regarding solar generation

1. Abstract -- During the last decade, the market
penetration of photovoltaic (PV) technology has been
increased tremendously worldwide. This trend is driven not
only by the associated environmental benefits that
characterize this technology, but also by the incentive
mechanisms developed in various Countries. In the EU
context, following the quick development in German and
Spanish PV sector, Italy is currently one of the most
interesting market. In view of these facts, it is strategic to
perform detailed technical and economical analyses to
establish energy performances and profitability of the PV
plants, depending on their configurations. The purpose of
this work is to carry out a comparative analysis for the
achievable performance of PV plants using different types
of mounting system (fixed and tracking) for various Italian
climatic conditions through specific computer simulations.
The final outcome is a detailed performance and economical
analysis on different mounting system configurations, for
the selection of most suitable choice with respect to energy
and economical points of views.
Index Terms - Ground-mounted PV plants, Fixed and
tracking mounting systems, energy performance analysis,
economical analysis.
I. NOMENCLATURE
STC = Standard Test Conditions (1000 W/m2
, 25°C,
AM 1.5).
Wp = Watt Peak, maximum power output at STC.
BOS = Balance Of System.
H = solar irradiation on module surface [kWh/m2
].
PR = Performance Ratio.
II. INTRODUCTION
Recent market surveys confirm that the production of
solar photovoltaic technology has grown about 40%
every year on average from 2003, with a peak of 60% in
2007. Germany is a clear leader in the European market,
with sales totaling 5.7 billion euros and more than
100,000 homes equipped with the photovoltaic systems
[1]. Overall, worldwide, half of the total production of
PV electricity, which amounts to 10 billion kWh, comes
from EU countries.
A key contribution to achieve these results is because of
the introduction of specific incentive policies, aimed to
enhance the development of this sector. In particular, at
EU level, the directive 2001/77/EC-Electricity production
from RES, defined the basic rules to apply feed-in tariff
to the electricity production by photovoltaic systems
connected to the electricity grid. This mechanism
provides remuneration to the energy produced by the PV
plants for a given number of years starting to their first
grid connection, according to rates expressed in € / kWh.
This incentive Programme was implemented in Italy
with the Decree “D.M 19/08/2005”, then modified by the
Decree “D.M. 19/02/2007” that introduced the feed-in
tariff mechanism for PV electricity production.
This kind of financing mechanism has significantly
increased the interest of national and international market
on system and design solutions that allow to increase
energy production for equal PV surface areas and
installed powers [2].
It must also be considered that southern Europe is
characterized by interesting solar irradiation levels and, in
particular, southern Italy, like some areas in the south of
Spain, combines abundant availability of agricultural
lands at low cost alongwith favorable weather conditions.
In fact, the irradiation value on an optimal-tilted and
oriented plane for the mentioned areas is on average over
1700 kWh/m2
.
Therefore, it is particularly important to analyze in
details the various spatial configurations that can be
adopted for the PV plant, carefully evaluating the
economic viability in relation with current market
material costs and required additional costs for their
implementation, management and maintenance.
III. METHODOLOGY
Energy productivity of PV systems depends on many
factors, which can mainly be summarized in the
following categories:
- type and technology of PV components;
- reference climatic context;
- ground-placing layout and tracking strategies.
In the present work, the first part is related to the detailed
specific analysis on each of the above-mentioned
categories, listing the performance reference-parameters
used in the present assessment. Then a 6.3 kWp sample
plant configuration has been chosen by selecting high
quality technological components and available ground-
placing layout and tracking strategies. Further, energy
performance simulation has been carried out for the
Performance analysis of ground-mounted
PV plants
N.Aste, C. Del Pero, R.S.Adhikari,
Dept. Building Environment Science & Technology (BEST) - Politecnico di Milano, Via Bonardi 3, 20133 Milano, Italy
165978-1-4244-2544-0/08/$20.00 ©2009 IEEE

2. sample PV plant, evaluating differences due to different
climatic contexts and ground mounting system
configurations. Subsequently, it was possible to carry out
a detailed profitability analysis, based on the costs of PV
plants prevailing in the current market .
IV. TECHNOLOGICAL COMPONENTS
The main technological components of a PV plant can
be divided into the followings categories:
A) PV modules: The main parameters that characterize
the energy performance of a photovoltaic module are:
- the nominal conversion efficiency, which indicates
the amount of electricity supplied by the module as
a function of incident solar radiation, determined in
standard test conditions (STC). This efficiency
depends on the peak power rating of the module and
its total area;
- the temperature coefficient, which indicates the
deviation percentage of the nominal efficiency of
the modules, depending on the temperature variation
in relation to STC;
- the performance-degradation coefficient, which
indicates the annual percentage decrement
compared to the rated power, during the module
operating cycle.
These parameters are provided through the technical
specifications of the manufacturer of the modules and in
order to ascertain the accuracy, these can be
experimentally verified by performing on-field analysis
of heat stress in outdoor conditions. In the present work,
analyzing the technical characteristics of several PV
modules available on the market and the results of some
experimental tests [3], the photovoltaic modules with
high power density characterized by higher performance
in comparison to the average market products, are
identified. This choice is aimed to evaluate ground
mounting systems and tracking strategies applying high
quality components, in order to determine the best
performance achievable in each case.
B) Inverter: The main characteristics of static-
converters can be summarized by:
- MPPT voltage range on DC side and capability to
manage independently the various strings of
modules;
- Euro-efficiency, which represents a weighted
average of DC/AC conversion efficiency at different
load input levels.
Analyzing the main products on the market it was
observed that most of them, on average, are characterized
by good performance levels. However, in presence of
high peak power PV systems, it is possible to select two
different configurations viz. distributed or centralized,
achievable through small size inverter or few units with
high power. In the present work, considering plant’s size,
just single-phase inverters have been evaluated.
C) Other BOS components: The other components of
the BOS of a PV plant include primarily electrical wiring
and the CC and CA boards, the monitoring
instrumentation and BT/MT transformers, if present. For
the purposes of this work, it was assumed that the choice
of these components does not significantly affect the final
performance of a system. Even if, generally, mounting
structures are included among BOS components, in the
present work they will be analyzed separately.
V. CLIMATIC CONTEXT
The characteristics of the weather conditions that
could significantly influence the energy production of a
photovoltaic system are, mainly:
- the total solar radiation level and the distribution
percentage of beam and diffuse components;
- the ambient air temperature.
In the present work three different Italian locations
were identified which represent various climatic
conditions that characterize the Country. Moreover, these
can also be used as a reference to Central and South
Europe contexts.
The solar irradiation and air temperature data were
obtained from the Meteonorm software [4]. In the Table
I, the average values of irradiation and air temperature are
shown for the selected sites, representation the different
level of irradiance.
TABLE I
WEATHER DATA FOR REFERENCE SITES
Irradiance
level
Reference
site
Irradiation on
horizontal plane
[kWh/m2
]
Annual
Average air
temperature
[°C]
Medium-Low
Milan
Northern Italy
1255 11.85
Medium
Rome
Central Italy
1549 15.79
Medium-High
Palermo.
Southern Italy
1690 18.01
VI. GROUND-PLACING LAYOUTS AND TRACKING
STRATEGIES
Photovoltaic modules can be placed on the ground
using different types of mounting structures, with fixed or
mobile planes. The last ones are available in different
configurations, with different technical and structural
solutions, capable to ensure different levels of energy
production. In the present work, the following ground-
placing layouts and tracking strategies have been
considered (Figure 1):
1. structures with fixed inclination and orientation;
2. one-axis tracking structures, provided with
horizontal axis parallel to the East-West
direction;
3. two-axis tracking structures.
4. one-axis tracking structures, provided with
horizontal axis parallel to the North-South
direction;
5. one-axis tracking structures with optimum tilted
axis, toward North-South direction;
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3. Fig. 1. Different configurations of ground-mounted PV
plant
In order to define the possible layouts for each analyzed
category, the following reference angles were chosen:
- γ, is the angle among the horizontal projection of the
normal to the surface and the South semi-axis; it
indicates the orientation of the surface compared to
the geographic South. The value is 0° when the
surface is oriented to the south, and this is positive
for rotations to the east and negative towards the
West.
- ψ, indicates the surface tilt compared to the
horizontal plane. The value is 0° when the surface is
horizontal, is positive for anticlockwise rotation and
negative for clockwise ones.
VII. PV PLANTS ENERGY SIMULATION
The estimation of the energy performance of a
photovoltaic system can be performed by different
methods of calculation or simulation procedures. In
particular, in order to carry out the preliminary analysis,
the PV electricity production can be evaluated by the
following simple expression:
STC
PVPV
I
H
PPRE ××=
where:
EPV, expressed in kWh, is the amount of electricity
produced during the analyzed period.
PPV is the rated PV nominal power (kWp).
H is the solar irradiation on the unit-surface under
consideration, during the analyzed period [kWh/m2
].
ISTC is the solar irradiance at Standard Test Conditions
(STC), equal to 1 kW/m2
.
PR represents the PV plant performance ratio. This
coefficient, whose average value is around 75-85%,
represents the overall effect of all elements influencing
the final productivity of a photovoltaic system connected
to the grid and can be defined according to the following
expression:
INVMWTBIO
kkkkkPR η×××××=
where:
kO indicates the influence of optical and spectral losses;
kBI indicates the influence of the low-irradiance losses;
kT indicates the temperature losses;
kW indicates the DC and AC wiring losses;
kM indicates the influence of the mismatching losses;
ηINV is the DC/AC conversion efficiency.
However, to carry out detailed annual productivity
analysis of a PV plant by this method could be laborious
and inaccurate. In fact, to precisely determine PR values
with short time steps requires long analytic examination
and, in reverse, to adopt average PR values cause
imprecise results.
For the performance of PV systems, there are a
number of quick and user-friendly estimation tools, such
as the PV Potential Estimation Utility developed by the
Joint Research Center of the European Commission [5].
These allow to determine the average solar radiation
available in various European locations and consequently
the PV productivity. However, they assume approximate
PR values, so the final accuracy is not typically high.
In order to obtain more detailed analysis, on the
market some simulation software are available that can
perform energy calculations using the hourly climatic
data. To do so, it is possible to use methods based on the
reconstruction of a Typical Meteorological Year (TMY),
using statistical series of data acquired during several
years. Therefore, this procedure allows to evaluate
accurately the amount of all the previously-mentioned
influence factors.
In the present study, it was so decided to use a tool that
allows to carry out evaluation with high level of
accuracy, based on previously described criteria. Then,
by defining the climatic context and the PV plant
parameters, it was possible to simulate the performance
behavior of different configurations with the PVSyst
specialist software [6].
This software is used to predict in detail the
performance of a specific photovoltaic system, using the
hourly meteorological data for the analyzed location as a
reference. In particular, starting from the horizontal plane
irradiation, the software is able to simulate the incident
radiation on fixed or tracking surfaces. Subsequently, by
defining the technical characteristics of the selected
components, such as inverters and modules, it was
possible to simulate the PV plant’s behavior, depending
on the operating conditions of the selected site and the
assumed configuration.
The result of the described process is the energy
production estimation for the analyzed typologies of PV
plants.
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4. VIII. PERFORMANCE ANALYSIS OF DIFFERENT PLANT
CONFIGURATIONS
On the basis of the choice of a reference configuration
of the PV plant’s components and the grounding-placing
layouts, detailed energy assessments have been carried
out for different climatic conditions. The reference
configuration is characterized by a 6.3 kWp plant which
consists in 30 modules (each of 210 Wp), one single-
phase inverter and cables and connectors on DC side.
The chosen pick represents roughly the maximum peak
power connectable to a single-phase inverter. As
previously said, technological components have been
selected among those with higher efficiency, compared to
the available alternatives on the market. In particular,
regarding the PV modules, the choice fell on SANYO
HIP-210 NHE5, with a peak power of 210 Wp.
With regard to the DC/AC converter, a POWER-ONE
OUT PVI-6000 inverter has been selected. This unit has a
rated power and an MPPT voltage range suitable for the
chosen modules configuration. Moreover, due to the lack
of isolation transformer and the presence of two separate
MPPT, it is capable to achieve high conversion
efficiencies of about 98%.
The performances associated to different spatial
variations and tracking logics were evaluated for the three
different representative climates sites. Table II shows the
results of energy performance for different configurations
of PV plant.
TABLE II
PR VALUES AND SPECIFIC ENERGY PRODUCTION
Site Plant type ψψψψ γγγγ
H on
modules
surface
PR
Energy
production
° ° kWh/m2
% kWh/kWp
Fixed 30 0 1333 80.9 1114
1 axis E-O variable 0 1396 81.3 1170
1 axis N-S 0 variable 1556 82.2 1311
1 axis N-S
tilted
30 variable 1661 82.6 1407
Milan
2 axis variable variable 1703 82.8 1445
Fixed 30 0 1693 81 1414
1 axis E-O variable 0 1807 81.5 1514
1 axis N-S 0 variable 2035 82.3 1712
1 axis N-S
tilted
30 variable 2190 82.6 1850
Rome
2 axis variable variable 2249 82.8 1920
Fixed 30 0 1813 80.7 1509
1 axis E-O variable 0 1936 81.1 1614
1 axis N-S 0 variable 2228 82.1 1867
1 axis N-S
tilted
30 variable 2370 82.3 1989
Palermo
2 axis variable variable 2427 82.4 2062
Analyzing the obtained results, following observations
can be made:
- PR increases for tracking configurations compared
to fixed ones, independently from the plant location;
- for tracking configurations, irradiation on the
modules surface and hence the productivity increase
more in southern locations, if compared with the
reference case. In facts, by moving towards South,
the ratio of beam and total available radiation is
higher than the North. In detail, in Milan the
average annual beam radiation is approximately
59% of the total, while in Palermo this ratio is
approximately 70% [7];
- the difference in productivity among various
specific configurations increases while decreasing
site latitude, in a proportional way to global
irradiation level;
- the maximum achievable enhancement with
tracking systems, compared to fixed ones, is
observed in Palermo, with values ranging between
7% for tracking systems with one-axis parallel to
north-south direction, and 37% for two-axis
systems.;
- biaxial configurations are always characterized by
highest energy production;
- the productivity of a biaxial configuration located in
Milan is higher than that of a fixed one placed in
Rome, and almost similar to the one generated by
fixed configuration placed in Palermo. As a
consequence, tracking systems could make more
productive a plant located in a place characterized
by low solar irradiation in comparison to a fixed
plant located in a higher solar irradiation climatic
zone.
Obtained results agree with literature data [8], which
confirms a maximum achievable performance
enhancement due to solar biaxial trackers placed in south
Europe ranging from 25% to 45%.
IX. COSTS ANALYSIS
In order to provide a complete evaluation about the
profitability of the described hypothesis, a market survey
was performed through some National System Integrators
[9] involved in turnkey PV systems implementation.
The first phase was useful to identify cost ranges for
each main category identified on the basis of market
prices of the various components. In addition, different
average cost impact was detected, in relation to
installation design and accessories for each plant type.
The total plant cost of each case, in fact, is determined by
both the variation of the market costs of component and
labour, but also by the contribution of each item on the
total cost. For example, in the configurations with
tracking system, the installation cost, expressed in €/kWp,
is on average higher than that of fixed installations.
Once determined the initial investment costs, it was
also necessary to quantify the costs of annual
management, maintenance and insurance.
Obtained results are summarized in the table below.
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5. TABLE III
AVERAGE CAPITAL COST AND ANNUAL MANAGEMENT, MAINTENANCE
AND INSURANCE COSTS FOR DIFFERENT PLANT TYPES
Fixed
1 axis
E-O
1 axis
N-S
1 axis N-
S tilted
2 axis
Specific
cost
€/kWp 5500 6000 6000 6500 7000
Total cost € 34650 37800 37800 40950 44100
Annual
costs
€/year 500 550 570 600 660
X. PROFITABILITY ANALYSIS
In order to precisely determine the suitability of
different hypotheses analyzed, taking into consideration
the impact of the cost due to maintenance of service
charges / insurance, compared with revenues generated
from the plant operation, an economic analysis has been
carried out by determining IRR (Internal Rate of Return).
The IRR is a capital budgeting metric also called
discounted cash flow rate of return (DCFROR) or rate of
return (ROR). It is an indicator of the efficiency or
quality of an investment, as opposed to net present value
(NPV), which indicates only the value or magnitude.
The IRR is the annualized effective compounded
return rate, which can be earned on the invested capital,
i.e., the yield on the investment. Put another way, the
internal rate of return for an investment is the discount
rate that makes the net present value of the investment's
income stream total to zero. Given a collection of pairs
(time, cash flow) involved in a project, the internal rate of
return follows from the net present value as a function of
the rate of return. A rate of return for which this function
is zero is an internal rate of return.
So, once defined the NPV value according to the
following formula:
¦
+
+−=
=
N
t
t
j
r
F
TCNPV
1 )1(
where:
TC is the total capital cost of the analyzed PV plant.
F is the annual cash flow, including incomes generated
both by the feed-in tariff and the energy trading with the
national electric grid.
t represents the analyzed year; it can varies from 1 (that is
the first working year of the plant) and N (corresponding
to the end of the PV modules’ warranty period, provided
by the manufacturer).
IRR is the r value by which NPV=0.
The reference conditions adopted in the analysis are listed
below:
- plant size: 6.3 kWp;
- feed-in tariff: 0.372 €/kWh (valid if the plant starts
working before 12/31/2009 [10]);
- yearly performance degradation coefficient: -0.5 %;
- tariff for the electricity sold to the grid: 0.98
€/kWh.;
- average increment in yearly electricity cost: 3 %;
- plant working life: 25 years.
Figure 2 summarize the obtained results for different
configurations.
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
12,00%
14,00%
Fixed 1 axis E-O 1 axis N-S 1 axis N-S
tilted
2 axis
Milan Rome Palermo
Fig. 2. IRR calculated for different location and plant
configurations
Observing reported data it is possible to assert that PV
plant with tracking system and N-S horizontal axis is the
one characterized by highest IRR in all the considered
climatic conditions, obtained values between 6.5%
(Milan) and 12% (Palermo). The second most profitable
ground-mounting configuration is the one with N-S tilted
axis tracking system, with IRR values very similar to the
first one. Configurations with lowest profitability, equal
to 4.9% in Milan and 9.6% in Palermo, are the ones
characterized by one E-O horizontal axis.
XI. CONCLUSIONS
According to obtained estimations, it is possible to
conclude that climatic context is not the main influence
factor on plants profitability. For example, a N-S singular
axis PV plant located in Rome, after 25 years working
life results more affordable than a fixed or an E-O axis
plant placed in Palermo, and generates almost the same
IRR than a two-axis installation situated in Palermo.
As a matter of fact, the biaxial configuration, always
characterized by the highest productivity, is not the most
economically profitable. N-S one-axis tracking systems,
despite lower specific energy production for each kWp,
resulted the best choice among all analysed locations
because of the lower capital and O&M costs.
On the contrary, tracking strategies are not always the
best choice under economical points of view. For
example, a fixed plant placed in Palermo guarantees
roughly the same profitability than a two-axis plant in
Rome.
The analysis carried out in the present work represents
just a first step for the designing of PV Plants, and further
examinations have to be carried out on large-scale ground
mounted PV central plants, evaluating shadowing
influence, ground costs and analyzing different
technological components.
169

6. REFERENCES
[1] A Jäger-Waldau. Photovoltaics Status Report 2008. JRC
2008.
[2] F.Asdrubali, G.Baldinelli, Analisi tecnico economica di
impianti fotovoltaici dotati di dispositivi ad inseguimento
solare, 2007, 62° Congresso Nazionale ATI.
[3] D. Chianese, Direct performance comparison of PV
modules, 22nd
EPVSEC, Milano, 2007 e N.Cereghetti,
Rapporto analisi sperimentale in condizioni outdoor di
moduli, SUPSI – DACD – ISAAC.
[4] METEOTEST, METEONORM meteorological reference,
www.meteonorm.com.
[5] Joint Research Centre - JRC - European Commission,
www.jrc.ec.europa.eu.
[6] PVSyst 4.3, developed by the University Center for the
Study of Energy Problems of Geneva.
[7] UNI 10349, Riscaldamento degli edifici - dati climatici.
[8] PV Potential Estimation Utility developed by the Joint
Research Center of the European Commission.
[9] Enerquos S.p.A., Solon S.p.A., Sunpower Corporation,
Enerpoint S.r.l..
[10] DECRETO 19/02/2007, Criteri e modalità per incentivare
la produzione di energia elettrica mediante conversione
fotovoltaica della fonte solare, in attuazione dell'articolo 7
del decreto legislativo 29 dicembre 2003, n. 387.
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