealth of resources to support students to understand and avoid plagiarism, visit:
student.unsw.edu.au/plagiarism. The Learning Centre assists students with understanding academic
integrity and how not to plagiarise. They also hold workshops and can help students one-on-one.
You are also reminded that careful time management is an important part of study and one of the
identified causes of plagiarism is poor time management. Students should allow sufficient time for
research, drafting and the proper referencing of sources in preparing all assessment tasks.
Repeated plagiarism (even in first year), plagiarism after first year, or serious instances, may also be
investigated under the Student Misconduct Procedures. The penalties under the procedures can
include a reduction in marks, failing a course or for the most serious matters (like plagiarism in an
honours thesis) even suspension from the university. The Student Misconduct Procedures are
available here:
www.gs.unsw.edu.au/policy/documents/studentmisconductprocedures.pdf
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Marking Scheme
Marks will be assigned according to:
• Accuracy – correctness of the results for the specified site and PV system design;
• Completeness – inclusion of all requested metrics and elements specified in this brief;
• Assumptions – the inclusion, correctness and reporting of all assumptions;
• Methodology – how well the methodology, analysis and modelling is illustrated and
presented to the client. For instance, can the client replicate your analysis and modelling
based on the information presented in the report?;
• Understanding – how well your understanding of the analysis, modelling and outcomes are
demonstrated throughout the report; and
• Communication – how well the report is presented, including, an assessment of grammar;
relevance of the analysis and figures presented; report structure; principles of data
visualisations; referencing; and the inclusion of an introduction and conclusion.