watson '13

Optimal hybrid renewable energy systems for power

generation on the University of the West Indies

(Experimental Study)

Application of Homer and MatLab

Daren Watson1, Dr. Dorville2

1Undergraduate, Department of Physics, University of the West Indies, Mona, 2013

2Lecturer, Department of Physics, University of the West Indies, Mona, 2013

Optimal hybrid RE systems for power generation on the University of the West Indies

2 Daren Watson, Dr. Dorville, Department of Physics, University of the West Indies, Semester II, 2013

Note to reader

“Mathematical models and computer simulations are useful experimental tools for building and

testing theories, assessing quantitative conjectures, answering specific questions, determining

sensitivities to changes in parameter values and estimating key parameters from data”

~ V.A Bokil, Oregon State University



Abstract

Rising prices of crude oil and Jamaica’s dependence on this essential but limited resource have

led to there being a massive energy bill for the government. This is felt by the consumers,

especially since energy production is monopolized by the Jamaica Public Service (JPS).

Furthermore, not every community has access to electricity due to a number of challenges such

as terrain, distance from the grid as well as neglect by the relevant authorities. Renewable

energy sources (solar, wind, hydro, biodiesel, and biomass) have been found to significantly

reduce the cost of energy (COE), provided that the different systems used have suitable

exposure to the resources needed for power generation. This study is intended to not only be a

experimental study, but also one which can be capitalized upon by potential investors or by the

government to make the lives of those in remote sections of the island more comfortable. The

objective serves a dual purpose due to the fact that its success would lead to the completion of

a first degree as well as allow for diversified alternative energy planning by interested

developers.

It was found that hybrid systems significantly reduce the cost of electricity as oppose to a

homogenous system, in certain instances. Homer was used to evaluate the feasibility of

different systems consisting of; wind turbine generators, solar panels and diesel generators.

Hydro turbines were not considered for the Homer simulations as further research is needed to

assess St. Andrew’s1 hydro power generation capabilities. MatLab’s open-source platform

allowed for scrutiny of the results obtained using Homer and therefore seeks to justify the

validity of the results in this paper, as well as to provide an alternative platform for data

analysis.

1St. Andrew – Parish of Jamaica, location of study

2Keywords: hybrid, renewable energy, solar, wind, diesel, feasibility, UWI



Acknowledgement

I would like to thank Dr. Dorville for his supervision of this dissertation, assistance in the

collection of data and his challenge for me to use MatLab, software with which I had no prior

experience, to create scripts which analyse the data used in this project.

I also want to acknowledge Dr. Amarakoon for the exposure to Homer, which was the catalyst

for me to select this topic for the project.

Furthermore, thanks to Dr. Duncan for his guidance and support as well as to all my

undergraduate lecturers in the Physics and Mathematics departments for adding to my

intellectual development during my tenure at the University of the West Indies.

Mr. Kwame Hall and Mr. Stanley Smellie provided their professional opinions which were

helpful during my running of the simulations.

Special thanks to Mr Bernard Lawrence, supervisor at the electrical division of the Estate

Management Department for his unwavering assistance during the process of gathering

information on UWI’s pre-existing energy sources as well as the future energy plans such as the

Cogeneration plant.

Last but not least, thanks to Mr Lenworth Barnett for the opportunity to tour UWI’s

Cogeneration plant. I was privileged to be the first student granted such an opportunity. This

was essential in my understanding of the facility.

Gratitude to all.



Table of Contents

Content Page

List of Figures…………………………………………………………………………………………………………………………….7

List of Tables………………………………………………………………………………………………………………………………8

Abbreviations…………………………………………………………………………………………………………………………….9

Chapter 1: Introduction 1.1: Research Objectives…………….……………………………………………………………..………………………11

1.2: Methodology…..………………………………………………..…………………………………………………..……12

1.3: Limitations……....……………………………………………..………………………………………………………….13

1.4: Literature Review….……………………………………………………..……………………………………….…….14

Chapter 2: Software Review

2.1: Homer Review………………………………………………………………………..…………………….…………….16

2.2: MatLab Review…………..……………………………………………………………………..………………….…….17

Chapter 3: Data Analysis

3.1: Collected Data…………………………………….....……………………………………………………..……………19

3.1.1: Wind Speed/Solar Irradiance……………………………………………………………………………...20

3.1.2: Load Demand…………………………………….….…………………...………………..……………………21

3.1.3: Costs and Economics…………………………………………………………….……………………………23

3.2: Proposed Hybrid System………………………………………………………………………..…………………...24

Chapter 4: Results (Homer Simulations)

4.1: Optimization Results………………………………………………………………………………….………………..26

4.2: Resource Analysis..………………………………………………………………………………..…………..……….28

4.3: UWI’s Design……………………………………………………………………………………………………………….32

4.3.1: System’s Operating Characteristics….…………………………………………………………………33



Chapter 5: Further Analysis 5.1: UWI’s Design - An Analytic Approach……………………….,…………………………………………………38

5.1.1: Mona Reservoir…………..……………………………………………………………………………………..39

5.1.2: Cogeneration Plant………………….….…………………………………………………………………..…42

5.1.3: External Wind Farm…………………….………………………………………………………………………46

5.1.4: Photovoltaic System……...…………………………………………………………………………………..48

5.2: Recommendations……………………….……………………………………………………………………………..50

Chapter 6: Data Analysis (MatLab Scripts)

6.1: Data Analysis using MatLab……………………………………………….....…………………………………….53

Chapter 7

7.1: Conclusion……………….….......…………………………………………………………………………..……………55

7.1.1: Future Research………………………………………………………………………….……………………..55

7.2: Glossary…………………………………………….………………………………………………………………………..56

7.3: References….……..………………………………………………..……………………………….….…………………57

7.4: Appendix of Data………………………………………………………………………...................................59

7.5: Appendix of Pictures……………………………………………………………………………………………………62



List of Figures

Title Page

Figure 1. A typical Optimal System Type plot from Homer……………………………………………………….16

Figure 2. MatLab’s command prompt………………………………………………………………………………………17

Figure 3. Cost curve for different RE components……………………………………………………………………23

Figure 4. Proposed Hybrid System……………………………………………………………………………………………24

Figure 5. The ideal combination of RET for the Mona Campus…………………………………………………32

Figure 6. Micro hydropower system for the Mona Campus………………………………………………….....40

Figure 7. Mona Reservoir below its storage capacity……………………………………………….………………41

Figure 8. Schematic showing the heat exchange process (Chillers)………………………………………….44

Figure 9. UWI’s Cogeneration Plant………………………………………………………………………………………….45

Figure 10. Solar array on the roof of the Physics Department………………………………………………….48

Figure 11. Command Prompt displaying the monthly average Solar Irradiance……………………….53

Figure 12. Overhead view of the UWI Mona Campus……………………………………………………………….62

Figure 13. Pre-existing generator standby systems………………………………………………………………….63

Figure 14. Mona Reservoir……………………………………………………………………………………………………….64

Figure 15. Weather station on the roof of the Physics Department…………………………………………65



List of Tables

Title Page

Table 1. Costs associated with the Homer simulations…………………………………………………………….23

Table 2. Typical Homer results for the Mona Campus………………………………………………………………26

Table 3. Components associated with the simulations…………………………………………………………….59

Table 4. Monthly averages of meteorological data, Physics Department……..………………………….59

Table 5. Monthly averages of meteorological data, Woodford……………..……..………………………….60

Table 6. Clearness Index for the campus 2011…………………………………………………………………………60

Table 7. Pre-existing generator units on the Mona Campus…………………………………………………….61



Abbreviation

Acronym Meaning

BPF……………………………………………………………………………..…………………..Biodiesel Production Facility

COE……………………………………………………………………………………………………………………….Cost of Energy

Gen….…………………………………………………………………………………………………………………………Generators

HFO…………………………………………………………………………………………………………...………….Heavy Fuel Oil

JPSCo…………………………………………………………………………………………Jamaica Public Service Company

Km………………………………………………………………………………………………………………………………..Kilometre

KW………………………………………………………………………………………………………………………………Kilowatts

KVA……………………………………………………………………………………………………………….….Kilovolts-ampere

LUCE………………………………………………………………………………………….Levelized Unit Cost of Electricity

NPC……………………………………………………………………………………………………………………Net Present Cost

MSB…………………………………………………………………………………………………….Mona School of Business

OST…………………………………………………………………………………………………………….Optimal System Type

OTEC………………………………………………………………………………………Ocean Thermal Energy Conversion

OUR.....................................................................................................Office of Utilities Regulation

PetroJam………………………………………………………………………………..Petroleum Corporation of Jamaica

PV…………………………………………………………………………………………………………………………….Photovoltaic

NREL……………………………………………………………………………….National Renewable Energy Laboratory

RET………………………………………………………………………………………………Renewable Energy Technology

RES…………………………………………………………………………………………………….Renewable Energy Sources

UWI………………………………………………………………………………………………..University of the West Indies



Chapter 1:

INTRODUCTION

RESEARCH OBJECTIVE

LIMITATIONS

Literature Review

METHODOLOGY



1.1 Research Objectives

With the advent of global warming and a push by governments to reduce their carbon

footprints, renewable energy is being touted as the next step towards global development.

Nonetheless, developing countries such as Jamaica, have for many years, been struggling with a

high energy bill due to their dependence on crude oil and fossil fuel.

On a more local scale, small alternative energy enterprises have difficulties with remaining

competitive due to the high costs of RET. However, should these technologies be made to

operate in a hybrid system, the cost of energy would significantly decrease and hence, a higher

demand from the consumers. This paper will show how RETs coupled with their appropriate

resources, can be analyzed and interpreted when conducting a pre-feasibility study for a

location. Its main objectives are as follows;

i. To determine the most economically viable and geographically suitable Hybrid

Renewable Energy systems for the University of the West Indies using Homer Energy.

ii. To initiate the creation of analytical tools (scripts) using MatLab; in which data can be

read and manipulated for use similar to that of Homer Energy.

iii. To serve as an experimental/ pre-study for future work involving remote communities in

Jamaica.



1.2 Methodology

i. The location of the study was selected based on the availability of data (focus was

placed on one particular area, provided that all the information required by Homer was

available for the location).

ii. The following data were collected for the selected location in (i) above;

Load Demand

Solar Resources

Wind Resources

Costs of components for the hybrid system

iii. Inputs such as the lifetime of the project, interest rates and other economical

requirements were synthesized or derived based on the current market.

iv. Field work: On-site assessment of the selected location was carried out, making note of

the following:

Geography

Structures

Pre-existing energy power sources

v. The data collected was used to complete the objective [i] using Homer energy.

vi. MatLab was used to analyse the meteorological data, with the aim to begin replicating

the operations of Homer in MatLab’s platform.

vii. The project report was written up and preparation made for the presentation of

findings.

viii. Present and submit the project for grading.



1.3 Limitations/ Assumptions

Ideally, such a study should be conducted with current data and not data recorded more than

one year prior to its completion. This is to ensure that the results represent the present

situation, versus that of years past. Due to time allocation for the completion of this research, it

was assumed that the data obtained reflected the present day conditions and hence, all

simulated results made mention of, was applicable at the time of this project.

The selection of the location was also a challenge as limited weather stations were in operation

across the island. Hence, it was determined that the University of the West Indies should be the

experimental location due to the fact that the data was already available for use. Provided that

this study was the basis for a more detailed and comprehensive look at hybrid systems in

Jamaica, its concept could be duplicated by someone with interest to install weather stations at

preferred locations and make assessments based on the local data received.

The Physics Department’s weather station was used to record all the meteorological data and it

was assumed that these parameters were a satisfactory representative of the entire campus.

Furthermore, all costs stated were in US dollars; where the prices were obtained from local

retailers, a conversion rate of 96 JMD: 1 USD was applied.

MatLab’s role was to do data analysis and calculations using the formulas from Homer Energy

for all inputs, thereby creating an open-source program. While this is possible, all the

calculations may not have been completed, once again due to time constraints. Homer had

limitations that would affect the results and were noted whenever the need arose.

With all that said, the main limitation was therefore time constraints, however, with the

assistance of a knowledgeable supervisor and guidance from other members of the

department, this paper would have substantial amount of work upon its submission with both

objectives fulfilled.



1.4 Literature Review

Alternative Energy technology has seen an exponential increase of interest from researchers

due to its capabilities for sustainable and long-term energy production. A wide range of studies

has been conducted pertaining to solar power and its efficient conversion into electrical energy.

The Massachusetts Institute of Technology is amongst the leading researchers in this field with

numerous breakthroughs in photovoltaic devices. There has also been far reaching

developments in wind and hydro power; with the building of Ocean Thermal Energy Conversion

plants (OTEC), Wind Farms (land and ocean) and other large scaled production facilities.

Nonetheless, studies have been done related to small scaled energy production. The National

Renewable Energy Laboratory (NREL) in Canada has developed multiple software such as

RETscreen and Homer to help researchers conduct feasibility assessment for RE usage. Homer is

however widely used than others due to the ease and simplicity of its GUI.

Case study of the resources of a remote area (Iqbal, 2007) to determine the optimal hybrid

system is an essential part of planning a production facility, especially since it is necessary to

ensure that the production of energy can be sustained and allow for a return in potential capital

spent on any plant development. Furthermore, comparisons can also be made for the cost of

energy should the local power company extend its grid to any area as opposed to setting up a

microgrid with solar panels and wind turbines (Hafez, 2012).

Several researches have been reviewed so as to guide the construct of this project; however

few has been seen to utilize open-source programs such as SciLab or MatLab to justify the

validity of their findings. Therefore, this paper should add to the advancement of feasibility

studies, given a more detailed analysis of Homer’s inputs and outputs.



Chapter 2:

SOFTWARE REVIEW

HOMER ENERGY

MATLAB



2.1 Homer Energy

Homer is a closed-source micro-power optimization model which simplifies the task of

evaluating designs of both off-grid and grid-connected power systems for a variety of

applications. When a power system is designed, one must make many decisions about the

configuration of the system. The large number of technology options and the variation in

technology costs and availability of energy resources make these decisions difficult. Homer’s

optimization and sensitivity analysis algorithms make it easier to evaluate the many possible

system configurations. To use HOMER, the model is provided with inputs, which describe

technology options, component costs, and resource availability. HOMER uses these inputs to

simulate different system configurations, or combinations of components, and generates

results that can be viewed as a list of feasible configurations sorted by net present cost. HOMER

also displays simulation results in a wide variety of tables and graphs that help to compare

configurations and evaluate them on their economic and technical merits. The tables and

graphs can be exported for use in reports and presentations.

Figure 1. A typical Optimal System Type plot from Homer



2.2 MatLab

MatLab is an open source, cross-platform numerical computational package and a high-level,

numerically oriented programming language. It can be used for signal processing, statistical

analysis, image enhancement, fluid dynamics simulations, numerical optimization, and

modeling, simulation of explicit and implicit dynamical systems and (if the corresponding

toolbox is installed) symbolic manipulations.

The language provides an interpreted programming environment, with matrices as the main

data type. By utilizing matrix-based computation, dynamic typing, and automatic memory

management, many numerical problems may be expressed in a reduced number of code lines,

as compared to similar solutions using traditional languages, such as Fortran, C, or C++. This

allows users to rapidly construct models for a range of mathematical problems. While the

language provides simple matrix operations such as multiplication, the MatLab package also

provides a library of high-level operations such as correlation and complex multidimensional

arithmetic.

Figure 2. MatLab’s command prompt, with the variable browser and command history included.

http://en.wikipedia.org/wiki/Open_source

http://en.wikipedia.org/wiki/Numerical_analysis

http://en.wikipedia.org/wiki/High-level_programming_language

http://en.wikipedia.org/wiki/Programming_language

http://en.wikipedia.org/wiki/Signal_processing

http://en.wikipedia.org/wiki/Statistical_analysis

http://en.wikipedia.org/wiki/Statistical_analysis

http://en.wikipedia.org/wiki/Image_processing

http://en.wikipedia.org/wiki/Fluid_dynamics

http://en.wikipedia.org/wiki/Optimization_(mathematics)

http://en.wikipedia.org/wiki/Dynamical_system

http://en.wikipedia.org/wiki/Interpreted_language

http://en.wikipedia.org/wiki/Matrix_(mathematics)

http://en.wikipedia.org/wiki/Data_type

http://en.wikipedia.org/wiki/Dynamic_typing

http://en.wikipedia.org/wiki/Garbage_collection_(computer_science)

http://en.wikipedia.org/wiki/Garbage_collection_(computer_science)

http://en.wikipedia.org/wiki/Fortran

http://en.wikipedia.org/wiki/C_(programming_language)

http://en.wikipedia.org/wiki/C%2B%2B

http://en.wikipedia.org/wiki/Computer_simulation

http://en.wikipedia.org/wiki/Correlation



Chapter 3:

DATA ANALYSIS

WIND RESOURCES

SOLAR RESOURCES

LOAD DEMAND

COSTS AND ECONOMICS

PROPOSED HYBRID SYSYEM



3.1 Collected Data

The University of the West Indies (see Appendix) was chosen as the experimental location due

to the fact that all the information required for a successful study was available. Moreover,

ground data was used and no artificial data synthesized, hence improving the accuracy of the

results. The weather station recorded data per min which was converted to monthly averages

for use by Homer Energy. Below are tables and graphs displaying the inputs required by the

software.



3.1.1 SOLAR & WIND RESOURCES

The energy resources were used as a representative of the entire campus. The data was

recorded using the Nomad Data Logger coupled with the Physics Department’s weather station

and manipulated for the purpose of this study. The annual average solar irradiance and wind

speed was 4.80 kWh/m2/d and 0.88 m/s respectively. These readings served as essential

parameters for the analysis of the systems considered. The graph below shows the interpolated

resource profile over a one-year period, giving insight into the variation of the wind and solar

radiation. Unfortunately, solar photovoltaic and wind power vary hourly, daily and seasonally,

making it difficult to predict and provide reliable energy to the grid on demand, as seen later.

This behavior could be described as being intermittent.

Graph 1. Showing the variation of the recorded meteorological ground data obtained on the

roof of the Physics Lab building.

1Appendix of Data contains the monthly values



3.1.2 LOAD DEMAND

From the given data of load demand for the entire year of 2011 (See Appendix of Data),

September was the month with the highest demand of energy, with the 20th day recording the

peak demand. September 20th’s load demand was therefore chosen as the threshold load,

around which the energy systems would be designed.

Graph 2. Peak daily load demand for September 2011

1Appendix of Data contains the annual distribution of load demand



The average hourly value was 3.4 MVA, with 5.3 MVA peak demand being recorded after noon.

This load profile is typical of most days on campus given the pattern of consumption developed

on campus. Cooling accounts for majority of the daily consumption. The use of air conditioning

units is a function of the time of day. By late morning to early afternoon (7am-2pm) as the

temperature increases, there is a trend towards the peak demand. Decline is noticed towards

the evening session (3pm-onwards) with students and staff proceeding off the campus.

Graph 3. Load Demand on September 20, 2011



3.1.3 COSTS AND ECONOMICS

The prices below were obtained from overseas retailers. All components were considered as

single purchases and no discount was accounted for, where bulk purchases would be required.

Given that this study is about finding the optimal hybrid system for the University of the West

Indies, the prices may not be the most competitive in the market; however, the selection of the

retailers would be more rigorous should this project be considered for implementation.

Table 1. Costs associated with the Homer simulations

Generator Solar Panels Inverter Wind Turbine

Figure 3. Costs Curve for different RE components

1Capital and Replacement costs are the same, hence one line on each plot.

Cost

Economics Inputs

Annual Real Interest Rates (%) 0% (Self-financing)

Project Lifetime (Years) 1

Components Type/ Model Retailer/ Source Cost (USD)

PV Solar Panel Not specified 65cents/Watt

Wind Turbine WES 5 Tulipo West Energy Solutions $1,100.00

Fuel Diesel Petrojam $1.20/Litre

Diesel Generator SDMO X3300 SDMO $639,015.00

Battery Surrette 6CS25P Rolls Battery $1259.00

Inverter/ Converter Outback Radian GS8048 Outback Power $4,295.00



3.2 Proposed Hybrid System

Before running the simulations, an assessment of the data was done and the ideal RE

components considered. Due to the size of the load i.e. University of the West Indies Mona

campus, two distinct situations were considered. One was to create a stand-alone system and

the other, a grid tie system which would therefore incorporate net billing.

Furthermore, load demand above and below the baseline load outlined above was taken into

account, as well as deviations in the annual average wind speed. No sensitivity analysis was

done with the solar resources, as this should not deviate much annually.

Figure 4. Proposed Hybrid System

Homer considered all the components above in the evaluations, but only those combinations

considered feasible was shown at the end.



Chapter 4:

RESULTS

• SIMULATIONS

OPTIMIZATION RESULTS

• FEASIBILITY

• VARIATION

Resource Evaluation

• RECOMMENDATIONS

UWI'S DESIGN



4.1 Optimization Results

The present cost of energy was found to be approximately $0.34/KWh, which was largely due

to the Fuel and IPP charge indicated on UWI’s April 2013 electricity bill. Multiple simulations

were conducted with varying sensibilities in load demand, wind speed, costs, and economics as

well as the capacity of each RE component.

As stipulated above, the aim of this part of the project was to determine the most economically

viable and demographically suitable hybrid renewable energy systems for the University of the

West Indies. In most cases, the cost of energy fell below $0.34/KWh. The table below illustrates

how the variation in parameters and renewable energy components affect this cost. It also lists

different systems that may be considered feasible, depending on the budget and interests of

the developer.

Table 2. Typical Homer results for the Mona campus

1Appendix of Data contains the sizes considered and their respective lifetime.

System

Architecture

Wind

Speed

m/s

Levelized

Cost of

Energy

$/kWh

Total Net

Present

Cost ($)

Initial Capital

Cost ($)

Carbon

Emission

(kg/yr)

Diesel Fuel

(l/yr)

Diesel

%

Wind

%

PV

%

0.886 0.333 10,028,536 7,979,636 21,000,000 8,000,000 71 0 29

4 0.304 9,147,382 8,529,962 19,000,000 7,243,963 62 9 29

0.886 0.339 10,170,782 7,766,958 16,223,268 8,120,904 71 0 29

Hybrid System I

[5.6MVA PV+

5MVA Generator +

6 MVA Inverter]

Hybrid System I

[5.6MVA PV+ 200

W.Turbine+ 5MVA

Generator + 6

MVA Inverter]

Hybrid System III

[5.6MVA PV+

4MVA Generator+

6MVA Inverter]



Consider the optimization plot below.

Graph 4: Optimal System Plot

Three electrical generators/ engines were simulated, with a PV setup of 5.3 MVA. A suitable

battery bank and inverter was also incorporated in the simulations. Varying amounts of low

‘start up’ wind turbines were also considered. Results show that firm generation1 components

are the most cost effective for this measure of load. This highlights the challenges faced by

developers, when planning large scale alternative energy projects.

Wind power as an option is highly infeasible unless resources outside of the studied site are

tapped into (See External Wind Farm).

1Firm generation, see Glossary



4.2 Resource Analysis

The University of the West Indies Mona campus spans 653 acres of land and currently has 5

faculties namely, Science and Technology, Medical Science, Law, Humanities and Education and

Social Sciences. Furthermore, multiple halls of residence (Taylor, Rex Nettleford, Irvine,

Chancellor, Mary Seacole, Towers, Post Graduate, ABC) are located on campus, in addition to a

multipurpose sports facility i.e. Mona Bowl. Currently, all its facilities are powered by the

Jamaica Public Service Company (JPS Co.) and hence, it is faced with an enormous energy bill

each year. Nonetheless, with proper planning and analysis, that energy bill can be decreased.

Results show that for UWI’s demand of 5.3MVA, solar power can be considered due to the

favorable exposure of the system to this resource. Fluctuation is however a concern and often

times this 5.6 MVA PV setup fails to meet the demand. Wind production was less substantial

with 0% input when the local average wind speed (0.886 m/s) was used.

Graph 5. Variation of power generated by renewable components (average wind speed = 4m/s)



Wind (Non-feasible, Variable)

The wind speeds recorded from the roof of the Physics Lab building were taken as the cohort

readings for the entire Mona campus, given the lack of weather stations anywhere else on the

studied location. Considering the data obtained, wind speed varied between 0.5 m/s and 1.35

m/s with the highest average occurring in June. This signified that wind power production was

not a feasible option for this location as most wind turbines are manufactured with cut-in speed

at around 2.5 – 3.0 m/s minimum. It was seen that wind power only becomes significant at

speeds of 4 m/s upwards. At this speed, 9% of the demand can be accounted for by wind

power. Furthermore, reasonable power production usually starts at around 6 m/s.

Unfortunately these speeds are foreign to the Mona campus due to the mountainous/forested

surroundings i.e. it is located in a valley.

Ideally, the inclusion of wind turbines into this project would increase the renewable fraction by

at least 1%; however this does not contradict its position as a non-feasible option. Nonetheless,

provided that a more microscopic study of the campus was done, one may find locations where

the wind speeds are of such that implementing this component would be beneficial to the

overall system.

The equation for wind power is given as

P=1/2ϱAv3

ϱ: density of wind for the particular location (kg/m3)

A: cross-sectional area of the rotor of the turbine (m2)

V: wind speed (m/s)

1Reference to wind power production is based on the performance of the WES 5 Tulipo turbine



Solar (Feasible, Variable)

Solar Radiation averaged between 3.84 kWh/m2/d and 5.34 kWh/m2/d monthly, with 7

months averaging 5 kWh/m2/d or more. Based on the power output from the PV panels during

Homer’s simulations, it was deduced that solar panels would be a viable component for the

studied area. Also, as is the global trend in energy production, PV’s are now being installed

commercially and residentially as the main source of alternative energy. This is due to the low

maintenance cost, component lifetime as well as tits environmentally friendly production of

energy. Should one deviate from the objectives of this study, a homogenous PV system may be

considered for UWI given the radiation it receives. In this case, investments would be necessary

for the development of battery banks suitable enough to ensure stability and continuity of

energy production and distribution.

On average, the panel’s output was 1025 kW during the day, a shortfall of 70% of the average

demand that would have to be compensated by the generators. Hence it must be highlighted

that sizing the PV system to meet UWI’s demand is not advisable. A more feasible option is to

implement small scaled installations to serve less intense loads.

With the mass production of panels especially out of India and China, there has been a steady

decrease in the cost per watt for this commodity (as low as $0.65/Watt). Other factors

contribute to the decline in capital cost for solar cells such as the oversupply of polycrystalline

silicon and the low demand by consumers. Therefore, it is up to the developers to seek the best

bargain possible, in a market where ‘consumer influence’ dominates.

The equation used for PV power production is given as

Ypv: Rated Capacity of the PV array (kW), fpv: PV derating factor (%)

GT: Solar radiation incident on the PV array in the current time step (kW/m2)

GT,STC: incident radiation at standard test conditions (1 kW/m2)

mk:@MSITStore:C:/Program%20Files/HOMEREnergy/HOMER/HOMER.CHM::/articles-calculating-PV-radiation.htm

mk:@MSITStore:C:/Program%20Files/HOMEREnergy/HOMER/HOMER.CHM::/def-pv-stc.htm



Diesel (Feasible, Firm)

Diesel generators were also an option as this device was applied around the campus as stand-

by power systems. To meet the demand, generators are required to operate continuously as

the efficiency of the panels and variations in the radiation widely impacted the solar energy

production. 70% of UWI’s demand would be supplied by fuel based sources while the next 30%

was accounted for from renewable energy sources.

This ratio of energy production highlights the strength of variable generation against firm

generation. Whilst the emphasis was placed on renewable sources, firm generation has to be

the main component of the hybrid system for the load considered. The main concern with the

installation of these devices in a stand-alone system is the fuel cost however.

At present, the JPS receive fuel through the Petroleum Corporation of Jamaica (Petrojam). This

fuel is subjected to inflation and the cost per barrel on the international markets. Therefore,

any attempt by UWI to rely on generators for continuous power supply would first require

studies on alternative fuel sources and their cost effectiveness in different systems. With that

said, diesel engines were considered, given their reliability and the ability to use them as

backup, stand-alone and gird-tied systems. It should also be noted that JPS has low efficiency

ratings for its current generator systems due to the number of years for which these systems

has been operating. Furthermore, with the construct of new technology, its current system

struggles to adapt and therefore has become unreliable. It was observed that UWI has a pre-

existing generator configuration (See Appendix of Pictures) whereby each building has its own

units to supply power during times of grid autonomy. Should one consider an off-grid set up, a

review of its current Gen sets must be conducted so as to ensure that the potential micro-grid

is efficient and will be able to meet the energy demand.



4.3 UWI’s Design

Based on the simulations, it was deduced that a PV/Generator hybrid system was the most

suitable combination to apply for this location. The proceeding is a more technical and

quantitative look at the desired system.

Figure 5. The ideal combination of RET for the Mona Campus

1The battery bank was included despite Homer not considering it as an option. This is in keeping with the fact that panels could

be employed to serve less intense loads and hence a bank would be required.



4.3.1 System’s Operating Characteristics

Below is a comparison of the different parameters considered in this study. The behavior of the

aforementioned design above can be seen from the plots as well. Although wind turbines are

not a part of the system, wind speeds were used as a variable to show its impact on other

variables.

1.

Graph 6: Fuel Cost vs. Wind Speed

As expected, fuel cost shows an inversely proportional relationship with wind speed. This is

essential if wind turbines were to be considered in the system. However, since for this design,

turbines were not a feasible option, the above plot is more of a parametrical comparison than a

practical one. For the local conditions considered, fuel cost is expected to be just under

$10,000,000 per year.



2.

Graph 7: Fuel Cost vs. Energy Demand

Fuel consumption and energy demand has a directly proportional relationship, hence it is

pivotal to find means of regulating the campus’ demand (See Cogeneration Plant). UWI’s

demand is 83,000 kWh/d, corresponding to a fuel cost of about $9,900,000 per year. Since

diesel was considered, it should be noted that this price fluctuates depending on the

international market and should be taken into consideration. Therefore, one may opt not to

size a diesel generator system to meet UWI’s total load demand, but rather to develop it in

such a way as to compensate a grid tied system.



3.

Graph 8: Levelized Cost of Energy vs. Energy Demand

It was observed that the Levelized COE increased as energy demand increased. This can be

attributed to the power output capacity of the system. The cost of energy is the ratio of the

system cost to the useful electrical energy produced. As seen below, multiple factors affect the

cost of energy. Selling excess electricity to the Jamaica Public Service would serve to reduce the

cost of energy, and therefore increase the profitability of the project as well.

Cann,tot: total annualized cost of the system ($/yr), Cboiler: boiler marginal cost ($/kWh)

Ethermal: total thermal load served (kWh/yr), Eprim,AC: AC primary load served (kWh/yr)

Eprim,DC: DC primary load served (kWh/yr), Edef: deferrable load served (kWh/yr)

Egrid,sales: total grid sales (kWh/yr)



4.

Graph 9: Renewable Fraction, COE vs. Wind Speed

This is a very important plot showing how the inclusion of wind turbines can affect the system.

The renewable fraction is a measure of how much of the system’s power originates from

renewable energy sources. This fraction only moves 1% for wind speeds less than 3 m/s, hence

adding to the well-known fact that this is not a feasible option for this location. Furthermore,

the cost of energy only decreases by 1% for the same speeds when we include wind turbines,

again attesting to its non-feasibility.



Chapter 5:

FURTHER ANALYSIS

UWI'S Design

Mona Reservoir

Cogeneration Plant

Photovoltaic System

Off Campus Wind Farm



5.1 UWI’s Design - An Analytic Approach

Notwithstanding Homer’s results, based on field work and further analytical enquiries, it is

possible for the Mona campus to adopt a renewable energy hybrid system that may or may not

be grid-tied and whose operating cost will not be substantially elevated due to fuel prices.

This can be achieved by considering the installation of RE technologies on and off the campus,

with adequate studies done on the resources, proper installations and a collaborative effort by

the various stakeholders i.e. academic and commercial.

This section seeks to take a closer look at the options available for Mona. As outlined above,

field work was done to get a firsthand look at the possibilities that existed. Sites visited include;

Mona Reservoir and Water Treatment Plant, St. Andrew

Cogeneration Plant, UWI Mona

1Woodford’s visit was not possible. Moreover, only the data was required for comparison purposes.



5.1.1 Mona Reservoir - Hydro-electric Potential

The Mona Reservoir is Jamaica’s largest raw water storage facility with a storage capacity of

800 million gallons (3.7 million m3). It is located in a natural depression along the eastern side of

the Long Mountain range, with adjoining areas being Karachi, Mona Estates, Beverley Hills and

for the purpose of this study, most importantly, the University of the West Indies. Water is

supplied to this facility from the Hope and Yallahs Rivers through an aqueduct at a rate of

approximately 0.8 m3/sec each day under normal circumstances (Barnett, 2010).

The reservoir supplies the Mona Water Treatment Plant (production capacity of 73,000 m3/day)

and the Hope Water Treatment Plant.

Development of a hydro plant by the reservoir may be seen as an unpractical move given the

fact that the reservoir is the only water source in the vicinity i.e. no elevated reservoir, stream

or river is nearby. Furthermore, given the low efficiency that is associated with such systems,

one may be hesitant to take this approach. Nonetheless, with the present day technologies and

advancements in hydro turbines, the potential for hydroelectric power is very robust and can

be considered as a component of UWI’s hybrid system.

The presence of a water treatment plant suggests that the water in the reservoir is flowing and

hence, one should be able to record a sufficient flow rate to run hydro turbine(s) and generate

electricity to meet a fraction of UWI’s 5.3MVA demand.

Notwithstanding, the project would have to consider the yearly drought that the island faces,

hence this system will have autonomous periods which would be determined by the National

Water Commission.

Consider below, the proposed hydro system to be employed by the campus for power

generation.



Figure 6. Micro hydropower system for the Mona Campus

The type of turbine to be used in this project is a Reaction turbine, of which the Kaplan turbines

are a subset. These turbines have their blades completely submerged in water and requires the

least gross head than that of other types of turbines. This system is ideal for this project as it

will not require much developmental changes to the area. The difficulty lies in actually setting

up the system, given the current set up of the treatment plant.

***Draft Tube: The draft tube directs the flow to the point of discharge.

It enables the turbine to be set above the tailwater level without losing any head.

Reduces the head loss at the submerged discharge, thereby increasing the net head

available to the turbine runner.



Considering a gross head of between 1.8m – 2.5m, these low head Kaplan turbines can produce

between 0.3kW – 1kW. Furthermore, multiple units can be installed to compensate for the

inefficiencies of a single system. The cost for a single unit varies between $20,000 USD and

$100,000 USD.

Drawbacks to this system:

1. Persistent drought throughout the year affects the capacity of the reservoir and would

therefore influence the production of energy by this system.

2. To get sufficiently large production to have an impact on the campus’ demand, multiple

turbines are need. One may not see this as a suitable pursuit given the fact that less

complex and more cost effective energy solutions are available.

Photographer: Daren Watson, 2013 Figure 7. Mona Reservoir below its storage capacity (April 26, 2013)

Whilst the inclusion of hydro into the hybrid system would improve the impact of renewable

energy sources on the overall cost of energy, low precipitation levels make it impractical to

implement this component.



5.1.2 Cogeneration Plant - Fuel Based Production

Unlike most energy sources, generators have proven to be amongst the most reliable and most

used mode of energy production. Currently, the University of the West Indies has over thirty

(30) stand-by generator sets, with each carrying a different power rating (see Appendix 6) to

match the location’s need.

Graph 10: Generator Capacity (KVA) vs. Location

All generators are diesel powered and based on the simulations in Homer, it was suggested that

this energy source was amongst the most feasible option. The problem lies however in the price

of diesel as mentioned before. Biodiesel was considered, but unless it can be justified without a

doubt that there will be a consistent level of waste to operate with, dependence on this fuel

may not provide a sustainable system. Furthermore, based on research conducted, it is more

difficult to install different stand-alone generators around the campus due to synchronization

issues and other electrical technicalities, hence we consider a Cogeneration Plant.



UWI’s Cogeneration Plant

With the push for energy diversification on campus and the aim to be a self-reliant energy

producer, the University of the West Indies has embarked on the development of a

Cogeneration Plant. As the name suggests, this facility will be required to serve two types of

load; electrical and thermal. Firm energy generation is vital for the sustainability of an off-grid

hybrid system of the magnitude considered in this project.

The cogen project installation involves two phases,

1. Absorption Chillers

2. Electrical Generators

Phase 1: Absorption Chillers

Thus far, three (3) chillers have been installed and is fully functional, providing cooling to the

Sutherland Global Services Call Centre, the new Medical Science building and the Mona

School of Business. The bell curve on page 22 is a major characteristic of the load consumption

on a typical day at the campus, largely attributed to the operation of air conditioning units.

Therefore, not only will the chillers provide cooling, but the electrical consumption should also

be reduced.

The efficiency of the cogeneration plant comes from its heat recovery ability. Two of the chillers

will require exhaust heat/gas from the generators to be implemented, and has a burner which

currently uses propane. Furthermore, water passed through the generators for cooling absorbs

the heat and is then transferred to the third chiller. Hence, what were usually waste products

have now become key components in a loop that ensure the efficient use of energy.

Refrigerant: Water Absorbent: Lithium Bromide



Figure 8. Schematic showing the heat exchange processes involved in the Absorption Chillers.

Phase 2: Electrical Generators

At the time of this report’s completion, no engines were installed for electrical power

production. However, within the next few months progress should be made in this phase of the

plan. At full capacity, the plant should be able to meet the 5.3MVA load demand, enabling UWI

to become an Independent Power Producer (IPP). Until this system is fully functional, no

decision has been made on the future of the stand-by generators around the campus.

Operational data from the running plant to access its reliability and reserve capacity is needed

before such a decision is finalized.

Feasibility is not only derived from the use of waste products in the chillers’ cycle, but also from

the fact that the engines to be used on the plant are capable of operating with multiple fuel

sources. Therefore any change in the market or contractual fuel arrangement would not hinder

the cost effectiveness of the plant due to its adaptability.

Rated Capacity: 5.6 MVA Fuel: Undecided Hours of Operation: Continuous Backup: JPS



Photographer: Daren Watson, 2013 Figure 9. UWI’s Cogeneration Plant (View of the Cooling Towers for the Absorption Chillers)

To conclude the discussion on Cogeneration Plants, it must be noted that this facility would be

the stabilizing force behind the hybrid system developed in this paper due to its reliability,

efficiency and ability to serve two types of load, electrical and thermal.



5.1.3 External Wind Farm - Wind Potential

Data from an off campus location shows that there exists the potential for wind power

generation in remote areas surrounding the campus.

Graph 11: Showing the Variation of the Recorded Ground Data from the Woodford weather station (owned and operated by the Meteorological Service of Jamaica)

This data was taken from the Woodford weather station, which is a remote residential farming

community at an elevation of 3000ft above sea level. The minimum monthly average was found

to be 2.2 m/s. This was significantly greater than the value recorded for the University of the

West Indies. Whilst further recordings and research are needed for Jamaica’s present wind

potential, consideration should be given to external wind power generation.

1Woodford is 7 miles from the location of study.



Graph 12: Site Comparison: Woodford vs. UWI

Wheeling

Wheeling occurs when an entity moves electricity from a power plant to a substation and then

to the load by the use of transmission and distribution lines. Given the fact the any wind farm

development would have to occur away from the campus, this mode of energy transport is

essential to its success. Currently it is expected to costs 50 – 100 USD/MW/KM to use JPS’s grid

for this purpose as stipulated by the OUR. This is a proposed tariff and is expected to decrease

as further negotiations takes place. The drawback to this plan however, is that under the

current recommendations set out by the OUR, wheeling will only be intended for firm

generation capacity as opposed to variable generation capacity (Makhijani, 2013).

‘Off Campus’ power generation whilst being a viable option, cannot be presently considered as

a component of UWI’s hybrid system due to legislative issues as outlined above. Nonetheless, it

is expected that once wheeling has been fully implemented locally, there will be a push for the

transport of variable generation capacity and an increase development in external wind and

solar power facilities.



5.1.4 Photovoltaic System - Solar Potential

As outlined in the simulations above, a solar system would be beneficial to the campus’ energy

needs. Although the Cogeneration Plant will be able to match the current demand, the

introduction of solar panels serves to reduce this same demand, leading to a reduction in the

output from the electrical generators. Hence, lowering the consumption of fuel and the overall

cost of energy. The initial investment for a PV system of 5.3MVA is substantially greater than

most RE systems of the same size. Panel efficiency and the variation of solar resources highlight

the risk of solely powering a campus off this type of generation.

Photographer: Daren Watson, 2013 Figure 10. Solar array on the roof of the Physics Department

Mona School of Business Solar Project

As an initial effort to have solar production on campus, the Mona School of Business (MSB)

currently has a small system installed. Due to confidentiality, much information on this project

cannot be diffused. Nonetheless, one important parametrical analysis that is important for its

sustainability can be mentioned. Studies done by a fellow graduate, Kevin Mills (2012)

produced a density of the probability of the type of sky (Clearness Index). This concept was

used by the Alternative Energy Research Group to measure the efficiency of the installed

system as a function of the type of sky.

The success of this pilot project will determine future installations on campus.



Graph 13. Monthly Clearness Index recorded in 2011

The data recorded gave a clear indication of the cloud conditions usually experienced by this

location. Radiation entering the atmosphere is usually attenuated by clouds, aerosols, water

vapor and pollutants. The extent of this attenuation can be seen from the Clearness Index,

which is the ratio between the irradiance on the ground and the irradiance on the top of the

atmosphere. Hence, the C.I. is directly proportional to the Transmittance of the atmosphere.

For the campus, the values obtained were between 0.466 and 0.584, representing partly cloudy

conditions for most of the year. Based on the work done by Mills, the expected efficiency of the

system should range between 11.3 - 11.6 percent. Therefore it would be more economical to

develop small scale projects as opposed to large scale developments.



5.2 Recommendations

Forecasting/ Stochastic Predictions: Given the vulnerability in performance of

renewable energy devices as a function of resources, a defined understanding of future

data is necessary to enable sustainability. Furthermore, several stochastic models were

developed for wind speed during the 90’s by Professor Chen, Dr. Amarakoon et al, which

should be utilized if applicable to the accurate prediction of current data recorded.

Biodiesel Production: As a privileged party to a USAID BPF proposal for the Mona

campus, I know that this implementation is possible and could increase the feasibility of

the cogeneration system. Below is an extract from the proposal.

“A number of fast food concessionaires and restaurants both on the UWI Mona Campus

and communities within its neighbourhood produce significant quantities of waste oil.

The Waste oil disposal poses a number of challenges for both local and municipal waste

management. Being non-biodegradable and combustible, improper waste oil disposal

may create both a public hazard and eventual environmental degradation. The waste oil

is a potential fuel source but to date there is no comprehensive programme to collect

and convert the oil to a valuable energy resource. This proposal presents a viable project

for converting used vegetable oil, a waste product that requires safe disposal, into

biodiesel, a form of diesel fuel that is readily manufactured from used or freshly

produced vegetable oil or animal fat using technology that is widely available and

readily accessible. The proposal falls under the climate change mitigation focal area of

the GEF Small Grants Programme. Accordingly, it will promote the use of alternative

fuels and environmentally sustainable transport. Furthermore, it is in conformity with

the thrust of the Government of Jamaica to diversify its fuel mix as articulated in the

National Biodiesel policy.” (Duncan et al., 2012)



Academic Collaboration: This study hinted that the issue of energy production,

especially that of variable sources, involves knowledge of the micro-climate existing

over UWI, electrical demands and equipments, geographical features, economical

awareness as well as fuel diversification. Hence collaboration amongst the various

research groups is essential for the successful planning of any renewable energy system

on the campus.

The Climate Studies Research Group has a vast amount of analytical models to assess

the resources available. The Material Science Research Group is currently leading the

biodiesel study for the campus and the Alternative Energy Research Group possesses

the expertise to make suitable proposals for the implementation of energy projects on

the campus.

Data Monitoring: The current availability of only one weather station on the Mona

campus is a restriction to the proper assessment of the variable energy resources in the

area. Whilst the data from the Physics building may be applicable for the Faculty of

Science and Technology (formerly Pure and Applied Sciences), similar conclusions does

not exists for the remaining locations.

Similarly, the installation of meters for each building would allow for a more microscopic

assessment as opposed to what was done in this project.



Chapter 6:

MATLAB ANALYSIS

1VIM editor, Excel: Analytical tools which assisted during the development of the scripts.

MATLAB VIM

editor

EXCEL

SciDavis



6.1 Data Analysis using MatLab

Scripts were created using MatLab to read the meteorological data from .csv files. The variation

of this data was viewed through plots generated as seen below and further calculations done.

To date, not all calculations have been scripted due to the extensive volume of formulae with

which one has to work with. Nonetheless, the process is ongoing and it is the view of this author

to have the MatLab program completed as soon as possible, and made available for future

reference.

Figure 11. Command Prompt displaying the Monthly Average Solar Irradiance



14. 15.

16. 17.

18. 19.

Graph 14,15: Plots displaying the Annual and Monthly Averages of Solar Irradiance Graph 16,17: Plots displaying the Annual and Monthly Averages of Wind Speed Graph 18,19: Plots displaying the Annual and September Load Demand



7.1 Conclusion

The University of the West Indies is the premier educational institution in the Caribbean and

has the responsibility of producing innovations that will facilitate the growth and development

of the region. Any attempt to become a self-powered entity should account for all the

renewable energy resources on and off campus. Conventional wisdom teaches that our tropical

climate only caters for solar panels, but one has the possibility to incorporate diesel generators,

wind turbines where suitable, as well as the potential for hydro power.

Based on observations, simulations and field work, the results obtained in this paper are in-line

with the meteorological resources for the university, hence the experimental study was a

success and all objectives completed.

7.1.1 Future Research

The real intent of this project was to serve as a pre-cursor to future work involving remote

communities in Jamaica. Hence, this author will be pursuing future endeavors on this path, with

the aim of enhancing the energy outlook for different areas. It is also my intention to

commence the development of a Hybrid Energy Resource Map which will facilitate knowledge

based installation of power solutions around the island.



7.2 Glossary

FEASIBLE SYSTEM: A system that satisfies the specified constraints

FIRM GENERATION CAPACITY: Electricity produced from fuel based resources such as oil,

biodiesel, ethanol etc. This type of production is more sustainable and reliable than that of

variable capacity.

HYBRID SYSTEM: A combination of power generation technologies

LEVELIZED COST OF ENERGY: The Levelized cost of energy (COE) as the average cost per kWh of

useful electrical energy produced by the system. To calculate the COE, HOMER divides the

annualized cost of producing electricity (the total annualized cost minus the cost of serving the

thermal load) by the total useful electric energy production.

NET PRESENT COST: The net present cost of a system is the present value of all the costs of

installing and operating the system over its lifetime, minus the present value of all the revenue

that it earns over its lifetime from selling power to the grid. The net present cost is the negative

of the net present value. It is the same as the lifecycle cost.

RENEWABLE FRACTION: The renewable fraction is the portion of the system's total energy

production originating from renewable power sources. HOMER calculates the renewable

fraction by dividing the total annual renewable power production (the energy produced by the

PV array, wind turbines, hydro turbine, and biomass) by the total energy production.

VARIABLE GENERATION CAPACITY: Electricity produced from renewable energy sources such

as wind, solar and hydro.



7.3 References

1. Abass, A. Zeinab, E. (2012). Design and Performance of Photovoltaic power system as a

renewable source for residential in Khartoum. International Journal of the Physical Sciences, 7,

4036-4042.

2. Aaserud, S. (2012). Four things tothink about when considering cogeneration. Retrieved April 20,

2013, from http://www.antares.org/blog/four-things-to-think-about-when-considering-

cogeneration/

3. Barnett, M. (2010). The Impact of the recent drought on the National Water Commission (NWC)

Supply Services to Kingston and St. Andrew. National Water Commission. Kingston

4. Call Associates Consultancy, (2000). Final Report on the environmental impact assessment of the

proposed development of the Mona Estates and Beverley Hills, St Andrew on the National Water

Commission’s Watershed. Kingston

5. Dorville, J. (2011). Wind and Hydro (Phys 3680) Chapter 2, Converters. University of the West

Indies. Kingston.

6. Dorville, J, Mills, K. (2012). Assessment of the PV Installation of the MSB Building. Physics

Department, University of the West Indies

7. Gilver, T. Lilienthal, P. (2005). Using Homer software, NREL’s Micropower Optimization Model to

explore the role of Gen Sets in Small Solar Power Systems (Case Study: Sri Lanka). Colorado

8. Golkosz, D. (2009). Why are Biodiesel fuel so different?. Retrieved April 12, 2013, from

http://pubs.cas.psu.edu/freepubs/pdfs/uc205.pdf.



9. Hakimi, S. (2011). Optimal Sizing of reliable hybrid renewable energy system considered various

load types. American Institute of Physics [doi: 10.1063/1.3655372].

10. Iqbal, M. (2007). Hybrid Energy System for Battle Harbour Island in Labrador. Memorial

University of Newfoundland. St. John’s. Canada.

11. McKenzie, D. (2013). India’s off grid Renewables changing lives. Retrieved March 28, 2013, from

http://www.renewableenergyworld.com/rea/news/article/2013/03/indias-off-grid-renewables-

initiative-is-changing-lives.

12. Makhijani, S. (2013).Power Wheeling programme must include Solar and Wind. Retrieved May 5,

2013, from

http://876connect.com/articles/view/power_wheeling_programme_must_include_solar_and_

wind

13. Nfah, E. (2009). Simulation of off grid generation options for remote villages in Cameroon.

University of Dschang. Cameroon.

14. Sami, K. Dahl, C. (2005). The economics of hybrid power systems for sustainable desert

agriculture in Egypt. Risoe National Laboratory. Denmark.

15. Smellie, S. Energy Conservation Project, UWI Mona. University of the West Indies, St. Andrew.

1Prices, Retrieved from http://www.sunelec.com.



7.4 Appendix of Data

Components Sizes Capital Cost ($)

Replacement Cost ($)

O & M Cost ($) Lifetime

PV Panels 2-5.6 MW 650/kW 650/kW N/A 20 years

Generators 1-2 MW 213/kW 213/kW N/A 10 years

Wind Turbines 200-500 turbines

1100/ turbine 1,100 N/A 15 years

Inverter 6 MW 537/kW 537/kW N/A 20 years

Battery 4 V/1900 Ah battery

1259/ battery 1259/ battery N/A

10569 kWh throughput

Table 3. Components associated with the simulations

Monthly Averages

Month Wind Speed (m/s) Solar Irradiance (kWh/m2/d)

January 0.75 4.16

February 0.81 4.33

March 1.01 5.08

April 1.08 5.19

May 0.93 5.19

June 1.38 5.34

July 0.91 5.04

August 0.96 5.17

September 0.83 4.99

October 0.87 4.66

November 0.54 4.65

December 0.56 3.84

Annual Average 0.88 4.80

Table 4. Monthly Averages of the meteorological data recorded at UWI



Monthly Averages

Month Wind Speed (m/s) Solar Irradiance (kWh/m2/d)

January 5.97 3.40

February - -

March - -

April 3.48 3.14

May 4.16 3.67

June 5.94 4.59

July 2.62 4.29

August 4.74 3.73

September 2.20 3.45

October 2.94 3.11

November 4.31 3.10

December 4.49 3.24

Annual Average 4.09 3.57

Table 5. Monthly Averages of the meteorological data recorded at Woodford

Months Clearness Index Type of Sky

January 0.534 Partly Cloudy

February 0.497 Partly Cloudy

March 0.519 Partly Cloudy

April 0.492 Partly Cloudy

May 0.479 Partly Cloudy

June 0.492 Partly Cloudy

July 0.466 Partly Cloudy

August 0.488 Partly Cloudy

September 0.499 Partly Cloudy

October 0.518 Partly Cloudy

November 0.584 Partly Cloudy

December 0.515 Partly Cloudy

Table 6. Clearness index for the campus throughout 2011



# LOCATIONS KVA PHASE VLL VLN

1 ICENS & Maintenance 215 3 380 220

2 Life Sciences 275 3 380 220

3 Mary Seacole Hall 40 1 220 110

4 Irvine Hall 4.5 1 220 110

5 Preston Hall 70 3 380 220

6 Rex Nettleford Hall 150 3 380 220

7 Mona Informatix 62 1 220 110

8 Vice Chancellor’s Residence 35 1 220 110

9 Sickle Cell Unit 200 3 380 220

10 Registry (Senate Building) 1000 3 380 220

11 Mona School of Business 1000 3 380 220

12 Taylor Hall 330 3 220 220

13 Main Library 250 3 380 220

14 Assembly Hall N/A 3 380 220

15 MITS 850 3 380 220

16 University Health Centre 150 3 220 220

17 Gerrard Laylor Hall (Postgrad) 33.5 1 220 110

18 Police Post 33.5 1 220 110

19 Mona Visitors' Lodge 330 3 380 220

20 Biotechnology Centre 242 3 380 220

21 UWIDEC (Open Campus) 58 3 380 220

22 New Undergrad Hall 275 3 380 220

23 New Postgrad Hall 1000 3 380 220

24 Medical Library 275 3 380 220

25 Chapel 33 1 220 110

26 Absorption Chiller Unit 800 3 380 220

27 Call Centre 500 3 380 220

28 PGME 125 3 220 110

29 Micro-Biology & Pathology 500 3 380 220

Terms Definition

KVA Rated Power

PHASE Number of output voltage

VLL Line to Line Voltage

VLN Line to Ground Voltage

Table 7. Pre-existing generator units on the Mona campus



7.5 Appendix of Picture

Figure 11. Overhead view of the UWI Mona campus



Photographer: Daren Watson, 2013

Figure 12. Pre-Existing Generator Standby Systems




Figure 13. Mona Reservoir, St. Andrew, Jamaica




Figure 14. Whisper 100 wind turbine on the roof of the physics department. (Ideal for the Woodford location)



WIND VANE CUP COUNTER ANEMOMETER

Photographer: Daren Watson, 2013 Photographer: Daren Watson, 2013

STEVENSON SCREEN


Figure 15. Weather Station on the roof of the Physics Department

watson '13

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