Simulation of Renewable Energy Sources using Home Pro

The goal of this paper is to present a lab simulation experiment on design, simulation and analysis of Stand-alone/Grid-Connected Renewable Power System for Residential Use for a place located in Victoria. The main resolution to be tackled in this report is how to optimize energy resources based on the available renewable energy.

EEET 2334/35 ASSIGNMENT Surname 1
UNIVERSITY
FACULTY
UNIT TITLE
EEET 2334/35 ASSIGNMENT
SIMULATION OF RENEWABLE ENERGY SOURCES USING HOME PRO
NAME OF STUDENT
REGISTRATION:
DATE:

EEET 2334/35 ASSIGNMENT Surname 2
Summery
The goal of this paper is to present a lab simulation experiment on design, simulation and analysis of
Stand-alone/Grid-Connected Renewable Power System for Residential Use for a place located in
Victoria. The main resolution to be tackled in this report is how to optimize energy resources based on
the available renewable energy. There are many energy resources currently available in Victoria, most
of which are renewable. This renewable resource can be utilized to manage the increasing energy
demand. Basing on the above considerations, various energy resources have been incorporated in this
design. Solar energy and wind power have been incorporated with utility grid, the utility grid has been
tapped from the nearby power supply.
A diesel generator has been used as a backup together with a solar battery. These components are
reliable to provide constant energy supply to the Victoria region. The feasibility analysis of the solar
power and wind energy will also be studied in this paper.
Introduction
Renewable energy utilities are distributed over different geographical areas throughout the world, this
is in contrast with non-renewable electrical energy resources which are on found in few or limited
countries in the world. The increase in utilization of renewable energy resources over the modern days
have led to reduction of energy shortages[2], mitigation of change in climate and also merits in
economic development [3]. Recent research has concluded that most of the climate change has been
induced by use of non-renewable energy sources, this have led to increase in the greenhouse gas, non-
renewable energy consumption that produces CGH gas should be held liable for the air pollution [5],
scientist have proposed that the main mitigation that could be done to reduce environmental
degradation are curb climate is to adopt renewable energy resources. Based on international public
surveys, people support the use and implementation of renewable energy sources such as solar power
and wind power [3]. At the international level, more than 30 countries have installed at least twenty
percent of the total national grid be from renewable energy sources. The world market for the
renewable energy sources is expected to increase by twenty percent in the coming decades, this could
even go beyond as stated by the Australian energy regulation bodies. Other countries, such as Norway
and Iceland have more than 95% of the total energy used sourced from renewable energy sources and
many other nations have a target of achieving 100% of their energy to be from renewable energy
sources. Examples include countries such as Denmark which switched to achieving renewable energy
use by 2050.
The simulation location of microgrid design is provided in the map below.

EEET 2334/35 ASSIGNMENT Surname 3
Modelling, Simulation and Optimisation Results
Modeling
The modeling of a Microgrid system involved a choice of different components integrated together.
The components used were as provided below.
 back-up generator (diesel or gas micro turbine)
 a utility Grid
 a PV system
 a converter and a battery
 Wind turbine.
Justification of component design choices used in modelling
back-up generator (diesel)
a diesel generator was used for off-grid power production. Diesel was preferred for its availability and
flame factor. The diesel generator used has a high capacity installed, the shaft efficiency is high, rapid
start and stop and with a minimal exhaust heat. This makes this generator more advantageous for the
simulation. In this model 2.6kW capacity diesel generator is used [13] [8]
a PV system
PV system utilizes the natural solar energy to produce power. A generic flat PV was chosen for this
modeling. It produces a 1kw/hr. its relative costs and maintenance is cheap.
The results provided in table below shows the systems justifications based on previous years[9].
Year
averages
PV systems
Efficiency
Solar Output
(Watt/m2)
Monthly Average

EEET 2334/35 ASSIGNMENT Surname 4
Radiation
(Watt/m2)
Output
(Watt/m2)
Output
(Watt/m2)
02.07.2016 68% 820 465.8
12.07.2016 683% 900 300
22.07.2016 68% 830 600
4.2016 68% 361.79 120.6
Convertor
Convertor was needed to convert the direct current from solar PV system and Battery
Battery
100kwa lithium ion battery is usedin model diagram because of its durability and efficiency in storing
power. The costs requirements and the maintenance cost used was 1000$ [7]
Wind turbine
Wind resources have been a good energy resource for a long time. It is important to recognize wind as a
renewable energy source. Wind speed of 6m/s was used for this case.

EEET 2334/35 ASSIGNMENT Surname 5
Figure 1. schematic model of electrical connections of Stand-alone/Grid-Connected
Renewable Power System for Residential Use
Simulation
This involved the design of the chosen system and considering the parameters outlined in the model.
During
this process, the energy optimization mathematics was performed using the Homer pro software, these
calculations were based on the real time parameters configured to the software which comprised several
components provided in the model. The components considered in the simulation were:
solar panel, convertor with battery and a generator. This was for the purpose of simulation and
evaluation of the Stand-alone/Grid-Connected Renewable Power System for Residential Use [6], [10].
When the simulation is complete, the homer pro will determine the best energy solution for the Victoria
region based on the parameters configured. HOMER Pro will simulate the modelled system by
estimating the
installing cost, replacement cost, operation and maintenance cost, fuel and interest rate [6].
Optimisation Results
The results tabled below were obtained from the simulation by HOMER Pro software.
The results were exported to a csv file in excel
Cost/
NPC
($)
Cost/
COE
($)
Cost/
Operating
cost ($/yr)
Cost/
Initial
capital
($)
System/
Ren Frac
(%)
-
9.43E+
09
-
12.761
6 -470449 21850
95.0374
3
-
9.43E+
09
-
12.719
4 -470413 21950
95.3600
4
-
9.41E+
09
-
115.53
4 -469352 11050 100
-
9.41E+
09
-
115.53
4 -469350
11102.3
8 100
-
9.41E+
09
-
115.52
1 -469298 11150 100
-
9.41E+
09
-
115.52
1 -469297
11155.5
7 100
-
9.40E+
09
-
115.43
4 -468945 11050 0
-
9.40E+
09
-
114.75
9 -468927 11150
8.88662
9

EEET 2334/35 ASSIGNMENT Surname 6
-
3.50E+
07
-
0.0473
2 -1745.37 15550
95.0374
3
-
3.43E+
07 -0.0462 -1709.41 15650
95.3600
4
-
448379
3
-
0.0547
2 -223.829 4850
8.88662
9
155110
0
0.0190
39 77.28909 1150 0
5.00E+
07
0.6139
94 2493.545 15550 17.0825
5.03E+
07
0.6171
67 2506.432 15567.5
18.5797
4
7.77E+
07
0.9542
77 3876.461 4850 0
8.39E+
07
1.0298
47 4183.645 1150 0
Sample screenshot of optimization results from the HOMER Pro software
PV/Capital Cost
($)
PV/Production
(kWh/yr)
G1/Capital Cost
($)
G1/Production
(kWh/yr)
G1/O&M C
($)
10800 53880.34
10800 53880.34 100 382.2376 60
52.38356 261.3374
100 382.2376 60
11.72988 58.51946 100 382.2376 60
100 382.2376 60
10800 53880.34
10800 53880.34 100 382.2376 60
100 382.2376 60
10800 53880.34
10717.5 53468.75 100 382.2376 60

EEET 2334/35 ASSIGNMENT Surname 7
100LI/Annual Throughput
(kWh/yr)
100LI/Nominal Capacity
(kWh)
100LI/Usable Nominal Capacity
(kWh)
0 9000.018 7200.014
0 9000.018 7200.014
4507.577 9000.018 7200.014
4232.104 9000.018 7200.014
4131.014 9000.018 7200.014
4070.677 9000.018 7200.014
0 9000.018 7200.014
0 9000.018 7200.014
Converter/Inverter Mean Output
(kW)
Grid/Energy Purchased
(kWh)
Grid/Energy Sold
(kWh)
Column
1 C
3.999421 1829.419 32801.89
4.026005 1716.036 32921.39
0.46375
0.46375
0.46375
0.46375
0 4062.45 0
0.04145266 3723.073 23.74822
3.999421 1829.419 32801.89
4.026005 1716.036 32921.39
0.04145266 3723.073 23.74822
4062.45 0
0.2126844
0.2179524
0.009376878
Optimization results for convertor and grid energy
Detailed results have been attached for a HOMER Pro software

EEET 2334/35 ASSIGNMENT Surname 8
The capacity calculation graph without the utility grid
The monthly
Practicality of the Optimisation Results
Arguably, the results obtained are mere estimates of energy sources that can be utilized in Victoria.
systems could be implemented and real practical estimations obtained.
The following assumptions made define the practicality of the design model.
 The use of wind energy in Victoria is impractical due to the huge costs required to install the
turbines, also the wind speed in the region is low. [16]
 The use of PV systems is impractical because of low solar radiation in the region. Its efficiency
is uncertain due to changing weather. [12] [10]

EEET 2334/35 ASSIGNMENT Surname 9
Discussion
Table- microgrid economics
the results above display the total cost required for the installation. The costs are too high. Installing the
wind turbines and solar systems raises the costs. The Grid system would be cheaper. [14]

EEET 2334/35 ASSIGNMENT Surname 10
Months
Daily Energy
Output (Watt/m2-
hr)
Monthly Energy
Output (Watt/m2-
hr)
Average
Monthly
Energy
Output
(Watt/m2-hr)
Average
Yearly
Energy
Output
(Watt/m2-hr)
january
546 16180.8
february 678 146357.25
march 539.84 1616
April 541.97 1987
May 448.54 359
Jun 476.61 799
july 474.07 14222.1
August 783 17131.8
September 234 2342
October 2343 2342 15957.25 191487
Total energy output for the region.
The variations in monthly energy production is due to changes in weather and natural resources that
influence the renewable energy sources. These factors are listed below.
a. Changes in solar radiation
b. Varying rainfall that causes changes in dam capacity and
c. Varying wind speeds

EEET 2334/35 ASSIGNMENT Surname 11
Sensitivity analysis chart.
Conclusion
The modeling of a Stand-alone/Grid-Connected Renewable Power System for Residential Use involved
a choice of different components integrated together. The model described is based on the solar
radiation as obtained from the Bureau of Metrology (BOM) website for Victoria. The sizing and
specifications used were based on the requirements of the assignment and those of the Victoria region
of Natte Yallock. [15] [11]
References
[1] G.D.Rai, Solar Energy Utilization, 5th Edition, Khanna Publishers
[2] S. Hasan Saeed and D.K. Sharma, Non-Conventional Energy Resources, 1st Edition, S.K.Kataria &
Sons, 2006-2007
[3] Suhas P Sukhatme Solar Energy–Principles of Thermal Collection & Storage, 2nd Edition, Tata Mc
Graw Hill
[4] Cost and Performance Trends in Grid connected Photovoltaic Systems and Case Studies: Report
IEA-PVPS T2-06:2007
[5] A Guide to Grid-Connected Photovoltaic Systems prepared by Cape & Islands Self-Reliance
[6] A. Rodrigues, T. Dentinho, C. Silva, E. Azevedo “Cost Benefit Analysis to select clean energy
solutions in dairy farm
milk collection posts in Azores”
[7] Parita G Dalwadi, Chintan R Mehta, “Feasiblity Study of Solar-Wind Hybrid Power System ”

EEET 2334/35 ASSIGNMENT Surname 12
[8] Majid Alabdul Salam, Ahmed Aziz, Ali H A Alwaeli, Hussein A Kazem, “Optimal sizing of
photovoltaic systems
using HOMER for Sohar,Oman”
[9] ZalalemGirma, “Hybrid renewable energy design for rural electrification in Ethiopia”
[10] Hani S.Algnaahi, Kamaruzzaman S., Mohamed A, Ahmed M. A. Haidar and Ahmed N. Abdalla
“Experimental study
of Using Renewable Energy in Yemen”
[11] BinduKansara, Prof. (Dr.) B. R. Parekh,“Modeling and simulation of Wind-Diesel hybrid system.”
[12]. R. G. Belu, A Project-based Power Electronics Course with an Increased Content of Renewable
Energy
Applications, June 14-17, 2009 Annual ASEE Conference and Exposition, Austin, Texas, 2009 (CD
Proceedings).
[13] R.G. Belu – Design and Development of Simulation System for Renewable Energy Laboratory,
2010 ASEEE
Conference & Exposition, June 20 - 23, Louisville, Kentucky (CD Proceedings).
[14] R.G. Belu and D. Koracin – E-learning Platform for Renewable Energy Sources, 2010 ASEEE
Conference &
Exposition, June 20 - 23, Louisville, Kentucky (CD Proceedings)
[15] R.G. Belu - Renewable Energy Based Capstone Senior Design Projects for an Undergraduate
Engineering
Technology Curriculum, 2011 ASEEE Conference & Exposition, June 26 - 29, Vancouver, BC, Canada
(CD
Proceedings).
[16] L. Arribas, L. Cano, M. Mata, and E. Llobet, "PV-wind hybrid system performance: A new
approach and a case
study," Renewable Energy, vol. 35, no. 1, pp. 128-137, 2010