- Email: [email protected]
Comparative study of photovoltaic solar systems connected to the grid: Performance evaluation and economic analysis
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Applied Energy Symposium and Forum, Renewable Energy Integration with Mini/Microgrids, REM 2018, 29–30 September 2018, Rhodes, Greece The 15th International Symposium on District Heating and Cooling to the Comparative study of photovoltaic solar systems connected Applied Energy Symposium and Forum, Renewable Energy Integration with Mini/Microgrids, grid: Performance evaluation and Rhodes, economic REM 2018, 29–30 September 2018, Greeceanalysis
Assessing the feasibility of using the heat demand-outdoor a,b c d, A. ELAMIMafunction *, B. HARTITI HAIBAOUI ,A. LFAKIR , P.Thevenin temperature aa,,A. long-term district heatconnected demand forecast Comparative study of for photovoltaic solar systems to†the ERDYS Laboratory, MEEM & DD Group, Hassan II University of Casablanca, FSTM BP 146, Mohammedia 20650, Morocco a,b,c a a Hassan IIand b economic c grid:LIMAT Performance evaluation analysis of Physics, university ,FSB, Casablanca, Morocco I. Andrić *,Laboratory, A. PinaDepartment , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc a
b
c Sultan Moulay Slimane University ,FSTB, BP 523 Beni Melall, Morocco LMOPS Laboratory, Department of- Instituto Physics University of Lorraine Metz, France a Technology a, c 1, 1049-001 Lisbon, d, Portugal IN+ Center for Innovation, and Policy Research Superiora,b Técnico, Av. Rovisco Pais b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c a Département Énergétiques Environnement - IMT Atlantique, 4FSTM rue Alfred Kastler, 44300 Nantes, ERDYS Laboratory,Systèmes MEEM & DD Group, et Hassan II University of Casablanca, BP 146, Mohammedia 20650,France Morocco Abstract b LIMAT Laboratory, Department of Physics, Hassan II university ,FSB, Casablanca, Morocco c Sultan Moulay Slimane University ,FSTB, BP 523 Beni Melall, Morocco The aim of this study targetsdLMOPS the performance analysis and of thePhysics economic evaluation of two photovoltaic systems connected to the Laboratory, Department University of Lorraine Metz, France a
d
A. ELAMIM *, B. HARTITI ,A. HAIBAOUI
,A. LFAKIR , P.Thevenin †
grid of 4.08 KWp, located in the same place in the roof of the research building at the Faculty of Sciences and Technologies Abstract Mohammedia, Morocco. This plant is composed of two types (mc-Si and pc-Si) of PV crystalline technology. The experimental has been over one-yearin period (2015). The parameters of the PV systemsfor include the total Abstract District heating data networks are recorded commonly addressed the literature as assessed one of the most effective solutions decreasing the energy generated, final yield, reference yield, performance ratio, capacity factor and monthly system efficiency. The economic greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat evaluation towchanged systemsthe is performance calculated using capital budgeting methods to determine economic in termsdecrease, of The aimDue of of this targets analysis and the economic evaluation ofheat two demand photovoltaic systems to the sales. tothestudy the climate conditions and building renovation policies, inprofitability the futureconnected could economic return of electricity generation. grid of 4.08 KWp, located in the same place in the roof of the research building at the Faculty of Sciences and Technologies prolonging the investment return period. The highest values in terms daily yield of (YF performance (PR=82%),technology. capacity factor (CF=21.93%), Mohammedia, Morocco. Thisofplant is final composed two=5.26h/day), types (mc-Si ofratio crystalline The main scope of this paper is to assess the feasibility of using the and heatpc-Si) demand –PV outdoor temperature function for heat demand levelized cost of electricity (LCOE=0.068€/kWh) and payback time (PB=12), have been recordedofbythe pc-Si systems solar module. Therefore, The experimental data has been recorded over one-year period (2015). The assessed parameters include theoftotal forecast. The technology district of Alvalade, located in Lisbon (Portugal), wasresearch used asprojects a case in study. ThePV district is consisted 665 this PV generated, system could be recommended, as well, in the future Morocco. energy final yield, reference yield, performance ratio, capacity factor and monthly system efficiency. The economic buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Keywords: Crystalline technology; performance ratio; final yield; capacity factor; capital budgeting; LCOE. evaluation of the tow systems is calculated using capital budgeting methods to determine economic profitability in terms of the scenariosPublished were developed (shallow, ©renovation 2019 The Authors. by Elsevier Ltd. intermediate, deep). To estimate the error, obtained heat demand values were economic return of electricity generation. This is an open access article under the heat CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) compared with results from a dynamic demand previously developedratio and (PR=82%), validated bycapacity the authors. The highest values in terms of daily final yield (YFmodel, =5.26h/day), performance factor (CF=21.93%), Selection and peer-review under responsibility of the scientific committee of the Symposium Forum, The results that when only weather change is considered, the margin ofbeen errorApplied could beEnergy someand applications levelized costshowed of electricity (LCOE=0.068€/kWh) and payback time (PB=12), have recorded byacceptable pc-Si solarfor module. Therefore, Renewable Energy Integration with Mini/Microgrids, REM 2018. scenarios considered). However, after introducing renovation (the error in annual demand was lower than 20% for all weather this PV technology could be recommended, as well, in the future research projects in Morocco. 1. system Introduction scenarios, the error value increased upperformance to 59.5% (depending on yield; the weather and factor; renovation scenarios combination Keywords: Crystalline technology; ratio; final capacity capital budgeting; LCOE.considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the demand is increasing burgeoning needs of aongrowing population and the decrease Energy in the number of heating hours ofrapidly 22-139hreaching during thethe heating season (depending the combination of weather and development of the international economy [1]. renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the The simplest energyThe technology, in terms of both design and installation, solar photovoltaic technology. It has an coupled scenarios). values suggested could be used to modify the functionis parameters for the scenarios considered, and 1. Introduction improve the accuracy of heat demand estimations.
Energy demand is increasing rapidly reaching the burgeoning needs of a growing population and the © 2017 The Authors. Published by Elsevier Ltd. development of the international economy [1]. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. technology, Tel. : +212-664-602-453. The simplest energy in terms of both design and installation, is solar photovoltaic technology. It has an Cooling. E-mail address : [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy * Corresponding author. under Tel. : +212-664-602-453. Integration with Mini/Microgrids, REM 2018. E-mail address : [email protected] 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy Selection andwith peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy Integration Mini/Microgrids, REM 2018. Integration with Mini/Microgrids, REM 2018. 10.1016/j.egypro.2019.01.006
A. ELAMIM et al. / Energy Procedia 159 (2019) 333–339 ELAMIM Abderrazzak et al/ Energy Procedia 00 (2018) 000–000
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important CO2 mitigation factor. Moreover, solar photovoltaic provides high reliability and low maintenance cost. The installation of photovoltaic solar panels depends on environmental and meteorological data such as ambient temperature, solar radiation, the daily duration of Sun and depends on the economic and financial characteristics of the country [2.3]. Due to its geolocation, between northern latitudes of 36-421 and eastern longitudes of 26-451, Morocco has great potential in terms of solar energy [4.5]. The average annual solar irradiation is 3000 h, which corresponds to 8.2 h per day. Thus, the annual value of average solar irradiation reaches 2600kW h / m² / year [6.7]. The purpose of the present document is to build a credible comparison between the performances of two crystalline PV technologies of a PV installation connected to the grid during one year under the weather conditions of Errachidia city in Morocco. These systems have been analysed in terms of the total energy generated, final yield, reference yield, performance ratio, capacity factor, monthly system efficiency, payback time, and LCOE. 2.
Materials and Methods
2.1 Site information and system description Mohammedia, located at 33 ° 41 '23' North and -07 ° 23' 23 East, in Morocco, is a port city on the west coast of Morocco between Casablanca and Rabat in the region of Casablanca-Settat. It is located on the coast of the Atlantic Ocean, 24 km north-east of the economic capital of the kingdom of Morocco. The city of Mohammedia has a Mediterranean climate which is characterized by mild/wet winters and warm/dry summers. During summer time (May to October), the maximum average temperatures are between 23 and 29 °C but can occasionally reach 35 °C. On the other hand, the minimum, generally, is registered between 14 to 19 °C. The Sunshine duration reaches 9 to 10 hours per day. In winter (November to April), the maximum average temperatures are between 20 and 23 °C and minimum of 9 to 12 °C and can often drop to 2 °C in the morning. The sunlight hours during winter is 5 to 6 hours.
Fig. 1. The different installed technologies. The considered technologies are represented by two PV panel types, mono-crystalline and poly- crystalline, each part of the plant has a power of 2.04 kWp as shown in Fig. 1. The characteristics of these PV panels are shown in the table 1. All the solar PV modules are positioned in a fixed direction facing south at an inclined angle of 30°. The inverter model used in each plant is SB2000HF30 and its specifications are listed in Table 1. Table 1. PV panels properties and Inverter specifications Inverter specifications Trademark
SOLARWORLD
Inverter model
SB 2000HF30
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Model Solar cell Maximum power at STC
SUNMODULE pc-Si mc-Si 255Wp 255Wp
Max PV power Max voltage Nominal voltage
2100 W 700V 220V/230V/240V
Optimum operating voltage Optimum operating current Open circuit voltage Short circuit current
30.9V 8.32A 38 V 8.88A
31.4V 8.15A 37.8V 8.66A
voltage range Grid frequency; range Max. output current Max input current
180V-280V 50/60 Hz 8.3 A 12.0 A
Temperature coefficient of maximum power Module efficiency
-0.41%/°C
-0.45%/°C
Maximum efficiency
96%
15.2 %
15.2 %
1. Performance analysis of PV systems 2.2 Performance analysis methodology The main parameters for the evaluation of PV system performance were analysed using the following parameters:
Final yield (YF): The total AC energy during a specific period (day, month, or year) (EAC) divided by the rated power of the installation (PPV, Rated). This parameter is considered as crucial, during the whole experiment, to compare between the different PV systems installation [8]. The final yield is given as: Y F E AC / P pv . Rated
(1)
Reference yield (YR): The reference yield (YR) represents the ratio of the incident energy in the array plane HI (kWh/m2) to the reference irradiance (G =1kW/m2) [9]. The reference yield is given by: YR H I / G
(2)
Performance ratio (PR): The performance ratio is the final yield divided by the reference yield. It provides important information about the overall effect of the losses [10]. The performance report (PR) is given as follows: (3) PR Y F / Y R
System efficiency: The monthly system efficiency (ηsys.m) describes the ratio of monthly energy output of the system to the total energy collected from the PV field [11]. It is given by: s ys , m E AC , m /( H I A a )
(4)
Where Aa (m2) is module (array) total area.
Capacity factor (CF): The capacity factor (CF) informs about the relationship between the actual annual electrical energy and the electrical energy that could be generated if the solar photovoltaic system operated with its total nominal power installed 24 hours a day over a period of one year [12]. It is expressed as: (5) CF E AC /( P pv . Rated 8760 )
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2.3 Economic Analysis The comparative economic analysis is carried out by calculating cash flow (Ci), NPV (Net Present Value), and the LCOE for the tow PV systems considered. The NPV is the difference between the value of revenues and the expenses incurred for an investment up to the date the investment was made [13]. A positive value of the NPV indicates that there is a positive surplus, so it is a financial gain for the investor, and for a negative value, a financial loss for the investor is reported. n (6) NPV D t 1 C i /(1 i ) t Where D is the capital outlay, i is the interest rate, and n is the project life.
The LCOE is an evaluation of lifetime energy cost and lifetime energy production [14]. The LCOE is given by: LCOE D
N
ES n 1
N
i
/(1 r ) n / EP (1 DR ) n /(1 r ) n n 1
(7)
Where D is the capital outlay, ES is the expenses, EP represents the energy production, r is the discount rate, DR is the degradation rate, and N is the life project.
The economic parameters were performed based on several assumptions: Item description, Inflation rate, discount rate, degradation rate and project life (Table 2) Table 2. Summary of various interest rates used in the economical study Item description Inflation rate Discount rate degradation rate Project life
3.
Value 1.6% 2.5% 0.35% 25
ref [19] [20] [20] ---
Results and discussion
The figure 2 represents the average daily yield (YR) and the related average final yield (YF) generated by the two PV systems during a period of one year. Obviously, the daily reference yield varies between 4.38 h/day and 6.87 h/day between December and August. The average annual value of the daily (YR) is approximately 5.96 h/day. The minimal daily final yield is predicted in December, for pc-Si technology, the value recorded is 3.53 h/day and 3.47 h/day for mc-Si technology. While the maximal daily final yield is predicted in May and the values are 5.65 h/day for pc-Si technology and 5.56 h for mc-Si technology.
A. ELAMIM et al. / Energy Procedia 159 (2019) 333–339 Author name / Energy Procedia 00 (2018) 000–000
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6
5.00
5
4.00
4
3.00
3
2.00
2
1.00
1
0.00
0
YF(mc‐Si)
YF(Pc‐Si)
25.00
80
20.00
60
15.00
40
10.00
20
5.00
0
0.00
CF(%)
6.00
100
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
7
PR(%)
7.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
YF and YR(h/day)
According to the results shown in figure 3, the highest values of the monthly performance ratio and the capacity factor, have been registered by pc-Si photovoltaic system. Moreover, the maximum performance ratio value has been recorded in November (low temperature and irradiation), while the minimum value of the same parameter was displayed in August (high temperature and irradiation). Furthermore, the maximum value for capacity factor for the two PV systems installation pc-Si and mc-Si reached respectively 23.52% 23.18%. The minimum values of the same parameter have reached 14.69% and 14.47% respectively for the PV systems pc-Si and mc-Si.
YR
Fig. 2. average daily YF and average YR
PR(mc‐Si)
PR(pc‐Si)
CF(mc‐Si)
CF(pc‐Si)
Fig. 3. Variation of monthly PR and CF.
The monthly system efficiency as seen in the fig 4 varied from 10.20 % to 13.73 % for pc-Si and from 10.59% to 13.60% for mc-Si. These results indicate that among the two PV systems installation, pc-Si system displayed the highest value. Accordingly, we note that the pc-Si technology has a superior performance compared to the mc-Si technology even if both types of panels have the same performance and rated power under STC (table 1). However, the temperature coefficient of power is different. The temperature coefficient indicates that as the temperature increases and the modules heat up, the output power of the solar panel decreases, which justifies this difference between the two technologies. Thus, it can be concluded that a higher negative value of the temperature power coefficient of the mc-Si photovoltaic panels, compared to that of pcSi panels in this study, leads to a decrease in the output power in the photovoltaic plant. 14.00 13.50 12.50
15
200
12.00 11.50
10
100
11.00 10.00
20
300
13.00
10.50
25
400
5 0
0 ηsys(mc‐Si)
ηsys(pc‐Si)
Fig. 4. Monthly average system efficiency.
mc‐Si Error mc‐Si Simulated
pc‐Si Error mc‐Si Measured
Fig. 5. Comparison of recorded data and simulation results
A. ELAMIM et al. / Energy Procedia 159 (2019) 333–339 ELAMIM Abderrazzak et al/ Energy Procedia 00 (2018) 000–000
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5000 4000 3000 2000 1000 0 ‐1000 ‐2000 ‐3000 ‐4000 ‐5000
€6,000.00
0
2
4
6
8 10 12 14 16 18 20 22 24
pc‐Si
mc‐Si
Net present value()
Accumulated Cash Flow (€)
The real data of the electrical energy generated by the PV systems connected to the grid were obtained with a monitoring system which allows the recording of the average productivity data every five minutes. The energy output from the inverters has been recorded for a whole year from 1st January 2015 until December 2015. Real data have been measured and compared with the simulated results as shown in fig 5. The difference gap between the estimated values and measured values, during the study period, varies between 1% in May 2015 and 16% in August/October 2015 for Poly-Si technology and between 5.61% in May 2015 and 21% in August 2015 for Mono-Si technology. The results show that there is an agreement between what is estimated and what is produced with an exception during the months of August and October where the error has been reported to be significantly high, which is reasonably explained by the difference in the irradiation data used in the simulations (from the NASA database).
€4,000.00 €2,000.00 €0.00 (€2,000.00) (€4,000.00)
Years
Fig. 6. Comparison of accumulated Cash Flows.
0%
10%
20%
Discount rate(%) mc‐si
pc‐si
Fig. 7. Comparison of Net Present Value
The accumulated cash flows for the investment are shown in the figure 6. This graph demonstrates the Payback time of the investment. All cash flows are positive from the first year to about 12.63 years for the mc and 12 for the poly after recovering the capital outlay. This occurs when the accumulated cash flow curve reaches zero. From this point, the curve enters in the positive quadrant because it has been fully recovered the capital outlay of the investment. Figure 7 shows the NPV for tow PV solar plants installed in Mohammedia (Morocco). The NPV is calculated using equation 1 for several discount rates ranging from 1% to 25 %. As expected, with low discount rates, 1% to 6.25 % for the mc-Si panels and 1 % to 6.46% for the pc-Si panels, a positive value of NPV is obtained. Which means that the PV installation provides net benefits to the investor. For higher discount rate, the value the NPV turns negative, which means that the PV installation would produces losses for investors, so in that condition the investment should not be implemented. The NPV reaches to zero when the discount rate matches the internal rate return (6.34% for mcSi and 6.65% for pc-Si) on investment. Table 3. Comparison of Levelized Cost of Energy for mc-Si and pc-Si PV systems at different discount rate
Discount rate (%)
LCOE (€/kWh) mc-Si
LCOE (€/kWh) pc-Si
2.5 5 7 10 15
0.077 0.096 0.113 0.141 0.191
0.075 0.094 0.11 0.137 0.185
Table 3 shows the Levelized Cost of Energy for the two types of PV systems (mc-Si and pc-Si) for different values of
30%
A. ELAMIM et al. / Energy Procedia 159 (2019) 333–339 Author name / Energy Procedia 00 (2018) 000–000
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the discount rate. Considering a standard discount rate of 2.5%, the LCOE for mc-Si and pc-Si PV systems are 0.077€/kWh and 0.075 €/kW h, respectively. The LCOE takes the value of 0.096€/kWh (mc-Si) and0.094 €/kWh at a discount rate of 5%. 4.
Conclusion
This paper evaluates the performance analysis and economic evaluation of a solar photovoltaic system connected to a 4.08 kWp grid designed to supply power to the Errachidia Faculty of Science and Technologies in Morocco. Tow types of PV (mc-Si, pc-Si) were studied and simulated. To choose the most appropriate option, the total energy generated, final yield, reference yield, performance ratio, capacity factor and monthly system efficiency, payback time, and levelized cost of energy have been examined and compared for the tow installed technologies. The main conclusions are: • The YF, PR, and CF of the mc-Si system are 5.17 h, 80.66%, and 21.56% respectively. • The YF, PR, and CF of the pc-Si system are 5.26h, 82.00%, and 21.93% respectively. • The monthly system efficiency varied between 10.59% and 13.60% for mc-Si and between 10.20% and 13.73% for pc-Si.
Tracking the accumulated cash flow versus time allows the computation of the payback, which is approximately 12.63 years for mc-Si, and 12 years for pc-Si.
The levelized cost of energy is 0.077€/kWh for mc-Si and 0.075€/kWh for pc-Si.
We conclude that the system using pc-Si technology has a slightly higher performance compared to the mc-Si technologies. Acknowledgements The authors would like to thank’’Institute for Research in Solar Energy and New Energies (IRESEN)’’ for completing the project PROPRE.MA References [1] Janis Latvels, Raitis Grzibovskis, Aivars Vembris, Dagnija Blumberga. Improvement of Solar PV Efficiency.Potential Materials for Organic Photovoltaic Cells. Environmental and Climate Technologies (2013). [2] Karaveli AB, et al., Comparison of large-scale solar PV (photovoltaic) and nuclear power plant investments in an emerging market, Energy (2015). [3] Marwan M. Fawzy et al. / Energy Procedia 113 (2017) 428 – 433 [4] ELAMIM, A.; HARTITI, B.; BARHDADI, A.; HAIBAOUI, A.; LFAKIR, A.; THEVENIN, P. PHOTOVOLTAIC OUTPUT POWER FORECAST USING ARTIFICIAL NEURAL NETWORKS. Journal of Theoretical & Applied Information Technology. 8/15/2018, Vol. 96 Issue 15, p5116-5126. 11p. [5] El Fadili, A., Giri, F., & El Magri, A. (2014). Reference voltage optimizer for maximum power point tracking in triphase grid-connected photovoltaic systems. International Journal of Electrical Power & Energy Systems, 60, 293-301. [6] A.Ghoshetal./Solar Energy Materials & Solar Cells157 (2016)1–9 [7] Tyagi VV, Rahim NAA, Rahim NA, Selvaraj JAL.Progress in solar PV technology: research and achievement. Renew Sustain Energy Rev 2013; 20:443–61. [8] Al-Otaibi, A., 2015. Performance evaluation of photovoltaic systems on Kuwaiti school’s rooftop. Energy Convers. Manage. 95, 110–119. [9] Sharma V, Chandel SS. Performance analysis of a 190 kWp grid interactive solar photovoltaic power plant in India.Energy 2013;55:476e85 [10] Rehman S, El-Amin I. Performance evaluation of an off-grid photovoltaic system in Saudi Arabia. Energy 2012; 46:451e8. [11] Adaramola, M., Vagnes, E., 2015. Preliminary assessment of a small-scale rooftop PV grid tied in Norwegian climatic conditions. Energy Convers. Manage. 90,458–465. [12] V. Sharma, S.S. Chandel / Energy 55 (2013) 476e485 [13] I. GUAITA-PRADAS and B. MARÍ SOUCASE, ‘Endorse of renewable energy plants, still an alternative investment in Spain?’ SOP Transactions on Economics Research (ER) Scientific Online Publishing, Vol. 1, Num. 2, pp.1-9. (2014) Scientific Online Publishing. [14] I. GUAITA-PRADAS and B. MARÍ SOUCASE, Profitability and sustainability of photovoltaic energy plants in Spain, Int. J. Sustainable Economy, Vol. 7, No. 3, 2015 [15] http://www.centralbanknews.info/ [16] AbderrazzakElamim ,Bouchaib Hartiti,Amine Haiboui, Abderrazak Lfakir, PhilipeThevenin,Performance evaluation and economical analysis of three photovoltaic systems installed in an institutional building in Errachidia, Morocco, Energy Procedia 147C (2018) pp. 121-129.
ScienceDirect Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2018) 000–000 Available online at www.sciencedirect.com
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Energy (2019) 000–000 333–339 EnergyProcedia Procedia159 00 (2017)
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Applied Energy Symposium and Forum, Renewable Energy Integration with Mini/Microgrids, REM 2018, 29–30 September 2018, Rhodes, Greece The 15th International Symposium on District Heating and Cooling to the Comparative study of photovoltaic solar systems connected Applied Energy Symposium and Forum, Renewable Energy Integration with Mini/Microgrids, grid: Performance evaluation and Rhodes, economic REM 2018, 29–30 September 2018, Greeceanalysis
Assessing the feasibility of using the heat demand-outdoor a,b c d, A. ELAMIMafunction *, B. HARTITI HAIBAOUI ,A. LFAKIR , P.Thevenin temperature aa,,A. long-term district heatconnected demand forecast Comparative study of for photovoltaic solar systems to†the ERDYS Laboratory, MEEM & DD Group, Hassan II University of Casablanca, FSTM BP 146, Mohammedia 20650, Morocco a,b,c a a Hassan IIand b economic c grid:LIMAT Performance evaluation analysis of Physics, university ,FSB, Casablanca, Morocco I. Andrić *,Laboratory, A. PinaDepartment , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc a
b
c Sultan Moulay Slimane University ,FSTB, BP 523 Beni Melall, Morocco LMOPS Laboratory, Department of- Instituto Physics University of Lorraine Metz, France a Technology a, c 1, 1049-001 Lisbon, d, Portugal IN+ Center for Innovation, and Policy Research Superiora,b Técnico, Av. Rovisco Pais b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c a Département Énergétiques Environnement - IMT Atlantique, 4FSTM rue Alfred Kastler, 44300 Nantes, ERDYS Laboratory,Systèmes MEEM & DD Group, et Hassan II University of Casablanca, BP 146, Mohammedia 20650,France Morocco Abstract b LIMAT Laboratory, Department of Physics, Hassan II university ,FSB, Casablanca, Morocco c Sultan Moulay Slimane University ,FSTB, BP 523 Beni Melall, Morocco The aim of this study targetsdLMOPS the performance analysis and of thePhysics economic evaluation of two photovoltaic systems connected to the Laboratory, Department University of Lorraine Metz, France a
d
A. ELAMIM *, B. HARTITI ,A. HAIBAOUI
,A. LFAKIR , P.Thevenin †
grid of 4.08 KWp, located in the same place in the roof of the research building at the Faculty of Sciences and Technologies Abstract Mohammedia, Morocco. This plant is composed of two types (mc-Si and pc-Si) of PV crystalline technology. The experimental has been over one-yearin period (2015). The parameters of the PV systemsfor include the total Abstract District heating data networks are recorded commonly addressed the literature as assessed one of the most effective solutions decreasing the energy generated, final yield, reference yield, performance ratio, capacity factor and monthly system efficiency. The economic greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat evaluation towchanged systemsthe is performance calculated using capital budgeting methods to determine economic in termsdecrease, of The aimDue of of this targets analysis and the economic evaluation ofheat two demand photovoltaic systems to the sales. tothestudy the climate conditions and building renovation policies, inprofitability the futureconnected could economic return of electricity generation. grid of 4.08 KWp, located in the same place in the roof of the research building at the Faculty of Sciences and Technologies prolonging the investment return period. The highest values in terms daily yield of (YF performance (PR=82%),technology. capacity factor (CF=21.93%), Mohammedia, Morocco. Thisofplant is final composed two=5.26h/day), types (mc-Si ofratio crystalline The main scope of this paper is to assess the feasibility of using the and heatpc-Si) demand –PV outdoor temperature function for heat demand levelized cost of electricity (LCOE=0.068€/kWh) and payback time (PB=12), have been recordedofbythe pc-Si systems solar module. Therefore, The experimental data has been recorded over one-year period (2015). The assessed parameters include theoftotal forecast. The technology district of Alvalade, located in Lisbon (Portugal), wasresearch used asprojects a case in study. ThePV district is consisted 665 this PV generated, system could be recommended, as well, in the future Morocco. energy final yield, reference yield, performance ratio, capacity factor and monthly system efficiency. The economic buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Keywords: Crystalline technology; performance ratio; final yield; capacity factor; capital budgeting; LCOE. evaluation of the tow systems is calculated using capital budgeting methods to determine economic profitability in terms of the scenariosPublished were developed (shallow, ©renovation 2019 The Authors. by Elsevier Ltd. intermediate, deep). To estimate the error, obtained heat demand values were economic return of electricity generation. This is an open access article under the heat CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) compared with results from a dynamic demand previously developedratio and (PR=82%), validated bycapacity the authors. The highest values in terms of daily final yield (YFmodel, =5.26h/day), performance factor (CF=21.93%), Selection and peer-review under responsibility of the scientific committee of the Symposium Forum, The results that when only weather change is considered, the margin ofbeen errorApplied could beEnergy someand applications levelized costshowed of electricity (LCOE=0.068€/kWh) and payback time (PB=12), have recorded byacceptable pc-Si solarfor module. Therefore, Renewable Energy Integration with Mini/Microgrids, REM 2018. scenarios considered). However, after introducing renovation (the error in annual demand was lower than 20% for all weather this PV technology could be recommended, as well, in the future research projects in Morocco. 1. system Introduction scenarios, the error value increased upperformance to 59.5% (depending on yield; the weather and factor; renovation scenarios combination Keywords: Crystalline technology; ratio; final capacity capital budgeting; LCOE.considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the demand is increasing burgeoning needs of aongrowing population and the decrease Energy in the number of heating hours ofrapidly 22-139hreaching during thethe heating season (depending the combination of weather and development of the international economy [1]. renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the The simplest energyThe technology, in terms of both design and installation, solar photovoltaic technology. It has an coupled scenarios). values suggested could be used to modify the functionis parameters for the scenarios considered, and 1. Introduction improve the accuracy of heat demand estimations.
Energy demand is increasing rapidly reaching the burgeoning needs of a growing population and the © 2017 The Authors. Published by Elsevier Ltd. development of the international economy [1]. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. technology, Tel. : +212-664-602-453. The simplest energy in terms of both design and installation, is solar photovoltaic technology. It has an Cooling. E-mail address : [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy * Corresponding author. under Tel. : +212-664-602-453. Integration with Mini/Microgrids, REM 2018. E-mail address : [email protected] 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy Selection andwith peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Renewable Energy Integration Mini/Microgrids, REM 2018. Integration with Mini/Microgrids, REM 2018. 10.1016/j.egypro.2019.01.006
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important CO2 mitigation factor. Moreover, solar photovoltaic provides high reliability and low maintenance cost. The installation of photovoltaic solar panels depends on environmental and meteorological data such as ambient temperature, solar radiation, the daily duration of Sun and depends on the economic and financial characteristics of the country [2.3]. Due to its geolocation, between northern latitudes of 36-421 and eastern longitudes of 26-451, Morocco has great potential in terms of solar energy [4.5]. The average annual solar irradiation is 3000 h, which corresponds to 8.2 h per day. Thus, the annual value of average solar irradiation reaches 2600kW h / m² / year [6.7]. The purpose of the present document is to build a credible comparison between the performances of two crystalline PV technologies of a PV installation connected to the grid during one year under the weather conditions of Errachidia city in Morocco. These systems have been analysed in terms of the total energy generated, final yield, reference yield, performance ratio, capacity factor, monthly system efficiency, payback time, and LCOE. 2.
Materials and Methods
2.1 Site information and system description Mohammedia, located at 33 ° 41 '23' North and -07 ° 23' 23 East, in Morocco, is a port city on the west coast of Morocco between Casablanca and Rabat in the region of Casablanca-Settat. It is located on the coast of the Atlantic Ocean, 24 km north-east of the economic capital of the kingdom of Morocco. The city of Mohammedia has a Mediterranean climate which is characterized by mild/wet winters and warm/dry summers. During summer time (May to October), the maximum average temperatures are between 23 and 29 °C but can occasionally reach 35 °C. On the other hand, the minimum, generally, is registered between 14 to 19 °C. The Sunshine duration reaches 9 to 10 hours per day. In winter (November to April), the maximum average temperatures are between 20 and 23 °C and minimum of 9 to 12 °C and can often drop to 2 °C in the morning. The sunlight hours during winter is 5 to 6 hours.
Fig. 1. The different installed technologies. The considered technologies are represented by two PV panel types, mono-crystalline and poly- crystalline, each part of the plant has a power of 2.04 kWp as shown in Fig. 1. The characteristics of these PV panels are shown in the table 1. All the solar PV modules are positioned in a fixed direction facing south at an inclined angle of 30°. The inverter model used in each plant is SB2000HF30 and its specifications are listed in Table 1. Table 1. PV panels properties and Inverter specifications Inverter specifications Trademark
SOLARWORLD
Inverter model
SB 2000HF30
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Model Solar cell Maximum power at STC
SUNMODULE pc-Si mc-Si 255Wp 255Wp
Max PV power Max voltage Nominal voltage
2100 W 700V 220V/230V/240V
Optimum operating voltage Optimum operating current Open circuit voltage Short circuit current
30.9V 8.32A 38 V 8.88A
31.4V 8.15A 37.8V 8.66A
voltage range Grid frequency; range Max. output current Max input current
180V-280V 50/60 Hz 8.3 A 12.0 A
Temperature coefficient of maximum power Module efficiency
-0.41%/°C
-0.45%/°C
Maximum efficiency
96%
15.2 %
15.2 %
1. Performance analysis of PV systems 2.2 Performance analysis methodology The main parameters for the evaluation of PV system performance were analysed using the following parameters:
Final yield (YF): The total AC energy during a specific period (day, month, or year) (EAC) divided by the rated power of the installation (PPV, Rated). This parameter is considered as crucial, during the whole experiment, to compare between the different PV systems installation [8]. The final yield is given as: Y F E AC / P pv . Rated
(1)
Reference yield (YR): The reference yield (YR) represents the ratio of the incident energy in the array plane HI (kWh/m2) to the reference irradiance (G =1kW/m2) [9]. The reference yield is given by: YR H I / G
(2)
Performance ratio (PR): The performance ratio is the final yield divided by the reference yield. It provides important information about the overall effect of the losses [10]. The performance report (PR) is given as follows: (3) PR Y F / Y R
System efficiency: The monthly system efficiency (ηsys.m) describes the ratio of monthly energy output of the system to the total energy collected from the PV field [11]. It is given by: s ys , m E AC , m /( H I A a )
(4)
Where Aa (m2) is module (array) total area.
Capacity factor (CF): The capacity factor (CF) informs about the relationship between the actual annual electrical energy and the electrical energy that could be generated if the solar photovoltaic system operated with its total nominal power installed 24 hours a day over a period of one year [12]. It is expressed as: (5) CF E AC /( P pv . Rated 8760 )
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2.3 Economic Analysis The comparative economic analysis is carried out by calculating cash flow (Ci), NPV (Net Present Value), and the LCOE for the tow PV systems considered. The NPV is the difference between the value of revenues and the expenses incurred for an investment up to the date the investment was made [13]. A positive value of the NPV indicates that there is a positive surplus, so it is a financial gain for the investor, and for a negative value, a financial loss for the investor is reported. n (6) NPV D t 1 C i /(1 i ) t Where D is the capital outlay, i is the interest rate, and n is the project life.
The LCOE is an evaluation of lifetime energy cost and lifetime energy production [14]. The LCOE is given by: LCOE D
N
ES n 1
N
i
/(1 r ) n / EP (1 DR ) n /(1 r ) n n 1
(7)
Where D is the capital outlay, ES is the expenses, EP represents the energy production, r is the discount rate, DR is the degradation rate, and N is the life project.
The economic parameters were performed based on several assumptions: Item description, Inflation rate, discount rate, degradation rate and project life (Table 2) Table 2. Summary of various interest rates used in the economical study Item description Inflation rate Discount rate degradation rate Project life
3.
Value 1.6% 2.5% 0.35% 25
ref [19] [20] [20] ---
Results and discussion
The figure 2 represents the average daily yield (YR) and the related average final yield (YF) generated by the two PV systems during a period of one year. Obviously, the daily reference yield varies between 4.38 h/day and 6.87 h/day between December and August. The average annual value of the daily (YR) is approximately 5.96 h/day. The minimal daily final yield is predicted in December, for pc-Si technology, the value recorded is 3.53 h/day and 3.47 h/day for mc-Si technology. While the maximal daily final yield is predicted in May and the values are 5.65 h/day for pc-Si technology and 5.56 h for mc-Si technology.
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6
5.00
5
4.00
4
3.00
3
2.00
2
1.00
1
0.00
0
YF(mc‐Si)
YF(Pc‐Si)
25.00
80
20.00
60
15.00
40
10.00
20
5.00
0
0.00
CF(%)
6.00
100
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
7
PR(%)
7.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
YF and YR(h/day)
According to the results shown in figure 3, the highest values of the monthly performance ratio and the capacity factor, have been registered by pc-Si photovoltaic system. Moreover, the maximum performance ratio value has been recorded in November (low temperature and irradiation), while the minimum value of the same parameter was displayed in August (high temperature and irradiation). Furthermore, the maximum value for capacity factor for the two PV systems installation pc-Si and mc-Si reached respectively 23.52% 23.18%. The minimum values of the same parameter have reached 14.69% and 14.47% respectively for the PV systems pc-Si and mc-Si.
YR
Fig. 2. average daily YF and average YR
PR(mc‐Si)
PR(pc‐Si)
CF(mc‐Si)
CF(pc‐Si)
Fig. 3. Variation of monthly PR and CF.
The monthly system efficiency as seen in the fig 4 varied from 10.20 % to 13.73 % for pc-Si and from 10.59% to 13.60% for mc-Si. These results indicate that among the two PV systems installation, pc-Si system displayed the highest value. Accordingly, we note that the pc-Si technology has a superior performance compared to the mc-Si technology even if both types of panels have the same performance and rated power under STC (table 1). However, the temperature coefficient of power is different. The temperature coefficient indicates that as the temperature increases and the modules heat up, the output power of the solar panel decreases, which justifies this difference between the two technologies. Thus, it can be concluded that a higher negative value of the temperature power coefficient of the mc-Si photovoltaic panels, compared to that of pcSi panels in this study, leads to a decrease in the output power in the photovoltaic plant. 14.00 13.50 12.50
15
200
12.00 11.50
10
100
11.00 10.00
20
300
13.00
10.50
25
400
5 0
0 ηsys(mc‐Si)
ηsys(pc‐Si)
Fig. 4. Monthly average system efficiency.
mc‐Si Error mc‐Si Simulated
pc‐Si Error mc‐Si Measured
Fig. 5. Comparison of recorded data and simulation results
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5000 4000 3000 2000 1000 0 ‐1000 ‐2000 ‐3000 ‐4000 ‐5000
€6,000.00
0
2
4
6
8 10 12 14 16 18 20 22 24
pc‐Si
mc‐Si
Net present value()
Accumulated Cash Flow (€)
The real data of the electrical energy generated by the PV systems connected to the grid were obtained with a monitoring system which allows the recording of the average productivity data every five minutes. The energy output from the inverters has been recorded for a whole year from 1st January 2015 until December 2015. Real data have been measured and compared with the simulated results as shown in fig 5. The difference gap between the estimated values and measured values, during the study period, varies between 1% in May 2015 and 16% in August/October 2015 for Poly-Si technology and between 5.61% in May 2015 and 21% in August 2015 for Mono-Si technology. The results show that there is an agreement between what is estimated and what is produced with an exception during the months of August and October where the error has been reported to be significantly high, which is reasonably explained by the difference in the irradiation data used in the simulations (from the NASA database).
€4,000.00 €2,000.00 €0.00 (€2,000.00) (€4,000.00)
Years
Fig. 6. Comparison of accumulated Cash Flows.
0%
10%
20%
Discount rate(%) mc‐si
pc‐si
Fig. 7. Comparison of Net Present Value
The accumulated cash flows for the investment are shown in the figure 6. This graph demonstrates the Payback time of the investment. All cash flows are positive from the first year to about 12.63 years for the mc and 12 for the poly after recovering the capital outlay. This occurs when the accumulated cash flow curve reaches zero. From this point, the curve enters in the positive quadrant because it has been fully recovered the capital outlay of the investment. Figure 7 shows the NPV for tow PV solar plants installed in Mohammedia (Morocco). The NPV is calculated using equation 1 for several discount rates ranging from 1% to 25 %. As expected, with low discount rates, 1% to 6.25 % for the mc-Si panels and 1 % to 6.46% for the pc-Si panels, a positive value of NPV is obtained. Which means that the PV installation provides net benefits to the investor. For higher discount rate, the value the NPV turns negative, which means that the PV installation would produces losses for investors, so in that condition the investment should not be implemented. The NPV reaches to zero when the discount rate matches the internal rate return (6.34% for mcSi and 6.65% for pc-Si) on investment. Table 3. Comparison of Levelized Cost of Energy for mc-Si and pc-Si PV systems at different discount rate
Discount rate (%)
LCOE (€/kWh) mc-Si
LCOE (€/kWh) pc-Si
2.5 5 7 10 15
0.077 0.096 0.113 0.141 0.191
0.075 0.094 0.11 0.137 0.185
Table 3 shows the Levelized Cost of Energy for the two types of PV systems (mc-Si and pc-Si) for different values of
30%
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the discount rate. Considering a standard discount rate of 2.5%, the LCOE for mc-Si and pc-Si PV systems are 0.077€/kWh and 0.075 €/kW h, respectively. The LCOE takes the value of 0.096€/kWh (mc-Si) and0.094 €/kWh at a discount rate of 5%. 4.
Conclusion
This paper evaluates the performance analysis and economic evaluation of a solar photovoltaic system connected to a 4.08 kWp grid designed to supply power to the Errachidia Faculty of Science and Technologies in Morocco. Tow types of PV (mc-Si, pc-Si) were studied and simulated. To choose the most appropriate option, the total energy generated, final yield, reference yield, performance ratio, capacity factor and monthly system efficiency, payback time, and levelized cost of energy have been examined and compared for the tow installed technologies. The main conclusions are: • The YF, PR, and CF of the mc-Si system are 5.17 h, 80.66%, and 21.56% respectively. • The YF, PR, and CF of the pc-Si system are 5.26h, 82.00%, and 21.93% respectively. • The monthly system efficiency varied between 10.59% and 13.60% for mc-Si and between 10.20% and 13.73% for pc-Si.
Tracking the accumulated cash flow versus time allows the computation of the payback, which is approximately 12.63 years for mc-Si, and 12 years for pc-Si.
The levelized cost of energy is 0.077€/kWh for mc-Si and 0.075€/kWh for pc-Si.
We conclude that the system using pc-Si technology has a slightly higher performance compared to the mc-Si technologies. Acknowledgements The authors would like to thank’’Institute for Research in Solar Energy and New Energies (IRESEN)’’ for completing the project PROPRE.MA References [1] Janis Latvels, Raitis Grzibovskis, Aivars Vembris, Dagnija Blumberga. Improvement of Solar PV Efficiency.Potential Materials for Organic Photovoltaic Cells. Environmental and Climate Technologies (2013). [2] Karaveli AB, et al., Comparison of large-scale solar PV (photovoltaic) and nuclear power plant investments in an emerging market, Energy (2015). [3] Marwan M. Fawzy et al. / Energy Procedia 113 (2017) 428 – 433 [4] ELAMIM, A.; HARTITI, B.; BARHDADI, A.; HAIBAOUI, A.; LFAKIR, A.; THEVENIN, P. PHOTOVOLTAIC OUTPUT POWER FORECAST USING ARTIFICIAL NEURAL NETWORKS. Journal of Theoretical & Applied Information Technology. 8/15/2018, Vol. 96 Issue 15, p5116-5126. 11p. [5] El Fadili, A., Giri, F., & El Magri, A. (2014). Reference voltage optimizer for maximum power point tracking in triphase grid-connected photovoltaic systems. International Journal of Electrical Power & Energy Systems, 60, 293-301. [6] A.Ghoshetal./Solar Energy Materials & Solar Cells157 (2016)1–9 [7] Tyagi VV, Rahim NAA, Rahim NA, Selvaraj JAL.Progress in solar PV technology: research and achievement. Renew Sustain Energy Rev 2013; 20:443–61. [8] Al-Otaibi, A., 2015. Performance evaluation of photovoltaic systems on Kuwaiti school’s rooftop. Energy Convers. Manage. 95, 110–119. [9] Sharma V, Chandel SS. Performance analysis of a 190 kWp grid interactive solar photovoltaic power plant in India.Energy 2013;55:476e85 [10] Rehman S, El-Amin I. Performance evaluation of an off-grid photovoltaic system in Saudi Arabia. Energy 2012; 46:451e8. [11] Adaramola, M., Vagnes, E., 2015. Preliminary assessment of a small-scale rooftop PV grid tied in Norwegian climatic conditions. Energy Convers. Manage. 90,458–465. [12] V. Sharma, S.S. Chandel / Energy 55 (2013) 476e485 [13] I. GUAITA-PRADAS and B. MARÍ SOUCASE, ‘Endorse of renewable energy plants, still an alternative investment in Spain?’ SOP Transactions on Economics Research (ER) Scientific Online Publishing, Vol. 1, Num. 2, pp.1-9. (2014) Scientific Online Publishing. [14] I. GUAITA-PRADAS and B. MARÍ SOUCASE, Profitability and sustainability of photovoltaic energy plants in Spain, Int. J. Sustainable Economy, Vol. 7, No. 3, 2015 [15] http://www.centralbanknews.info/ [16] AbderrazzakElamim ,Bouchaib Hartiti,Amine Haiboui, Abderrazak Lfakir, PhilipeThevenin,Performance evaluation and economical analysis of three photovoltaic systems installed in an institutional building in Errachidia, Morocco, Energy Procedia 147C (2018) pp. 121-129.