energies

Article
Economic Analysis of a Photovoltaic System:
A Resource for Residential Households
Federica Cucchiella, Idiano D’Adamo * and Massimo Gastaldi
Department of Industrial and Information Engineering and Economics, University of L’Aquila,
Via G. Gronchi 18, 67100 L’Aquila, Italy; federica.cucchiella@univaq.it (F.C.); massimo.gastaldi@univaq.it (M.G.)
* Correspondence: idiano.dadamo@univaq.it; Tel.: +39-0862-434-464

Academic Editor: Jayanta Deb Mondol

Received: 28 March 2017; Accepted: 11 June 2017; Published: 15 June 2017

Abstract: New installed annual solar photovoltaic (PV) capacity was equal to 76.1 GW in 2016
(+49%), reaching the total of 305 GW around the world. PV sources are able to achieve a greater
energy independence, to tackle the climate change and to promote economic opportunities. This work
proposes an economic analysis based on well-known indicators: Net Present Value (NPV), Discounted
Payback Time (DPBT) and Levelized Cost of Electricity (LCOE). Several case studies are evaluated for
residential households. They are based on three critical variables: plant size (1, 2, 3, 4, 5 and
6 kW), levels of insolation (1350, 1450 and 1550 kWh/(m2 ×y)) and share of self-consumption
(30%, 40% and 50%). The profitability is verified in all case studies examined in this work. The role of
self-consumption, that is the harmonization between demanded and produced energy, is strategic
in a mature market to improve financial performance. A sensitivity analysis, based on both
electricity purchase and sales prices (critical variables), confirms these positive results. The Reduction
in the Emissions of Carbon Dioxide (ERcd ) signifies an environmental improvement when a PV
system is used as an alternative to a mix of fossil fuels. Finally, a policy proposal is examined based
on a fiscal deduction of 50% fixing the period of deduction equal to 5 years.

Keywords: economic analysis; energy; photovoltaic; residential sector; sustainability

1. Introduction
The Energy Union Framework Strategy set out the ambition to move away from an economy
dependent on fossil fuels [1]. The share of renewables reached 16.7% of the gross final energy
consumption of the European Union in 2015 (this indicator is equal to 20% in the Europe 2020
strategy). Furthermore, European countries agreed on a new 2030 Framework on climate and energy,
in which is defined to reach at least 27% by 2030 [2].
The widespread development of renewable energy sources (RESs) is mainly driven by the aim
to contrast the climate change and the reduction of greenhouse gas (GHG) emissions, in addition
to the reduction of energy dependency that characterizes most European countries [3–5]. RESs play
a key-role in the transition towards a low-carbon economy and are guided by sustainable principles [6].
The sustainability of PV source is a popular topic in literature [7,8] and the growth of this resource
is impressive in the last years. Global solar power market grew by about 49% to around 76.1 GW
in 2016, from about 51.2 GW in 2015 in according to data provided by Solar Power Europe. China (45%),
US (19%) and Japan (11%) represent three quarters of this installed power capacity. European countries
present, on the other hand, a value equal to 6.9 GW, with a 20% decrease compared to the 8.6 GW
installed in 2015 (Table 1). Germany and Italy occupy the third and the fifth position in the ranking of
cumulative installed capacity in 2016, respectively. Italy is one of the leading countries in the world
in which solar energy contributes largely to the national energetic demand [9]. However, the power
installed capacity in 2016 is very low (1%) compared with that installed in China.

Energies 2017, 10, 814; doi:10.3390/en10060814 www.mdpi.com/journal/energies

Energies 2017, 10, 814 2 of 15

Table 1. Top five countries—installed PV.

Countries Power Installed in 2016 1 % Total of 2016 Countries Cumulative Power Installed % Total
China 34.2 GW 45 China 77.7 GW 1,2 25
US 14 GW 19 Japan 43.0 GW 1,2 14
Japan 8.6 GW 11 Germany 40.9. GW 3 13
Europe 6.9 GW 9 USA 39.6 GW 1,2 13
India 4.5 GW 6 Italy 19.3 GW 4 6
Other 7.9 GW 10 Other 84.5 GW 29
Total 76.1 GW 100 Total 305 GW 1,2,3,4 100
1 Solar Power Europe; 2 IEA-PVPS; 3 Fraunhofer ISE (1.2 GW); 4 Anie Rinnovabili (370 MW).

The development of the PV sector is linked to subsidies. They are strategic in developing
markets [10,11] and the share of self-consumption becomes relevant in mature markets [12,13].
The next years will be characterized by an integration of PV installations in urban areas with
the development of models of distributed generation increasing numbers of prosumers (consumers
are also producers) [14,15]. The impacts of climate change, the increasing demand for energy and
the diminishing fossil fuel resources have favoured the development of PV technologies in building
applications [16]. Economic assessment and policy implications need to be evaluated [17] and the role
of residential sector investigated in PV market without subsidies [18]. These assessments required also
the definition of environmental improvements [19].
The literature on investment decisions shows whether to make an investment or not [20].
NPV, DPBT, Internal Rate of Return (IRR), Benefit to Cost Ratio (B/C) and LCOE are the indicators
typically used in the PV context [21]. NPV and DPBT are basically used to evaluate residential PV
systems [18], IRR can cause conflicting answers (multiple IRR can occur) when compared to NPV
in mutually exclusive investments [22], B/C permits to translate environmental impacts in economic
terms [23] and LCOE is typically used to compare the cost of the energy obtained from different
sources [24]. The grid parity is obtained when the solar PV LCOE is comparable with conventional
technologies grid electricity prices [13]. The International Energy Agency Report 2015 (projected costs
of generating electricity) defines that the costs of generating electricity vary in according to both market
conditions and operative conditions of the use of individual technologies. Consequently, it is not
possible to define that a technology is the cheapest in different case studies (Table 2).

Table 2. Projected costs of generating electricity.

LCOE (€/kWh) Min 1 Max 1

Italy
Solar PV Residential 0.15 0.24
Solar PV Commercial 0.13 0.20
Solar PV Large 0.11 0.16
On Shore Wind 0.07 0.10
Smally Hydro 0.12 0.19
Biogas 0.20 0.26
Solid Biomass 0.27 0.32
Solid Waste Incineration 0.15 0.19
Geothermal 0.06 0.09
Natural Gas CCGT 0.09 0.09
OECD Countries
Solar PV Residential 0.09 0.34
Solar PV Commercial 0.05 0.21
Solar PV Large 0.05 0.27
On Shore Wind 0.03 0.20
Off Shore Wind 0.09 0.30
Natural Gas CCGT 0.06 0.13
Coal 0.06 0.11
1 International Energy Agency–2015 Edition. Conversion factor: 1$ = 0.93€.
Energies 2017, 10, 814 3 of 15

The sustainability of a PV system is defined also by estimation of the energy and environmental
performances. A previous analysis has quantified these values for Italian context: Energy Payback
Time (EPBT) is equal to 2.4–3.0 years, Greenhouse Gas Payback Time (GPBT) is equal to 2.5–3.2 years,
Energy Return on Investment (EROI) is equal to 6.2–7.9 and Greenhouse Gas Return on Investment
is equal to 5.8–7.5 [25]. ERcd permits a comparison between PV source and a mix of fossil fuels [18].
This paper evaluates the profitability of a photovoltaic system for residential households.
Discounted Cash Flow (DCF), a well-known methodology, is proposed and three indicators are used:
NPV, DPBT and LCOE. The analysis is applied to several case studies that depend on three critical
variables: (i) plant size; (ii) levels of solar irradiation and (iii) share of self-consumption. Furthermore,
alternative values of both electricity purchase and sales price are considered in according to
modifications that will characterize the Italian energy bill. The work is completed by an environmental
evaluation through the calculation of ERcd and is defined a policy proposal with relative economic
advantageous for consumers.
The paper is organised as follows: Section 2 presents the methodology used in this paper and
an economic model is defined to evaluate the profitability of PV system in households. Results in terms
of NPV and DPBT are proposed in Section 3 and a sensitivity analysis is conducted in Section 4. Finally,
Section 5 proposes a discussion of the results and Section 6 presents some concluding remarks.

2. Materials and Methods

DCF is a valuation method used to estimate the profitability of an investment opportunity.
The determination of an investment’s cash flows is based on the incremental approach and
an appropriate discount rate is used to aggregate cash flows. This method considers only cash
inflows and outflows [12,26]. NPV, DPBT and LCOE are three financial typically used indicators.
The first is defined as the sum of present values of individual cash flows, the second represents
the number of years needed to balance cumulative discounted cash flows and the initial investment
and the third ascribes all future costs to the present value, resulting in a present price per unit energy
value [27–29]. NPV does not consider the size of the plant and consequently the ratio between NPV
and size of PV system is also used.
Italy is a PV mature market, in which subsidies, such as Feed-in-Premium or Feed-in-Tariff, are no
longer provided. The Italian Council of Ministers has approved a 50% tax deduction (compared to
the usual 36%) for PV systems used to produce electricity for self-consumption and not for commercial
purposes. The deduction is divided into ten equal yearly amounts. Furthermore, the Net Metering
Service is provided by Gestore Servizi Energetici (GSE), which is the institutional actor responsible for
the control of renewable energies plants. It regulates the electricity generated by a consumer/producer
in an eligible on-site plant and injected into the grid and the share extracted from the grid [10,18].
Three items typically characterize cash inflows: (i) fiscal deduction; (ii) saving energy through
internal consumption and (iii) selling energy not used for internal consumption. The first item
produces a reduction in the taxable costs in the income statement, while the second in the energy bill.
Consequently, they are costs with negative value and so can be interpreted as revenues in according
to approach used by [18,30]. In this paper the purchase price of electricity (that will be evaluated
as savings using the PV system) is calculated using market data and the sale of energy is evaluated
by increasing the energy price produced and sold to the grid of a certain delta in accordance with
a previous paper [31]. Investment costs are the main item of cash outflows, but are characterized
by a great reduction in the last years (was equal to 4500 €/kW in residential sector in 2010) [12].
The amount of energy produced is calculated with the approach used by Cucchiella et al. [23].
The mathematical reference model, for the calculation of NPV, DPBT and LCOE, is reported below:

NPV = DCI − DCO (1)

DPBT
t
∑ (CIt − COt )/(1 + r) = 0 (2)
t=0
Energies 2017, 10, 814 4 of 15

N
LCOE = DCO/ ∑ EOut,t (3)
t=1

N NTaxD
ωself,c × EOut,t × pct + ωsold × EOut,t × pst
∑ ∑ (Cinv /NTaxD ) × TaxDu−sr /(1 + r)t


DCI = t +
t=1 (1 + r) t=1
(4)
pct+1 = pct × (1 + infel ); pst+1 = pst × (1 + infel ) (5)
Ndebt −1
∑ Cinv /Ndebt + (Cinv − Clcs,t ) × rd /(1 + r)t


DCO =
t=0
N P ×C ×(1+inf)+P
Cass ×Cinv ×(1+inf)+SPel,t ×PCtax (6)
+ ∑ Cm inv

t=1 (1+r)t
PCi ×Cinv
+ + Cae
(1+r)10

Cinv = Cinv,unit × (1 + Vat) × Pf × ηf (7)

EOut,t = tr × Kf × ηm × ηbos × Acell × Pf × ηf (8)

EOut,t+1 = EOut,t × (1 − dEf ) (9)

N
EOut = ∑ Eout,t (10)
t=1

where DCI = discounted cash inflows; DCO = discounted cash outflows; t = single period;
CI = cash inflows; CO = cash outflows; EOut = energy output of the system; Cinv = total investment
cost; Clcs = loan capital share cost; SPel = sale of energy; ηf = number of PV modules to be installed
and Pf = nominal power of a PV module. Other economic inputs, used in this analysis, are defined
in Table 3.
In particular, it is paid a price of 10.9 cent €/kWh compared to 9.8 cent€/kWh for plants
that annually feed in the grid a net amount of electricity below the reference value of 3750 kWh.
The feasibility of solar systems varies significantly due to the changes in all parameters involved
in the economic evaluation [32]. Several case studies are proposed in this paper in according to
the combinations of the following variables:

• plant size, in which values that typically characterize the residential sector are selected [33].
Starting with an initial size equal to 3 kW and 6 kW, six plant sizes (1, 2, 3, 4, 5 and 6 kW)
are considered.
• levels of solar irradiation, in which Italy presents several insolation levels due to its geographical
conformation. Three values are considered for each area of the country [23]. In fact, a northern
region (1350 kWh/m2 ×y in Lombardia), a central region (1450 kWh/m2 ×y in Abruzzo) and
a southern region (1550 kWh/m2 ×y in Puglia) are evaluated.
• share of self-consumption, that varies in function of consumers’ use [12]. Three different values
(30%, 40% and 50%) are hypothesized.

Furthermore, the choice concerning these variables is coherent with the survey conducted among
several business operators [18].
From an environmental perspective, the life cycle analysis of GHG emissions from electricity
technologies presents a wide range: natural gas 290–930 gCO2 eq/kWh, oil 510–1170 gCO2 eq/kWh, coal
675–1689 gCO2 eq/kWh and photovoltaic 5–92 gCO2 eq/kWh [34]. ERcd is calculated as the difference
between emissions released by a mix of fossil fuels (EFF cd ) and ones produced by PV source (Ecd ),
PV

when is used a PV system in alternative to fossil fuels. This reduction is linked to the amount of energy
produced (EOut ):
ERcd,unit = EFFcd − Ecd
PV
(11)
Energies 2017, 10, 814 5 of 15

N  
ERcd = ∑ EFF PV
cd − Ecd × EOut,t (12)
t=1

A previous analysis has estimated the following emissions for an Italian case study:
EFF
cd = 776 gCO2 eq/kWh (considering a mix of 45% oil, 44% natural gas and 11% coal) and
EPV
cd = 49 gCO2 eq/kWh. Consequently, the reduction in the emissions can be estimated equal to
727 gCO2 eq/kWh using a PV system alternatively to fossil sources [18].

Table 3. Economic inputs [10,18].

Acronym Variable Value

Acell Active surface 7 m2 /kWp
Administrative and electrical connection
Cae 250 €
cost
Cinv,unit Specific investment cost 1900 €/kW
dEf Decreased efficiency of a system 0.7%
inf Rate of inflation 2%
infel Rate of energy inflation 1.5%
kf Optimum angle of tilt 1.13
N Lifetime of a PV system 20 y
Ndebt Period of loan 15 y
NTaxD Period of tax deduction 10 y
ηbos Balance of system efficiency 85%
ηm Module efficiency 16%
pc Electricity purchase price 19 cent €/kWh
ps Electricity sales price 9.8–10.9 cent €/kWh
PCass Percentage of assurance cost 0.4%
PCi Percentage of inverter cost 15%
PCm Percentage of maintenance cost 1%
PCtax Percentage of taxes cost 43.5%
r Opportunity cost of capital 5%
rd Interest rate on a loan 3%
tr Average annual insolation 1350–1550 kWh/(m2 ×y)
S Size 1–6 kW
TaxDu-br Specific tax deduction (baseline rate) 36%
TaxDu-sr Specific tax deduction (subsidized rate) 50%
ωself,c Percentage of energy self-consumption 30–50%
ωsold Percentage of the produced energy sold 50–70%
Vat Value added tax 10%

3. Results
Citizens’ awareness of environmental issues has increased sharply in the last years. They want
to apply solutions to the changes of ecosystems. However, a citizen is also an investor and
consequently, the economic feasibility must be evaluated. In this paper fifty-four case studies
are proposed. They depend by the combinations of the following variables: six plants size, three
levels of solar irradiation and three different share of self-consumption. NPV, NPV/Size, DPBT and
LCOE are calculated for each case study in Tables 4–7, respectively.

Table 4. Net Present Value (€) of small-scale photovoltaic systems.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 265 781 1296 1623 1809 2843
Lombardia 40% 492 1234 1977 2719 3171 4203
50% 719 1688 2657 3626 4595 5318
Energies 2017, 10, 814 6 of 15

Table 4. Cont.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 428 1106 1783 2128 2583 3817
Abruzzo 40% 671 1593 2514 3435 3949 5278
50% 915 2080 3245 4409 5490 6373
30% 590 1430 2270 2650 3356 4791
Puglia 40% 850 1951 3051 4013 4751 6353
50% 1111 2471 3832 5193 6362 7471

Table 5. Net Present Value/Size (€/kW) of small-scale photovoltaic systems.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 265 391 432 406 362 474
Lombardia 40% 492 617 659 680 634 701
50% 719 844 886 907 919 886
30% 428 553 594 532 517 636
Abruzzo 40% 671 797 838 859 790 880
50% 915 1040 1082 1102 1098 1062
30% 590 715 757 663 671 799
Puglia 40% 850 976 1017 1003 950 1059
50% 1111 1236 1277 1298 1272 1245

Table 6. Discounted Payback Time (years) of small-scale photovoltaic systems.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 16 7 6 7 7 6
Lombardia 40% 8 6 5 5 5 5
50% 6 5 4 4 4 4
30% 14 6 5 6 5 5
Abruzzo 40% 7 5 4 4 4 4
50% 6 4 4 3 4 3
30% 7 5 5 5 5 5
Puglia 40% 6 4 4 4 4 4
50% 5 4 3 3 3 3

Table 7. Levelized cost of electricity (€/kWh) of small-scale photovoltaic systems.

Plant Size
Region
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
Lombardia 0.12 0.11 0.11 0.11 0.11 0.11
Abruzzo 0.11 0.10 0.10 0.10 0.10 0.10
Puglia 0.10 0.10 0.10 0.10 0.10 0.10

The profitability is always verified. This work proposes a quantitative analysis and the financial
feasibility varies in function of several variables. The maximum value is equal to 1298 €/kW in 4 kW
plant located in Puglia with a self-consumption of 50% and the minimum value is equal to 265 €/kW
in 1 kW plant situated in Lombardia with a self-consumption of 30%.
The southern regions have more benefits than northern ones, as they enjoy greater levels of
insolation and consequently, the financial indicator presents a better performance [23]. The average
value of NPV/Size is equal to 626 €/kW in Lombardia considering eighteen scenarios of this region.
The increase is equal to 174 €/kW when is evaluated a territory with a level of insolation greater
Energies 2017, 10, 814 7 of 15

than 100 kWh/(m2 ×y). In fact, the average value of NPV/Size is equal to 800 €/kW and 972 €/kW
in Abruzzo and Puglia, respectively.
The literature has defined also as the self-consumption is the critical variable that influences
the profitability or less of a PV system in a mature market without subsidies [12,13]. Consumers
can try to match own consumption with peaks of production solar, but not always this is possible.
For example, work commitments or health visits can be valid obstacles to this aim. Consequently,
the use of intelligent machinery and/or battery storage is a valid solution [35,36]. The average value
of NPV/Size is equal to 543 €/kW, 804 €/kW and 1050 €/kW, when are considered eighteen scenarios
with a self-consumption of 30%, 40% and 50%, respectively.
The optimal configuration of plant size is well described in literature and it depends by the final
purpose (technical, environmental, economic or a mix of them) [23,37]. The average value of
NPV/size ranges:

• from 671 € per kW installed for the 1 kW plant

• to 860 € per kW installed for the 6 kW plant

Considering for each the respective nine case studies. The unitary cost of investment is the same
for all sizes analysed and consequently NPV increases with the size of the plant. However, this is not
always verified due to the reduction of the sale price of energy. For example, a 4 kW plant is more
profitable than a 5 kW one in seven of nine case studies.
The DPBT results are coherent with the NPV ones. In fact, the profitability is always verified.
In the worse scenario, the investor defines the cut-off period equal to the lifetime of the plant and
consequently, a DPBT > 20 defines that the investment cannot be recovered within this period.
DPBT is equal to 3 years in six case studies, but generally presents interesting values. In fact, it is equal
to 4 years and 5 years in seventeen and fifteen case studies, respectively. The choice of third-party
funds permits to distribute the investment cost over the years instead to place it in the year zero.
NPV and DPBT define the profitability of a PV system considering both discounted cash inflows
and outflows, while LCOE is able not to provide the same result. However, LCOE results obtained
in this work are very interesting. They are equal to 0.10–0.11 €/kWh (only 1 kW plant with
1350 kWh/(m2 ×y) is 0.12 €/kWh). This range is lower than minimal value proposed in Table 2
concerning Italy (0.15 €/kWh) and is similar to one calculated for OECD countries (0.09 €/kWh).
In according to existing literature, the reduction of PV investment costs has pushed this technology
towards greater competitiveness [21,24]. A comparison with values of other technologies proposed
in Table 2 confirms this evaluation.
A useful tool is represented by the analysis of the distribution of discounted cash inflows (Table 8)
and discounted cash outflows (Table 9). In these tables are reported the average values among six sizes
analysed. The main item of revenues is represented by the selling of energy only when is evaluated
the scenario with the share of energy self-consumption equal to 30%. Previous analysis have defined as
the avoided cost in energy bill is the main item in correspondence of 35% and 32% of self-consumption
for a 3 kW and 6 kW plants, respectively [18]. Also, in this work the saving energy through internal
consumption is equal to 44–45% in scenario with self-consumption of 40% that is greater than 33–34%.
This last value is the percentage of revenues produced by selling of electricity. The difference increases
when is evaluated a self-consumption equal to 50% (52–54% as avoided cost in energy bill and 26%
as selling of energy). Furthermore, these two items are cash flows for all lifetime of the plant, while
the fiscal deduction is verified only during the first ten years. Its contribution is relevant and equal
to 20–24%. As highlighted in Section 2, the investment cost is the main expenditure item (62–66%).
Maintenance cost is the greater among operative ones (16–17%) and the replacement of inverter during
the tenth year has a relevant impact on this item. The variation of self-consumption has not a direct
impact on operative costs, but an increase of electricity self-consumption determines also a reduction
in sold electricity and also the taxes cost are reduced. For this motive, the item “other operative costs”
is characterized by lower percentages when is increased the share of self-consumption.
Energies 2017, 10, 814 8 of 15

Table 8. Distribution of discounted cash inflows.

Saving Energy through Sale of Energy not for

Region Self-Consumption Fiscal Deductions
Internal Consumption Internal Consumption
30% 24% 35% 41%
Lombardia 40% 23% 44% 33%
50% 22% 52% 26%
30% 23% 35% 42%
Abruzzo 40% 21% 45% 34%
50% 21% 53% 26%
30% 22% 36% 42%
Puglia 40% 21% 45% 34%
50% 20% 54% 26%

Table 9. Distribution of discounted cash outflows.

Region Self-Consumption Investment Costs Maintenance Costs Other Operative Costs

30% 64% 16% 20%
Lombardia 40% 65% 17% 18%
50% 66% 17% 17%
30% 63% 16% 21%
Abruzzo 40% 64% 16% 20%
50% 66% 17% 17%
30% 62% 16% 22%
Puglia 40% 64% 16% 20%
50% 65% 17% 18%

4. Sensitivity Analysis
NPV results are based on the assumptions of a set of input variables. Hence, variance of
the expected NPV could occur. This limitation can be overcome by implementing a sensitivity
analysis on the critical variables [31,38]. The new electricity tariff will produce changes on two critical
variables examined in previous works [12,18]. The first is the annual electricity purchase price that
assesses the reduction of energy costs reported in electricity bill. An increase of this value is a positive
scenario for investors. Variations are proposed in the range of about 1–2 cent €/kWh, both in positive
and negative terms. Consequently for each plant size are evaluated the following four alternative
scenarios: pc++ (pc = 21 cent €/kWh); pc+ (pc = 20 cent €/kWh); pc− (pc = 18 cent €/kWh) and pc−−
(pc = 17 cent €/kWh) with an initial value of pc equal to 19 cent €/kWh—Table 10.

Table 10. Sensitivity analysis electricity purchase price-Net Present Value/Size (€/kW).

1 kW 2 kW 3 kW
Self-Consumption
pc++ pc+ pc− pc−− pc++ pc+ pc− pc−− pc++ pc+ pc− pc−−
Lombardia
30% 388 327 204 143 513 452 329 268 555 493 371 310
40% 656 574 410 329 781 699 536 454 822 741 577 495
50% 923 821 617 515 1049 946 742 640 1090 988 783 681
Abruzzo
30% 559 494 362 296 685 619 487 421 726 660 529 463
40% 847 759 584 496 972 884 709 621 1014 926 750 662
50% 1134 1025 805 695 1260 1150 930 821 1301 1191 972 862
Puglia
30% 731 660 520 449 856 786 645 575 898 827 686 616
40% 1038 944 757 663 1163 1070 882 788 1205 1111 923 829
50% 1345 1228 993 876 1471 1353 1119 1001 1512 1395 1160 1043
Energies 2017, 10, 814 9 of 15

Table 10. Cont.

4 kW 5 kW 6 kW
Self-Consumption
pc++ pc+ pc− pc−− pc++ pc+ pc− pc−− pc++ pc+ pc− pc−−
Lombardia
30% 528 467 344 283 484 423 301 239 596 535 413 351
40% 843 762 598 516 798 716 552 471 768 702 570 505
50% 1111 1009 804 702 1123 1021 817 715 1091 989 784 682
Abruzzo
30% 664 598 466 401 648 582 451 385 768 702 570 505
40% 1035 947 771 683 965 878 702 614 1055 968 792 704
50% 1322 1212 993 883 1317 1208 988 878 1282 1172 953 843
Puglia
30% 803 733 592 522 812 742 601 530 939 869 728 658
40% 1191 1097 910 816 1138 1044 856 763 1247 1153 965 871
50% 1533 1416 1181 1064 1507 1390 1155 1038 1480 1362 1128 1011

The second is the annual electricity sales price that assesses incomes coming from the selling of
energy not consumed. It is applied the same variation of the previous variable. Consequently for
each plant size are evaluated the following four alternative scenarios: ps++ (ps = 13 cent €/kWh);
ps+ (ps = 12 cent €/kWh); ps− (ps = 10 cent €/kWh) and ps−− (ps = 9 cent €/kWh) when is sold a net
amount of electricity lower than 3750 kWh (initial value of ps equal to 10.9 cent €/kWh). If, instead,
the reference value is greater than 3750 kWh, all prices are decreased of 1 cent€/kWh (initial value of
ps equal to 9.8 cent €/kWh) with ps++ , ps+ , ps− and ps−− equal to 12, 11, 10 and 9 cent €/kWh—Table 11.

Table 11. Sensitivity analysis electricity sales price-Net Present Value/Size (€/kW).

1 kW 2 kW 3 kW
Self-Consumption
ps++ ps+ ps− ps−− ps++ ps+ ps− ps−− ps++ ps+ ps− ps−−
Lombardia
30% 387 329 214 156 512 454 339 281 553 496 380 323
40% 595 546 448 399 720 671 573 524 762 713 615 566
50% 804 763 683 642 929 889 808 767 970 930 849 809
Abruzzo
30% 558 496 372 310 683 621 497 435 725 663 539 477
40% 782 729 624 571 907 855 749 697 949 896 791 738
50% 1006 963 876 832 1131 1088 1001 958 1173 1129 1042 999
Puglia
30% 729 663 530 464 854 788 656 590 896 830 697 631
40% 969 912 800 743 1094 1038 925 869 1135 1079 966 910
50% 1208 1162 1069 1023 1333 1287 1194 1148 1375 1328 1236 1189
4 kW 5 kW 6 kW
Self-Consumption
ps++ ps+ ps− ps−− ps++ ps+ ps− ps−− ps++ ps+ ps− ps−−
Lombardia
30% 608 514 325 231 569 475 287 192 595 537 422 364
40% 847 767 608 529 806 727 568 489 804 755 656 607
50% 1042 978 848 784 1055 990 861 796 1026 961 832 767
Abruzzo
30% 752 651 449 348 739 638 436 334 766 704 580 518
40% 1038 953 782 697 976 891 721 635 990 938 832 780
50% 1248 1179 1040 971 1245 1176 1037 968 1213 1144 1005 936
Puglia
30% 900 792 576 467 909 801 585 476 938 871 739 673
40% 1198 1107 925 833 1151 1060 877 786 1177 1121 1003 952
50% 1454 1380 1232 1158 1432 1357 1209 1135 1408 1333 1239 1111
Energies 2017, 10, 814 10 of 15

This work proposes four hundred and thirty-two alternative scenarios. They are obtained by
the combinations of six plants size, three levels of insolation and three share of self-consumption with
four values of electricity purchase price and also with four values of electricity sales price.
The profitability is verified in all scenarios taken into consideration. The maximum and minimum
values are verified in the same scenario proposed in Section 3, when the electricity purchase price
is increased/decreased of 2 cent €/kWh. They are equal to 1533 €/kW and 143 €/kW, respectively.
The aim of this section is give solidity to results obtained in previous section, while is not assigned
a probability to single alternative scenarios. This quantitative analysis offers a photography, in which
is illustrated the change of NPV in function of electricity sales and purchase prices.
An increase of about 1 cent €/kWh of electricity purchase price determines the increase of
NPV especially in case studies characterized by a greater amount of energy self-consumption.
In fact, from the perspective of levels of insolation this increase is equal to 70 €/kW in Puglia,
66 €/kW in Abruzzo and 62 €/kW in Lombardia, when is considered a self-consumption of 30%.
From the perspective of harmonization between consumption and production of energy the increase
of NPV/Size, with a level of insolation of 1550 kWh/(m2 ×y), is equal to 117 €/kW, 94 €/kW and
70 €/kW for a rate of self-consumption of 50%, 40% and 30%, respectively. These values are verified
for all sizes examined considering the model proposed in Section 2, in which the variable assumes
the same value and presents a linear relationship with relative revenues.
An increase of about 1 cent €/kWh of electricity sales price produces the increase of NPV especially
in case studies characterized by a lower amount of energy self-consumption. This increase is not
the same for all sizes analysed and it depends by two different prices of selling that change during
the lifetime of PV investment. For example, when is evaluated a 1 kW or 2 kW or 3 kW plant with
a self-consumption of 30% (reference value equal to 12 cent €/kWh) and a 6 kW plant always with
the same self-consumption (reference value equal to 11 cent €/kWh), NPV/Size increases of 64 €
per kW installed. In a 4 kW o 5 kW plant, instead, the change is equal to 108–113 €/kW.

5. Discussion
A comparison with existing literature, that analyses case studies of the same country, highlights
that the investment in PV plants is characterised by a moderate profit and a low risk. A summary
of economic values reported in literature is as follows: 716–913 €/kW [12], 1804–2386 €/kW [39],
1101–3312 €/kW [23] and (−1300)–3300 €/kW [33] for a 3 kW plant. Considering instead a 6 kW
plant, NPV/Size is equal to 565–2000 €/kW [23] and 250–2000 €/kW [33]. A review on the various PV
incentive systems has defined an average NPV equal to 9570 €/inhabitant under a feed-in premium
tariff in 2012, 5906 €/inhabitant under an all-inclusive feed-in tariff in 2013, 2065 €/inhabitant under
a 50% tax deduction in 2013 and 2380 €/inhabitant under both 50% tax deduction in 2014 with
a reduction of investment costs [40]. Also, DPBT proposes interesting values with existing literature:
3–12 years [12], 4–8 years [41] and 7–15 years [21]. The case studies proposed in this work show
that the profitability can reach very interesting values and consumers also play a key-role. In fact,
NPV is significant when an alignment between consumption and production of energy is obtained
considering furthermore the reduction of PV investment costs.
An increase of energy bill is seen with behaviour by the citizens, which is justified by the sector
operators to balance the higher costs. The components of the energy bill are several and their cost
varies in function of time bands. On the one hand, consumers’ responsibility can be enhanced making
their own economic benefits coincident with the national energy strategy. On the other hand, a country
can opt to achieve not only its energy and environmental targets, but also to play a leading role towards
establishing a model based on a circular economy. Italy has already reached the 2020-target fixed by
the European Union in terms of energy from renewables in gross final energy consumption in 2014,
but offers a great potential to reach further sustainable objectives [4].
From an environmental perspective, ERcd varies from 19.6 to 22.5 tCO2 eq per kW installed during
the whole lifetime of a PV investment (20 years)—Table 12. In fact, for example the electricity produced
Energies 2017, 10, 814 11 of 15

by a 1 kW plant in Abruzzo is equal to 1560 kWh/y. Considering a decrease of productivity during

the lifetime (see Table 3), it is possible to calculate the total energy produced by this system in 20 years.
It is equal to 28,936 kWh. Multiplying this value for the unitary reduction of emissions equal to
727 gCO2 eq/kWh–see Section 2 (electricity produced by fossil fuels replaced by one obtained by
PV systems), it is calculated the environmental indicator equal to 21 tCO2 eq.

Table 12. Reduction in the Emissions of Carbon Dioxide (tCO2 eq).

Plant Size
Region
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
Lombardia 19.6 39.2 58.8 78.3 97.9 117.5
Abruzzo 21.0 42.1 63.1 84.1 105.2 126.2
Puglia 22.5 45.0 67.5 89.9 112.4 134.9

The environmental analysis, like the economic one, depends on the assumptions of the input variables.
Alternative scenarios show the reduction in the emissions can vary from 687 to 777 gCO2 eq/kWh using
a PV system as an alternative to fossil sources [18] and consequently, the final value of ERcd is also
modified. It ranges from 18.5–20.9 tCO2 eq per kW installed in Lombardia, 19.9–22.5 tCO2 eq per kW
installed in Abruzzo and 21.3–24.0 tCO2 eq per kW installed in Puglia.
This paper verifies that the aims of environmental protection and economic profit can co-exist
investing in PV systems under the perspective of a residential consumer and the development of
RES contribute in a significant way to reach a greater energy independence, especially for a country
characterized by a low production of fossil fuels. Future research directions are aimed at improving
the diffusion of PV systems. From an environmental perspective, technological evolution can improve
the performance of these systems and reduce the emissions of manufacturing processes relative to
the production of PV system components. Also, their recycling is crucial for a perspective that
analyses the lifecycle of a product. From the economic side, the integration of PV plants with
battery storage or heat pumps permits one to increase the percentage of self-consumed energy.
PV is a policy-driven market [42]. Subsidies cannot be seen as a perpetual assistance and consequently
they are typically removed once a sector achieves maturity. Fiscal deductions are a useful policy
adopted by a government that does not cause higher costs for citizens [43]. In this direction, a previous
study has evaluated two tools to favour PV investments in the residential sector: (i) a rate of fiscal
deduction equal to 50% (instead of 36%) and (ii) a period of deduction equal to 5 years (instead of
10 years) [18].
The first point is evaluated in baseline scenario (see Table 3), while the analysis of the second point
completes this work. If the tax return of a consumer permits a reduction of this period, the revenues
are concentrated in the early years determining an increase of NPV and an improvement of DPBT.
Both are proposed in Tables 13 and 14, respectively.

Table 13. Net Present Value/Size (€/kW)—A new proposal.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 363 489 530 504 460 572
Lombardia 40% 590 715 757 778 732 799
50% 817 942 984 1005 1017 984
30% 526 651 692 630 614 734
Abruzzo 40% 769 895 936 957 888 978
50% 1013 1138 1179 1200 1196 1160
30% 688 813 855 760 769 896
Puglia 40% 948 1074 1115 1101 1048 1157
50% 1209 1334 1375 1396 1370 1343
Energies 2017, 10, 814 12 of 15

Table 14. Discounted Payback Time (years)—A new proposal.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 4 3 2 2 2 2
Lombardia 40% 3 3 2 2 2 2
50% 3 2 2 2 2 2
30% 3 3 2 2 2 2
Abruzzo 40% 3 2 2 2 2 2
50% 3 2 2 2 2 2
30% 3 2 2 2 2 2
Puglia 40% 3 2 2 2 2 2
50% 3 2 2 2 2 2

The results obtained confirm the advantages of this proposal. DPBT is equal to 2 years in forty-two
case studies and the increase of NPV is equal to 98 € per kW installed in all scenarios. This aspect
is linked to linear relationship between cash inflows and returns obtained by fiscal deduction that
is proposed in Section 2.
Finally, eco-efficiency is defined as the ratio between the (added) economic value of what has been
produced and the (added) environment impacts of the product [44]. An eco-efficiency comparison
among several energy technologies represents a future address research, but according to values
obtained in this work it is possible to estimate two possible indicators:

• Profits per unit of emissions (PREM), calculated as the ratio between NPV per unit of energy
produced and EPV cd —Table 15. For example, NPV is equal to 265 € (see Table 4) in a 1 kW
plant in Lombardia with self-consumption equal to 30% and Eout is equal to 26,941 kWh
(see Equation (10)). Dividing their ratio for EPV
cd (49 gCO2 eq/kWh—see Equation (11)) a value of
PREM equal to 201 €/tCO2 eq is obtained.
• Costs per unit of emissions (COEM), calculated as the ratio between LCOE and EPV cd —Table 16.
For example LCOE is equal to 0.12 €/kWh (see Table 7) in a 1 kW plant in Lombardia and
cd is 49 gCO2 eq/kWh (see equation (11)), so COEM is equal to 2365 €/tCO2 eq.
EPV

Table 15. Profits per unit of avoided emissions (€/tCO2 eq) of small-scale photovoltaic systems.

Plant Size
Region Self-Consumption
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
30% 201 296 327 307 274 359
Lombardia 40% 373 467 499 515 480 531
50% 545 639 671 687 696 671
30% 302 390 419 375 364 449
Abruzzo 40% 473 562 591 606 557 620
50% 645 733 763 777 774 749
30% 389 472 499 437 443 527
Puglia 40% 561 644 671 662 627 699
50% 733 815 843 857 840 822

Table 16. Costs per unit of avoided emissions (€/tCO2 eq) of small-scale photovoltaic systems.

Plant Size
Region
1 kW 2 kW 3 kW 4 kW 5 kW 6 kW
Lombardia 2365 2270 2239 2223 2214 2207
Abruzzo 2222 2134 2105 2090 2081 2075
Puglia 2098 2015 1988 1974 1966 1960
Energies 2017, 10, 814 13 of 15

6. Conclusions
Solar PV generates renewable electricity by converting energy from the Sun. Its energy
is intermittent and depends on the weather conditions. PV sources present lower levels of production
than other RESs. However, PV is a relevant player in the global electricity market as highlighted by its
notable growth in the last years all over the world. This topic is timely and multidisciplinary. This work
shows economic profits in residential sector, but also environmental advantages. Furthermore, a policy
proposal is suggested.
Several countries aim to delete or reduce subsidies given to PV systems. Business operators
can apply for a reduction of investment costs by proposing specific business plans for consumers,
but the sector is not always able to restart. Italy is an example, in fact it is fifth country globally for
installed PV capacity in 2016, but the power installed in the last years after the end of subsidies is low.
The residential sector permits all citizens to improve their quality of life in terms of reduction of
GHG emissions. Plant sizes from 1 kW to 6 kW are analysed in this work and the financial indicators are
very interesting. Certainly, they are lower than ones obtained during the subsidy period (in particular
when the incentive was given for energy produced, but also to incentives linked to the energy fed
into the grid). Actually, the profits increase significantly with an alignment between the amount of
demanded and supplied electricity.
LCOE is equal to 0.10–0.11 €/kWh and a comparison with other technologies underlines the fact
that the PV source can be competitive. Furthermore, the profitability is verified in all case studies.
In our baseline scenario, NPV ranges from 265 to 1298 €/kW and DPBT is typically equal to 3–5 years.
Sensitivity analysis, in which both electricity purchase and sales price are changed, confirms these
results. Furthermore, a policy proposal can be an attractive measure for the sector. The period of
deduction can be fixed also equal to 5 years and the unitary tax deduction is maintained equal to 50%
(NPV ranges from 363 to 1396 €/kW and DPBT is equal to 2 years). Finally, ERcd varies from 19.6 to 22.5
for each kW installed during the 20 years of useful life of the investment. The eco-efficiency indicator
(PREM) ranges from 201 to 822 €/tCO2 eq. Finally, PV investments increase the energy independence
of a country and the installations of these systems produce a positive environmental improvement and
offer economic opportunities.

Author Contributions: The authors contributed equally to this work. Federica Cucchiella performed part of
the research and finalized writing of the paper; Idiano D’Adamo performed part of the research and wrote
the draft paper and Massimo Gastaldi designed the research and analysed the data.
Conflicts of Interest: The authors declare no conflict of interest.

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