SOLA9104 Assessment 2

HRES Case Study Report (Individual)

1 Overview

The purpose of this assignment is to assess your knowledge of HRES operation, HOMER functionality, and how to use HOMER to conduct a techno-economic analysis of a HRES.

For this assessment, you will be assigned a case study, and complete the tasks outlined in this brief. Case studies include:

1)  Tuvalu – Vaitupu

2)  Tuvalu – Nanumaga

3)  Tuvalu – Funafuti

4)  Cook Islands – Mangaia

5)   Bamyan hospital

2 Report structure

Your final submission will consist of a written report and Excel spreadsheet to show method and working. It is expected that the report be no longer than 15-20 pages (minimum 11pt font) excluding references and appendix. The report should include the sections described below. The task associated with each section is described in Section 3.

1.   Introduction

2.   Site assessment

3.   RE resource assessment

4.   Risk assessment

5.   Load assessment

6.   Design scenarios

a.   Minimum Renewable Fraction (MRF) = 0% (diesel only)

b.   MRF = 30% (diesel and solar PV)

c.   MRF = 60% (diesel, solar PV and battery)

7.   Relationship between COE and MRF

8.   Sensitivity analysis

9.  Advanced grid

10. References

11. Appendix

3 Task breakdown

3.1 Introduction

Briefly describe the context of your case study, including key elements such as loads, climate and location. Explain what questions you are trying to answer with your modelling and analysis.

3.2 Site Assessment

The site assessment should consist of the following:

•    A description of the site in terms of its location, the community (people, demographics, etc.), and the environment, and whatever else you identify as being important.

• Existing electrical infrastructure

All sources of information and assumptions must be given and referenced.

3.3 RE resource assessment

The RE resource assessment should consist of the following:

• Weather data analysis (temperature, wind, irradiance).

•    Suitability assessment for solar PV generation

•    Suitability assessment for alternative types of RE generation (even though they won’t be part of the design).

All sources of information and assumptions must be given and referenced.

3.4 Risk assessment

Highlight and describe any potential risks (logistics, environmental sensitivity, natural disasters etc.) identified following the site and RE resource assessment which may potentially have an impact on the viability of a HRES.

All sources of information and assumptions must be given and referenced.

3.5 Load assessment

Using the bottom-up approach, develop and present 24 daily average load profiles for your case study, one for each month for each weekend/weekday. These will be based on the information you obtained from the case study brief and any other data gathered (e.g., technical data for appliances, appliance ownership, appliance use, etc.).

•    Provide comment on your load profiles so the reader is able to understand their make-up, highlighting important aspects which may impact on your HRES design.

•    Calculate key metrics: peak demand (kW), minimum demand (kW), and daily energy consumption (kWh) for each daily load profile

•    All working for this task is to be done in an Excel spreadsheet and submitted to Moodle.

The load profile developed in this section is to be used for all following tasks. All sources of information and assumptions must be given and referenced.

3.6 Design scenarios

3.6.1   Scenario 1 - MRF = 0% (diesel only)

This task consists of four (4) sub-tasks:

1.   Use the method given in the lecture notes to manually size three (3) diesel generators to meet the load of your case study.

a.  All working for this sub-task is to be done in an Excel spreadsheet and submitted to Moodle.

2.   Build a system in HOMER using the diesel generators from sub-task 1

a.   If your system isn’t feasible, use HOMERS search space functionality to find a system with a set of generators as close as possible to those calculated in sub-task 1.

3.   Use HOMERs search space functionality to design a diesel only system which gives the lowest COE, while still meeting the load demand for your case study.

a.   Include a description of the final design (component sizes, HOMER parameters, COE etc.) and the search space method used.

4.   Download the HOMER results data for your two scenarios (sub-task 2 and 3) and for both scenarios, use it to create (a set of?) daily average profiles for the columns (load, generation, fuel consumption etc.) for a month that you think best explains the reason for the difference in COE between the two systems. Provide this explanation.

3.6.2   Scenario 2 - MRF = 30% (diesel and solar PV)

This task consists of five (5) sub-tasks:

1.   Use the method given in the lecture notes to size a solar PV system designed to meet 60% of average daily daytime load demand (kWh) for your case study.

a.  All working for this sub-task is to be done in an Excel spreadsheet and submitted to Moodle.

2.   Build a system in HOMER which includes the solar PV system from sub-task 1 and the diesel generators from Scenario 1 – Sub-task 1.

a.   If your system isn’t feasible, use HOMERS search space functionality to find a system with a set of generators as close as possible to those calculated in Scenario 1 - Sub-task 1.

b.   Manually size three (3) diesel generators using the new net load (consumption minus solar PV generation) of your case study

3.   Build a system in HOMER using the solar PV system from sub-task 1 and the diesel generators from sub-task 2

a.   If your system isn’t feasible, use HOMERS search space functionality to find a system with a set of generators as close as possible to those calculated in sub-task 2.

4.   Use HOMERs search space functionality to design a system consisting of solar PV and diesel generation which gives the lowest COE for a MRF = 30%, while still meeting the load demand for your case study.

a.   Include a description of the final design (component sizes, HOMER parameters, COE etc.) and the search space method used.

5.   Download the HOMER results data for your two scenarios (sub-task 3 and 4) and for both scenarios, use it to create (a set of?) daily average profiles for the columns (load, generation, fuel consumption etc.) for a month that you think best explains the reason for the difference in COE between the two systems. Provide this explanation.

3.6.3   Scenario 3 - MRF = 60% (diesel, solar PV and battery)

This task consists of four (4) sub-tasks:

1.   Use the method given in the lecture notes to size a solar PV system and battery designed to meet 60% of average daily load demand (kWh) for your case study.

a.  All working for this sub-task is to be done in an Excel spreadsheet and submitted to Moodle.

2.   Build a system in HOMER using the solar PV system and battery from sub-task 1 and then use HOMERs search space function to add a set of diesel generators which gives the lowest COE for a MRF = 60%, while still meeting the load demand for your case study.

a.   Include a description of the final design (component sizes, HOMER parameters, COE etc.) and the search space method used.

3.   Use HOMERs search space functionality to design a system consisting of solar PV, battery and diesel generation which gives the lowest COE for a MRF = 60%, while still meeting the load demand for your case study.

a.   Include a description of the final design (component sizes, HOMER parameters, COE etc.) and the search space method used.

4.   Download the HOMER results data for your two scenarios (sub-task 2 and 3) and for both scenarios, use it to create (a set of?) daily average profiles for the columns (load, generation, state of charge, fuel consumption etc.) for a month that you think best explains the reason for the difference in COE between the two systems. Provide this explanation.

3.7 Relationship between COE and MRF

This task consists of three (3) sub-tasks:

1.   Build a system in HOMER with the lowest COE for the remaining MRF percentages (increments of 10%). Create a plot which shows the relationship between (lowest) COE and MRF

2.   Build a system in HOMER with values 0-100%, with increments of 10%, entered into the Sensitivity Variable Editor for MRF. Create a plot which shows the relationship between (lowest) COE and MRF

3.   Compare the two plots and discuss the differences (if any). Explain what you’ve learnt about HOMER from doing this task.

3.8 Sensitivity Analysis

This task consists of two (2) sub-tasks:

1.   For each HOMER system (0-100% MRF) used in Sub-task 1 of Section 3.7, perform a  sensitivity analysis using the Sensitivity Variable Editor for each of the systems used the following parameters:

a.   Maximum annual capacity shortage (%)

b.   Operating reserve for Solar power output (%)

c.   Diesel price ($/L)

d.   Minimum state of charge (%)

2.   Create a box and whisker plot for each parameter which shows how sensitive the COE is to each parameter for each 10% increment of MRF

3.9 Advanced grid for battery scheduling

This task consists of three (3) sub-tasks:

1.   Using your 60% MRF system, remove the diesel generators and add a grid connection

a.   Use a Scheduled rate with following Time of Use (TOU) tariff defined under Rate Definition

Peak 4-9pm (50c/kWh)

Off-peak 9pm-7am (15c/kWh)

Shoulder 7am-4pm (25c/kWh)

b.   Give a monthly breakdown of Energy purchased (kWh), Peak load (kW), and Energy charged ($)

2.   Download the HOMER results data and analyse the data to determine how best to edit the rates under Rate Definition to control battery charging/discharging to maximise the reduction in Energy purchased (kWh), Peak load (kW), and Energy charged ($) for each month.

3.   Provide analysis of the downloaded data explaining how you determined how best to edit the rates.

3.10 References

List your references here

3.11 Appendix

Put any content referenced in the main body of your report (that isn’t included in the references section) here. If it’s not referenced in the main body of your report it won’t be read.

4 Assumptions

Use the following assumptions when designing your system:

System

•    All components on AC except battery on DC bus (connected via converter)

Operating reserve

•    Load in current time step = 10%; Annual peak load = 0%; Solar power output = 10%; Wind power output = 0%

Electric Load:

•    Use default Random Variability

Battery:

•    Battery control = LF

Economic:

•    All values in $USD

• Discount Rate: 6%

• Inflation: 2.5%

•    Project lifetime: 20 years (components have different lifetime, present assumptions for each)

•    O&M costs for all components = 1% of capital

Diesel generators:

• Capital cost = $4250 x kVA^0.5

•    Default settings for parameters otherwise

•    Diesel = $2/L

• Use default fuel curve

Losses:

•    Component losses (solar PV inverter, battery, cabling, etc.): make your own assumptions, provide references

Solar PV system

•    Solar PV panel degradation: make your own assumptions, provide references. Set under Multi-year in HOMER.

5 Additional information

•    We’ll be very strict with the page limit and will not mark any information beyond the limit. The purpose of this is for you to decide what’s relevant and to show your work and results in a succinct way.

•    The Appendix can exceed the page limit, and it will not be marked.

•    Any existing diesel generation on-site is to be ignored as part of your design.

•    Appendix content should only be included if it’s referenced in the main body of your report.