A profitability assessment of small-scale photovoltaic systems in an electricity market without subsidies

Energy Conversion and Management 129 (2016) 62–74

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A profitability assessment of small-scale photovoltaic systems in an electricity market without subsidies Federica Cucchiella ⇑, Idiano D’Adamo, Massimo Gastaldi Department of Industrial and Information Engineering and Economics, University of L’Aquila, Via G. Gronchi 18, 67100 L’Aquila, Italy

a r t i c l e

i n f o

Article history: Received 23 May 2016 Received in revised form 1 September 2016 Accepted 24 September 2016

Keywords: Economic analysis Environmental analysis Photovoltaic Residential sector

a b s t r a c t The installation of photovoltaic power plants in 2015 compared to 2014 registered a growth of 25.6%, reaching a cumulative power equal to 229 GW. In developed solar markets, as many European countries, the sector is pushed by the alignment between the electric power demanded and the one offered. Consequently, self-consumption makes consumers active players of the energy transition. Italy is evaluated as a case study in this paper, in fact is the first country in the world where solar energy contributes largely to the national energetic demand. This paper aims to evaluate photovoltaic systems in residential sector without subsidies. Economic and environmental results are proposed and the indicators used are Net Present Value, Discounted Payback Time and Reduction in the Emissions of Carbon Dioxide. Three sizes (3 kW, 6 kW and 20 kW) are evaluated. In addition, a sensitivity analysis of critical variables (investment cost, annual electricity purchase price, annual electricity sales price, opportunity cost, tax deduction unitary, period of fiscal deduction, average annual insolation and percentage of energy self-consumption) demonstrates the robustness of the economic results. Also for environmental evaluation, alternative scenarios are proposed varying the value of emissions released by source energy analysed (photovoltaic, coal, oil and gas). Economic and environmental results suggest that small-scale photovoltaic systems can support the transition towards a sustainable energy mix. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction The reduction of pollutant emissions and energy dependence on fossil fuels has driven many countries to encourage the use of renewable energy sources (RESs) with the aim to develop an economy with low carbon levels [1]. Sustainable development is a broad topic and the degradation of ecosystems is a complex challenge that requires responses based on environmental, economic and social impacts [2]. It is therefore appropriate to imagine urban areas integrated with RES installations, because in the future will be increasingly diffuse models of distributed generation characterized by increasing numbers of prosumers (consumers are also producers) [3]. The reliability and stability of electric systems is strongly influenced by the variability and non-dispatchable nature of RESs [4]. From one side conventional power system is centralized and typically transmit electricity over long distances, while from the other

⇑ Corresponding author. E-mail addresses: [email protected] (F. Cucchiella), idiano.dadamo@ univaq.it (I. D’Adamo), [email protected] (M. Gastaldi). http://dx.doi.org/10.1016/j.enconman.2016.09.075 0196-8904/Ó 2016 Elsevier Ltd. All rights reserved.

side Distributed Energy System (DES) is a decentralized more flexible technology located close to the load it serves [5]. Energy storage system (ESS) and demand side management (DSM) are two options for increased self-consumption [6]. A review on this topic has quantified the percentage increase of energy self-consumption: 10–24% with an ESS of 0.5–1 kW h per installed kW PV power and 2–15% with a DSM [7]. DES and ESS enable to collect energy from many resources representing an opportunity to reduce environmental impacts and improve supply security [8]. Moreover, a critical aspect is given by their costs that currently are very high [9]. The break-even point (BEP) of the increase of self-consumption at which residential photovoltaic (PV) battery systems become economically viable in a mature market is proposed by [10]. Distributed generation from RESs and penetration of renewables into the electric grid are playing a crucial role in the electricity energy market [11]. Smart grids could help to better integrate RESs with distribution and transmissions systems and they try to solve power’s unbalances issues and other technical problems in real time [12]. Micro-grids are a specific portion of a smart grid and they operate in order to optimize energy fluxes [13]. A new

F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74

63

Nomenclature Acell BEP bos Cae Cinv Cinv,unit Cres DCF dEf DES DPBT DSM Ecoal cd Egas cd Eoil cd EFF cd EPV cd ERcd EOut ESS FiT GHG GSE I inf infel IEA IPCC

active surface breakeven point balance of system administrative and electrical connection cost total investment cost unitary investment cost residual capital Discounted Cash Flow Decrease efficiency of system Distributed energy system Discounted Payback Time demand side management emissions released by a coal plant per unit of produced energy emissions released by a gas plant per unit of produced energy emissions released by an oil plant per unit of produced energy emissions released by fossil fuels per unit of produced energy emissions released by a photovoltaic plant per unit of produced energy reduction of carbon dioxide emissions energy output of the system energy storage system feed-in Tariff greenhouse gas Gestore Servizi Energetici discounted cash inflows rate of inflation rate of energy inflation International Energy Agency International Panel on Climate Change

methodology that resolve the problem of optimal electrical microgrids design is proposed by [14] and furthermore, the development of an innovative device, which is based on a bidirectional converter, is analysed for the interface to the supply utility grid of combined RES based generators and ESS [15]. PV is a safe energy source, clean and competitive that can contribute to sustainable growth and plays a key role in the electricity global market [16]. In a starting stage of market the profitability of PV investments is determined by subsidies [17], while in a mature market this role is determined by the harmonization of consumption with the production [18]. A review of current grid codes in some countries with high PV penetrations and their management strategies are proposed by [19]. Policy choices can be oriented towards decreasing fossil fuel subsidies and tackle other barriers to RESs [20]. In such contexts, energy policy can be evaluated with appropriate quantitative analyses and the objectives of environmental protection and economic profit can coexist investing in PV systems [21]. This work is aimed at providing economic and environmental assessments to support future decisions concerning resource PV even in countries, where government subsidies are absent. With this regard, the analysis is conducted taking as a case study Italy and evaluating specifically the residential sector, regarded as the locomotive of the future PV power installed in the world [22]. The conclusions of the work will be replicated for other national markets, since the nature of government incentives is ‘‘only” to support the development of the sector [23]. To sustain the obtained results it is proposed sensitivity analyses for both the economic and the environmental variables.

Kf LCA N Ndebt NTaxD NPV NREL

gbos gf gm

O pc pcoal pgas poil ps PCass PCi PCm PCtax Pf PV r rd RES RPS t tr TaxDunit

xself;c xsold

Vat

optimum angle of tilt life cycle analysis lifetime PV system period of loan period of tax deduction Net Present Value National Renewable Energy Laboratory bos efficiency number of PV modules to be installed module efficiency discounted cash outflows electricity purchase price percentage of coal in energy mix percentage of gas in energy mix percentage of oil in energy mix electricity sales price percentage of assurance cost percentage of inverter cost percentage of maintenance cost percentage of taxes nominal power of a PV module photovoltaic opportunity cost of capital interest rate on loan renewable energy system Renewable Portfolio Standard time of cash flow average annual insolation tax deduction unitary percentage of energy self-consumption percentage of the produced energy sold to the grid value added tax

2. Materials and methods The methodology used in this paper is based on several steps. This section proposes an overview of PV sector initially concerning the global context (Section 2.1) and then is analysed the Italian one (Section 2.2). Model assumptions and economic inputs are proposed in Section 2.3 and environmental inputs are defined in Section 2.4. Consequently, it is possible to define the aims of this paper:
Results propose economic and environmental assessments in baseline scenario (Section 3).
Sensitivity analysis (Section 4) and scenario analysis (Section 5) are applied to economic aspects in order to evaluate alternative scenarios.
Sensitivity analysis (Section 6) is applied to environmental concerns in order to evaluate alternative scenarios.
Policy implications are proposed in Section 7.
Section 8 presents concluding remarks.

2.1. The global photovoltaic sector overview The cumulative installed solar PV power capacity is equal to 229 GW in 2015. This value is very significant, compared to 41 GW in 2010. Europe accounts for the major global share at 97 GW but the Asia-Pacific countries have a similar value (96 GW) to the end of 2015. Finally America reaches 31 GW and Middle East/Africa only 3 GW [24]. 50.6 GW have been installed

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in 2015, an increase of 25.6% than 40.3 GW installed in 2014. Since 2013, countries such as China, Japan and the USA drive the growth – Table 1. Italy occupies the fifth position in the ranking of cumulative installed capacity in 2015, but it is the first country in the world where solar energy contributes largely to the national energetic demand in according to an International Energy Agency (IEA) report [25]. For this reason, Italy is here chosen as case study. Solar Power Europe analyses the main policy drivers for solar PV in 2015 and the following percentage distribution is revealed [24]:






Feed-in Tariffs (FiTs) 63.2%. Self-consumption/Net-metering 15.0%. Direct subsidies/Tax breaks 11.5%. Power Purchase Agreements 8.2%. Green-certificates/Renewable Portfolio Standards (RPSs)-based schemes 2.0%.

FiT plays a key-role in the development of the sector in China and Japan and the same action is carried out by RPSs and a 30% Investment Tax Credit in USA. These tools have favoured the development of utility-scale power plants. However, changes are planned for 2016. In fact, China has proposed a new incentive scheme. The subsidy level is kept the same as before for selfconsumed PV projects, while it is reduced for PV power plants which selling all electricity to grid. Japan has opted to limit and control growth, moving from uncapped FiTs to a tender-based system for large plants [26]. 2.2. The Italian photovoltaic sector status After a decrease of both energy production and consumption in last two years (2013 and 2014), there is a change of trend in 2015. In fact, national energy production and national energy consumption is equal to 270,703 GW h and 315,234 GW h, respectively. PV source has experienced significant growth, rising from 193 GW h in 2008 to 24,676 GW h in 2015 in according to last previsions released by Terna, which manages electricity transmission in Italy – Table 2 [27]. Table 1 Top 10 countries for installed capacity in 2015. Source [26]. Annual installed capacity (GW)

This PV production corresponds to 9.1% of national production and 7.8% of national consumption (both these values in 2008 were lower than 0.1%) in 2015. These values are estimations and so it is possible to highlight variations between definitive and estimated values (for example, PV production was considered equal to 23,299 GW h in 2014, while it is really quantified equal to 21,838 GW h [10]). After the 5th FiT scheme, which considered an all-inclusive FiT for the share of net energy injected into the grid and a premium rate on the share for net energy consumed on site, a 50% tax deduction (compared to the usual 36%) is approved by the Italian Council of Ministers for PV plants for private and small individual businesses purposes. The deduction is divided into ten equal yearly amounts. Furthermore, the Net Metering Service is provided by GSE (Gestore Servizi Energetici), 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 one withdrawn from the grid. Hence, a contribution is paid to customers basing on both injections and withdrawals of electricity in a given calendar year and on their market values (for PV plants up to 500 kW). Under simplified purchase and resale hypotheses, producers sell the electricity generated and injected into the grid to GSE at the local price or at a minimum price guaranteed on the first 2 million kW h per year. 2.3. Model assumption and economic inputs The investments profitability analyses are carried out based on Discounted Cash Flow (DCF). Net Present Value (NPV) and Discounted Payback Time (DPBT) are two indicators to assess, respectively, the profit of the investment project and the time frame in which process reaches the financial balance [28]. From the revenues side, the potential items are:
Saving energy through internal consumption.
The sale of energy not for internal consumption.
Fiscal deduction. Instead concerning the costs side, literature analysis highlights that [29]:

Cumulative installed capacity (GW)

China Japan USA UK India Germany Korea Australia France Canada

15.2 11.0 7.3 3.5 2.0 1.5 1.0 0.9 0.9 0.6

China Germany Japan USA Italy UK France Spain Australia India

43.5 39.7 34.4 25.6 18.9 8.8 6.6 5.4 5.1 5.0

Total

50.6

Total

229


Investment cost is the main item of expenditure.
Operating cost is low due to the free solar radiation and maintenance costs that are limited. The mathematical reference model, for the calculation of NPV and DPBT, is reported below and successively, economic and technical inputs, used in this analysis, are quantified in Table 3. 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

Table 2 Energy power from photovoltaic source 2008–2015 in Italy. Source [27].

a

2008

2009

2010

2011

2012

2013

2014

2015a

PV energy production (GW h) Tot energy production (TW h)

193 307.07

677 281.11

1874 290.75

10,668 291.45

18,633 287.81

21,229 278.83

21,838 269.15

24,676 270.70

% PV of tot energy production Tot energy consumption (TW h)

0.06 339.48

0.2 320.27

0.6 330.46

3.7 334.64

6.5 328.22

7.6 318.48

8.1 310.54

9.1 315.23

% PV of tot energy consumption

0.06

0.2

0.6

3.2

5.7

6.7

7.0

7.8

Estimated.

F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74


2300–2460 € per capita under both 50% tax deduction in 2014 with a reduction of investment costs.

Table 3 Economic and technical input data. Sources: [32,33]. Acronym

Value 2

Acell Cae Cinv,unit Cres dEf inf infel kf

7 m /kWp 250 € 1800***–2000*,** €/kW f (Cinv, Size, Ndebt) 0.7% 2% 1.5% 1.13 85% f (Size) 16% 20y 15y 10y

gbos gf gm

N Ndebt NTaxD * ** ***

Acronym

Value

PCass PC m PCtax Pf Pinv pct pst r rd TaxDunit tr

0.4% 1% 27.5% f (Size) 15% 19 cent €/kW h 9.8**,***–10.9*cent €/kW h 5% 3% 50% 1450 kW h/m2 y 30% 70% 10%

xself;c xsold Vat

[30]. Assumed investment costs are taken from literature sources and can be considered coherent to current market values. This approach is justified by two considerations. Similar costs are obtained in a survey conducted among a great number of firms in 2015 [31] and the reduction of investment costs in PV sector is been favoured by the value of installed power [26]. Italian PV market in 2015 is characterized by a very low value [27], not allowing operators to apply further reductions. Future scenarios will be evaluated in a survey involving business operators, which will be presented in Section 5. The amount of energy produced (EOut) is calculated with the approach used by [32].

DPBT X t¼0

It ¼

N X It  Ot t t¼0 ð1 þ rÞ

ð1Þ

It  O t ¼0 ð1 þ rÞt

ð2Þ

N X xself;c  EOut;t  pc þ xsold  EOut;t  ps t

t

ð1 þ rÞt

t¼1

þ

Cinv N TaxD X NTaxD

 TaxDunit

ð1 þ rÞt

t¼1

with

Cinv ¼ Cinv;unit  ð1 þ VatÞ  Pf  gf pctþ1 ¼ pct  ð1 þ inf el Þ

ð3Þ

pstþ1 ¼ pst  ð1 þ inf el Þ

Ot ¼

Ndebt X1 t¼0

The profitability of PV systems can vary significantly due to the changes in all parameters involved in the economic evaluation [34]. Several works propose not only baseline scenarios, but also alternative scenarios in which critical variables are changed. The results proposed in Table 4 are based on the data in the literature. NPVs are related to small-scale applications, and the ratio between NPV and size of PV plant is able to compare these values. Positive DPBT varies in a wide range in PV residential systems: 3–12 years [18], 4–8 years [35] and 7–15 years [36]. 2.4. Environmental inputs From environmental perspective, it is possible to calculate the Reduction in the Emissions of Carbon Dioxide (ERcd) from the amount of EOut on the assumption that the energy is produced using a PV system compared to the use of fossil fuels [41].

= 3 kW. = 6 kW. = 20 kW.

NPV ¼

65



Cinv Ndebt

 t

þ ðCres Þt  rd

ð 1 þ rÞ t

þ

N   X PV EFF cd  Ecd  EOut;t

with ð5Þ

Literature analysis presents a comparison of the various incentive systems with their financial feasibility [33]:
4519–5050 € per capita under feed-in premium tariff in 2012.
2756–3150 € per capita under all-inclusive feed-in tariff in 2013.
1920–2210 € per capita under 50% tax deduction in 2013.

ð6Þ

t¼1

GHG covers six categories of greenhouse gases (CO2, CH4, N2O, HFC, PFC and SF6). It is measured using the CO2 equivalent (CO2eq), a metric that compares the emissions from various GHG based upon their global warming potential. International Panel on Climate Change (IPCC) proposes aggregated results of a literature review concerning the Life Cycle Analysis (LCA) of GHG emissions from electricity generation technologies [42]: natural gas 290– 930 gCO2eq/kW h, oil 510–1170 gCO2eq/kW h, coal 675–1689 gCO2eq/kW h and photovoltaic 5–92 gCO2eq/kW h. Their mean values are used in baseline scenario: 610 gCO2eq/ kW h, 840 gCO2eq/kW h, 1182 gCO2eq/kW h and 49 gCO2eq/kW h for natural gas, oil, coal and PV, respectively. In particular, concentrating the attention towards PV source the analysis of works highlights that the range of GHG/kW h can widely varies: 15–76 gCO2eq/kW h [43], 10.5–50 gCO2eq/kW h [44] and 13–39 gCO2eq/kW h [45]. These values can be attributed to the technologies evaluated, LCA methods and relative assumptions. The National Renewable Energy Laboratory (NREL) developed and applied a systematic approach to review LCA literature. The harmonization of estimates of life cycle GHG emissions is equal to 46 gCO2eq/kW h [46]. PV systems located in Italy are considered by [47]: PV source has a range from 71 to 92 gCO2eq/kW h. These values are influenced by both the type of solar cells and the location in which the plant is installed. It is obtained a value of GHG/kW h equal to 77 gCO2eq/kW h for monocrystalline PV located in Rome considering the emissions associated with the life

N X ðPCm  Cinv  ð1 þ infÞ þ PCass  Cinv  ð1 þ infÞÞt þ xsold  EOut;t  pst  PCtax Pinv  Cinv þ Cae þ t ð1 þ rÞ ð1 þ rÞ10 t¼1

EOut;t ¼ tr  Kf  gm  gbos  Acell  Pf  gf EOut;tþ1 ¼ EOut;t  ð1  dEf Þ

ERcd ¼

ð4Þ

cycle of PV electricity production equal to 2333 kgCO2eq and the total energy output of the system during its lifetime equal to 30,436 kW h. Alternative scenarios can be evaluated as follows. From one side, 2333 kgCO2eq is proposed by [48], while a lower value is defined by [49]. Considering the emissions associated to PV system equal to 1867 kgCO2eq, the GHG/kW h become equal to 61 gCO2eq/kW h. From the other side, when the life cycle of a PV system is equal to 25 years (and not 20 years), the total energy produced is equal to 37,400 kW h and consequently, GHG/kW h become equal to 62 gCO2eq/kW h. Also other authors confirm that

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F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74

Table 4 A summary of current economic values from the literature in residential PV systems. Size (kW) 3 3 3 3 3 6 6 10 10 * **

NPV (€/kW) *

716–913 277–1810** 1804–2386* (1300)-3300** 1101–3312* 250–2000** 565–2000* 1500* (900)-4300**

Reference

Size (kW)

[18] [18] [38] [39] [32] [39] [32] [29] [29]

10 10 12 20 20 20 20 20 20

NPV (€/kW)

Reference

*

2039 1139–2938** 500–2200** 493–655* (21)-1503** 3000–5500** 2802* 2123* 1223–3022**

[37] [37] [39] [18] [18] [40] [38] [37] [37]

Baseline scenario. Alternative scenario.

solar irradiation and operating lifetime determine great changes in LCA results [50]. To calculate the carbon dioxide emissions per unit of energy produced as a result of the use of fossil fuels (EFF cd ), it is necessary on the one hand to define the single value of the emissions associgas coal ated with each source (Eoil cd ; Ecd ; Ecd ), on the other hand their

weight percentage in a hypothetical energy mix (poil ; pgas ; pcoal ) [41]. oil oil gas coal EFF þ Egas þ Ecoal cd ¼ Ecd  p cd  p cd  p

Table 5 Indicators – baseline scenario.

Energy output of PV system (kW h) Reduction in the emissions of carbon dioxide (tCO2eq) Discounted Payback Time (y) Net Present Value (€) Net Present Value (€)/kW

3 kW

6 kW

20 kW

86,808 63.1

173,617 126

578,722 421

6 1519 506

6 2620 437

4 12,476 624

ð7Þ

In order to assess the environmental benefit, this value will then be compared with emissions of carbon dioxide per unit of energy released by a photovoltaic system (EPV cd ) - see Eq. (6). Regarding the percentage of individual fossil fuels composing the portfolio of renewable energy, the 2013 Italian energy balance shows that (net of renewable and imports) the consumptions of oil, natural gas and coal amounted to 45%, 44% and 11%. These values are compared with the energy balances of the previous three years confirming the same percentage distribution [51]. The following emissions are estimated: EFF cd = 610 ⁄ 0.44 + 840 ⁄ 0.45 + 1182 ⁄ 0.11 = 776 gCO2eq/kW h EPV cd = 49 gCO2eq/kW h. Consequently, it is possible to achieve a reduction in the emissions of carbon dioxide (ERcd) equal to 727 gCO2eq/kW h using a PV system alternatively to fossil sources. 3. Results After the estimation of the values to be associated with the input variables of the model, it is possible to estimate EOut and ERcd that can be achieved using a PV system as an alternative to the use of fossil fuels. The estimates are based on a system of generation of energy characterized by the variables described in Table 3 and three plants size are analysed: 3 kW, 6 kW and 20 kW. In particular, for both a traditional system and one based on PV energy, the amount of energy produced in the entire useful life (N = 20) – estimated from Eq. (5) – it is equal to 28,936 kW h per kW installed. For example, for the plant of 3 kW, the energy produced in the first year is 4680 kW h and, due to the annual decrease efficiency of system, the energy totally produced in the lifetime is 86,808 kW h. Eq. (6) allows estimating ERcd, specifically, there is a reduction of emission of 21 tCO2eq for each kW installed (Table 5). Eq. (2) allows to estimate DPBT and the results are illustrated in Table 5. They are contained in a range between 4 and 6 years. NPV, estimated from the Eq. (1), ranges, instead, between 437 and 624 € per kW installed. 3 kW system presents results more advantageous than 6 kW one and this result is connected to the higher sale price for the energy that is recognized for systems of

3 kW. For plants that annually feed in the grid a net amount of electricity below the reference value of 3750 kW h, it is paid a price of 10.9 cent €/kW h compared to 9.8 cent €/kW h, which, however, is applied when the energy fed in grid is in the range of 3750– 25,000 kW h. At the same time, the 3 kW system achieves results under-performing compared to the system of 20 kW. The result is related to the higher cost of investment unit (+10%). The selling of energy represents the main revenue, but this result is strictly linked to the initial assumption concerning the share of energy self-consumption (equal to 30%) - Table 6. In fact, in alternative scenarios, which in detail will be analysed in the next section, saving energy through internal consumption (avoided costs in energy bill) become the main revenue. This happens with xself;c equal to 35% in 3 kW plant and 32% in both 6 kW and 20 kW plants. In baseline scenario, saving energy through internal consumption is equal to 35–37%, that become 44–47% and 53–55% in alternative scenarios with xself;c equal to 40% and 50%, respectively. Instead, the selling of energy is equal to 39–42% in baseline scenario becoming 33–34% and 24–26% respectively in two abovecited alternative scenarios. Fiscal deductions, in comparison with other two items of revenues, are present in business plan only

Table 6 Distribution of revenues (in percentage). 3 kW

6 kW

20 kW

23 35 42

25 36 39

23 37 40

Alternative scenario (xself;c = 40% and xsold = 60%) Fiscal deductions 22 Saving energy through internal consumption 44 Sale of energy not for internal consumption 34

23 46 31

21 47 32

Alternative scenario (xself;c = 50% and xsold = 50%) Fiscal deductions 21 Saving energy through internal consumption 53 Sale of energy not for internal consumption 26

22 54 24

20 55 25

Baseline scenario (xself;c = 30% and xsold = 70%) Fiscal deductions Saving energy through internal consumption Sale of energy not for internal consumption

F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74 Table 7 Distribution of costs (in percentage).

Investment Administrative and electrical connection Maintenance Assurance Taxes

3 kW

6 kW

20 kW

64 3 16 4 13

66 1 17 4 12

64 1 16 4 14





for the first 10 years (see Section 2.2), but however their value is relevant (23–25% in baseline scenario). The investment cost is the main item of expenditure (64–66%). Among the operative costs, the maintenance has the weight greater (16–17%) and this depends also by the replacement of inverter during the tenth year of useful life of PV system (see Section 2.2) equal to 6–7% - Table 7. The results show that investments in PV allow to reach two objectives, to be economically viable and at the same also pursue the objectives of environmental improvement. The reductions of emissions of carbon dioxide are, in fact, very significant and allow on one side to contribute to the achievement of greater energy independence and on the other to make more green the production of electrical energy. The analysis of the Italian market is particularly interesting since it is a mature market, in which investment costs have been reduced substantially, and there is also the absence of subsidies, making future investments less profitable. The business was initially dominated by the value of the incentive recognized to energy produced (Conto Energia IV) and then from that related to the energy fed into the grid (Conto Energia V), but, in the current market, the construction of such facilities is profitable, when there is an alignment between the amount of electric power demanded, and the one offered. Self-sufficiency plays therefore a key role to ensure that investments in PV systems result (even without incentives) economically attractive and this tends to be even more relevant in the presence of high prices charged for electricity bills [18]. The following sensitivity analysis allows to analyse the results leaving the hypothesis that from a range of variation is defined a unique value of input. It will be possible to perform a more complete analysis, which allows to evaluate scenarios in which the variables recorded assume both a positive variation and/or a negative one. 4. Economic assessments: sensitivity analysis The results are linked to the assumptions on input variables, therefore, there may be a strong variability of the expected results. This limit may be overcome proceeding with a sensitivity analysis applied to critical variables [52]. Considering PV system in a market without subsidies, a previous work has analysed the variables in residential sector and results indicate the following critical variables [10]:
Unitary investment cost (Cinv,unit), it recorded in recent years a strong reduction, therefore compared to the baseline values of 1800 and 2000 €/kW, are hypothesized two possible reductions of 5% and 10%. Additionally to these optimistic are also defined those pessimistic where it is assumed, instead, an increase in this input considering variations of 5%, 10%, +5%, +10%.
Annual electricity purchase price (pc) assesses the reduction of electrical energy costs reported in the energy bill. An increase of this variable is a positive scenario for PV investors. Variations are in the range of about 1–2 cent €/kW h, both in positive and negative terms. Given that, pc can assume values going from 17










67

up to 18 cent €/kW h (pessimistic scenarios), or 20 up to 21 cent €/kW h (optimistic scenarios). Annual electricity sales price (ps) assesses incomes from the selling of extra energy. This is similar to the previous variable and, so, it has the same variation. For example, ps (that in the baseline scenario with a 3 kW plant can be equal to 10.9 cent €/kW h, can reach values going from 9 to 10 €/kW h (pessimistic scenarios), or from 12 to 13 cent €/kW h (optimistic scenarios). Opportunity cost (r) provides a measure of performance of an alternative investment, but similar to that under consideration for risk characteristics. Given the baseline value (5%), it will be analysed with increases and decreases of 1% and 2%. Tax deduction unitary (TaxDunit), set at 50%, is the legislative support for such investments, the basic rate is in fact 36%. In addition to such a scenario, it is also verified what would happen in a scenario in which there is a reduction of the period of deduction (NTaxD - from 10 to 5 years). Average annual insolation (tr), due to the particular conformation, assumes in Italy different levels and so (compared to the baseline value of 1450 kW h/m2 y) is appropriate to proceed considering values that characterize the northern areas (minimum value approximately equal to 1300 kW h/m2 y) and southern areas (maximum value of approximately 1600 kW h/m2 y). Percentage of energy self-consumption (wself,c) measures the degree of harmonization between consumption and production of energy, in the current post-incentives, this variable is found to be decisive in the assessment of economic feasibility. Based on the consumption behaviours of investors and on their attitude to change, there are provided various scenarios with an additional increase of 10% (wself,c is equal to 0% when all the energy produced is sold and, on the contrary, is equal 100% when all the energy produced is consumed).

Consequently, it is appropriate to carry out further analysis for the three size systems considered: 3 kW (Table 8), 6 kW (Table 9) and 20 kW (Table 10). The profitability is verified in 95% of scenarios taken into consideration. Only 5 scenarios of 96 analysed present a negative NPV and it is strongly linked to the energy self-consumption level: when (i) wself,c is equal to 0% in 20 kW plant and when wself,c is equal to 0% and 10% in both 3 kW and 6 kW plants. Consequently, it is relevant to estimate their BEP (wself,c):
13% for 3 kW plant.
13% for 6 kW plant.
6% for 20 kW plant. These values are coherent with existing literature [10], in which PV systems in residential sector without subsidies are evaluated. BEP ranges from 8% to 18% in 3 kW plant and from 7% to 21% in 6 kW plant. These variations are linked to the value of average annual insolation considered in the analysis (it ranges from 1300 kW h/m2 y to 1600 kW h/m2 y). The results of the sensitivity analysis show that the plants located in the areas mostly sunny (1600 kW h/m2 y) have on average a higher NPV of about 465 € (6 kW and 20 kW plants) and 487 € (3 kW plant) for each installed kW compared to areas less irradiated (1300 kW h/m2 y). Moreover the 1% change in the opportunity cost of capital produces a variation of about 80–90 € per kW installed. Energy bill avoided costs determine an improvement in NPV of about 66 € per kW installed considering an increase equal to 1 cent €/kW h. While, when the electricity sale price is increased of about 1kW h cent €/kW h, NPV (due to avoided costs) increases of 112 € per kW installed (3 kW plant) and 121 € per kW installed

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Table 8 Sensitivity analysis – NPV for 3 kW power system. Variable

Value

NPV (€)

Variable

Value

NPV (€)

Cinv,unit

2200 €/kW 2100 €/kW 1900 €/kW 1800 €/kW 17 cent €/kW h 18 cent €/kW h 20 cent €/kW h 21 cent €/kW h 9 cent €/kW h 10 cent €/kW h 12 cent €/kW h 13 cent €/kW h 7% 6% 5% 4%

990 1254 1783 2048 1124 1321 1716 1914 942 1246 1853 2156 1093 1290 1786 2100

TaxDunit NTaxD tr

36% 5y 1300 kW h/m2 y 1375 kW h/m2 y 1525 kW h/m2 y 1600 kW h/m2 y 0% 10% 20% 40% 50% 60% 70% 80% 90% 100%

805 1828 788 1154 1884 2249 1164 268 788 2249 2980 3711 4441 5172 5863 6164

pc

ps

r

wself,c

Baseline value = 1519 €.

Table 9 Sensitivity analysis – NPV for 6 kW power system. Variable

Value

NPV (€)

Variable

Value

NPV (€)

Cinv,unit

2200 €/kW 2100 €/kW 1900 €/kW 1800 €/kW 17 cent €/kW h 18 cent €/kW h 20 cent €/kW h 21 cent €/kW h 8 cent €/kW h 9 cent €/kW h 12 cent €/kW h 13 cent €/kW h 7% 6% 5% 4%

1562 2091 3149 3678 1830 2225 3015 3410 1527 2134 3348 3955 1869 2215 3094 3651

TaxDunit NTaxD tr

36% 5y 1300 kW h/m2 y 1375 kW h/m2 y 1525 kW h/m2 y 1600 kW h/m2 y 0% 10% 20% 40% 50% 60% 70% 80% 90% 100%

1193 3238 1228 1924 3316 4012 -2079 -512 1054 4186 5844 7671 9132 10,593 11,975 12,579

pc

ps

r

wself,c

Baseline value = 2620 €.

Table 10 Sensitivity analysis – NPV for 20 kW power system. Variable

Value

NPV (€)

Variable

Value

NPV (€)

Cinv,unit

1980 €/kW 1890 €/kW 1710 €/kW 1620 €/kW 17 cent €/kW h 18 cent €/kW h 20 cent €/kW h 21 cent €/kW h 8 cent €/kW h 9 cent €/kW h 12 cent €/kW h 13 cent €/kW h 7% 6% 5% 4%

9632 11,054 13,898 15,319 9843 11,159 13,793 15,109 8834 10,857 14,904 16,927 9591 10,926 14,281 16,393

TaxDunit NTaxD tr

36% 5y 1300 kW h/m2 y 1375 kW h/m2 y 1525 kW h/m2 y 1600 kW h/m2 y 0% 10% 20% 40% 50% 60% 70% 80% 90% 100%

8195 14,332 7837 10,156 14,795 17,115 3186 2035 7255 17,696 22,917 28,137 33,358 38,692 43,660 45,672

pc

s

p

r

wself,c

Baseline value = 12,476 €.

(6 kW and 20 kW plants). A great influence on results is given by the percentage of self-consumed energy (see Table 6), but however also the market prices and national energetic policy have a keyrole. From these results may derive useful indications for the various stakeholders involved in the implementation of a project relating to the construction of a PV system:


Legislator – Tax deduction of 36% generates lower profits amounting approximately to 214 € (for 20 kW plant) and 238 € (for 3 kW and 6 kW plants) per kW installed. This profits reduction could produce a contraction in the creation of new plants and the reduction of installed power would cause a reduction of pollutant emissions as the energy internally produced. The gained results also confirm that a variation of period

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of deduction could determine positive effects. If, whenever possible, there is a reduction in the timeframe of 5 years, the revenues would be concentrated in the early years, allowing investors to have a DPBT of 2 years for all the dimensions analysed in this research. The increase in earnings would be equal to 93 € (20 kW plant) and 103 € (3 kW and 6 kW plants) per kW installed.
Company – A 5% reduction of 3 kW and 6 kW plant costs generates an increase of 90 € per kW installed, while for the 20 kW plant the increase is 70 € per kW installed. Firms with a strong management and technical know-how are able to offer prices of turnkey plant more profitable, necessary for a market recovery.
Investor – Compared to what was recorded in the incentive period, currently the return on this type of investment is lower and the difference is particularly marked when compared to what occurred with the Conto Energia IV. However, also if lower, the investment profitability is almost always verified with the exception of cases where the energy produced is all sold. A low level of risk represents the benefits of these investments, by the times of reasonable return and by the relevant contribution to environmental protection. In addition, the profitability of the project may increase if the investor synchronizes the own energy consumption with energy supply; in fact, for a 10% increase of self-produced energy that is also consumed, there is a profit increase of 240 € (3 kW plant) and 260 € (6 kW and 20 kW plants) per kW installed. If, however, the investor cannot or will not change their consumption habits, can compare the delta savings obtained by ESS with the related cost. 5. Economic assessments: scenario analysis The results will be further consolidated with a scenario analysis that allows to analyse possible future events by considering alternative possible input values [18]. The scenario analysis assesses the impact on indicator, when input variables change simultaneously, while in sensitivity analysis only one variable is modified. In this part of work is conducted a survey involving business operators (for a total of 10 respondents). They are selected on the base of their know-how in energy sector and the number of years of experience is relative to PV market – Table 11. Expert panels are used, when specialized input and opinion are required for an assessment. To each operator was asked to answer some questions concerning the evaluation of PV in Italian market. The aim is to define a scenario analysis in which evaluate the profitability of PV systems. Starting by critical variables defined in sensitivity analysis, they are investigated through specific questions. To each answer was possible to assign a probability value – Table 12. Concerning four variables (insolation level, opportunity cost, annual electricity sales price and annual electricity purchase price) was asked to define the number of values to consider in a profitability analysis, unlike other two variables (tax deduction and percentage of selfconsumption), for which, instead, were investigated to identify Table 11 Survey participants – photovoltaic market. No.

Role

Country

No. years of experience

1 2 3 4 5 6 7 8 9 10

President President General Manager General Manager Sales Manager Sales Manager Production Manager Production Manager Business Consultant Business Consultant

Germany Japan United States Italy Germany Italy China Taiwan UK India

6 5 4 5 4 6 5 5 4 4

Table 12 Questionnaire – photovoltaic market in Italy. 1. What is the correct value of tax deduction? Baseline (36%) 0% Support legislative (50%) 100% 2. What is the expected rate of reduction of investment costs? 5% 5% 10% 30% 15% 15% 20% 25% 25% 10% 30% 5% 35% 5% 40% 5% 3. The insolation level is very different from North to South. How many values can be considered? 1 5% 2 30% 3 45% 4 10% 5 10% 4. Opportunity cost influences the economic result. How many values can be considered? 1 50% 2 25% 3 15% 4 5% 5 5% 5. The profitability is strictly linked to the selfconsumption. What is its value in residential sector? 10% 5% 20% 10% 30% 35% 40% 20% 50% 15% 60% 10% 70% 5% 6. How many values of annual electricity sales price can be considered in residential sector? 1 40% 2 25% 3 25% 4 5% 5 5% 7. How many values of annual electricity purchase price can be considered in residential sector? 1 2 3 4 5

30% 30% 30% 5% 5%

the most probable value. Concerning last critical variable examined in this work (investment cost), was asked to quantify its reduction in future scenarios. This survey defines that:
The totality of interviewed believe that is appropriate to maintain the tax deduction equal to the discounted rate of 50%.
The investment costs can be reduced significantly. In particular, the main expected rates of reduction are equal to 10% and 20%. In this regard, it should be noted that researches on this topic estimate for 2017 a reduction in the cost of plant by 30–40% in the residential sector [53].
Due to the conformation of Italian territory input values relative of insolation level are very different from North to South. Considering this peculiarity, it is appropriate to analyse multiple scenarios.

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The role of opportunity cost for a specific territory not required another evaluations. It is linked to macro-economic conditions.
Both electricity purchase and sales price are linked to macroconditions that characterized the electric sector. More scenarios can be evaluated, but however as highlighted in Table 6 their relevance on revenues depends by harmonization between energy production and consumption.
The data on self-consumption percentage are strongly linked to the consumption habits, therefore, for this variable it is proper to proceed evaluating multiple scenarios. In particular, the baseline value (equal to 30%) has the highest probability, followed by 40% and 50%.

The analysis results show that even in post-market incentives it is possible, under certain conditions, to invest in PV systems and obtain a profitability equal, if not more, than those achieved when the incentive schemes were in force. In baseline scenarios a plant of 3, 6 and 20 kW enables to obtain a profitability per installed kW amounting to 506, 437 and 624 €/kW (see Table 5). Fig. 1 proposes the NPV percentage increase (D%) per kW installed with respect to the baseline scenarios. These increases are always positive: the minimum value is achieved at the Low Optimistic scenarios and the maximum one at the High Optimistic. For example, a 3 kW plant (compared to the value in the baseline scenario of 506 €/kW) the values of NPV per kW installed range

Three plants size (3 kW, 6 kW, 20 kW), and two different places of insolation (tlow e thigh , that respectively are equal to 1375 r r and 1525 kW h/m2 y, whereas in the initial scenario it is 1450 kW h/m2 y) are considered in scenario analysis. From these assumptions, three possible scenarios are defined:


for installation in areas with low solar radiation between 792 and 1199 €/kW;
for installation in areas with medium solar radiation between 926 and 1346 €/kW;
for installation in areas with high solar radiation between 1061 and 1493 €/kW.


Low Optimistic, where investment costs are reduced by 10% (C10% inv ) and the percentage of self-consumption is assumed to be 40% (w40% self, c).
Medium Optimistic, where w40% self,c is 40% and investment costs decrease by 20% (C20% inv ).
High Optimistic, where C20% inv and the percentage of selfconsumption is assumed to be 50% (w50% self,c).

For a 6 kW PV system, ranges are (relative to a baseline scenario that stores 437 €/kW):
745–1169 €/kW for installation in areas with low solar radiation;
874–1312 €/kW for installation in areas with medium solar radiation;
1004–1455 €/kW for installation in areas with high solar radiation.

The results of the scenario analysis are shown in Table 13, for each scenario are estimated NPV and DPBT indicators.

Table 13 Scenario analysis for 3 kW, 6 kW and 20 kW power systems. 3 kW

6 kW

20 kW

tlow r

tr

thigh r

tlow r

tr

thigh r

tlow r

tr

thigh r

Low optimistic NPV (€) NPV (€)/kW DPBT (y)

2376 792 4

2779 926 4

3182 1061 4

4468 745 4

5244 874 3

6021 1004 3

17,950 898 3

20,794 1040 2

25,744 1287 2

Medium optimistic NPV (€) NPV (€)/kW DPBT (y)

2905 968 4

3308 1103 3

3711 1237 3

5526 921 4

6303 1051 3

7080 1180 3

20,540 1027 3

23,383 1169 2

28,604 1430 2

High optimistic NPV (€) NPV (€)/kW DPBT (y)

3598 1199 3

4038 1346 3

4479 1493 3

7011 1169 3

7869 1312 3

8727 1455 2

23,130 1157 3

25,973 1299 2

31,464 1573 2

3 kW plant

6 kW plant 200%

195% 168%

166% 144%

137% 118% 91%

110%

100%

152% 170% 168% 85% 65%

111%

70%

tr

trhigh

129% 108%

83%

56%

trlow

141%

20 kW plant 233%

87%

106%

67%

44%

trlow

Low Optimistic

tr

trhigh

Medium Optimistic

Fig. 1. NPV percentage increase.

trlow

High Optimistic

tr

trhigh

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F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74

Finally, for the 20 kW plant (starting from a baseline value of 624 €/kW) ranges are:
898–1157 €/kW for installation in areas with low solar radiation;
1040–1299 €/kW for installation in areas with medium solar radiation;
1287–1573 €/kW for installation in areas with high solar radiation. Consistent with the NPV, also DPBT presents results more efficient. This ratio varies for the three systems respectively in the ranges 3–4 years (3 kW plant), 2–4 years (6 kW plant) and 2–3 years (20 kW plant). The payback is obtained in a period less than the baseline scenario, in which amounted to 6 years for systems of 3 kW and 6 kW and 4 years for a 20 kW plant. In consideration of various aspects such as (i) the evolution of prices of turnkey PV systems, (ii) increasing consumer attention towards environmental issues and (iii) an increasingly competitive electricity market, these scenarios turn out to be highly probabilistic. PV source, so even without subsidies, may be a viable solution for the generation of electricity in the residential sector. The profitability of PV systems is a necessary condition for their development. A comparison with the literature (see Table 4) is not simple due to several operative conditions. In general, there is a clear non-profitability of some plants focused on the selling of all the produced energy. PV investment can reach great profits under certain conditions, but it is necessary to propose an adequate business plan to investors in real applications.

6. Environmental assessments The environmental analysis, like the economic one, depends on the assumptions of the input variables. Reducing emissions is equal to the product of the energy produced by a PV system and lower emissions associated with the use of a cleaner energy source [54]. The following values, proposed by literature, are used in basegas coal PV line scenario: Eoil cd ; Ecd ; Ecd ; Ecd equal to 610, 840, 1182 and 49 gCO2eq/kW h, respectively (see Section 2.4). The evaluation of GHG emissions released by energy resources requires to evaluate several variables and the production phase generates strong variations [55]. To remove this constraint and deliver results that have greater reliability are evaluated alternative scenarios. In fact, the advantage of combined methods for corporate environmental evaluation is proposed by [56]. It is conducted a survey involving researchers, policy makers, firms administrators and consultants in order to evaluate several perspectives. They are selected on the base of their know-how in the energy and/or environmental sector (for a total of 20 respondents) with a high number of years of experience in these topics – Table 14. To each of them was asked to assign a probability to the potential value of the emissions associated with 4 resources (natural gas, oil, coal and photovoltaic) starting from literature data, but with the opportunity to propose also other values estimated as most appropriate [57]. An explicative evaluation proposed by one of the interviewees is reported for example in Table 15. The results define as almost all interviewees have chosen values near the range proposed by literature. They have allowed to greatly confine the variation range between the minimum value and the maximum value of emissions. An increase of emissions released by fossil fuels or a decrease of ones released by PV source (see Eq. (6)) generate an increase of ERcd. Consequently, the apex ‘‘ + ” indicates the maximum values of emissions concerning fossil fuels and the minimum value of emissions concerning PV source.

Table 14 Survey participants – Environmental evaluation. No.

Role

Country

No. years of experience

1

Director of Research Centre

23

2 3 4 5 6 7

Director of Research Centre Full Professor Full Professor Associate Professor Associate Professor Director (Public Body – Environmental office) Director (Public Body – Environmental office) Director (Public Body – Economic office) Director (Public Body – Economic office) Politician Politician General Manager – Energy company General Manager – Energy company Manager - Environmental services company Manager - Environmental services company Head energy division - Firm Head energy division - Firm Independent consultant (Energy sector) Independent consultant (Environmental sector)

United States Brazil China Japan India Turkey Germany UK

17

United States Denmark

22

Portugal China Italy Spain France

21 19 20 18 16

Italy

17

Japan Germany UK

18 16 17

India

17

8 9 10 11 12 13 14 15 16 17 18 19 20

21 25 22 16 18 19

20

A sensitivity analysis is conducted in this part of the work, in which are been defined new scenarios that assume, for individual sources, maximum or minimum values proposed by the survey and not the mean value of literature analysis. The following values are evaluated in according to survey:
Eoil; = 750 gCO2eq/kW h and Eoil;þ = 950 gCO2eq/kW h. cd cd gas;
Ecd = 500 gCO2eq/kW h and Egas;þ = 700 gCO2eq/kW h. cd = 1100 gCO2eq/kW h and Ecoal;þ = 1300 gCO2eq/kW h.
Ecoal; cd cd
EPV;þ = 30 gCO2eq/kW h and EPV; = 70 gCO2eq/kW h. cd cd The amount of carbon dioxide emissions produced per each unit of energy produced is evaluated for each scenario (Table 16). For example, considering Eoil; equal to 750 gCO2eq/kW h, it is cd obtained EFF cd

equal to 736 gCO2eq/kW h and consequently,

PV FF PV EFF cd  Ecd is 687 gCO2eq/kW h. This difference (Ecd  Ecd ) is equal to (Table 16):


727 gCO2eq/kW h in baseline scenario.
687–777 gCO2eq/kW h in alternative scenarios. In baseline scenario with an annual average insolation equal to 1450 kW h/m2 y and considering the technical assumptions related to the PV system (see Table 3), the electricity produced by 1 kW plant is equal to 1560 kW h/y (see Eq. (6)). Multiplying this value by the energy currently generated by fossil fuels (and which could be replaced by PV systems) it is possible to estimate the reductions of tCO2 eq that may be avoided. ERcd,1 is equal to 1.13 tCO2eq in baseline scenario considering only the first year of life of the plant (obtained multiplying 1560 kW h/y and 727 gCO2eq/kW h). This analysis is repeated using as input data variables of the new scenarios as above cited. The results are proposed in Table 16 and is verified a decrease of emissions never below 1 tonne during the first year of life of the plant.

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Table 15 Estimation of GHG emissions (gCO2eq/kW h) associated to energy resources – an example.

Literature Min Max

Natural gas

Oil

Coal

Photovoltaic

290 930

510 1170

675 1689

5 92

Estimation

v

p

v

p

v

p

v

p

Value Value Value Value Value

400 500 600 700 800

5% 20% 45% 25% 5%

650 750 850 950 1050

5% 25% 40% 25% 5%

1000 1100 1200 1300 1400

5% 25% 35% 30% 5%

30 40 50 60 70

15% 20% 30% 25% 10%

v = value; p = probability.

Table 16 Sensitivity analysis – environmental aspects.

EFF cd

EPV cd

 (gCO2eq/kW h) ERcd;1 (tCO2eq/y)

Baseline

oil; Ecd

oil;þ Ecd

Egas; cd

Egas;þ cd

Ecoal; cd

Ecoal;þ cd

EPV;þ cd

EPV; cd

727

687

777

679

767

718

740

706

746

1.13

1.07

1.21

1.06

1.20

1.12

1.15

1.10

1.16

It is possible to extend these calculations to the three dimensions of plant and quantify the potential environmental savings that can be avoided during the 20 years of useful life of the investment – Table 17. For example, this value is equal to 59.6 tCO2eq considering a scenario. It is obtained multiplying the energy 3 kW plant in Eoil; cd generated by PV system during the 20 years (equal to 86,808 kW h - see Table 5) and the reduction of emissions in alternative scenario (equal to 687 gCO2eq/kW – see Table 16). The overall values are the following:
58.9–67.4 tCO2eq considering a 3 kW plant.
118–135 tCO2eq considering a 6 kW plant.
393–450 tCO2eq considering the 20 kW plant. The environmental analysis achieves the most significant changes, when are analysed the oil and gas resources. In fact, they have a high weight in the energy mix. This section is completed evaluating the environmental savings of PV systems during 2008–2015 period in Italy – Table 18. For example, the PV production amounted to 24,676 GW h (see Table 2)

in 2015 and considering the reduction of emissions in the baseline scenario (that amounts to 727 gCO2eq/kW h – see Table 16), it is get a saving of around 17,939 ktCO2eq. In total over the period 2008–2015 reductions in the emissions of carbon dioxide are approximately:
54,606 ktCO2eq in baseline scenario.
51,001–58,362 ktCO2eq in alternative scenarios.

7. Policy implications PV is a policy-driven market. The PV industry has grown significantly in recent years and the adoption of subsidies has encouraged the sector expansion. However, all countries should remove the incentives, when the maturity of sector has been reached. In fact, they can’t be seen as a perpetual assistance. Italy, as the literature has shown, acts as a forerunner to such market scenarios and it is therefore a good example of a case study. In particular, some authors have analysed the three main critical elements [30]:

Table 17 Reduction in the emissions of carbon dioxide (tCO2eq) for 3 kW, 6 kW and 20 kW plants.

3 kW 6 kW 20 kW

Baseline

oil; Ecd

oil;þ Ecd

Egas; cd

Egas;þ cd

Ecoal; cd

Ecoal;þ cd

EPV;þ cd

EPV; cd

63.1 126 421

59.6 119 398

67.4 135 450

58.9 118 393

66.6 133 444

62.3 125 416

64.2 128 428

61.3 123 409

64.8 130 432

Table 18 Reduction in the emissions of carbon dioxide (ktCO2eq) in Italy from 2008 to 2015. Baseline

oil; Ecd

oil;þ Ecd

Egas; cd

Egas;þ cd

Ecoal; cd

Ecoal;þ cd

EPV;þ cd

EPV; cd

2008 2009 2010 2011 2012 2013 2014 2015

140 492 1362 7756 13,546 15,433 15,876 17,939

133 465 1287 7329 12,801 14,584 15,003 16,952

150 526 1456 8289 14,478 16,495 16,968 19,173

131 460 1272 7244 12,652 14,414 14,828 16,755

148 519 1437 8182 14,292 16,283 16,750 18,926

139 486 1346 7660 13,378 15,242 15,680 17,717

143 501 1387 7894 13,788 15,709 16,160 18,260

136 478 1323 7532 13,155 14,988 15,418 17,421

144 505 1398 7958 13,900 15,837 16,291 18,408

Total

54,606

51,602

58,362

51,001

57,611

53,930

55,583

53,029

56,034

F. Cucchiella et al. / Energy Conversion and Management 129 (2016) 62–74


Subsidies, initially, were given to the energy produced by a PV plant and not to the quantity of energy delivered to the grid.
Too much high subsidies values, subsequently translated in bill costs paid by citizens.
Subsidies did not favoured only strategic investments, but also speculative ones. In non-subsidized electricity markets, these aspects are no more relevant and only the intermittent nature of this resource become a critical aspect. ESS represents an optimal solution, but their development is currently blocked by high investment cost. The use of PV panels can be economically more advantageous, when they are integrated with other technologies: for example with heat pumps in residential sector or in hybrid plants (typically coupled with biomass) in industrial context. In fact, the aim is to maximize the share of self-consumption. Since the electricity contributes, more than any other power sector, to reduce the share of fossil fuels in the global energy mix, policy makers can support the development of PV energy through simple measures that do not cause higher costs for citizens: 1. The unitary tax deduction can be maintained equal to 50% (in fact, the baseline rate is 36%). 2. The period of deduction can be fixed also equal to 5 y (currently, it is 10 y). 3. Bureaucracy can be simplified. 4. The reduction of the burden on citizens and firms when they become independent from the national electric grid.

73

unitary reduction in the emissions of carbon dioxide equal to727 gCO2eq/kW h using a PV system alternatively to fossil sources. Considering the three sizes evaluated in this paper, it is possible to define the value of ERcd during the 20 years of useful life of the investment. It is equal to 21 tCO2eq for each kW installed. Each energy resource can be characterized by a specific value of emissions of carbon dioxide and this requires developing a sensitivity analysis. The reduction of emissions ranges from 687 to 777 gCO2eq/kW h and it is verified a decrease of emissions never below 1 tonne during the first year of life of the plant in all scenarios. ERcd is equal to 19.6–22.5 tCO2eq for each kW installed during the 20 years of useful life of the investment. The minimum value is reached with a low value of emissions released by a gas plant (equal to 500 gCO2eq/kW h), while the maximum value with a high value of emissions released by an oil plant (equal to 950 gCO2eq/kW h). Given these results, it is possible calculate the emission reductions of carbon dioxide in the period 2008–2015 in Italy: 54,606 ktCO2eq in baseline scenario and from 51,001 to 58,362 ktCO2eq in alternative scenarios. Furthermore, this paper suggests to apply two tools to favour PV investments in residential sector: (i) fiscal deduction with a rate equal to 50% (instead of 36%) and (ii) the possibility to have a period of deduction equal to 5 years (instead of 10 years). The replacement of fossil fuels with renewable ones allows to have clean and safe energy and to reduce air pollution, which is one of the major challenges of modern society. Furthermore, the use of renewables increases the sustainability of a country. New data are obtained in this paper from both environmental and economic perspective. Small-scale photovoltaic systems can favour the transition towards a sustainable energy mix.

8. Conclusions The paper evaluates the economic feasibility of small-scale PV systems in an electricity market without subsidies. Furthermore, also the environmental perspective is investigated. The development of PV sources in the last years is very impressive. The topic is well analysed in literature, but however it is characterized by changes. In particular, the role of subsidies is strategic in the initial phase of sector in a country and then the role of self-consumption become relevant. The profitability is verified in almost all scenarios. In baseline scenario, NPV is equal to 506, 437 and 624 € per kW installed in 3, 6 and 20 kW plants, respectively. DPBT varies from 4 years (in 20 kW plant) to 6 years (in both 3 and 6 kW plants). The main item of revenue is represented often by savings energy through internal consumption (avoided costs in energy bill) and this result depends by the share of self-consumption. It is verified, when this value is at least equal to 32% in both 6 kW and 20 kW plants and to 35% in 3 kW plant. Value of variables can be subjected to variations and in this way sensitivity and scenario analysis can give solidity to results obtained. The profitability of PV system is not verified only when the energy produced is almost all sold. BEP analysis (wself,c) defines the following values: 6% in 20 kW plant and 13% in both 3 kW and 6 kW plants. Considering optimistic scenarios, characterized by a reduction of investment cost and an increase of self-consumption share, economic indicators became more profitable. NPV ranges from 926 to 1346 € per kW installed in 3 kW plant. This indicator, instead, varies from 874 to 1312 € per kW installed in 6 kW plant and from 1040 to 1299 € per kW installed in 20 kW plant. A comparison with existing literature defines as these values are very interesting and consequently, it is confirmed that the investment in PV systems in residential sector presents wide margins of profits, when virtuous investors synchronize their consumption to peak radiation. Literature shows as emissions released by PV power production are much lower than ones of fossil fuels. This paper quantifies the

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