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Life Cycle Energy Analysis of Photovoltaic Systems in the Arava: A Generation
Scale Comparison
Thesis · November 2009
DOI: 10.13140/2.1.2604.0320
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Ben-Gurion University of the Negev
Jacob Blaustein Institutes for Desert Research
Albert Katz International School for Desert Studies
Life Cycle Energy Analysis of Photovoltaic Systems in the
Arava: A Generation Scale Comparison
Thesis submitted in partial fulfillment of the requirements for the degree of "Master
of Science"
By: Suleiman Asi Halasah
Date……………………
Ben-Gurion University of the Negev
Jacob Blaustein Institutes for Desert Research
Albert Katz International School for Desert Studies
Life Cycle Energy Analysis of Photovoltaic Systems in the
Arava: A Generation Scale Comparison
Thesis submitted in partial fulfillment of the requirements for the degree of "Master
of Science"
By: Suleiman Asi Halasah
Under the Supervision of: Prof. David Pearlmutter and Prof. Daniel Feuermann
Department of Environmental Studies
Author's signature …………….………………………
Date …………….
Approved by the Supervisor…………….…………….
Date …………….
Approved by the Chairman
of the Graduate Program Committee …….…………
Date ……………
I
To my Parents,
If they didn’t teach it to me,
They taught me how to learn it.
II
Abstract
Since the 1970s, studies have shown that the human race can get a substantial
portion of its electrical power without burning fossil fuels or creating nuclear
reactions, through the direct conversion of solar energy. The potential for
exploiting solar energy is especially high in parts of the Middle East, such as the
Arava region (the focus of this study) - which on average receives 20% more solar
radiation than is typical for southern Europe. Solar energy can be converted into
electrical power both by thermal technologies and photovoltaic (PV) technologies,
and of these PV has an inherent versatility because it can easily be implemented at
different scales. When considering the supply of solar electricity for a given region,
this flexibility can be exploited. In this study, three scales are considered:
centralized PV power plants, the integration of PV systems at the urban or
settlement (i.e. kibbutz) scale, and integration in individual buildings (BIPV). While
these different systems may be compared in terms of their cost-effectiveness, the
"costs" of producing them are not just monetary – because like any other
industrial activity, the process of manufacturing PV systems consumes energy and
generates pollutants. To evaluate these costs, Life-Cycle Energy Analyses (LCEA)
are performed for different PV systems at different scales, by examining the
energy inputs they require in relation to the yearly energy that they generate. One
measure that is used for comparison is the energy pay-back time (EPBT) of the PV
system: the lower the EPBT is, the more appropriate the system may be as an
alternative to fossil fuel-based generation. Other metrics like land use, energy
return factor and CO2 emissions are also compared. The analysis compares the
III
same technology at different scales, and the "best” technology for each scale, as
determined through the criteria of conversion efficiency and availability in the
market
place.
Based
on
this
comparative
life-cycle
energy
analysis,
recommendations can be formulated regarding the appropriateness of different
PV generation scales for the Arava region.
IV
Acknowledgments
I would like to acknowledge and extend my heartfelt gratitude to the following
persons who have made the completion of this thesis possible:
My supervisors, Prof. David Pearlmutter and Prof. Daniel Feuermann, for their
vital encouragement, support and much needed motivation and time.
Prof. Alon Tal, for his understanding and assistance. The Albert Katz
International School for Desert Studies of the J. Blaustein Institutes for Desert
Research, Ben-Gurion University of the Negev, for making this study possible
The Arava Institute for Environmental Studies and Kibbutz Ketura Building
Committee, especially the Building Manager Seth Kessler, for assisting in the
collection of the data for the chapters.
Most especially to my family and friends.
V
Table of Contents
ABSTRACT................................................................................................................... II
ACKNOWLEDGMENTS............................................................................................... IV
TABLE OF CONTENTS ..................................................................................................V
LIST OF FIGURES AND TABLES .................................................................................... IX
LIST OF FIGURES ................................................................................................................ IX
LIST OF TABLES .................................................................................................................. XI
ABBREVIATION AND TERMS .................................................................................... XIII
1.
2.
BACKGROUND ..................................................................................................... 1
1.1
SYSTEM SCALING...................................................................................................... 4
1.2
LIFE-CYCLE ENERGY .................................................................................................. 6
METHODOLOGY................................................................................................... 8
2.1
OVERVIEW ............................................................................................................. 8
2.2
LIFE-CYCLE ENERGY ANALYSIS................................................................................... 11
2.3
ENERGY OUTPUT .................................................................................................... 12
2.4
EMBODIED ENERGY AND ENERGY PAYBACK TIME ......................................................... 20
2.4.1 Energy for Cell Materials: ............................................................................. 21
2.4.1.1 Crystalline and Ribbon Silicon Based Cells ............................................ 21
2.4.1.2 Thin Film Modules ................................................................................. 23
VI
2.4.2 Energy for the Capsulation Materials ........................................................... 24
2.4.3 The Balance-of-System ................................................................................. 25
2.4.4 Concentrator Photovoltaic Systems .............................................................. 25
2.4.5 Energy for Transportation............................................................................. 26
3.
2.5
THE ENERGY PAYBACK TIME .................................................................................... 27
2.6
THE ENERGY RETURN FACTOR (ERF) ......................................................................... 28
2.7
CO2 EMISSIONS OFFSET........................................................................................... 28
2.8
SYSTEM SCALING ................................................................................................... 30
2.9
TRANSMISSION LOSSES ............................................................................................ 32
RESULTS AND DISCUSSION ................................................................................ 35
3.1
ENERGY OUTPUT .................................................................................................... 35
3.1.1 Efficiencies .................................................................................................... 40
3.1.2 North-South horizontal axis tracking ............................................................ 40
3.1.3 East-West horizontal axis tracking ............................................................... 41
3.1.4 Stationary plates with zero azimuth and tilt equals latitude ....................... 42
3.1.5 Concentrating dual-axis tracking .................................................................. 43
3.1.6 Polar tracking ................................................................................................ 44
3.1.7 Stationary plates with zero azimuth and zero tilt: ....................................... 45
3.1.8 Summary ....................................................................................................... 46
VII
3.2
EMBODIED ENERGY ................................................................................................ 48
3.2.1 Single Crystalline Silicon Module .................................................................. 49
3.2.2 Multi crystalline Silicon Module .................................................................... 50
3.2.3 Ribbon Silicon Module................................................................................... 50
3.2.4 Amorphous Silicon Module ........................................................................... 51
3.2.5 Cadmium Telluride (CdTe) module................................................................ 52
3.2.6 Copper Indium Diselenide (CIS) Module........................................................ 53
3.2.7 The Balance-of-System ................................................................................. 54
3.2.8 FLATCON System ........................................................................................... 54
3.2.9 SolFocus System ............................................................................................ 55
3.2.10
3.3
Summary ................................................................................................... 56
EVALUATION METRICS ............................................................................................. 58
3.3.1 Energy Pay-Back Time ................................................................................... 58
3.3.2 Land use ........................................................................................................ 60
3.3.3 The Energy Return Factor (ERF) .................................................................... 63
3.3.4 CO2 offset per aperture area......................................................................... 63
3.3.5 CO2 offset per land area................................................................................ 64
3.1.1 Sensitivity of results ...................................................................................... 69
3.1.2 Summary ....................................................................................................... 72
VIII
4.
SYSTEM SCALING COMPARISON ........................................................................ 75
4.1 COMPARING THE DIFFERENT SCALES FOR THE SAME TECHNOLOGY ......................................... 77
4.2 COMPARE THE "BEST" SYSTEM FOR EACH SCALE ................................................................ 79
5.
CONCLUSIONS ................................................................................................... 82
APPENDIX I ERROR ANALYSIS ................................................................................. 84
ERROR PROPAGATION ....................................................................................................... 84
REFERENCES ............................................................................................................. 90
IX
List of Figures and Tables
List of Figures
Figure ‎1.1: The Arava valley. ............................................................................................. 2
Figure ‎1.2: Different types of photovoltaic cells based on cell material. .......................... 4
Figure ‎2.1: Methodology flow chart describing the necessary steps for system
comparison ...................................................................................................................... 10
Figure ‎2.2: IFIAS scheme of levels in energy analysis [30] .............................................. 20
Figure ‎2.3: Silicon cell manufacturing processes [33]. .................................................... 22
Figure ‎2.4: Different stages for Thin Film module production. ....................................... 24
Figure ‎2.5: Kibbutz Ketura aerial photo. ......................................................................... 31
Figure ‎3.1: The collectable energy on surfaces with different installations. All dates
refer to climate data for a typical year, at Yotvata station. ........................................... 37
Figure ‎3.2: Yearly collectable energy and calculated electrical output of different
configurations of Photovoltaic systems. Note that the 2-axis tracking systems collect
only beam radiation. ....................................................................................................... 39
Figure ‎3.3: Monthly energy output in kWh m-2 for North-South horizontal tracking. .... 41
Figure ‎3.4: Monthly energy output in kWh m-2 for East-West horizontal tracking. ....... 42
Figure ‎3.5: Monthly energy output in kWh m-2 for Stationary plates with zero azimuth
and tilt equals latitude. ................................................................................................... 43
Figure ‎3.6: Monthly energy output in kWh m-2 for concentrating dual-axis tracking
systems. ........................................................................................................................... 44
Figure ‎3.7: Monthly energy output in kWh m-2 for Polar tracking.................................. 45
X
Figure ‎3.8: Monthly Energy output in kWh m-2 for Stationary plates with zero azimuth
and zero tilt. .................................................................................................................... 46
Figure ‎3.9: Total initial embodied energy for different Photovoltaic modules. .............. 49
Figure ‎3.10: Energy Pay-Back Time (EPBT) in years, for different flat-plate PV
technologies in different installations. ............................................................................ 58
Figure ‎3.11: Different contributions to the EPBT, for FLATCON and SolFocus Systems. . 59
Figure ‎3.12: The land area required for each system per unit of yearly energy output. 62
Figure ‎3.13: The Energy Return Factor for the systems considered................................ 65
Figure ‎3.14: CO2 emissions offset for the different systems on rooftop installation. ..... 66
Figure ‎3.15: CO2 emissions offset for the different systems on open field installation. . 67
Figure ‎3.16: CO2 emissions offset per land area ............................................................. 68
‎Figure 3.17: The effect of the life time on the CO2 emissions offset. ............................. 71
Figure ‎4.1: Different available areas for PV deployment in Kibbutz Ketura. .................. 76
Figure ‎I.1: The calculated output with error margins and the measured output. .......... 88
XI
List of Tables
Table ‎2.1: Empirical constants for Equations 1 and 2. .................................................... 15
Table ‎2.2: Equations needed for the output energy calculations in different
configurations. ................................................................................................................ 18
Table ‎2.3: Efficiencies and temperature coefficient for different photovoltaic
technologies. ................................................................................................................... 19
Table ‎2.4: Amounts of different types of silicon and energy needed for the single
crystalline silicon PV module. .......................................................................................... 23
Table ‎2.5: Amounts of different types of silicon and energy needed for the multi
crystalline silicon PV module. .......................................................................................... 23
Table ‎2.6: Amounts of different types of silicon and energy needed for the ribbon silicon
PV module. ...................................................................................................................... 23
Table ‎2.7: CO2 emissions for Israel’s electricity mix. ....................................................... 29
Table ‎3.1: Conversion efficiency values for the different Photovoltaic technologies. .... 40
Table ‎3.2: Embodied Energy for Single Crystalline Silicon (Single-Si) module [34]. ........ 50
Table ‎3.3: Embodied Energy for Multi Crystalline Silicon module [34]. .......................... 50
Table ‎3.4: Embodied Energy for Ribbon Silicon module [34]. ......................................... 51
Table ‎3.5: Material Production Energy for a-Si module [38]. ......................................... 52
Table ‎3.6: Embodied Energy for CdTe module [40]. ........................................................ 53
Table ‎3.7: Embodied Energy for CIS module [41]. ........................................................... 54
Table ‎3.8: Initial embodied energy for the BOS .............................................................. 54
XII
Table ‎3.9: Embodied Energy for FLATCON system [29]................................................... 55
Table ‎3.10: Embodied Energy for SolFocus module [10]. ................................................ 56
‎Table 3.11: The effect of different assumptions on the study’s metrics. ....................... 69
Table ‎4.1: The results of comparing the same technology in different scales. ............... 79
Table ‎4.2: The results of comparing the “best” technology for each scale..................... 81
XIII
Abbreviation and terms
a-Si
Amorphous Silicon Thin Film.
BIPV
Building-integrated photovoltaic
BOS
Balance-of-system.
CdTe
Cadmium telluride Thin Film.
CIS
Copper Indium Selenide Thin Film.
E
Solar irradiance on module.
Eo
Reference solar irradiance, 1000 W m-2.
EPBT
Energy Pay-Back Time.
ERF
Energy Return Factor.
GCR
Ground Cover Ratio.
GER
Gross Energy Requirement
I
Phase-to-phase current.
Ib
The direct beam component of the solar radiation, W m-2.
Icoll
The collectable solar radiation on the surface, W m-2.
Id
The diffuse component of the solar radiation (Id=Ig-Ibcosθz), W m-2
IFIAS
Institutes for Advanced Study
Ig
The global radiation, W m-2.
Kd
The incident angle modifier for the diffuse radiation.
Ki
The incident angle modifier for the direct beam component.
KIPV
Kibbutz-integrated photovoltaic
L
One-way length of conductor.
XIV
PER
Process Energy Requirement
Pn
Active power to be transmitted.
RIPV
Region-integrated photovoltaic
RL
Resistance per km.
Ta
Ambient temperature.
Tc
Cell temperature, °C.
Tm
Back surface module temperature.
WS
Wind speed measured at standard 10m height, m s-1.
day
Length of day in hours.
β
The surface tilt angle.
δ
Solar declination angle.
θi
The incident angle.
θz
The zenith angle.
λ
The latitude.
ρg
The ground reflectivity.
ω
Hour angle (rad).
1
1.
Background
Globally, the generation of electrical energy mostly depends on fossil fuels [1].
For example, in 2004 fossil fuels (coal, oil and natural gas) provided about 86% of
the United States' energy for different uses [2]. Fossil fuels have multiple impacts
on the environment and human development. Fossil fuel burning generates a
number of pollutants and it is the main source of CO2 emissions leading to
environmental degradation. At the same time, fossil fuel availability is diminishing
due to extensive and continued use by a growing population undergoing rising
levels of development [3].
Since the 1970s, studies have shown that the human race can get a substantial
portion of its electrical power through direct conversion of solar energy, without
burning fossil fuels or creating nuclear fission reactions in the electrical generation
process [4]. The 122 petawatts of solar insolation reaching the earth's surface is
plentiful compared to the 13 terawatts of the world Total Primary Energy Supply in
2005 [4]. Additionally, solar electric generation has the highest power density per
unit area (global mean of 170 W m-2) among renewable energies [4]. Researchers
expect that solar energy will become the most economic solution for most energy
applications, and the only viable energy option throughout the world [2].
2
In the Middle East, research shows that the
Arava region is one of the most highlysaturated areas in solar radiation, with the
average annual total radiation equaling 2153
kWh m-2 per year [5] compared to 1700 kWh m2
per year in Southern Europe and 1300 kWh m-
2
per year in south Germany [3]. The Arava is
166 km (103 miles) long from the Gulf of Aqaba
Figure ‎1.1: The Arava valley.
Source: http://samuelhendriks.wordpress.com/
to the southern shore of the Dead Sea, with a small population on the Israeli side
comprised mainly of kibbutzim. The population of these kibbutzim is less than
4,000 people, but their average annual demand for electricity is 6.25 MWh per
person [6] (including private consumption as well as services such as laundry,
dining room, guest houses, etc.)1.
Different technologies can be used to convert solar energy into electrical
power, and these can be categorized into two main groups: thermal technologies
and photovoltaic (PV) technologies [1]. While thermal systems are considered
appropriate only for large-scale installations, PV technology is considered a reliable
alternative to fossil fuel which can be implemented in a wide range of settings [7].
It produces little or no environmental pollution at the point of use [8], and this
gives it a market status as an environmentally-preferable product.
1
Only for Yahel, Ketura, Lotan and Grofit.
3
Photovoltaic systems can be compared based on different criteria, with the
most common ones relating to the cell material and the level of solar collection
and/or concentration. Cell material criteria differentiate systems considering the
semiconductor material used to form the solar cells, which may also be divided
into two main groups, as shown in Figure 1.2: Silicon and Non-silicon Thin Film [9],
with Silicon further sub-divided into crystalline, polycrystalline and amorphous
materials. These materials may differ widely in their conversion efficiency as well
as in their production costs.
The concentration criterion considers the level to which sunlight is
concentrated in the system: III-V semiconductors are mainly used in concentrating
systems, though Silicon has also been used. Concentrating systems use less cell
material than flat-plate collectors, and have a higher conversion efficiency. High
concentration can therefore significantly reduce the required cell area and overall
cost [10], but it requires a tracking system to ensure that the collector is
continuously facing in the direction of the direct beam radiation.
4
Figure ‎1.2: Different types of photovoltaic cells based on cell material.
This study divides the components of the photovoltaic systems into two main
components:
1.
The module: This includes the photovoltaic cell, the capsulation and the
frame. In the case of concentrator photovoltaics (CPV) the
concentrator, made of lenses or mirrors, is also added to the module
components.
2.
The Balance-of-System (BOS): this includes all the components except
the PV module, including the support structure, foundations, the
inverter, the tracker, electrical wiring, etc.
1.1
System scaling
The PV technology can be implemented at different scales, ranging from the
most localized and widely distributed (building-integrated PV) to the most highly
centralized (large PV power plants). Research has indicated several advantages for
5
the integration of PV systems in individual buildings as compared with
conventional PV power plants [11]. The first is the potential utilization of built
surfaces that already exist for other purposes, with concurrent savings of
construction materials needed for supporting structures, especially foundations,
and the possible substitution of cladding material with PV.
Integration with
buildings also offers the possibility of recovering the thermal energy dissipated by
the PV system and using it in different applications, and potentially reducing
electrical transmission losses by shortening the distance between generation and
end-use.
On the other hand, building-integrated PV is not necessarily applicable for
large-scale electrical demand. While it is appropriate for small-scale generation
using flat panels, systems that are efficient for large-scale generation may require
concentration, tracking and special mounting that is not necessarily practical on
roofs and building facades. The most obvious example is the large parabolic dish,
which requires dual axis tracking that can concentrate up to 10,000 suns and thus
vastly increases the generated electricity per unit area of PV cell. The newly
developed Heliostat Concentrator Photovoltaic is another example of new large
scale power plant [12].
Some existing technologies can be considered scalable, which could increase
their potential range of future applications. For example the SolFocus Gen1
system, which can generate a peak power of 2.25kW, consists of 9 modules with
each module made of 16 units of one PV cell and one concentrator [10] – and
6
simply by increasing or decreasing the number of modules or units, can be
adapted to generate at a different scale.
1.2
Life-cycle energy
Like any other anthropogenic activity, the process of manufacturing PV
systems consumes energy and generates pollutants. To be able to compete with
fossil fuels, two important characteristics of PV systems are required:

The energy supplied by the system over its operational life time should
be significantly greater than its embodied energy (i.e. the energy
required for its production, installation, operation and subsequent
disposal).

The net emissions of greenhouse gases resulting from the life-cycle
embodied energy consumption of the PV system should be significantly
lower than the emissions from electricity generated by competing fossil
fuel options.
The extent to which these requirements are fulfilled can be addressed by
means of life-cycle energy analysis (LCEA), in which the embodied energy "costs"
that accumulate over the entire production process for the PV module and the
balance-of-system (BOS) components, as well as for the installation (and in some
cases, removal) processes, are quantified and compared with the energy produced
over time by the system. The ratio of the total primary energy input to the yearly
primary energy-equivalent generated by the system represents the energy payback time (EPBT) of the PV system, in years. A low EPBT is one measure of a
7
system's appropriateness as an alternative to fossil fuel-based generation. The
Energy Return Factor (ERF) is another measure for the energy efficiency of the
system, representing the ratio between the energy generated by the PV system to
the energy consumed, over the system's entire life cycle [7]. A similar analysis can
be made for greenhouse gases emissions, by evaluating the quantities of CO2, SF6,
CF4 and other greenhouse gases emitted in the PV system life-cycle and comparing
these values to emissions from fossil fuel-based electricity generation options [7].
Based on such criteria, this study firstly develops a methodology for judiciously
finding the proper choice of a PV system, or a mix of systems and their respective
scales, for a given region. Secondly, it investigates – by way of a case study – a
number of system configurations and evaluates their suitability for the population
in the Arava region of Israel, by considering the power generation scale, energy
payback time, and the system’s lifetime energy production. We discuss the relative
benefits, purely from an energy point of view (leaving the ever-changing economic
arguments aside), of utilizing large central systems that satisfy the electrical
demand of the region, and of building smaller individual systems for each kibbutz –
or even for each individual household. The recommendations are based on a lifecycle energy analysis of the various systems, as well as practical considerations
within the regional and local context.
8
2.
Methodology
2.1
Overview
Figure 2.1 illustrates the steps necessary to arrive at a comparison of PV
systems with regard to (1) EPBT, CO2 emissions offset and other life-cycle energy
measures, and (2) the suitability of the various system scales for the particular
region under consideration. A review of available systems will define the list of PV
technologies and practical systems one is willing to consider for the task.
Thereupon two tasks are to be performed: calculation of the systems’ energy
output, and assessing their embodied energies (the left and the right side of the
flow chart). For the energy output, these systems must be distinguished in terms
of the type of installation (stationary, different tracking strategies, etc.) as they
have differing amounts of available solar energy. A simulation, based on
established calculational methods and available meteorological data is used to
determine both the available solar energy and the expected output of the systems.
In parallel, the embodied energy of the systems must be determined (including
taking into account differences in installation, such as open fields or rooftops). This
is one of the more difficult tasks, as published embodied energy data are sparse
for some of the systems. Once these two core numbers are established, the lifecycle energy metrics can be determined.
For the scaling comparison, it was assumed that the capacity of each system
should be sized to match the average demand of the geographic unit in question
(household, kibbutz or entire region), even though we assume that all systems are
grid-connected therefore bypass problems related to storage. Given the particular
9
break down of roof top areas, free land, or areas that could be shaded by PV
panels, a mix of different PV systems can then be established (see chapter 4).
10
Prepare a list of PV
technologies considered
Prepare a list of
installation types
Embodied
energy
calculations
Output energy
calculations
· Get solar radiation data for the
region of interest.
· To account for the metrological
conditions, further data, wind speed
and ambient temperature. will be
needed.
· Panel efficiency.
· Temperature coefficient of the PV
panels considered.
· Set the minimum mutual shading
losses due to the required GCR (or
set the CGR due to the minimum
accepted losses)
Define the
boundary of the
system.
Get needed data for
different processes
and materials
(depends on the
system’s boundaries)
· Calculate the cell
temperature.
· Calculate the potential
collectable energy for
different installations.
Calculate total yearly output
Calculate total
embodied energy
of the system
Calculate the required area per unit
output and GCR
Calculate life cycle energy (for
the system’s lifetime, including
degredation)
Calculate the energy payback time for different
technologies and different
installation types
· Find out the electricity demand of
the region of interest.
· Calculate the potential electrical
transmission losses in the region
of interest.
·
·
·
Examine different scenarios for different scales:
Rooftop scale.
Urban integrated.
Centralized power plant.
For different scales, calculate the potential
output by calculating the available area,
taking into consideration shading, and
transmission losses (if applicable).
Compare the same
system by scale
Compare the “best”
system by scale
Calculate life cycle
energy and CO2
offset
Figure ‎2.1: Methodology flow chart describing the necessary steps for system comparison
11
2.2
Life-cycle Energy Analysis
In order to compare different PV systems, a Life-Cycle Energy Analysis (LCEA)
was performed which accounts for both the input (Einput), or "embodied," energy
required for production and maintenance of the system, and the output, or
electrical energy generated by the system over a yearly cycle. This analysis results
in an energy payback time (EPBT) value for each system, as well as in estimates of
net life-cycle energy production and emissions for a pre-defined service life. The
assumption here is that the output of each system’s LCEA is basically sizeindependent. The input energy can be expressed in terms of the Gross Energy
Requirement (GER) and the Process Energy Requirement (PER) [7] which include
primary energy input during:
·
system manufacturing;
·
system and material transportation;
·
system installation;
·
system operation; and
·
system decommissioning, which is not included in this study:
These values were compiled from analysis of published studies, and in some
cases from directly contacting the manufacturers of the PV systems or reviewing
their data sheets (see detail in Sec. 2.4 below).
The electrical energy generated by the PV system was evaluated by simulation
based on solar geometry as given by Rabl [13], and on PV performance
characteristics. The calculation requires geographical and PV system parameters.
12
Meteorological data were obtained from the meteorological station at Yotvata, a
location that is representative for the entire Arava region. These data comprise
hourly global and direct beam radiation, air temperatures and wind speed, and
cover an entire year. It should be noted that the data (for example, total yearly
radiation) can change from year to year by as much as 5%, but this should have a
negligible effect on the analysis as the comparison between the systems is relative.
Data from two experimental systems, installed at Kibbutz Ketura, were used to
evaluate the output of the simulation software (See Appendix I).
Eight different photovoltaic technologies were considered in this study, six of
which are flat plate PV: Single- and Multi- Crystalline Silicon, Ribbon Cast Silicon,
Amorphous Silicon Thin Film (a-Si), Cadmium Telluride Thin Film (CdTe) and
Copper Indium Selenide Thin Film (CIS). The other two technologies, SolFocus and
FLATCON, are concentrating PV systems which concentrate solar radiation up to
500 suns and use multi-junction photovoltaic cells. The cells of these two
concentrating systems are passively cooled.
The choice of these technologies (among the many which have been
developed) depended mainly on the availability of detailed data, permitting a
reliable comparison between systems.
2.3
Energy output
Based on the hourly global and direct beam radiation data for Yotvata, the
potential collectable energy was calculated for a variety of different installations:
North-South horizontal axis tracking flat plate PV, East-West horizontal axis
13
tracking flat plate PV, Dual-axis tracking concentrator PV, Stationary flat plate PV
with tilt equals latitude (29.9°), Polar (north-south tilt=latitude axis) tracking flat
plate PV, and stationary flat plate PV with zero tilt. The calculations account for
15% losses in the flat-plate systems and 2.6% for concentrators due to mutual
shading, assuming a 50% ground cover ratio (GCR) for flat-plate systems (40% for
polar tracking) and a 12.7-17.5% GCR for concentrators [14-16]. The output of
different systems is not differentiated by the particular type of wiring used. This
study assumes that flat panels, regardless of make and installation respond
identically for different types of radiation (direct, diffuse and reflected); i.e., they
have the same incidence angle modifier (a correction to the collectable solar
radiation due to changes in reflection off the glazed surfaces as a function of
incidence angle).
The output energy for the photovoltaic cell depends on its efficiency, which is a
function of the cell’s temperature; in the case of flat plate photovoltaic, the cell’s
operating temperature was calculated by taking into account the tabulated
environmental parameters such as solar radiation, wind speed and ambient
temperature. The module was assumed to have a glass/cell/Tedlar sandwich,
which is the "worst case" scenario [17]. Equation (1) gives the simple relation used
to calculate the module temperature [17]:
(1)
where:
Tm = back surface module temperature, °C.
14
Ta = ambient temperature, °C.
E = solar irradiance on module, W m-2.
Eo = reference solar irradiance, 1000 W m-2.
WS = wind speed measured at standard 10m height, m s-1.
T1 = empirical constant determining upper temperature limit at low wind
speed, °C.
T2 = empirical constant determining upper temperature limit at high wind
speed, °C.
b = empirical coefficient determining the rate that module temperature drops
as wind speed increases.
The cell temperature was calculated by using Equation 2:
(2)
where ΔT = empirical constant determining the temperature difference
between the cell temperature and the back surface module temperature, °C.
Table 2.1 shows the values of the empirical constants for different sandwich
types:
15
Type
T1 (°C)
T2 (°C)
b
ΔT (°C)
Glass/cell/glass
25.0
8.2
- 0.112
2
Glass/cell/Tedlar
19.6
11.6
- 0.223
3
Table ‎2.1: Empirical constants for Equations 1 and 2.
In the case of concentrator photovoltaic, the cell was assumed to operate at a
temperature higher than the ambient temperature by 30°C2.
The collectable energy of the different installations was calculated based on
Equation 3 [18]:
(3)
where:
Icoll = the collectable solar radiation on the surface, W m-2.
Ig = the global radiation , W m-2.
Ib = the direct beam component of the solar radiation , W m-2.
Id = the diffuse component of the solar radiation (Id=Ig-Ibcosθz), W m-2.
θi = the incident angle.
Ki = the incident angle modifier for the direct beam component.
2
Since the considered concentrator devices have solar concentration ratios of several hundred, only the
direct beam radiation is absorbed. When beam radiation is available, the sky is necessarily clear with a
beam radiation being in a relatively narrow band. This permits using a simple temperature increase.
16
Kd = the incident angle modifier for the diffuse radiation. Calculated for θ=60°
for diffuse radiation and θ=75° for ground reflected radiation [18].
β = the surface tilt angle.
ρg = the ground reflectivity.
The variables in Equation 3 were calculated for each of the different
installation types, with the effect of seasonal, daily, and hourly sun position
accounted for. In order to evaluate these different variables, several parameters
are required. The solar declination angle (δ) was calculated using Equation 4 [13]:
(4)
where n is the day number (n=1 for January 1).
Then the solar time was calculated, based on the standard time, by using the
equation of time [13]:
Solar time= Standard time + 4(Lst-Lloc) + E (in minutes)
(5)
where:
(6)
and:
(7)
17
where:
Lst = the standard meridian for the local time zone (330° for Yotvata).
Lloc = the longitude of the location in question in degrees west (325° for
Yotvata).
n = the day number.
The zenith angle (θz) was calculated based on equation 8 [18]:
(8)
where:
λ = the latitude.
ω = hour angle (rad) related to solar time t by:
where day = length of day in hours.
Table 2.2 shows the different equations used:
(9)
18
Parameter
Incident
Angle (θi)
[13, 19]
Surface tilt
angle β‎
[13, 19]
Incident
angle
modifier
Ki [20] [21]
Collectable
Radiation
(Wh)
North-South tracking
East-West tracking
Concentrating
Dual Axis
tracking
Stationary Tilt =
latitude
Polar tracking
0
-
Fixed = 29.9°
Table ‎2.2: Equations needed for the output energy calculations in different configurations.
In both the North-South and East-West tracking systems, in order to account for both the ground reflected and diffuse radiation the study
accounts for the diffuse radiation as a stand-alone system (without inter-array disturbance) and ignores the ground reflection.
19
After estimating the collectable radiation, and taking into consideration the
temperature effect, the potential output energy was calculated according to
Table 2.3:
Technology
Multi-Si [22-23]
Single-Si [22, 24]
a-Si [22]
CdTe [22, 25]
CIS [22, 26]
Ribbon [22]
SolFocus [27]
FLATCON [27]
Nominal Efficiency
14%
19.3%
6%
10.76%
12%
13.2%
25%
26%
Temperature coefficient %/°C
-0.4%
-0.38%
-0.25%
-0.25%
-0.36%
-0.47%
-0.046%
-0.046%
Table ‎2.3: Efficiencies and temperature coefficient for different photovoltaic technologies.
To account for the system losses, which includes the inverter losses and
losses in the wiring, a 10% reduction in the output energy was introduced [28]
[29].
20
2.4
Embodied Energy and Energy Payback Time
Figure ‎2.2: IFIAS scheme of levels in energy analysis [30]
Embodied energy data were collected from published studies on the relevant
manufacturing processes involved in PV system production, and from
manufacturers' data sheets as well. All electrical energy inputs were converted to
primary energy units by using the Union for the Co-ordination of Electricity
Generation and Transmission (UCPTE) average electricity generation efficiency of
32% [31] in units of kWh m-2 of panel surface (some data were available in
kWh/kWp, and were converted by using the module’s power rating and area).
The system boundaries were defined in terms of the International Federation
of Institutes for Advanced Study (IFIAS) scheme of orders as adopted by ISO 14040.
This study included processes up to Level 2, which incorporates: direct energy for
21
processes, material manufacturing, and transportation, which together are
estimated to cover up to 90% of direct energy inputs [32] as shown in Figure 2.2.
2.4.1
Energy for Cell Materials:
The manufacturing processes for PV cell materials vary for the different
technologies under investigation, though all silicon-based technologies, i.e. Singlecrystalline, Multi-crystalline, Ribbon cast multi-crystalline and Amorphous silicon
share the same raw material for the cell. Thin film technologies share many
processes, such as the Transparent Conductive Oxide substrate (TCO), for example.
Concentrator systems are based on III-V semiconductor material.
2.4.1.1
Crystalline and Ribbon Silicon Based Cells
Data were collected from several studies [1, 33-34] that are based on the
"Ecoinvent" data base, and measured data were obtained for several production
lines for crystalline, amorphous and ribbon silicon. Figure 2.3 shows the different
stages for preparing the cell materials for the silicon-based technologies; this study
assumes that the solar grade silicon (SoG-Silicon) is the type used for silicon-based
photovoltaic, which is prepared by a modified Siemens process of the metallurgical
grade silicon (MG-silicon).
22
Silica sand
MG-Silicon
SoG Silicon
Single-Si
Multi-Si
Silane
Ribbon
Wafer sawing
Cell production
a-Si deposition
Figure ‎2.3: Silicon cell manufacturing processes [33].
For the crystalline silicon cells, this study assumes a cell area of 156 cm2, which
gives about 60 cells per 1 m2 of module area, with 6% of the wafer being lost due
to sawing losses. Tables 2.4, 2.5 and 2.6 show the detailed calculations for the
single-crystalline, multi-crystalline and ribbon silicon modules [34]. The Siemens
process is used for carbon-thermal reduction of quartz to produce MG silicon,
which requires 20 kWh per kg of MG silicon produced [1].
Regarding the ribbon cast modules, a 1 m2 effective module size was assumed,
requiring 0.91 kg of solar grade silicon (1.03 kg of MG silicon) and an energy input
of 45.2 kWh per m2 of ribbon [34].
23
Process
Output
Energy requirement
Total Energy required
per unit area of aperture
Silica sand to MG-Si
1.771 MG-Si
20 kWh kg-1 MG-Si
35.42 kWh m-2
MG-Si to SoG Si
1.568 SoG Si
343.75 kWh kg-1 SoG
539 kWh m-2
SoG to single-Si
0.992 m2 of single-Si wafer
474.53 kWh m-2 wafer
470.73 kWh m-2
Cell production
60 cells (156 cm2)
1.86 kWh cell-1
111.6 kWh m -2
PV module
1 module
20.83 kWh module
20.83 kWh m-2
Table ‎2.4: Amounts of different types of silicon and energy needed for the single crystalline silicon PV module.
Process
Output
Energy requirement
Total Energy required per
unit area of aperture
Silica sand to MG-Si
1.872 MG-Si
20 kWh kg-1 MG-Si
37.44 kWh m-2
MG-Si to SoG Si
1.6566 SoG Si
343.75 kWh kg-1 SoG
569.45 kWh m-2
SoG to multi-Si
0.992 m2 of multi-Si wafer
94.7 kWh m-2 wafer
94 kWh m-2
Cell production
60 cells (156 cm2)
1.86 kWh cell-1
111.6 kWh m -2
PV module
1 module
20.83 kWh module
20.83 kWh m-2
Table ‎2.5: Amounts of different types of silicon and energy needed for the multi crystalline silicon PV module.
Process
Output
Energy requirement
Total Energy required per
unit area of aperture
-1
Silica sand to MG-Si
1.03 MG-Si
20 kWh kg MG-Si
20.6 kWh m-2
MG-Si to SoG Si
0.91 SoG Si
343.75 kWh kg-1 SoG
313 kWh m-2
SoG to ribbon-Si
1 m2 of ribbon-Si
143 kWh m-2 wafer
143 kWh m-2
PV module
1 module
20.83 kWh module
20.83 kWh m-2
Table ‎2.6: Amounts of different types of silicon and energy needed for the ribbon silicon PV module.
2.4.1.2
Thin Film Modules
The stages of manufacturing thin film modules can be summarized by the flow
chart in Figure 2.4 [33]:
24
Semiconductor metals:
Cadmium
Indium
Tellurium
a-Si
etc.
Panel materials:
Glass
Aluminum
EVA film
etc.
Auxiliary materials:
Gases
Acids
etc.
Panel and laminate production
Figure ‎2.4: Different stages for Thin Film module production.
A number of previous studies [31, 35-38] were reviewed in order to estimate
the embodied energy of Thin Film modules. While some of these studies present
embodied energy values, few of them explicitly define the system boundary as
including processes up to IFIAS Level 2.
For CdTe, thermal evaporation is used for the deposition of the absorber and
window layers and the CdTe would be evaporated from the compound [35].
Published data regarding CIS modules are very scarce; nevertheless, detailed
energy content data for the ST40 Siemens module were found in [36-37]. More
detailed data were found for the United Solar UPM-880 tandem junction
commercial power generation module a-Si modules [38]; the average of the lower
and upper values was considered in the study.
2.4.2
Energy for the Capsulation Materials
The main contributor to the embodied energy of the module, beyond the cell
itself, is the aluminum frame. It is assumed that 25% of the aluminum is recycled
[39] for the silicon based cells (except a-Si). For the a-Si module, the embodied
25
energy of the frame was calculated as an average of two extreme cases, using 30%
recycled for the lower value and 100% new aluminum for the upper value. For
CdTe and CIS, the frame contributes almost 50% of the energy required for the
module fabrication [40-41].
2.4.3
The Balance-of-System
The Balance of System (BOS) was assumed, firstly, to contribute a fixed amount
of embodied energy to each type of module: 125 kWh m-2 was added to account
for the operating and maintenance of the system, and another 125 kWh m-2 for
the inverter, which was assumed to require replacement twice during the system’s
life time. The BOS also includes embodied energy for the support structure, whose
value varied with the type of installation – with a required input of 200 kWh m-2
estimated for the rooftop installation, and 500 kWh m-2 for the open field [1]. The
latter value is considerably higher than the former, due mainly to the high
embodied energy of required concrete foundations. The single-axis tracking
system has a negligible effect on the embodied energy calculations; from [42] and
[43] a 2 kWh m-2 value for its embodied energy is estimated.
2.4.4
Concentrator Photovoltaic Systems
In relation to flat plate collectors, concentrator photovoltaic systems have very
small cell areas; thus the main contributors to the embodied energy are the
concentrator, tracker and the Balance of System.
Few publications study in detail the embodied energy of concentrator PV
systems; comprehensive data can be found in [10, 29]. The FLATCON and SolFocus
26
systems are examples considered for concentrator PV for this study. The FLATCON
system has an aperture area (i.e. the total area receiving solar radiation) of 25.6
m2 and 2000 kg of weight with a 26% module efficiency; values of embodied
energy from [29] were converted to kWh m-2 to be comparable to other systems.
The SolFocus system has an aperture area of 12.7 m2 and weighs 405 kg and has a
25% module efficiency [10, 44].
For the FLATCON system the components were divided into five main
categories: the cell, which includes the cell materials, processes and the heat
spreader; the chip material which includes the chip packing process; the module,
including the glass and sealing material used and the high voltage interconnection
board; the electrical work which includes the inverter and the wiring; and the
tracker.
Likewise, for the SolFocus system materials and processes were divided into six
different categories: the cell, including the cell materials, processes, cell packaging
and the heat spreader; the concentrator, which includes the glass, materials and
the processes to prepare the mirrors; the frame which has two main components:
the cover glass and the aluminum frame; the tracker; and the electrical work
which includes the inverter, interconnect board and the wiring.
2.4.5
Energy for Transportation
All systems were assumed to be shipped from Hamburg, Germany to Ashdod,
Israel (7,100 km) by general cargo vessels
with average fuel
(crude oil)
consumption of 6.7 g t-1.km-1 [45]. The amount of fuel was converted to primary
27
energy by using the factor 42MJ kg-1 [46], which results in 0.0782 kWh t-1 km-1.
Within Israel, systems were assumed to be transported from Ashdod to the area of
the Arava, with an average distance of 268 km, by lorry, using a factor of 3.5 MJ t-1
km-1 (0.972 kWh t-1 km-1) [7]. Flat plate panel weight was assumed to be 15 kg m-2
on average [7], while SolFocus concentrator modules were assumed to weigh 405
kg [44], and FLATCON concentrator systems 2000 kg [29].
2.5
The Energy Payback Time
The Energy payback time was calculated using Equation 10 [7]:
(10)
Where Egen is the yearly primary energy savings due to electricity generation by
the PV system. In order to convert the PV electrical output into savings due to
avoided conventional generation, the UCPTE average generation efficiency of 32%
[31] was again used.
To calculate the amount of land needed per unit of output (in m2 Wh-1 yr-1) for
both stationary and single-axis horizontal tracking systems, an additional square
meter of land was assumed necessary for each square meter of panels (i.e. 50%
Ground Cover Ratio – GCR), which can be achieved by means of a Backtracking
technique [47], while 40% of the total land area was used in the case of polar
28
tracking [48]. For dual-axis tracking concentrator systems, a GCR of 12.7% was
estimated for the FLATCON system [14] and a 17.5% GCR was taken for SolFocus3.
2.6
The Energy Return Factor (ERF)
As the EPBT does not give an indication of the energy balance over the
system’s entire life time, we introduce the system's life time (L) in years to
compute the Energy Return Factor, given by Equation 11 [7]:
(11)
The ERF thus represents the ratio between the system’s total generated energy
during its operational life time and the amount of input energy required by the
system.
2.7
CO2 emissions offset
The amount of CO2 emissions from fossil fuel power plants in Israel was
estimated based on a generation mix of 75% coal, 11% natural gas and 14% heavy
fuel oil and gasoil [49]. Table 2.7 shows the CO2 emissions for the different
components of the mix [50], with the average found to be 0.904 kg kWh-1.:
3
This value was obtained from direct contact with SolFocus company, and it is important to mention that
it was not optimized for an area-limited application: SolFocus claimed that much better GCR can be
achieved.
29
coal
gas
0.951
0.600
Intensity of CO2 emissions (kg kWh-1)
75%
11%
Electricity percentage produced
-1
0.713
0.066
Actual emissions per fuel type (kg kWh )
Table ‎2.7: CO2 emissions for Israel’s electricity mix.
heavy fuel
oil
0.894
14%
0.125
The study assumes a 20-year operational life time for systems using thin film
technology (a-Si, CIS and CdTe) [31, 38] and 30 years for all the other systems [33,
41, 51-52], with a 1% yearly degradation [41].
By multiplying the CO2 emissions offset by the GCR, the result will be the total
CO2 offset per land area, with is a metric that accounts for all the different
parameters of the PV systems in this study: embodied energy, yearly output,
system life span and ground cover density.
total
100%
0.904
30
2.8
System Scaling
A central focus of this study is to compare the life-cycle energy efficiency of PV
systems at different scales of generation, from the most localized (buildingintegrated, or BIPV) to the most centralized (one regional PV power plant, or
RIPV). An intermediate-scale scenario termed "kibbutz-integrated PV” (KIPV) was
defined as utilizing both rooftops and subsidiary structures, as well as open
agricultural land, for the deployment of PV arrays. While all of the systems are
assumed to be grid-connected to avoid intractable difficulties associated with
energy storage, each was sized to offset the representative electrical demand
within the given geographical area.
The models used for these three scale-based scenarios were defined as
follows:
·
A typical residential kibbutz building in the Arava was selected for
considering the Building Integrated Photovoltaic (BIPV) scale.
·
Kibbutz Ketura was used as a model for the Kibbutz Integrated
Photovoltaic scale, since its population size and electricity consumption
level are representative of the kibbutzim in the Arava [6].
·
For the centralized power plant scale, a 12.5 MWp generation capacity
was designed to offset the total electricity demand of the region (25
GWh yr-1) [6] (assuming approximately 2000 kWh produced per kWp
installed).
Two different scaling comparisons were considered:
31
 Comparing the different scales of generation using a single
technology which can be practically and efficiently implemented at
each scale. In this case, life-cycle energy differences are mainly due
to BOS issues (installation, supporting structures, etc.)
 Comparing the “best” technology for each scale. Rather than
defining a "lowest common denominator" system, this comparison
identifies the technology which can be deployed most efficiently at
the given scale based on the criteria of EPBT and availability in the
market place.
The
roof-top
area
available for potential PV
installation
Kibbutz
within
Ketura
was
from
aerial
estimated
photos, made available
by the kibbutz planning
committee.
effective
Using
land
the
area
needed for each Wh yr-1
gives the potential for the
electricity generation in
Figure ‎2.5: Kibbutz Ketura aerial photo.
the kibbutz- integrated PV scale. The average kibbutz house rooftop area was used
as the model for the BIPV scale.
32
The average residential building roof area was estimated as 160 m2. The
concentrated PV option is not included in this scale for practical reasons of
structural compatibility. In Ketura an area of 12,000 m2 of available roof top area
was estimated, with 10,940 m2 considered useful for PV installation, after taking
into consideration a 10% of area losses due to the effect of the roof edges and
shading by trees.
The kibbutz-integrated PV scale assumes a mixture of installations on existing
building roof tops and shading structures (e.g. for parking areas, pedestrian paths
and other public open spaces) and field arrays requiring new support structures.
The area of potential sidewalks, parking lots and other public spaces and building
shading is about 17,290 m2, with a useable area of about 8,645 m2.
Regarding the centralized power plant, a dedicated land area is assumed to be
available for this scale (the land availability and cost is not considered in this
study). The amount of required land area is calculated for both the single-system
comparison and for the "best" system at this scale.
2.9
Transmission losses
Estimating
the
transmission
losses
in
distribution
systems
is
not
straightforward, as many variables come into play such as distance, the quality of
the conductors, the humidity, the transformers' maintenance situation, etc.
Different studies [53-54] give values in the range of 6-8% losses (including the
finely branched distribution networks in the load areas) for a distribution grid that
extends over a land area of about 104 km2. The total area of the kibbutzim in the
33
Arava was found to be sufficiently small that internal transmission losses within
them would be negligible, and thus only the high voltage transmission line losses
between them were included in this study.
Transmission losses among high voltage transmission lines were calculated by
using Equation 12:
(12)
where:
I: phase-to-phase current.
RL: Resistance per km.
L: one-way length of conductor.
Pn: active power to be transmitted.
For a 161 kV transmission line, assuming that the reactive transmitted power is
50 MVA which gives a value of P equal to 46 MW (assuming a power factor of
0.92), I equals to 179.5 A, a DIN 48204 cable type with 0.09486 Ω.km-1 resistance,
and a 1 km of cable length, the percentage of transmission line losses were
estimated to be equal to 0.02% per km [55]. This means that for a region the size
of the Arava, and with an average distance of 50km between a central point and
each kibbutz, there would be only 1% transmission losses, which is negligible.
However, the replaced transmission losses are larger, as the electricity that does
not need to be transported from a power station in the center of the country will
34
be reduced: if the central station is 200 km from the region, the saving on
transmission losses would be about 4%.
35
3.
Results and Discussion
In this chapter, results are presented in separate sections relating to the
different stages of the life-cycle energy analysis. The first section presents the
electrical energy output of the selected PV technologies, as calculated for the
conditions of the Arava region, and the second section compares the embodied
energy of each system. The third section shows the results of the main combined
life-cycle energy metric, i.e. energy pay-back time, and also considers the spatial
area requirements of each type of installation. Based on the life-cycle energy
results, a system-scaling comparison is presented in the next chapter (Chapter 4)
which applies these results to a range of implementation scenarios.
3.1
Energy output
The seasonal variation in collectable solar radiation is shown in Figure 3.1. On a
typical summer day, the peak collectable radiation can reach up to 1000 W m-2,
while in winter about 75% less energy is collected on cloudy days – though a
typical sunny winter day can provide 80% radiation of the summer day.
It is important to notice the seasonal difference of the potential collectable
energy for different installation types. The option of north-south horizontal axis
tracking (i.e., the panel tracks from east to west over the daytime hours) allows for
the highest collection in summer time, though its performance drops significantly
in winter. By contrast, the east-west axis tracking shows the best performance of
any option in winter. The dual axis tracking is considered in this study only for a
concentrating PV (CPV) system, which has very low collectable radiation on cloudy
36
days since it does not utilize diffuse radiation. The stationary (south-facing) panel
with its tilt angle equal to the latitude shows a relatively stable performance in
both seasons. On balance over the year, the polar axis tracking shows (see Fig. 3.2)
the best overall performance as it combines the benefits of the stationary with tilt
equals latitude and the tracking systems.
On summer days the Arava valley can receive up to 14 hours of solar radiation,
four of them with collectable energy greater that 800 W m-2 for all installation
types. While daylight in winter is limited to fewer hours, the collectable radiation
on a clear winter day is between 600 and 900 W m-2 for over four hours in most
configurations.
37
Cloudy winter day (December 24th)
3
8
13
Hour
18
1100
1000
900
800
700
600
500
400
300
200
100
0
Sunny winter day (December 23rd)
Collectable Energy [W m-2]
1100
1000
900
800
700
600
500
400
300
200
100
0
Collectable Energy [W m-2]
Collectable Energy [W m-2]
Summer day (June 21st)
6
11
Hour
16
1100
1000
900
800
700
600
500
400
300
200
100
0
5
10
15
Hour
Figure ‎3.1: The collectable energy on surfaces with different installations. All dates refer to climate data for a typical year, at Yotvata station.
38
The potential yearly energy output of different photovoltaic systems is
illustrated in Figure 3.2. Regardless of PV cell material, the north-south axis
tracking systems (with both horizontal and polar axes) show the highest potential
output of all the flat-plate options, as their yearly collectable energy exceeds that
of the other installation types by 10-20%. The stationary installation with zero
azimuth and tilt equals latitude has the lowest output. Single crystalline silicon
(Single-Si) technology shows the highest output among the flat-plate PV systems in
all installation types. In the case of polar tracking north-south tracking (and even
north-south axis tracking), Single-Si output is comparable to that of the two-axis
tracking concentrator systems with high efficiency. This is due to the fact that the
higher efficiency of the cells in the concentrating collectors is compensated for by
the loss in diffuse radiation. Also, the dual axis tracking increases the collectable
beam radiation vs. the single axis tracking not by a large amount (polar axis
tracking collects only about 4% less beam radiation than the two axis tracking
system [13]). Thin-film amorphous silicon (a-Si) has the poorest output among all
cell technologies compared, regardless of installation type. The monthly
breakdown of these totals is given in Figs. 3.3-3.7 below.
39
Figure ‎3.2: Yearly collectable energy and calculated electrical output of different configurations of Photovoltaic systems. Note that the 2-axis tracking systems collect only beam
radiation.
40
3.1.1
Efficiencies
Technology
Multi-Si
Single-Si
a-Si
CdTe
CIS
Ribbon
SolFocus
FLATCON
Nominal
Efficiency
14%
19.3%
6%
10.76%
12%
13.2%
25%
26%
Actual Efficiency
12.0%
16.6%
5.2%
9.4%
10.4%
11.3%
22.1%
23.0%
Table ‎3.1: Conversion efficiency values for the different Photovoltaic technologies.
The energy output comparisons given in the preceding sections are a direct
expression of the conversion efficiencies of each PV cell technology, which are
summarized in Table 3.1. It is important to notice that the nominal efficiency is the
module rated efficiency, while the calculated one takes into consideration the
temperature effect the system losses, i.e. inverter and electrical losses.
Among the flat plate technologies, the single crystalline silicon (Single-Si) has
the highest conversion efficiency of 16.6%, while the amorphous silicon has a poor
one that is as low as 5.2%. On the other hand, the CPV systems achieve relatively high
efficiencies that vary between 22.1% and 23% for the SolFocus and the FLATCON
systems respectively, this is due to the high concentration of the light and the high
efficiency of the III-V PV cells.
3.1.2
North-South horizontal axis tracking
Figure 3.3 shows the month-by-month output energy in the case of northsouth (N-S) axis tracking, with collectable energy on the right-side axis and on the leftside axis the potential output of different PV systems after taking into account inverter
losses. N-S axis tracking allows for a maximum collectable energy of approximately
41
300 kWh m-2 per month in June, which is the highest single-month value for any
60
350
50
300
250
40
200
30
150
20
100
10
50
0
0
multi-Si
single-Si
a-Si
CdTe
CIS
Ribbon
Monthly Collectable Energy [kWh m-2]
Monthly PV Output [kWh m-2]
installation considered in this study.
Collectable Energy
Figure ‎3.3: Monthly energy output in kWh m-2 for North-South horizontal tracking.
The single crystalline silicon (Single-Si) technology has the highest output
among all the materials compared, with a peak over 52 kWh m-2 in June (the highest
monthly total for any non-concentrating system in the study) and a total yearly
generation equal to 416 kWh m-2. In the thin film category, the copper indium
diselenide (CIS) has the highest annual total output of 259 kWh m-2. Silicon ribbon is a
good competitor to the thin film technology, as it can generate a total of 282 kWh m-2
per year.
3.1.3
East-West horizontal axis tracking
The performance of east-west tracking is much better in winter than northsouth tracking, though the overall yearly collectable energy is less. Figure 3.4 shows
42
the monthly available energy for the east-west tracking installation on the right side
Monthly PV Output [kWh m-2]
45
300
40
250
35
30
200
25
150
20
15
100
10
50
5
0
0
multi-Si
single-Si
a-Si
CdTe
CIS
Ribbon
Monthly Collectable Energy [kWh m-2]
axis, which reaches a yearly total of 2261 kWh m-2.
Collectable Energy
Figure ‎3.4: Monthly energy output in kWh m-2 for East-West horizontal tracking.
For this installation type, single crystalline silicon (Single-Si) technology also
has the highest output, with yearly potential total generation equal to 376 kWh m-2.
The thin-film category again shows a drop in the total generation potential; the copper
indium diselenide (CIS) has total annual output of 234 kWh m-2, and silicon ribbon can
generate a total of 254 kWh m-2 per year.
3.1.4
Stationary plates with zero azimuth and tilt equals latitude
Among the different types of flat-plate installations, stationary south-facing
panels (tilt=latitude) have the lowest annual total collectable energy of 2154 kWh m-2.
Figure 3.5 summaries the collectable energy and the outputs of different photovoltaic
technologies for this case.
43
250
Monthly PV output [kWh m-2]
40
200
35
30
150
25
20
100
15
10
50
5
0
Monthly Collectable Energy [kWh m-2]
45
0
multi-Si
single-Si
a-Si
CdTe
CIS
Ribbon
Collectable Energy
Figure ‎3.5: Monthly energy output in kWh m-2 for Stationary plates with zero azimuth and tilt equals
latitude.
Single crystalline silicon (single-Si) technology again has the highest total
output of 358 kWh m-2. The copper indium diselenide (CIS) has annual total output of
223 kWh m-2, and silicon ribbon can generate a total of 242 kWh m-2 per year.
3.1.5
Concentrating dual-axis tracking
For dual-axis tracking concentrators, the total yearly amount of collectable
energy is 2183 kWh m-2 as shown in Figure 3.6. It is important to stress the point that
in the dual-axis tracking CPV options diffuse radiation is not included; this is due to the
characteristics of the optics of the concentrators, as the diffuse radiation magnitude
will be reduced by of the concentration ratio (typically 500) of the system, which
makes its value negligible.
44
However, high efficiency solar cells are used in this configuration: the SolFocus
system and the FLATCON system, with 482 kWh m-2 and 501 kWh m-2 of total output
energy respectively, generate a higher total yearly output than any of the nonconcentrating options. This difference is especially pronounced in the peak summer
months, with the FLATCON system producing 64 kWh m-2 – the highest monthly
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
300
250
200
150
100
50
Monthly Collectable Ebergy [kWh m-2]
Monthly PV output [kWh m-2]
output value in the study.
0
SolFocus
Flatcon
Collectable Energy
Figure ‎3.6: Monthly energy output in kWh m-2 for concentrating dual-axis tracking systems.
3.1.6
Polar tracking
Figure 3.7 shows the monthly collectable and output energy for the case of
polar tracking, which combines N-S axis tracking with a fixed south-facing orientation
(tilt=latitude). The total yearly available energy for this installation is 2606 kWh m-2,
the highest among all installation types considered in this study.
45
Monthly PV Output [kWh m-2]
50
250
40
200
30
150
20
100
10
50
0
0
multi-Si
single-Si
a-Si
CdTe
CIS
Ribbon
Monthly Collectable Energy [kWh m-2]
300
Collectable Energy
Figure ‎3.7: Monthly energy output in kWh m-2 for Polar tracking.
Single-Si technology again has the highest output among all the cell materials
compared, with a total yearly generation equal to 434 kWh m-2 – the highest of any
non-concentrating system. In the thin film technology, CIS has the highest annual total
output of 271 kWh m-2. Silicon ribbon is a close competitor to thin film, with a total of
294 kWh m-2 per year.
3.1.7
Stationary plates with zero azimuth and zero tilt:
Figure 3.8 shows the monthly collectable and output energy in the case of
stationary plates with zero tilt. The total yearly available energy for this installation is
around 1974 kWh m-2.
46
250
Monthly PV Output [kWh m-2]
40
200
35
30
150
25
20
100
15
10
50
5
0
Monthly Collectable Energy [kWh m-2]
45
0
multi-Si
single-Si
a-Si
CdTe
CIS
Ribbon
Collectable Energy
Figure ‎3.8: Monthly Energy output in kWh m-2 for Stationary plates with zero azimuth and zero tilt.
Single-Si technology has the highest potential among all the technologies compared,
with a total yearly generation equals to 328 kWh m-2. In the thin film technology; the
copper indium diselenide has the highest annual total output of 205 kWh m-2. Silicon ribbon
is can generate a total of 222 kWh.m-2 per year.
3.1.8
Summary
The potential of annual total collectable energy in the Arava region varies,
depending on the installation type, from 2,638 kWh m-2 for a polar tracking system to
2,154 kWh m-2 for stationary plates with tilt equals latitude. In terms of overall output,
then, the polar axis tracking configuration is the best of the non-concentrating
alternatives (this study excludes the dual axis tracking for flat plates because of its
operating complications and the relatively low improvement on the output). The
stationary with tilt equals latitude has a very good potential when considering the
simplicity and maintenance.
47
As mentioned, the collectable energy in the dual-axis tracking cases described
is lower than the polar axis tracking flate plate system, because the technologies
considered with this type of tracking are concentrator photolovaltaic (CPV) systems,
which do not effectively utilize the diffuse component of incoming solar radiation.
When the available direct radiation is diminished by clouds, fog, haze or dust, the CPV
systems have a very low output compared to the flat plat technologies – which do
absorb significant quantities of diffuse radiation. Considering the collectible energy of
the various systems, we observe that the N-S axis tracking and the dual axis tracking
systems show the largest seasonal variation (summer peak to winter low is a factor of
about 2.5) while for the other systems it is substantially lower. This is a result of the
accentuated sensitivity of these systems to beam radiation.
As expected because of its relatively low efficiency, the amorphous silicon (aSi) thin-film technology shows the poorest performance in terms of output – with
values ranging from 1048 kWh m-2 of panel area in the case of stationary with zero tilt
to 137 kWh m-2 of panel area with polar axis tracking. On the other hand, single
crystalline silicon (Single-Si) shows the best performance among flat plate PVs, with its
output varying from 328 kWh m-2 in the case of horizontal stationary to 434 kWh m-2
with polar axis tracking.
Ultimately, the dual-axis tracking CPV systems have the highest output per m2
of aperture area, which is expected because of their high conversion efficiency. On the
other hand, the land area requirements are expected to be high due to the dual axis
tracking (see the land use section in this chapter). As a result of that, the annual
output varies from 482 to 501 kWh m-2 for the SolFocus and the FLATCON systems
48
respectively, This is expected because of their high conversion efficiency. On the other
hand, the land area requirements are expected to be high due to the dual axis tracking
(see the land use section in this chapter).
3.2
Embodied Energy
The embodied energy for the different PV systems considered in this study is
shown in Figure 3.9. In the case of flat panels, these values refer to the initial
embodied energy required for the production of the PV modules, in units of primary
energy per square meter, and do not include BOS (operation, maintenance, support
structure, foundations, inverter and tracking system for the flat-plates). Values for the
CPV technologies, however, include the embodied energy for the whole system, per
square meter of aperture area. By this comparison the CPV technology systems have a
higher embodied energy than most of the flat plate systems, with values as high as
1149 kWh m-2 for the SolFocus system and 848 kWh m-2 for FLATCON. On the other
hand, the flat plate technologies’ embodied energy varies between 1373 kWh m-2 for
Single-crystalline and 357 kWh m-2 for CIS.
1149
1200
848
1400
1029
400
357
600
498
800
625
1000
693
Embodied Energy [kWh m-2]
1600
1373
49
200
0
Technology
Figure ‎3.9: Total initial embodied energy for different Photovoltaic modules.
3.2.1
Single Crystalline Silicon Module
Table 3.2 shows that in the case of Single-crystalline silicon, the highest energy
demand is embodied in the various stages of silicon production – which together
account for 1178 kWh m-2 of the module’s total embodied energy of 1373 kWh m-2.
The aluminum frame is the only other major energy consuming item, with 139 kWh
m-2.
50
kWh m-2
Item
MG-Silicon from Silica
SoG-Si from MG-Si
Single-Si from SoG-Si
Wafer sawing
Cell production
Module finishing
Aluminum frame
Glass
Transport
Total
35
539
471
0
112
21
139
44
12
1373
Table ‎3.2: Embodied Energy for Single Crystalline Silicon (Single-Si) module [34].
3.2.2
Multi crystalline Silicon Module
As shown in Table 3.3, the amount of embodied energy for silicon production
in the multi crystalline silicon module is lower than for Single-Si, dropping to 833 kWh
m-2. Accordingly, the total energy demand for manufacturing a Multi-Si module is also
reduced, at 1029 kWh m-2.
Item
MG-Silicon from Silica
SoG-Si from MG-Si
Multi-Si from SoG-Si
Wafer sawing
Cell production
Module finishing
Aluminum frame
Glass
Transport
Total
kWh m-2
37
570
94
0
112
21
139
44
12
1029
Table ‎3.3: Embodied Energy for Multi Crystalline Silicon module [34].
3.2.3
Ribbon Silicon Module
As shown in Table 3.4, the amount of embodied energy for a ribbon silicon
module is 693 kWh m-2, as the amount of energy needed for silicon production drops
51
significantly to 498 kWh m-2. In this case the aluminum frame represents a more
significant proportion of the total embodied energy of the module.
Item
MG-Silicon from
Silica
SoG-Si from MG-Si
Silicon ribbons
Module finishing
Aluminum frame
Glass
Transport
Total
kWh m-2
21
313
143
21
139
44
12
693
Table ‎3.4: Embodied Energy for Ribbon Silicon module [34].
3.2.4
Amorphous Silicon Module
In Table 3.5, energy inputs needed for amorphous silicon (a-Si) material
production and processes are shown. Unlike the crystalline silicon modules, the a-Si
has as its single-largest embodied energy item the aluminum frame, which in this case
requires 290 kWh m-2 which is the average of the upper and lower values. The grid
forming and the transparent conductive oxide (TCO) require negligible amount of
energy. The total amount of embodied energy needed for the a-Si module is 625 kWh
m-2.
52
Item
Aluminum Frame
Encapsulation
Stainless Steel Substrate
Steel Backing Plate
Deposition Materials
Busbar
Back reflector
Grid
TCO
Encapsulation
Amorphous Si alloy deposition
TCO deposition
Back reflector deposition
Substrate wash
TCO etch
Short passivation
Grid pattern screen print
Testing and Packing
System transportation
Total
kWh m-2
290
80
52
33
6
2
0
0
0
42
28
24
22
17
5
5
5
0
12
625
Table ‎3.5: Material Production Energy for a-Si module [38].
3.2.5
Cadmium Telluride (CdTe) module
As illustrated in Table 3.6, the embodied energy of a CdTe module is
distributed among a large number of materials and processes, with the aluminum
frame representing the highest embodied energy of any single component. The CdTe-,
CdS- and TCO-layer depositions all contribute to a high energy demand in the
manufacturing process. The substrate glass also contributes significantly to the total
embodied energy, which reaches 498 kWh m-2.
53
Item
kWh m-2
Substrate glass
Substrate cleaning
TCO-layer deposition
CdS-layer deposition
Laser patterning
CdTe-layer deposition
Thermal treatment by CdCl2
Mechanical patterning
Carbon-contact formation
Ag-contact formation
44
1
45
53
3
74
19
5
24
5
Passivation
Performance test
Aluminum frame
Back cover sheet
Other materials
Other energy input
Overhead
Transport
Total
4
1
78
47
45
2
36
12
498
Table ‎3.6: Embodied Energy for CdTe module [40].
3.2.6
Copper Indium Diselenide (CIS) Module
The main contributor to the embodied energy of CIS is the aluminum frame,
with 161 kWh m-2. The glass cover needs 73 kWh m-2, and the NH4OH for material
treatment comes in the third with 43 kWh m-2. The overall embodied energy, as
shown in Table 3.7, is 357 kWh m-2 – the lowest of any module compared here.
54
kWh.m-2
Item
Aluminum frame
Front glass
NH4OH
Back glass (2 mm)
EVA (0.018”)
H2Se
DEZ
Moly
J-box Set
Carton
Etchants
Shield glass
Tedlar TPAT
Nitrogen
161
48
43
25
19
11
5
5
4
4
4
3
2
2
kWh m-2
Item
H2S
Cu / Ga
Indium
Copper ribbon
Silicon
Adhesives
Solvents /
cleaners
Thiourea
Solder / paste
Argon
B2H6 / N2
CdSO4
Transportation
Total
2
1
1
1
0
0
0
0
0
0
0
0
12
357
Table ‎3.7: Embodied Energy for CIS module [41].
3.2.7
The Balance-of-System
For flat-plates technologies, Table 3.8 is used for the BOS values:
Item
Embodies energy (kWh m-2)
The inverter
125
Operating and maintenance
125
Support structure (Rooftops)
200
Support structure (Open fields)
500
Tracker
2
Table ‎3.8: Initial embodied energy for the BOS
The support structure (including the civil work) is 2.5 times higher for the open
field installations than for the rooftops, as the rooftop installations use the existing
surfaces as support structures.
3.2.8
FLATCON System
The values for the FLATCON system are shown in Table 3.9 in kWh per module,
the total is calculated in kWh m-2 of aperture area. The main contributor to the
55
embodied energy is the tracker with its components, which have an embodied energy
value of 356 kWh m-2 of aperture area. The PV cell itself with the processes needed to
prepare it comes second with 179 kWh m-2 of aperture area, and the module with the
float-glass as the main component comes next with 166 kWh m-2 of aperture area.
Item
Cumulated
Energy Demand
(kWh)
1419
11
Germanium wafer
Hydrogen
Hydride gases
13
Metalorganics
1
Energy for MOVPE Process
Energy for Cleanroom
Solvents
472
1158
39
Acids
3
Materials for
photolithography
Noble metals for
evaporation
Energy for cell technology
Copper heatspreader
Materials for chip
packaging
Energy for chip packaging
Float-glass
44
Item
Silicone sealing material
Silicone for lens array
High-voltage
interconnection board
Further module materials
Energy for module
fabrication
Zinced steel
Concrete foundation
Energy for system
installation
Inverter
144
972
Tracking sensor and
electronics
AC and DC wiring
Transport of the system
444
Total
317
361
2939
Total (kWh m-2)
Cumulated Energy
Demand (kWh)
222
467
556
6
72
8056
1000
75
833
61
389
1632
21705
848
Table ‎3.9: Embodied Energy for FLATCON system [29].
3.2.9
SolFocus System
The values for the SolFocus system are shown in Table 3.10 in kWh per
module, the total is calculated in kWh m-2 of aperture area. The mirror concentrator
has the highest embodied energy value among all the components the value gets as
high as 441 kWh m-2 of aperture area, unlike the FLATCON system, the SolFocus
56
tracker comes in the second place with 295 kWh m-2 of aperture area and then the PV
cell and its preparation processes and materials with 440 kWh m-2 of aperture area.
Item
Ge wafer – Cell
Hydrogen
Hydride gases
Metalorganics
MOVPE process
Cleanroom – Cell
Solvents
Acids
Photolithography materials
Cumulated Energy
Demand (kWh)
399
3
4
0
133
326
11
1
13
Evaporation noble metals
Cell technology
Chip packaging materials
Chip packaging
Copper Heat Spreader
Float Glass - Primary
Mirror
Silver
89
41
125
102
117
Cut
Slump – heat
Slump – vacuum
Cut
Drill
Grind
Spray x2
Bake
19
250
46
19
6
53
39
83
912
13
Item
Transportation - Conc.
Soda Lime Glass
Sputter (Ag)
Coat (Quartz)
Borsolicate glass
Aluminum Frame
Glass Cover
Sealant
Capital Equipment Assembly
Labor - Assembly
Zinced Steel Pipe
Zinced Steel Drive
Zinced Steel Torque Tube
Motor
Aluminum Module Rails
Tracking Sensor and
Electronics
Concrete Foundation
AC and DC Wiring
Interconnect Board
Inverter
Transportation
Installation
Total
Total (kWh m-2)
Cumulated Energy
Demand (kWh)
3734
16
240
19
146
483
363
37
49
528
1458
620
624
86
68
61
828
146
208
1703
330
40
14295
1149
Table ‎3.10: Embodied Energy for SolFocus module [10].
3.2.10 Summary
For crystalline silicon based PVs, the main contributor to the embodied energy
is the photovoltaic cell itself, as the process of extracting the silicon is a very
energy-intensive process. Thus reducing the required energy depends on
technological improvement. The aluminum frame is also another significant
57
contributor whose effect can be reduced by increasing the amount of recycled
aluminum used.
In the case of the thin film technology, the aluminum frame is the main
contributor to the embodied energy, which makes the potential to reduce the
embodied energy higher than the crystalline silicon PVs, since frameless thin film
panels are expected to be produced soon. Glass and encapsulation come next, so
using other less energy-intensive materials can improve the figures for the
embodied energy.
The story is different in the case of concentrator photovoltaics. The primary
aim of developing the CPV technology is to reduce the required PV cell size and
increase the relative aperture area. The cell here is not the main contributor to the
embodied energy. In order to concentrate the sunlight, a larger amount of glass is
being used, in the form of mirrors (for SolFocus) or lenses (for FLATCON); this
increases the weight of the panel and the module, which in turn increases the
requirements for the support structure and foundations. Steel is the main material
for this, and the zinced steel pipe is on the top of the list of the energy-intensive
materials used.
The CPV technology modules need to be always facing the sun, and this
requires a precise dual-axis tracking system – another source for the increase in
the embodied energy.
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
North-South Roof top
North-South Open Field
East-West Roof top
East-West Open Field
Stationary tilt=latitude Roof top
Stationary tilt=latitude Open Field
Polar Roof top
Polar Open field
Stationary tilt=0 Roof
Stationary tilt=0 open
Energy Bapback Time [Years]
58
3.3
Evaluation metrics
3.3.1
Energy Pay-Back Time
Energy Payback Time
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
BOS
Module
Single crystalline Si
Multi crystalline Si
Ribbon Si
CdTe
CIS
Figure ‎3.10: Energy Pay-Back Time (EPBT) in years, for different flat-plate PV technologies in different installations.
a-Si
59
CPV
0.9
Energy for system
installation
0.8
Transport of the system
Energy Pay Back Time [Years]
0.7
Tracker
0.6
Electrical
0.5
Module
0.4
Frame
0.3
Chip Material
0.2
Concentrator
0.1
Cell
0.0
FLATCON
SolFocus
Figure ‎3.11: Different contributions to the EPBT, for FLATCON and SolFocus
Systems.
As shown in Figure 3.10, the energy pay-back time of flat plate technologies
varies from 1.1 to 5.0 years. The case of roof top installation always has a shorter
energy pay-back time than the open field configuration, due to the lower BOS costs
when embodied energy for foundations is eliminated. The CIS technology shows very
good results in terms of pay-back time, especially when compared to the multicrystalline silicon PV. The a-silicon PV has the longest EPBT of all technologies
compared.
While the embodied energy of the solar cell itself contributes significantly to
the energy pay-back time in flat plate PV, the photovoltaic material has less effect in
60
the case of the thin film technology, where the balance-of-system has the highest
contribution.
In the case of CPV, the energy pay-back times for the two systems under
investigation were 0.8 and 0.6 for SolFocus and FLATCON respectively. It is clear that
the balance-of-system is the main contributor in both systems while the cell forms a
smaller portion as shown in Figure 3.11.
3.3.2
Land use
Another metric to evaluate solar electricity generation is the amount of land
needed per unit energy output. The values vary depending on the land cover ratio
of the panels, and the best ratio is for stationary flat plates with zero tilt, which
can reach 100% (though with lower collectable radiation than any other system).
For single axis tracking systems the ratio can be as high as 50%, which is equal to
the one for stationary flat plates with tilt equals latitude, if the backward tracking
technique was used, in the case of polar tracking, the value is 40%. The dual axis
tracking systems have the worst ratio due to mutual shading; the values are 12.7%
for FLATCON and 17.5% for SolFocus.
With 4.8 m2 MWh-1 the Single-crystalline silicon is the best option, among the
compared technologies and installations, when the area/land is a limiting factor.
The CPV technologies require more land with 15.7 m2 MWh-1 for the FLATCON
system and 11.9 m2 MWh-1 for the SolFocus system.
Different PV cell technologies require different areas per unit energy output.
Figure 3.12 shows the results of the required area in m2 per MWh of annual
61
output. Single-crystalline silicon PV has the lowest land requirement among all
technologies under consideration and amorphous silicon needs the largest area.
Among different installation types, the north-south axis tracking shows the
best performance among flat plate installations (excluding stationary horizontal),
and the stationary with tilt equals latitude required a little more area than the
east-west axis tracking.
62
15.7
16.9
15.2
18.00
16.00
4.9
4.5
Ribbon
5.4
3.0
4.2
CIS
9.7
8.5
9.2
8.0
multi-Si
5.8
8.3
Ribbon
9.0
9.9
7.7
8.5
5.6
6.00
7.9
7.4
multi-Si
4.8
5.3
7.1
Ribbon
7.7
6.6
8.00
8.5
10.00
9.4
12.00
10.2
11.9
14.00
4.00
2.00
North-South horizontal
tracking
East-West horizontal
tracking
Twoaxis
tracking
Stationary flat-plate,
azimuth= 0, tilt=
latitude=29.9 N
Polar Tracking
Figure ‎3.12: The land area required for each system per unit of yearly energy output.
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
CIS
CdTe
a-Si
single-Si
multi-Si
Flatcon
SolFocus
Ribbon
CIS
CdTe
a-Si
single-Si
CIS
CdTe
a-Si
single-Si
0.00
multi-Si
Land Area [m2 MWh-1 yr]
17.7
20.00
18.3
Land use per Wh Produced
Stationary flat-plate,
azimuth=0, tilt=0
63
3.3.3
The Energy Return Factor (ERF)
Unlike the EPBT, the ERF gives an indication of the energy balance of the PV
systems over their full life time; for example an ERF value of 4 for a certain system
means that it generates the equivalent of 4 times the amount of energy which
was consumed for its production and operation. Figure 3.13 shows the ERF for the
systems investigated in this study.
Assuming 30 years of operational life time for the crystalline silicon-based flat
plates and CPVs, and 20 years for the thin film flat plates, the CPV systems show
the best ERF ratio of 54 for FLATCON and 38 for SolFocus – which emphasizes the
high conversion efficiency of CPV. The flat plate technologies have an average ERF
of 12, with the stationary a-Si panels in an open field as the lowest and the ribbon
silicon plates with polar tracking as the highest.
3.3.4
CO2 offset per aperture area
Figures 3.14 and 3.15 show the CO2 emissions offset for the different systems
in units of tons per unit area of aperture, assuming a life time of 30 years for the
crystalline silicon and CPV systems and 20 years for the thin film systems.
With 9.6 and 10.4 tCO2 m-2 respectively, the SolFocus and FLATCON CPV
systems show a very high potential for CO2 offsetting. With a small difference,
Single-Si plates come next. The potential gets to 22% lower for a-Si plates.
64
3.3.5
CO2 offset per land area
This metric is the only one, among all metrics used in this study, which
accounts for all the different parameters; the embodied and yearly output energy,
the operational life time and the GCR.
Figure 3.16 shows the CO2 offset per land area for both rooftops and open
fields. The stationary flat plates with zero tilt has the highest values due to the
high GCR, which can reach theoretically 100% (several solutions can be
implemented to guarantee access for maintenance). It can also be seen that for
this configuration, the added benefit of rooftop installation is largest.
According to this metric, Single-Si is showing the best performance among all
technologies, as the amount of CO2 it is offsetting varies between 3.3 – 5.8 tons
for open fields and 3.39 – 6.08 tons in the case of rooftop installations. These
values are due to the relatively high efficiency and the long operational life time
of this technology.
65
Energy Return Factor
54
60
38
50
40
15
12
5
4
7
5
8
10
10
13
20
16
13
11
14
12
13
CIS
18
14
10
CdTe
17
14
19
16
multi-Si
17
13
Ribbon
15
6
4
6
5
9
11
11
14
12
16
13
18
14
11
9
12
15
20
16
15
12
16
14
12
CIS
17
13
10
6
5
10
CdTe
20
16
13
18
16
30
North-South horizontal
tracking
East-West horizontal
tracking
Two-axis
tracking
Stationary flat-plate,
azimuth= 0, tilt=
latitude=29.9 N
ERF Rooftop
Polar tracking
ERF Open field
Figure ‎3.13: The Energy Return Factor for the systems considered.
Stationary flat-plate,
azimuth= 0, tilt= 0
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
a-Si
single-Si
CIS
CdTe
a-Si
single-Si
multi-Si
Flatcon
SolFocus
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
a-Si
single-Si
multi-Si
0
66
CO2 offset (Open fields)
12.0
10.4
9.6
8.0
6.0
8.3
7.9
6.9
5.5
5.3
4.0
2.7
2.0
6.5
5.8
4.8
4.7
3.3
2.4
0.9
4.5
4.4
2.9
2.2
0.7
5.8
5.6
2.9
2.7
4.0
3.5
3.9
1.9
1.0
0.6
2.4
0.5
North-South horizontal tracking East-West horizontal tracking Concentrator
Stationary flat-plate
Two-axis azimuth= 0, tilt= latitude=29.9 N
tracking
Polar Tracking
Figure ‎3.14: CO2 emissions offset for the different systems on rooftop installation.
Stationary flat-plate
azimuth=0, tilt=0
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Flatcon
SolFocus
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
0.0
multi-Si
tCO2 m-2aperture
10.0
67
CO2 offset (Rooftops)
9.0
8.6
8.1
8.0
7.2
6.8
6.0
6.1
5.7
5.1
4.9 4.8
3.1
3.0
4.3
4.2
1.2
3.2
2.9
2.6
3.0
2.0
4.7
3.7
3.5
4.0
6.1
5.9
5.6
5.0
2.5
1.0
2.2
2.6
1.3
0.9
1.0
0.7
North-South horizontal tracking
East-West horizontal tracking
Stationary flat-plate
azimuth= 0, tilt= latitude=29.9
N
Polar Tracking
Figure ‎3.15: CO2 emissions offset for the different systems on open field installation.
Stationary flat-plate
azimuth=0, tilt=0
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
0.0
multi-Si
tCO2 m-2aperture
7.0
CO2 offset per land area (Rooftop)
North-South horizontal tracking East-West horizontal tracking Concentrator
Stationary flat-plate
Two-axis azimuth= 0, tilt= latitude=29.9 N
tracking
Figure ‎3.16: CO2 emissions offset per land area
Polar Tracking
CO2 offset per land area (Open field)
Stationary flat-plate
azimuth=0, tilt=0
Ribbon
CIS
CdTe
a-Si
1.9
0.5 0.73
2.4
2.2
1.49
1.27
4.0
3.9
2.64
2.20
2.35
3.43
3.39
3.60
4.19
4.25
4.07
5.8
6.08
CO2 Offset per land area
single-Si
multi-Si
Ribbon
1.4
1.2
CdTe
CIS
0.4 0.51
a-Si
3.3
2.42
2.3
multi-Si
single-Si
2.33
3.3
2.38
2.47
3.5
2.53
2.80
2.2
1.47
1.24
2.2
2.3
1.56
1.32
2.4
2.7
1.77
1.51
Ribbon
1.3
1.1
CdTe
CIS
0.3 0.45
1.3
1.7
a-Si
single-Si
multi-Si
Flatcon
SolFocus
Ribbon
1.4
1.2
CdTe
CIS
0.4 0.49
0.00
a-Si
1.6
1.4
4.00
single-Si
multi-Si
Ribbon
CIS
CdTe
0.5 0.59
1.00
a-Si
3.9
2.87
5.00
single-Si
2.00
2.7
3.00
multi-Si
t CO2 m2land
68
6.00
69
3.1.1
Sensitivity of results
The values of the various metrics presented in the preceding discussion are dependent
on many assumptions, including the operational lifetime of the PV systems, the ground
cover ratio (GCR), and the system boundary (IFIAS level) for the life-cycle analysis. Table
3.11 gives an overview of these assumptions, and shows which of the metrics are
quantitatively affected by each of them.
Assumption
EPBT
Land use
ERF
CO2 offset per
CO2 offset per
aperture area
land area
GCR
No
Yes
No
No
Yes
Mutual shading losses
Yes
No
Yes
Yes
Yes
Module efficiency
Yes
Yes
Yes
Yes
Yes
IFIAS level for LCA
Yes
No
Yes
Yes
Yes
System operational lifetime
No
No
Yes
Yes
Yes
No
No
No
Yes
Yes
Total CO2 emissions for the
electricity mix
‎3.11: The effect of different assumptions on the study’s metrics.
The extent to which each metric is affected by the input values contained in these
assumptions may be examined using sensitivity analysis, by which the input values are
adjusted systematically and a new comparison is made between the systems. In this
discussion, the assumption regarding the systems' operational lifetime is presented as an
example of this sensitivity analysis. Table 3.11 shows that this assumption affects the
energy return factor (ERF) metric, as well as the lifetime CO2 emissions (both per aperture
area and per land area).
70
In the original analysis, it was assumed that the thin-film PV systems have an
operational life of 20 years, and that all the other technologies have a lifetime of 30 years.
In the sensitivity analysis this relationship is reversed, so that the thin-film options are
assumed to last only 30 years and all the others 20 years. Figure 3.17 shows the effect of
this change on the lifetime CO2 emissions per unit of aperture area for the different
systems (all with rooftop installation).
It may be seen that the CO2 offset value for the thin-film a-Si system (in a horizontal
stationary configuration, for example) approximately doubles with a 30-year lifespan, but
is still by far the lowest of all technologies in that configuration, even when the non-thinfilm options are assumed to only last 20 years. On the other hand, the CO2 offset for CIS
thin-film technology (in the same configuration, with a 30-year span) becomes the highest
of all technologies when the non-thin-film span is reduced to 20 years.
The latter result represents a qualitative change in the conclusions of the analysis, and
show how sensitive these conclusions may be to the particular assumptions made. It is
therefore of utmost importance that the assumptions underlying LCA studies such as this
are, as much as is possible, based on accurate and experimentally supported information.
North-South horizontal
tracking
East-West horizontal
tracking
Stationary flat-plate
azimuth= 0, tilt=
latitude=29.9 N
‎3.17: The effect of the life time on the CO2 emissions offset.
Polar Tracking
Stationary flat-plate
azimuth=0, tilt=0
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
single-Si
multi-Si
Ribbon
CIS
CdTe
0.7
1.5
2.6
2.6
2.2
2.6
4.1
4.2
3.8
4.9
4.5
4.7
3.8
4.3
3.7
3.8
4.8
4.9
4.8
4.2
4.1
3.9
3.5
3.2
3.0
2.9
2.5
2.9
3.2
3.1
2.6
2.2
1.8
1.7
1.3
0.9
1.0
a-Si
1.0
4.5
6.1
5.6
5.9
5.5
6.1
5.4
5.6
5.1
4.7
7.2
6.8
7.0
single-Si
multi-Si
Ribbon
CIS
CdTe
a-Si
3.6
3.5
3.1
3.0
8.0
single-Si
multi-Si
Ribbon
CIS
3.0
2.1
5.0
CdTe
2.0
1.2
5.2
5.7
8.6
8.1
9.0
a-Si
single-Si
4.0
3.6
6.0
multi-Si
tCO2 m-2aperture
71
CO2 offset (Rooftops)
0.0
72
3.1.2
Summary
The energy pay-back time encompasses both the embodied energy and the energy
output of the PV system, with both in comparable primary energy units.
While the particular installation type (tracking or stationary) has little effect on the
embodied energy, it strongly affects the energy output under the given conditions of the
Arava and therefore has a significant influence on the energy payback.
As expected, roof top installations have a significantly lower energy pay-back time than
flat-plate open field arrays, due to the embodied energy savings achieved by utilizing
existing structures and thereby avoiding new concrete foundations. These differences are
amplified when relatively inefficient PV material such as a-Si is used, and the payback
period is lengthened. On the other hand, rooftop installation is not considered a practical
option for the concentrating dual axis tracking systems, whose high output efficiency may
give them the shortest payback time.
For flat plate technologies, the module is responsible for between 44-75% of the energy
pay-back time, and the rest is the balance-of-system, in the case of roof top installation. In
the open field case, the module's contribution is reduced to 32-65% of the energy pay-back
time. In either case, the PV cell itself is the main component of the module's embodied
energy. On the other hand with CPV, the cell is a relatively a small contributor to the energy
pay-back time; its effect is between 10% to 20% of the whole energy pay-back time while
73
the rest is coming from the cell’s support structure, the concentrator, tracker and the
foundation and module support structure.
Among the flat plate technologies, Copper Indium Diselenide yields the shortest energy
pay-back time, with a value as low as 1.1 years for roof top installation and 1.5 for open
field in the case of polar-axis tracking. The longest EPBT is for the amorphous silicon, with
values as high as 5.0 years and 3.9 years for roof top and open field respectively in the
stationary with zero tilt installation. The CPV technologies, SolFocus and FLATCON, show a
very good potential with low energy pay-back times equal to 0.8 and 0.6 years respectively.
On the other hand, the required land area for producing each annual MWh of electricity
is lowest for the stationary horizontal flat-plates, despite their low output efficiency. For
tracking systems, the north-south horizontal axis has the lowest land demand, mainly
because it is the most tolerant to mutual shading losses caused by the GCR and it generates
more yearly energy than east-west horizontal axis tracking. The polar and dual-axis tracking
systems have relatively low GCR values.
As the EPBT does not give an indication of the energy balance over the system’s total
operational life time, the Energy Return Factor is used to represent the ratio between the
system’s total generated energy during its operational life time and the amount of energy
consumed by the system’s production. CPV systems have the highest ERF due to their high
output, and Ribbon silicon panels have the highest ERF value among flat-plate technologies
due to their low embodied energy and their relatively high module efficiency, and due to
74
the long life span of silicon technologies (30 years) relative to thin-film (20 years). Thus the
CIS thin-film technology, which has the shortest EPBT, does not have the highest ERF.
Amorphous silicon has the lowest ERF due to its low output efficiency, and single-Si comes
next because of its high embodied energy requirements.
As a result of the energy balance of the different systems and taking into consideration
their operational life time, the total amount of fossil fuel-generated electricity abated by
the PV system was calculated and converted to equivalent CO2 emissions as shown in
Figures 3.14 and 3.15. Since the CO2 emissions calculations are based on the difference of
the operational life time output and the embodied energy, rather than the ratio, the effect
of the embodied energy becomes less significant while the effect of the output energy and
the system’s operational life time will have more impact. For example, a comparison of the
Single-Si values of the CO2 emissions offset for polar tracking on both rooftops and open
fields shows that the effect of the difference in BOS energy on the total CO2 emissions is
only 4%.
75
4.
System Scaling comparison
In order to evaluate the life-cycle energy efficiency of PV systems at different scales of
deployment, this study establishes three different levels of scale: 1) Building-integrated PV
(BIPV); 2) Kibbutz (urban) integrated PV; and 3) Regionally integrated PV (Centralized
power plant).
The comparison between these models is made in two ways, using two different
models for comparison:
1. Different scales with the same technology, whereby the single most adaptable
technology is chosen and compared at different scales.
2. Choosing the most suitable technology for each scale.
In both models, the selected technology is chosen based on criteria of applicability,
market availability and total output per unit area.
The building-integrated scale uses the available rooftop area of households for PV
installation; in this case the house owner will be responsible for the system’s maintenance.
The use of existing built surfaces will reduce the embodied energy requirements by
eliminating the need of civil work and foundations.
On the other hand, the kibbutz-integrated case utilizes not only rooftops of public
buildings in the kibbutz, but also areas of open space that require shading and are assumed
76
to have structures for this purpose. This increases the area available, and the kibbutz
administration (the municipality in the case of cities and towns) will be responsible for the
maintenance of the systems. The different available potential areas for PV technologies in
Kibbutz Ketura, the model settlement used in the case study, are shown in Figure 4.1.
Roof top
Public space shading
Open field
Figure ‎4.1: Different available areas for PV deployment in
Kibbutz Ketura.
The third scale is the centralized power plant, which is sized to generate 12.5 MWp in
order to match the total annual electricity demand of the kibbutzim in the Arava (which is
77
equal to 25 GWh yr-1). It is assumed here that land availability in the Arava is not the
limiting factor in determining system size. Implementation at this scale allows for
centralized maintenance, but it introduces transmission losses due to the transmission of
the power to the point of use (estimated as 0.02% km-1). The embodied energy for this type
of installation is higher than the first two scales, since it requires foundations and civil
work.
4.1 Comparing the different scales for the same technology
By using the different metrics from Chapter 3, the Single-crystalline silicon flat
plate technology was chosen as the most suitable single technology for
implementation at all scales (the CPV options were eliminated in this case as
unsuitable for rooftop installation). Per unit aperture area, Single-Si has the highest
electrical output of all flat-plate options (Fig. 3.2), and the highest CO2 offset (Figs.
3.14-3.15). Despite this material's relatively high embodied energy, only CIS has a
significantly shorter EPBT (Fig. 3.9), and Single-Si has the second highest ERF after
Ribbon silicon (Fig. 3.13).
Due to the relative complexity of the single-axis tracking systems, stationary
panels were considered as the most practical installation option for all cases,
including rooftops and shading structures, and tilt equals latitude was chosen
because of its significantly higher output (relative to tilt=0) per unit module area.
78
The output per unit area of the system is 358 kWh m-2 and it’s space requirement is
5.6 m2 MWh-1 yr.
Installations on shading structures have the same energy pay-back times as that
of the building integrated PV, since the shading devices are needed anyway and the
use of PV will not require additional costs. However, by utilizing available areas
within the kibbutz other than residential rooftops, the PV system may be sized to
produce as much electricity as the entire kibbutz consumes
The energy pay-back time for the systems discussed below will be 1.9 years for
the rooftop installation with ERF equal to 16, and 2.2 years for the open field with
ERF equals to 13. Referring to the available area in Kibbutz Ketura, the following
results were obtained:
a. For the building integrated PV: The potential useable roof top area is equal
to 10,940 m2. Taking into consideration a 50% cover ratio, the total PV area
is 5,470 m2. In the case of stationary panels with tilt equals latitude this gives
1,958 MWh yr-1 of electricity, after taking into consideration 15% losses due
to mutual shading, the total goes down to 1,664 MWh yr-1, which covers
51% of Kibbutz Ketura’s demand. The system will offset 37,196 tons of CO2.
b. For kibbutz integrated PV: an area of 24,567 m2 was identified on public
building rooftops and as shade for parking lots, sidewalks and open spaces,
which gives 12,284 m2 as usable PV area. The potential output will be 3,738
79
MWh yr-1, with an actual output of 3,250 MWh yr-1 because of mutual
shading in the case of stationary panels with tilt equals latitude (this covers
100% of the kibbutz demand). The system will offset 85,531 tons of CO2.
c. The 12.5 MWp centralized power plant (which is capable of generating 25
GWh yr-1): taking into consideration the 0.02%.km-1 transmission losses, an
additional 0.25 MWp is added to the plant capacity, based on the values of
the area needed per energy unit output in Figure 3.11, an area of 141
dunams of land for stationary plates with tilt equals latitude. The energy
pay-back time in this case will be 2.2 years. The power plant will offset
958,800 tons of CO2.
Table 4.1 shows a summary of the results of comparing the same technology in
different scales.
Scale
EPBT
(years)
ERF
tCO2
BIPV
1.9
16
37,196
KIPV
1.9
16
85,531
RIPV
2.2
13
479,400
Table ‎4.1: The results of comparing the same technology in
different scales.
4.2 Compare the "best" system for each scale
a. Building integrated PV: The Single-crystalline silicon PV with north-south axis
tracking is the best system for this scale, since it is the least costly of tracking
80
systems and the most tolerant to mutual shading losses due to the GCR [16].
Based on the area of residential rooftops, this option potentially gives 2,275
MWh yr-1 of electricity, which in practice is 1,934 MWh yr-1 due to the 50%
GCR (this configuration covers 60% of the kibbutz electricity demand). The
energy pay-back time in this case will be 1.7 years, and the system will offset
44,307 tones of CO2 with a value of ERF equal to 18.
b. Kibbutz-integrated PV: For this scale, a combination of two different
installation types was selected, one for the rooftops and one for shading
areas, with the requirement that the total output should sum up to 3,250
MWh yr-1 to meet the annual electricity demand of Kibbutz Ketura [6]:
The available area of public building rooftops is 9,874 m2. For this option, the
north-south horizontal axis tracking is used, which will form 4,937 m2 of PV
area, and after taking into consideration 15% shading losses it generates
1,484 MWh yr-1 (42% of the kibbutz electricity need). The energy pay-back
time will be 1.7 years, with 18 as a value for the ERF and it will offset 39,990
tons of CO2.
Stationary panels with zero tilt, single crystalline silicon panels were chosen
for shading of public spaces, with an area of 7,419 m2. This generates 1,885
MWh yr-1 (58% of the kibbutz need). The energy pay-back time will be 2.1
years, with 14 as a value for the ERF and the system will offset 45,256 tons
of CO2.
81
In total, the kibbutz-integrated PV system will offset 61,238 tons of CO2. By
repeating the kibbutz-integrated PV scenario in different kibbutzim in the
Arava, the annual demand of the region can be met easily. Such an option
would use minimal land area, making efficient use of rooftops and public
shaded areas. This will also reduce the transmission losses because of the
point-of-use generation.
c. A 12.5MWp centralized power plant (plus 0.25MWp to recover the
transmission losses): For this scale the best system is a CPV, from the land
use point of view, is the SolFocus CPV with 11.9 m2 MWh-1 yr required of
land area. The energy pay-back time of a power plant based on this
technology will be 0.8 years, with a 38 ERF. It will need 304 dunams of land
and offset 510,720 tons of CO2.
Table 4.2 shows a summary of the results of comparing the “best” technology
for each scale.
Scale
EPBT
ERF
tCO2
1.7
18
44,307
Shading
2.1
14
45,256
Rooftops
1.7
18
39,990
Total (weighted average)
1.9
15.7
85,246
0.8
38
510,720
(years)
BIPV
KIPV
RIPV
Table ‎4.2: The results of comparing the “best” technology for each scale.
82
5.
Conclusions
This study has examined the life cycle energy balance of different PV systems in terms
of a large number of variables, and found that each of them is in fact significant to the final
comparison. Cell technology, installation type, system life span, and ground cover ratio are
all factors which can fundamentally alter at least one of the evaluation metrics. This makes
the selection of technology and installation type very sensitive to the different
circumstances of the case under investigation.
It was found that utilizing existing infrastructure, such as existing building roofs and
shade structures, does significantly reduce the embodied energy requirements (by at least
15%) and in turn the energy payback time of PV systems due to the avoidance of energyintensive BOS components like foundations. Considering different system scales, the study
indicates that the building integrated PV and the kibbutz (urban) integrated PV scenarios
are acceptable alternatives to a centralized, large scale regional PV power plant.
High-efficiency CPV systems were found to yield the shortest EPBT, the highest ERF and
offset the most CO2 – if land is not a limitation. Because the studied CPV systems have a
very low ground cover ratio, they require large field installations which are not appropriate
for local integration. On the other hand, the kibbutz-integrated model offers an alternative
by which non-concentrating systems may be used locally, and while their efficiency per unit
module area is lower, their life-cycle energy and carbon offset potential per unit land area
is greater.
83
The life-cycle energy analysis does not provide a direct analysis of the economics of PV,
but does provide relevant indicators of the relative economic benefits of different systems.
In particular, as energy costs rise, and a high price is put on CO2 emissions, these metrics
will become more directly relevant economically.
The specific situation of the Arava region with its electricity demand, population
distribution, and metrological conditions was used as a case study. Some eight different PV
systems with varying tracking strategies were included in the analysis, ranging from thinfilm PV to Silicon-based flat plate collectors to high-concentration PV systems. These
systems are only representing part of the wealth of PV systems on the market. Thus, the
conclusions reached here, as well as the rankings among the systems, must be re-evaluated
whenever new ones are considered as alternatives. This study should then serve as a
template for analyzing such systems, or others that may use different materials or even
only different production processes, efficiencies or ground cover ratios, for example.
Future work is needed to be done in order to investigate such constraints as rooftop
orientation in different urban settlement patterns, and analyze the implications for
choosing the most suitable system. Issues regarding the GCR and mutual shading of both
stationary and tracking systems should be considered in greater detail, in order to optimize
the system in terms of the life-cycle energy metrics that were considered here.
84
Appendix I
Error Analysis
Error Propagation
If R is a general function of one or more variables, i.e. R(X,Y,…), then the uncertainty in R
is obtained by taking the square root of the sum of the partial derivatives of R with respect
to each variable multiplied by the uncertainty in that variable (for independent random
errors), as explained in the following equation [56]:
Where δR, δX and δY is the error in the corresponding variable.
In the case of fractional uncertainty, where the error is expressed as a percentage of the
read value, the actual uncertainty will be calculated using the following equation [56]:
(13)
Where: F.U. is the fractional uncertainty.
In this study, the following uncertainty will be assumed:
± 5% of fractional uncertainty for global radiation, ± 3% for direct beam radiation, ± 1 m
s-1 for wind speed, ± 0.5 °C for temperature and ± 0.05 for the albedo, these values lie
within the error margin for the metrological readings [57-59].
85
Since actual measured data is only available for stationary flat plate with tilt equals
latitude, the error calculations were performed only for this installation type.
The data was measured in kibbutz Ketura, of a thin film amorphous silicon plate, made
by Bangkok Solar, with efficiency equals to 5.1%, power temperature coefficient of -0.19%
°C-1 and an area of 0.79 m2.
For cell temperature:
(14)
And:
(15)
where:
Tm=back surface module temperature, °C.
Ta=ambient temperature, °C.
E=solar irradiance on module, W m-2.
Eo=reference solar irradiance, 1000 W m-2.
WS=wind speed measured at standard 10m height, m s-1.
86
T1=empirical constant determining upper temperature limit at low wind speed °C.
T2= empirical constant determining upper temperature limit at high wind speed °C.
b= empirical coefficient determining the rate that module temperature drops as wind
speed increases s m-1.
For the collectable energy:
(16)
Where:
Icoll: the collectable solar radiation on the surface.
Ig: the global radiation.
Ib: the direct beam component of the solar radiation.
Id: the diffuse component of the solar radiation (Id=Ig-Ibcosθz)
θi: the incident angle.
Ki: the incident angle modifier for the direct beam component.
Kd: The incident angle modifier for the diffuse radiation. Calculated for θ=60° for diffuse
radiation and θ=75° for ground reflected radiation.
87
β: the surface tilt angle.
ρg: the ground reflectivity.
And:
(17)
where:
o/p: the output energy of the panels, W m2.
A: the module’s aperture area, m2.
η: the module efficiency.
: Temperature coefficient, % °C-1.
Figure I.1 shows the error in the calculated values and a comparison with the actual
output for three different days.
05:40
06:30
07:20
08:10
09:00
09:50
10:40
11:30
12:20
13:10
14:00
14:50
15:40
16:30
17:20
18:10
4:50
5:40
6:30
7:20
8:10
9:00
9:50
10:40
11:30
12:20
13:10
14:00
14:50
15:40
16:30
17:20
18:10
06:00
06:50
07:40
08:30
09:20
10:10
11:00
11:50
12:40
13:30
14:20
15:10
16:00
16:50
Output [W m-2]
88
The Calculated and Measured Outputs
45
45
45
40
40
40
35
35
35
30
30
30
25
25
25
20
20
20
15
15
15
10
10
10
5
5
5
0
0
0
Time
Time
Time
6 Jan 2008
21 March 2008
10 May 2008
Figure ‎I.1: The calculated output with error margins and the measured output.
89
In Figure I.1. we observe that part of the calculated power output falls within the
error bars – particularly during the mid-day hours, while for the morning and
afternoon hours the discrepancy is outside the error bars. We can speculate where
these apparently systematic errors stem from: One reason might be that the
meteorological data (taken from Yotvatah some 10 km from the experimental site) are
somewhat different from the local ones, due to a different micro climate. Another
possibility might be that the orientation of the panels was not quite due south which
would explain the delayed morning rise in output. However, for the purpose of our
study, the simulation is considered sufficiently accurate to allow quantitative
comparisons between systems under the reasonable assumption that simulation
errors or data errors will affect the different systems similarly without distorting the
results in favor of one or the other system.
90
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