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Performance analysis of 954,809 kWp PV array of Sheikh Zayed solar power plant (Nouakchott, Mauritania)
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ORIGINAL RESEARCH ARTICLE
Renewable Energy Focus Volume 32, Number 00 March 2020
Performance analysis of 954,809 kWp PV array of Sheikh Zayed solar power plant (Nouakchott, Mauritania) Mohamed El Hacen Jeda,*, Razika Ihaddadenea,*, Nabila Ihaddadenea,*, Cheikh ELBanany Elhadji Sidib and Menny EL Bahc a
Department of Mechanical Engineering, Mohamed Boudiaf University, M’Sila, Algeria Centre International de Formation et de recherché en Energie Solaire (CIFRES)-Ecole Supérieur Polytechnique-UCAD, BP 5085 Dakar-Fann, Senegal c Unité Énergies renouvelables, Département de Physique, Université de Technologie et de Médecine (UDTM), BP 880 Nouakchott, Mauritania b
Abstract
Amid all renewable energies, solar PV is of particular interest, mainly in Africa. Mauritania is an example of African countries which, gives great concern to produce electricity via PV installations. This study is carried out on the performance evaluation of a 954,809 kWp photovoltaic array made up of microamorphous silicon situated in Nouakchott (capital of Mauritania) at Sheikh Zayed solar power plant. The measures of one year of operation from September 2014 to August 2015 were evaluated according to the IEC 61724. The results obtained demonstrate that the photovoltaic array performances depend on both insolation and environmental conditions. The array capture loss ranges vary from a minimum value of 1.63 h/day to a maximum value of 2.46 h/day. So, the system loss is relatively stable, with an average value of 0.12 h per day. The monthly performance ratio varies from 0.61% in August to 0.71% in November, with a monthly average value of 0.66%. The monthly average capacity factor achieves its maximum and minimum in October (20.54%) and January (11.66%), respectively. The energy generated by the PV array (Edc) and the energy fed to the utility grid (Eac) during November moth, are affected by the insolation and the module temperature. However, wind speed variation does not influence those energies. Two linear models, depending on insolation and module temperature, are proposed for the evaluation of Edc and Eac during this month. These laters present a coefficient of determination (R2) of 0.96. Introduction Energy is a key element of the essential foundations of the prosperity of modern civilization and economic development. With the increase of the world population, the demand for energy increases considerably. Nowadays, the return to renewable energies has become a necessity to contribute to civilization and development.
*Corresponding authors El Hacen Jed, M. ([email protected]), Ihaddadene, R. ([email protected]), Ihaddadene, N. ([email protected])
Among all renewable energies, solar photovoltaic (PV) is of particular interest in Africa since it has a large solar deposit. Mauritania is an African country with a good solar potential varying between 1900 and 2200 kW h/m2/year [1]. This country is mostly reliant on fossil fuels. Fossil fuels account for about 66% of the primary energy consumption, while the remaining 34% comes from biomass, which is mostly used for cooking and heating. Mauritania, under its 2016 Accelerated Growth and Shared Prosperity Strategy, considers energy to be a priority for poverty reduction. Thus, Mauritania’s government is working on expanding its
1755-0084/ã 2019 Elsevier Ltd. All rights reserved. https://doi.org/10.1016/j.ref.2019.11.002
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electricity supply and encourages investment in the renewable energy sector to boost the economy of the country [2]. Electricity in Mauritania is mainly generated through thermal diesel engine generators. Due to increasing energy demand and insufficient installed power capacity, total energy consumption exceeds national energy production by about 35%. Hence, fossil fuels must be imported from out to overcome people’s needs. The policy adopted by Mauritania aims to meet the growing demand for energy with fewer fuel imports by integrating renewable energies as a free source of energy. Indeed, electricity demand is growing by 10% a year, mainly due to rising industry and domestic demand. In a highgrowth scenario of the electricity sector, grid-connected demand (excluding mining activities) is projected to grow by 450% between 2010 and 2030 [3]. For this, the need for sound policies to lead the future demand expansion in electricity is necessary. Indeed, planned investments in national electricity production, including several new wind and solar projects, would increase the contribution of renewable energies to 36% by 2020 and 41% by 2030 [4]. The solar power plant, Sheikh Zayed, located in the capital of Mauritania, Nouakchott, is considered to be the largest solar photovoltaic power plant in Africa. This powerhouse was built in the context of the Mauritanian state policy that encourages all renewable clean energy projects. It produces 15 MW, which represents about 10% of the total load of the city of Nouakchott. This project was developed by Masdar, funded by the United Arab Emirates government and designed by ENVIROMENA. This latter is owned by the Mauritanian electricity company SOMELEC [5]. The performance of a grid-connected PV system depends on two key factors, namely the technical and environmental factors. The technical factors include the technology of the photovoltaic cells [6], those of the inverters, and the type of installation used. While, the environmental factors depend on weather conditions such as; solar radiation, ambient temperature, humidity, wind speed [7], and dust accumulation [8,9].When Solar power plants are installed in arid zones, where the severe external conditions are penalizing (heat, humidity, salinity, dust), they deteriorate quickly. Indeed, the harsh outside conditions accelerate the aging of the photovoltaic modules when compared to those installed in temperate climatic zones [10,11]. Moreover, dust accumulation on the photovoltaic module reduces the transmittance of the PV module glass and consequently degrades the PV module’s power output [12,13]. The study of photovoltaic solar power plants, according to the IEC 61724 standard, becomes imperative to determine the performance of the PV systems (efficient operation or not). In addition, the successful integration of a grid-connected PV system necessitates the knowledge of their operational performance under site climatic conditions [14]. Monitoring input parameters, when studying solar plant performance, yields several advantages such as optimal sizing and survival of the power plant. The knowledge of global horizontal irradiance and the ambient temperature of a site helps us to predict the energy gain, making the idea of building or not the photovoltaic installation in this location. Moreover, the study of the plant performance is of use in identifying the operational uncertainty, which helps in improving its yield [15]. A number of studies has been carried out on the evaluation of the performance of solar PV plants installed around the world [16–21]. Indeed, Ayompe et al. [16] studied the monthly, seasonal, and annual performance of 1,72 kWp grid-connected PV systems 46
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installed in Dublin (Ireland), from November 2008 to October 2009. They found that the annual average daily array yield, reference yield, and final yield of the installed solar plant were of 2,62 kW/kWp/day, 2,85 kW h/kWp/day, and 2,41 kWh/kWp/ day, respectively. In addition, the annual average daily PV module efficiency, system efficiency, and inverter efficiency were about14,9%, 12,6%, and 89,2%. Moreover, the annual average daily capture losses and system losses were about 0,22 h/day and 0,23 h/day, respectively. The capacity factor and the annual average daily performance ratio were about 17,74% and 81,5%, respectively. Attari et al. [19] studied the evaluation of a grid-connected PV system installed on the government-building roof located in Tanger (Morocco). This study was performed for one year from 1st January to 31st December. The PV system studied is composed of 20 modules with 250 Wp and one inverter. The final yield and the performance ratio were found to vary from 1,96 to 6,42 kW h/kWp and 58%–98% respectively. The annual capacity factor of this system was about 14,84%. ski and Staszkiewicz [20] presented an analysis of a phoWichlin tovoltaic installation built on a roof car park located in eastern Cairo (Egypt). The annual yield of energy supplied into the grid was about 587 MW h per year. The average annual final yield was about 3,7 KWh/KWp. Moreover, the average annual performance ratio was 0,62 and the total losses of this installation were roughly 30%. Daher et al. [15] studied the performance of a 302,4 kWp gridconnected PV system in Djibouti. They analyzed the first 4 years of this system for coastal, desert maritime climate zones according to the IEC 61724. The results found showed that the monthly average daily array yield and the final yield were about 5,1 kWh/kWp and 4,7 kW h/kWp, respectively. The average performance ratio of the PV arrays and the global grid-connected system were 90% and 84%, which are in agreement with the monthly average daily PV module efficiency (12,68%) and the system efficiency (11,75%). This study aims to analyze the performance of the 954.809 c photovoltaic system located in Nouakchott, Mauritania, according to IEC 61724 standard. This research document is organized as follows: in Section ‘‘Material and methods’’, the description of Sheikh-Zayed power station and the performance evaluation of PV array are presented. The results found and their discussion are given in Section ‘‘Results and discussion’’. Finally, a conclusion, with the important results found, closes this investigation.
Material and methods Description of Sheikh-Zayed power station Sheikh-Zayed power station is located in the north of Nouakchott in Mauritania at a latitude of 18 150 N and longitude of 15 980 W. Figure 1 shows a photo of this solar power plant. Sheikh Zayed Solar Power Plant was one of the largest solar power installations in Africa when installed. It is the first such utility-scale installation in Mauritania, supplying 10 percent of Mauritania’s grid capacity. It produces 25,409 MW h of electricity annually and releases approximately 21,225 t of carbon dioxide per year. The plant was installed in March 2013 with 15 MWp, comprising a fixed ground-based array of 290826 PV modules with two different thin-film technologies (amorphous silicon and micro-amorphous silicon) each with a different power rating. The modules are oriented due south and inclined by 10 .
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FIGURE 1
Sheikh Zayed solar PV plant. FIGURE 3
The photovoltaic modules generate a direct current (DC) from the incident solar radiation impinging their surfaces. Since the power distribution network and electrical loads operate on alternating current (AC), the inverters are used to convert the direct current (DC) from the photovoltaic modules into alternating current (AC). Moreover, alternate voltage is always kept constant by the inverter according to the limits of the distribution network. However, the supplying current varies depending on the incident solar radiation. The AC output of the inverter is at low voltage (LV) that should be raised to a medium voltage (MV) of 33 kV by means of step-up transformers. The transformers are connected to the switchgear in a ring configuration that terminated at the North substation. This latter is connected to the SOMELEC electricity distribution network [5]. The conversion chain is shown in Figure 2. Sheikh-Zayed power plant is composed of eight (8) power block stations designated as Room. Each power block is composed of two arrays. All power blocks have two inverters except one, which possesses three inverters. In other words, the eight rooms are as follows; Room A (Inverter 1, Inverter 2), Room B (Inverter 3, Inverter 4), Room C (Inverter 5, Inverter 6), Room D (Inverter 7, Inverter 8), Room E (Inverter 9, Inverter 10), Room F (Inverter 11, Inverter 12), Room G (Inverter 13, Inverter 14), Room H (Inverter 15, Inverter 16 and Inverter 17).This investigation was devoted to the study of the photovoltaic array 1 of Sheikh-Zayed power station, as shown in Figure 3. It contains a total of 1872 Masdar photovoltaic modules, each with an area of 5,72 m2, and peak power of 510 Wp. The technical characteristics under standard conditions of the PV modules used in this array are regrouped in Table 1. Their technology
Schema of the arrays of Sheikh-Zayed solar PV plant.
is that of micro-amorphous silicon (mc-Si) thin film. In addition, the modules are connected in series to increase the system voltage to the desired level, in order to maximize the power peak. The system is designed for a maximum rating of 1000 V, where three (3) modules are connected in series to form a series. Two (2) series connected in parallel constitute a circuit, and three circuits joined in parallel form a string. Peak power of 954,809 kWp is supplied from104 strings in the PV array (1). The DC/AC inverter, which is used in the array 1, is supplied by SMA Solar Technology (760 kW). The transformer (1600 kVA), made by CELME, intensifies the low voltage output of the inverters to a medium voltage at 33 kV. It is connected to two SMA 760 kW inverters [22]. A monitoring system is used to control the inverters and report performance parameters, system status, and weather data to a local or remote user. The data collected is averaged over 5-min intervals. These data serve to calculate hourly, weekly, monthly, and yearly performance parameters. Our study covers a period of one year from September 1, 2014, to August 31, 2015. The data used are module temperature, wind speed, solar insolation, energy generated by the PV array system (Edc), and the energy output (Eac).
Performance evaluation of PV array Performance parameters of PV array are established by the international energy agency. They are described in IEC standard 611724. As noted in the literature [16–18], the normalized
FIGURE 2
Conversion chain in the solar PV plant.
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TABLE 1
Masdar 510 PV module characteristics under (STC). PV module made of
Impp (A)
Vmpp (V)
Isc (A)
Voc (V)
Pmpp (Wp)
(mc-Si)
2,24
227,7
2,64
292
510
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indicators gather energy output, array yield, final yield, reference yield, module efficiency, inverter efficiency, system efficiency, performance ratio, capacity factor, and energy loss (array capture loss and system loss).
1. Energy generated by the PV array system (Edc) The total daily recorded value of DC power output (Edc,d) is given by the following equation: Edc;d ¼
t¼Trp X
Pdc T r
ð1:1Þ
4. Array yield of PV field (Ya) The efficiency of the PV field (Ya) is defined as the ratio between the total generated energy Edc (kWh) by the PV rows for a defined period (day, month or year) and the nominal power P0 (kWc) of the rows under the standard conditions (STC: irradiation = 1000 W/m2, ambient temperature = 25 C and AM 1.5-G reference spectrum). The daily efficiency of the PV field (Ya,d) is given by the following equation: Y a;d ¼
t¼1
The monthly DC energy generated (Edc,m) is given as: Edc;m ¼
N X
Edc;d
ð1:2Þ
d¼1
where; Tr is the recording time interval; Trp the reporting period; N the number of operating days of the plant per month; Pdc is the DC power (result of the current times the voltage). It is given as follows: Pdc ¼ V dc I dc
ð1:3Þ
Edc;d PpvðratedÞ
ð4:1Þ
The monthly efficiency of the PV field (Ya,m) is given by the following equation: X N 1 Y a;m ¼ Y a;d ð4:2Þ N d¼1
5. Final yield of the PV system or system yield (Yf) The final efficiency (Yf) corresponds to the total energy produced by the PV system Eac (kWh) per the installed nominal power P0 (kWp). This quantity represents the number of hours during which the PV field should operate at its rated power. The daily final efficiency (Yf,d) and the monthly final efficiency (Yf,m) are given by the following equations:
2. Energy output or energy fed to the utility grid (Eac)
Y f ;d ¼
ð5:1Þ
The energy generated by the PV system (Eac) is the measure of the energy across the inverter output terminals, recorded every 5-min by the data logger. The total daily recorded value of AC power output (Eac,d) is given by the following equation:
Eac;d PPVðratedÞ
Y f ;m ¼
X N 1 Y f ;d N d¼1
ð5:2Þ
Eac;d ¼
t¼Trp X
Pac T r
ð2:1Þ
6. Pv module efficiency (hpv)
ð2:2Þ
The module efficiency or energy efficiency (hpv) presents the effective energy generated by the module with respect to the available radiation. The daily PV array efficiency is given by the following equation:
t¼1
The monthly AC energy generated (Eac,m) is given as: Eac;m ¼
N X
Eac;d
d¼1
hpv;d ¼
If the AC power given as follows: Pac ¼ Vac Iac:
(2.3)
3. Reference yield (Yr) The reference efficiency (Yr) is the ratio between the total amount of solar radiation Ht (kWh/m2) intercepted by the surface of the PV solar panels and the amount of reference radiation G0 (1 kW/m2). It depicts the number of hours during which the illumination is equal to that of the reference. Yr defines the solar resource of the PV system. It is given by: Yr ¼
48
Ht G0
Edc;d 100 G Am
ð6:1Þ
where; Edc,d is the dc energy generated by the PV array system; G presents the global solar irradiation; Am presents the area of the PV module. The monthly average PV module efficiency is calculated as follows: hpv;m ¼
Edc;m 100 G Am
ð6:2Þ
7. Inverter efficiency (hinv) ð3Þ
Inverter efficiency (hinv) supposed to be higher than the module and system efficiencies. It is also called conversion efficiency,
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expressed as the ratio between the AC power generated by the inverter and the DC power produced by the photovoltaic panel system. The monthly inverter efficiency is given by the following equation: hinv;m ¼
Edc;m 100 Eac;m
ð7Þ
8. System efficiency (hsys) The photovoltaic system efficiency is related to the balance of the systems comprising the PV generator and inverter module. The monthly system efficiency can be calculated by applying the following equation: hsys;m ¼ hpv hinv
ð8Þ
9. Standardized performance index (PR) The performance ratio (PR) indicates the overall effect of the losses in the energy production of the rows of a PV system. The PR values indicate how well a PV system approaches the ideal performance under real-world operating conditions. PR is defined as the ratio between the final yield and the reference yield. It is a dimensionless quantity, given as follows: PR ¼
Yf Yr
ð9Þ
10. System losses by conversion (Ls) The losses of the system by conversion (LS) are due to the inverter conversion losses (DC-AC current) and are defined by the difference between the yield of the PV field Ya and the final yield Yf. The system losses are given as follows: Ls ¼ Y a Y f
ð10Þ
11. Array capture loss (Lc) The array capture loss (Lc) is defined by the difference between the reference yield and the array yield of the PV field. It represents the losses due to panel temperatures, wiring, partial shading, spectral losses, soiling, errors in the search for the maximum power point, conversions (DC-AC), etc. Lc is given by the following equation: Lc ¼ Y r Y a
4.51 kWh/m2/day (January) to a maximum of 7.12 kW h/m2/day (October and April) as shown in Figure 4. The seasonal daily average insolation for spring (March–May), autumn (September– November), summer (June–August), and winter (December–February) is 7.03 kW h/m2/day, 6.76 kW h/m2/day, 6.73 kW h/m2/day and 5.19 kW h/m2/day, respectively. Thus, the insolation varies according to the seasons. Indeed, the spring, summer, and autumn seasons show higher insolation compared to the winter season. Moreover, monthly wind speed variation is also illustrated in Figure 4. As seen, wind speed varies from 1.26 m/s recorded in November to 3.43 m/s noted in July. The monthly variation of PV module temperature during the studied period is illustrated in Figure 5. The module temperature varies from 26.57 C, registered in November, to 41.60 C noted in September. The monthly average variation array yield, final yield, and reference yield are depicted in Figure 6. The monthly average final yield varies from a minimum of 2.80 h/day (January) to a maximum of 4.93 h/day (October). The final annual yield is 4.26 h/day. Almost the same value as that of a Moroccan solar power station (4.4 h/day) [19]. The final annual yield found is higher than that of Egypt (3.7 h/day) [20], Spain (3.8 h/day) [21], and Ireland [16] (2.41 kWh/kWp/day). The monthly average reference yield follows the same pace as the final yield. It varies between a minimum of 4.51 h/day, recorded in January, and a maximum of 7.12 h/day registered in October, as noted in Figure 6. Moreover, the monthly average array yield has the same gait as the two cited yields (reference and final yields). It varies from a minimum of 2.89 h/day, recorded in January, to a maximum of 5.06 h/day registered in October. The yield values, recorded for the month of January, are low because of its low incident solar radiation (see Figure 4). Furthermore, the reference yield is proportional to the insolation. During the year of study, a difference between the array yield and the final yield is observed. Indeed, the final yield takes into account the DC/AC conversion losses produced in the inverter.
ð11Þ
12. Capacity factor (CF) The capacity factor (CF) is a parameter for representing the energy delivered by an electrical power distribution system. If the system delivers full rated power continuously, its CF will be unity. It is defined as the ratio of actual annual energy output to the amount of energy the PV system can deliver at its rated capacity for 24 h per day during a year. The capacity factor is given as follows: CF ¼
Y f ðannualÞ 24 365
ð12Þ
Results and discussion In the current investigation, the meteorological data and the performance of the studied array were analyzed. The monthly daily average insolation on the PV array varies from a minimum of
FIGURE 4
Variation of monthly average daily insolation and wind speed for the studied period in Nouakchott.
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ORIGINAL RESEARCH ARTICLE FIGURE 5
Monthly average variation of the PV module temperature of Sheikh-Zayed power plant for one year of study.
FIGURE 6
FIGURE 7
Monthly variation of daily average array capture loss (Lc) and system loss (Ls) of Sheikh-Zayed power plant (array1) during one year of study.
FIGURE 8
Monthly average array yield (Ya), reference yield (Yr) and final yield (Yf ) of Sheikh-Zayed power plant during one year of study.
Monthly variation of performance Ratio of Sheikh-Zayed power plant (array1) for one year of study.
Figure 7 shows the monthly variation of the array capture loss and the system loss of Sheikh-Zayed power station plant (array 1) during one year of study. The array capture loss is greater than that of the system, which regroups all kinds of losses occurring in the solar conversion process from PV modules to the inverters. The array capture loses vary from a minimum of 1.63 h/day, noted in April, to a maximum of 2.46 h/day registered in February. Important losses are observed in summer. They are directly related to the dust deposit on the panels and to their high temperatures during this period. The system loss is relatively stable, with an average of 0.12 h per day. Precisely, it varies from 0.088 h/day to 0.32 h/day. Thus, the inverters of the PV system perform well in DCAC conversion. The average system losses, of an Egyptian solar plant, are about 0.28 h/day [20], which are higher than those found in the current study (array 1). Moreover, the system losses of a Moroccan solar plant vary between 0.14 h/day and 1.89 h/day, and the capture
losses range from 0.025 h/day to 0.76 h/day [19]. Therefore, the system losses of Morocco solar power plant are higher than those of array 1 of Sheikh-Zayed power plant. Figure 8 shows the monthly evolution of Performance ration (PR). As seen, it ranges from 0.61% to 0.71% recorded in August and November, respectively. Thus, the monthly average Performance Ratio of array 1 is 0.66%. This value is in the range of (60%– 90%) reported for the solar power plants [16]. It is lower than the performance ration of Morrocan (0.79) [19] and Djiboutian (0,84) [15] solar plant. However, it is higher than that found for an Egyptian solar plant (0.62) [20]. Generally, a PR greater than 0.8 corresponds to a system whose performance approaches the ideal performance under STC conditions. In addition, a system with a PR less than 0.7 must be suspected to failure or malfunction from system components (panels, inverters, etc.) or environmental parameters (nearby shading, an excessive dusting of panels, etc.).
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FIGURE 9
Monthly variation of the capacity factor of Sheikh-Zayed power plant (array1) for one year of study.
Figure 9 shows the monthly evolution of the daily capacity factor for one year. The capacity factor varies in the same manner as the final yield, which evolves like the generated energy Eac. The monthly average capacity factor is at its maximum in October, amounting to 20.54% where the final yield is also the highest one, in the order of 4.93 h/day. Moreover, it is low in January with a value of 11.66%, where the final yield is also low at about 2.80 h/ day. The annual average capacity factor is 17.74%. It is in the norms (0.10–0.20), as mentioned by Ayompea et al. [16]. The capacity factor in the study case of Morocco is 14.84% [19], which is lower than that found in our study. Figure 10 shows the average monthly changes in the efficiencies of the PV module and the system. The monthly average PV module efficiency ranges from a minimum of 5.61% (May) to a maximum of 6.49% (November). The monthly average system
FIGURE 10
Monthly variation of the PV System efficiency of Sheikh-Zayed power plant (array1) during one year of study.
FIGURE 11
Monthly variation of the Inverter efficiency of Sheikh-Zayed power plant (array1) during one year of study.
efficiency follows the same pace as the PV module efficiency. It ranges from a minimum of 5.46% recorded in May to a maximum of 6.32% reached in November. The monthly average inverter efficiency varies from 96.96% in January to 97.44% in October, as noted in Figure 11. This efficiency has an annual average of 97.20%. Noting that the inverter efficiency lies in the range of (95%–98%) at actual operating conditions, as reported by Ayompea et al. [16]. The annual average inverter efficiency, in the case study of Morocco, is about 96.7% [19]. It is lower than that found in our study. So, this result shows that the inverter of Sheikh-Zayed power plant (array1) is in very good working condition according to the standards and compared to other working inverters. For the current plant installed in Nouakchott, this drop in the performance ratio can be explained by certain environmental factors such as fairly high temperatures and dust. In addition, the disrespect of the optimal tiltangle of the photovoltaic panels (10 instead of 15 ), to avoid the effect of sharing the modules, has a significant effect on the reduction of the performance of the studied installation. This disrespect of the optimal tilt angle is also due to the economic gains made when buying the necessary cables to separate each row from the other. Moreover, the high temperature of the rooms, where the inverters are placed, leads to increase system losses, and consequently, the automatic shutdown of the inverter. Although these rooms are equipped with air conditioners, this does not always work (insufficient cooling load). Therefore, regular maintenance of these devices may contribute to increasing the performance of the system. It is noted that the performance index PR of the photovoltaic plant (array 1) during one year of study takes the highest value in November. Thus, during this month, the photovoltaic plant has worked well. In order to determine the effect of the meteorological conditions (insolation G, module temperature Tm and wind speed V) on the performance parameters (energy generated by the PV array system (Edc), energy fed to the utility grid (Eac), array yield of PV field (Ya), reference yield (Yr), final yield (Yf), PV module efficiency (hpv), system efficiency (hsys), inverter efficiency (hinv), 51
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TABLE 2
Statistical analysis on the effect of meteorological conditions on PV array 1 performance for November month.
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Parameters
R2 (G)
R2 (Tm)
R2 (V)
Eac Edc Ya Yr Yf hpv hsys hinv
0.9536 0.9613 0.9512 1 0.9507 0.6195 0.3893 0.3883
0.8405 0.8314 0.8257 0.7933 0.8269 0.5877 0.4931 0.4948
0.4231 0.4237 0.4232 0.3598 0.4237 0.4068 0.4592 0.4605
(Eac,G) (Edc,G) (Ya,G) (Yr,G) (Yf,G) (hpv,G) (hsys, Tm) (hinv, Tm)
FIGURE 12
Variation of Eac energy as a function of insolation for 5 min step interval.
FIGURE 13
the capture losses (Lc), and system losses (Ls)) during this month, a statistical analysis was performed. The coefficient of determination of the effect of meteorological conditions on each parameter and the dominant influence parameter were determined. The results obtained are regrouped in Table 2. It is noted that the insolation G has a greater effect than the module temperature and the wind speed on Eac, Edc, Ya, Yr, Yf, hpv during this month. On the other hand, the effect of the module temperature is more important than the insolation on the hinv and hsys. The wind speed has a less important effect than the insolation and the module temperature on Eac and Edc. Indeed, it presents, a determination coefficient of 0.4231 and 0.4237, respectively. We note that the energy fed to the utility grid (Eac) varies linearly with the insolation, as illustrated in Figure 12. Moreover, the Eac energy is related to insolation according to the following relationship, presenting a high-determination coefficient (0.9536): Eac ¼ 0:654 G þ 6:59
ð10Þ
Similarly, the above energy is related to the module temperature according to a linear law as seen in Figure 13 of the form: Eac ¼ 12:2 Tm þ 375
ð11Þ
Moreover, this linear law presents a determination coefficient of 0.8405. The energy generated by the PV array system (Edc) is also influenced by the two previous meteorological parameters 52
Variation of Eac energy as a function of module temperature for 5 min step interval.
(insolation (G) and module temperature (Tm)) during November month. The energy generated (Edc) varies linearly with G and Tm as illustrated in Figures 14 and 15, respectively. The linear evolutions found have a determination coefficient of 0.9613, 0.8348, respectively. They are given as follows: Edc ¼ 0:68 G þ 6:4
ð13Þ
Edc ¼ 22:1 Tm þ 375
ð14Þ
According to these results, two models of the evolution of the Eac and Edc energies have been proposed as a function of the insolation G and the module temperatureTm during this month. They are given as: ð15Þ Eac ¼ 0:535 G þ 4:506 Tm 79:96 R2 ¼ 0:9588 Edc ¼ 0:5522 G þ 4:53 Tm 80:21 R2 ¼ 0:959
ð16Þ
These equations have a determination coefficient (R2) of 0.96. They allow evaluating the Edc and Eac energies as a function of the insolation (incident radiation) and the module temperature. Noting that these models can be improved by taking into account other meteorological parameters such as ambient temperature and humidity.
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FIGURE 14
Variation of Edc energy as a function of insolation for 5 min step interval.
yield, final yield, and reference yield have the same pace during the year, their maximums occur in October and their minimums in January. They are proportional to incident solar radiation. The array capture loss is greater than the system loss. Indeed, the array capture loss ranges from a minimum of 1.63 h/day to a maximum of 2.46 h/day, while the system loss is relatively stable around an average value of 0.12 h per day. The monthly performance ratio varies from 0.61% in August to 0.71% in November. Its monthly average value is 0.66%. The capacity factor varies in the same manner as the final yield, which evolves like the generated energy Eac. The monthly average capacity factor is high in October (20.54%) and low in January (11.66%). The monthly average PV module efficiency ranges from a minimum of 5.61% to a maximum of 6.49%. The monthly average inverter efficiency varies from 96.96%, recorded in January, to 97.44% registered in October. The monthly average system efficiency ranges from a minimum of 5.46%, recorded in January, to 6.32% noted in November. During November month, the energy generated by the PV array Edc and the energy fed to the utility grid Eac, depend on the incident radiation and the module temperature. In addition, those energies are independent of wind speed. So, tTwo linear models, with a coefficient of determination (R2) of 0.96, have been proposed for their evaluation. They are given as: Edc ¼ 0:5522 G þ 4:53 Tm 80:21ðR2 ¼ 0:959Þ Eac ¼ 0:535 G þ 4:506 Tm 79:96ðR2 ¼ 0:9588Þ
Conflict of interest We have no conflict of interest.
References
FIGURE 15
Variation of Edc energy as a function of module temperature for 5 min step interval.
Conclusion The performance of the 954.809 kWp grid-connected photovoltaic system of a Mauritanian power station was evaluated. The impact of insolation, module temperature, and wind speed on the functioning of array 1 of this solar plant have been assessed. The analysis was performed for one-year of study, from September 1, 2014, to August 31, 2015, according to the IEC 61724 standards. Monthly variation of the daily average radiation incident on the PV array varies from a maximum of 7.12 kW h/m2/day (October and April) to a minimum of 4.51 kWh/m2/day (January). The Spring, Summer, and Autumn seasons show higher insolation than Winter season. The monthly average variation of array
[1] A.A.B. Ru´jula, N.K. Dia, Energy Policy 38 (1) (2010) 99–115. [2] Power Africa in Mauritania | Power Africa | U.S. Agency for International Development, 28-mars-2018. [En ligne]. Disponible sur: https://www.usaid.gov/ powerafrica/mauritania. [Consulted: 17-juin-2019]. [3] Photovoltaics & Concentrated solar power (CSP) | Gopa Intec., https://www. gopa-intec.de/fields-of-activity/photovoltaics-concentrated-solar-power-csp. [4] https://www.irena.org/publications/2015/Sep/ Renewables-Readiness-Assessment-Mauritania [5] Enviromena Power Systems, Introduction To Photovoltaic Basics–B1 Mauritania 15 MWp Solar Power Project, www.enviromena.com. [6] S. Edalati, M. Ameri, M. Iranmanesh, Appl. Energy 160 (2015) 255–265. [7] B. Marion, et al., Performance parameters for grid-connected PV systems, in: Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 2005, Lake Buena Vista, FL, USA, (2005), pp. 1601–1606. [8] S. Rehman, I. El-Amin, Energy 46 (1) (2012) 451–458. [9] Z. Abderrezzaq, M. Mohammed, N. Ammar, S. Nordine, D. Rachid, B. Ahmed, Impact ofdust accumulation on PV panel performance in the Saharan region, 18th International Conference on Science and Technology of Automatic Control and Computer Engineering, IEEE (2017) 471–475. [10] D.H. Daher, L. Gaillard, M. Amara, B. Lips, C. Me´ne´zo, Suivi expe´rimental des performances d’une centrale solaire photovoltaı¨que a` Djibouti, 3ie`me Colloque International Francophone d’Energe´tique et me´canique les e´nergies renouvelables et la me´canique applique´e a` l’industrie (2014), p. ART–17. [11] H. Ibrahim, N. Anani, Energy Procedia 134 (October) (2017) 276–285. [12] A. Sayyah, M.N. Horenstein, M.K. Mazumder, Sol. Energy 107 (2014) 576–604. [13] B. Guo, W. Javed, B.W. Figgis, T. Mirza, Effect of dust and weather conditions on photovoltaic performance in Doha, Qatar, in: 2015 First Workshop on Smart Grid and Renewable Energy (SGRE), Doha, Qatar, (2015), pp. 1–6. [14] G. Makrides, B. Zinsser, M. Norton, G.E. Georghiou, M. Schubert, J.H. Werner, Renew. Sustain. Energy Rev. 14 (February (2)) (2010) 754–762.
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[15] D.H. Daher, L. Gaillard, M. Amara, C. Me´ne´zo, Renew. Energy 125 (September) (2018) 729–737. [16] L.M. Ayompe, A. Duffy, S.J. McCormack, M. Conlon, Energy Convers. Manag. 52 (February (2)) (2011) 816–825. [17] D. Micheli, S. Alessandrini, R. Radu, I. Casula, Energy Convers. Manag. 80 (2014) 436–445. [18] M. Mpholo, T. Nchaba, M. Monese, Renew. Energy 81 (September) (2015) 845–852. [19] K. Attari, A. Elyaakoubi, A. Asselman, Energy Rep. 2 (2016) 261–266.
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ski, J. Staszkiewicz, Photovoltaic installation for a roofed car park in [20] M. Wichlin Egypt as an example of effective use of solar energy, E3S Web of Conferences (2018), vol. 49, p. 00127. [21] H.A. Kazem, T. Khatib, K. Sopian, W. Elmenreich, Energy Build. 82 (October) (2014) 123–129. [22] Enviromena Power Systems, Overview Of System Components–B2 Mauritania 15 MWp Solar Power Project, www.enviromena.com.
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Performance analysis of 954,809 kWp PV array of Sheikh Zayed solar power plant (Nouakchott, Mauritania) Mohamed El Hacen Jeda,*, Razika Ihaddadenea,*, Nabila Ihaddadenea,*, Cheikh ELBanany Elhadji Sidib and Menny EL Bahc a
Department of Mechanical Engineering, Mohamed Boudiaf University, M’Sila, Algeria Centre International de Formation et de recherché en Energie Solaire (CIFRES)-Ecole Supérieur Polytechnique-UCAD, BP 5085 Dakar-Fann, Senegal c Unité Énergies renouvelables, Département de Physique, Université de Technologie et de Médecine (UDTM), BP 880 Nouakchott, Mauritania b
Abstract
Amid all renewable energies, solar PV is of particular interest, mainly in Africa. Mauritania is an example of African countries which, gives great concern to produce electricity via PV installations. This study is carried out on the performance evaluation of a 954,809 kWp photovoltaic array made up of microamorphous silicon situated in Nouakchott (capital of Mauritania) at Sheikh Zayed solar power plant. The measures of one year of operation from September 2014 to August 2015 were evaluated according to the IEC 61724. The results obtained demonstrate that the photovoltaic array performances depend on both insolation and environmental conditions. The array capture loss ranges vary from a minimum value of 1.63 h/day to a maximum value of 2.46 h/day. So, the system loss is relatively stable, with an average value of 0.12 h per day. The monthly performance ratio varies from 0.61% in August to 0.71% in November, with a monthly average value of 0.66%. The monthly average capacity factor achieves its maximum and minimum in October (20.54%) and January (11.66%), respectively. The energy generated by the PV array (Edc) and the energy fed to the utility grid (Eac) during November moth, are affected by the insolation and the module temperature. However, wind speed variation does not influence those energies. Two linear models, depending on insolation and module temperature, are proposed for the evaluation of Edc and Eac during this month. These laters present a coefficient of determination (R2) of 0.96. Introduction Energy is a key element of the essential foundations of the prosperity of modern civilization and economic development. With the increase of the world population, the demand for energy increases considerably. Nowadays, the return to renewable energies has become a necessity to contribute to civilization and development.
*Corresponding authors El Hacen Jed, M. ([email protected]), Ihaddadene, R. ([email protected]), Ihaddadene, N. ([email protected])
Among all renewable energies, solar photovoltaic (PV) is of particular interest in Africa since it has a large solar deposit. Mauritania is an African country with a good solar potential varying between 1900 and 2200 kW h/m2/year [1]. This country is mostly reliant on fossil fuels. Fossil fuels account for about 66% of the primary energy consumption, while the remaining 34% comes from biomass, which is mostly used for cooking and heating. Mauritania, under its 2016 Accelerated Growth and Shared Prosperity Strategy, considers energy to be a priority for poverty reduction. Thus, Mauritania’s government is working on expanding its
1755-0084/ã 2019 Elsevier Ltd. All rights reserved. https://doi.org/10.1016/j.ref.2019.11.002
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electricity supply and encourages investment in the renewable energy sector to boost the economy of the country [2]. Electricity in Mauritania is mainly generated through thermal diesel engine generators. Due to increasing energy demand and insufficient installed power capacity, total energy consumption exceeds national energy production by about 35%. Hence, fossil fuels must be imported from out to overcome people’s needs. The policy adopted by Mauritania aims to meet the growing demand for energy with fewer fuel imports by integrating renewable energies as a free source of energy. Indeed, electricity demand is growing by 10% a year, mainly due to rising industry and domestic demand. In a highgrowth scenario of the electricity sector, grid-connected demand (excluding mining activities) is projected to grow by 450% between 2010 and 2030 [3]. For this, the need for sound policies to lead the future demand expansion in electricity is necessary. Indeed, planned investments in national electricity production, including several new wind and solar projects, would increase the contribution of renewable energies to 36% by 2020 and 41% by 2030 [4]. The solar power plant, Sheikh Zayed, located in the capital of Mauritania, Nouakchott, is considered to be the largest solar photovoltaic power plant in Africa. This powerhouse was built in the context of the Mauritanian state policy that encourages all renewable clean energy projects. It produces 15 MW, which represents about 10% of the total load of the city of Nouakchott. This project was developed by Masdar, funded by the United Arab Emirates government and designed by ENVIROMENA. This latter is owned by the Mauritanian electricity company SOMELEC [5]. The performance of a grid-connected PV system depends on two key factors, namely the technical and environmental factors. The technical factors include the technology of the photovoltaic cells [6], those of the inverters, and the type of installation used. While, the environmental factors depend on weather conditions such as; solar radiation, ambient temperature, humidity, wind speed [7], and dust accumulation [8,9].When Solar power plants are installed in arid zones, where the severe external conditions are penalizing (heat, humidity, salinity, dust), they deteriorate quickly. Indeed, the harsh outside conditions accelerate the aging of the photovoltaic modules when compared to those installed in temperate climatic zones [10,11]. Moreover, dust accumulation on the photovoltaic module reduces the transmittance of the PV module glass and consequently degrades the PV module’s power output [12,13]. The study of photovoltaic solar power plants, according to the IEC 61724 standard, becomes imperative to determine the performance of the PV systems (efficient operation or not). In addition, the successful integration of a grid-connected PV system necessitates the knowledge of their operational performance under site climatic conditions [14]. Monitoring input parameters, when studying solar plant performance, yields several advantages such as optimal sizing and survival of the power plant. The knowledge of global horizontal irradiance and the ambient temperature of a site helps us to predict the energy gain, making the idea of building or not the photovoltaic installation in this location. Moreover, the study of the plant performance is of use in identifying the operational uncertainty, which helps in improving its yield [15]. A number of studies has been carried out on the evaluation of the performance of solar PV plants installed around the world [16–21]. Indeed, Ayompe et al. [16] studied the monthly, seasonal, and annual performance of 1,72 kWp grid-connected PV systems 46
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installed in Dublin (Ireland), from November 2008 to October 2009. They found that the annual average daily array yield, reference yield, and final yield of the installed solar plant were of 2,62 kW/kWp/day, 2,85 kW h/kWp/day, and 2,41 kWh/kWp/ day, respectively. In addition, the annual average daily PV module efficiency, system efficiency, and inverter efficiency were about14,9%, 12,6%, and 89,2%. Moreover, the annual average daily capture losses and system losses were about 0,22 h/day and 0,23 h/day, respectively. The capacity factor and the annual average daily performance ratio were about 17,74% and 81,5%, respectively. Attari et al. [19] studied the evaluation of a grid-connected PV system installed on the government-building roof located in Tanger (Morocco). This study was performed for one year from 1st January to 31st December. The PV system studied is composed of 20 modules with 250 Wp and one inverter. The final yield and the performance ratio were found to vary from 1,96 to 6,42 kW h/kWp and 58%–98% respectively. The annual capacity factor of this system was about 14,84%. ski and Staszkiewicz [20] presented an analysis of a phoWichlin tovoltaic installation built on a roof car park located in eastern Cairo (Egypt). The annual yield of energy supplied into the grid was about 587 MW h per year. The average annual final yield was about 3,7 KWh/KWp. Moreover, the average annual performance ratio was 0,62 and the total losses of this installation were roughly 30%. Daher et al. [15] studied the performance of a 302,4 kWp gridconnected PV system in Djibouti. They analyzed the first 4 years of this system for coastal, desert maritime climate zones according to the IEC 61724. The results found showed that the monthly average daily array yield and the final yield were about 5,1 kWh/kWp and 4,7 kW h/kWp, respectively. The average performance ratio of the PV arrays and the global grid-connected system were 90% and 84%, which are in agreement with the monthly average daily PV module efficiency (12,68%) and the system efficiency (11,75%). This study aims to analyze the performance of the 954.809 c photovoltaic system located in Nouakchott, Mauritania, according to IEC 61724 standard. This research document is organized as follows: in Section ‘‘Material and methods’’, the description of Sheikh-Zayed power station and the performance evaluation of PV array are presented. The results found and their discussion are given in Section ‘‘Results and discussion’’. Finally, a conclusion, with the important results found, closes this investigation.
Material and methods Description of Sheikh-Zayed power station Sheikh-Zayed power station is located in the north of Nouakchott in Mauritania at a latitude of 18 150 N and longitude of 15 980 W. Figure 1 shows a photo of this solar power plant. Sheikh Zayed Solar Power Plant was one of the largest solar power installations in Africa when installed. It is the first such utility-scale installation in Mauritania, supplying 10 percent of Mauritania’s grid capacity. It produces 25,409 MW h of electricity annually and releases approximately 21,225 t of carbon dioxide per year. The plant was installed in March 2013 with 15 MWp, comprising a fixed ground-based array of 290826 PV modules with two different thin-film technologies (amorphous silicon and micro-amorphous silicon) each with a different power rating. The modules are oriented due south and inclined by 10 .
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FIGURE 1
Sheikh Zayed solar PV plant. FIGURE 3
The photovoltaic modules generate a direct current (DC) from the incident solar radiation impinging their surfaces. Since the power distribution network and electrical loads operate on alternating current (AC), the inverters are used to convert the direct current (DC) from the photovoltaic modules into alternating current (AC). Moreover, alternate voltage is always kept constant by the inverter according to the limits of the distribution network. However, the supplying current varies depending on the incident solar radiation. The AC output of the inverter is at low voltage (LV) that should be raised to a medium voltage (MV) of 33 kV by means of step-up transformers. The transformers are connected to the switchgear in a ring configuration that terminated at the North substation. This latter is connected to the SOMELEC electricity distribution network [5]. The conversion chain is shown in Figure 2. Sheikh-Zayed power plant is composed of eight (8) power block stations designated as Room. Each power block is composed of two arrays. All power blocks have two inverters except one, which possesses three inverters. In other words, the eight rooms are as follows; Room A (Inverter 1, Inverter 2), Room B (Inverter 3, Inverter 4), Room C (Inverter 5, Inverter 6), Room D (Inverter 7, Inverter 8), Room E (Inverter 9, Inverter 10), Room F (Inverter 11, Inverter 12), Room G (Inverter 13, Inverter 14), Room H (Inverter 15, Inverter 16 and Inverter 17).This investigation was devoted to the study of the photovoltaic array 1 of Sheikh-Zayed power station, as shown in Figure 3. It contains a total of 1872 Masdar photovoltaic modules, each with an area of 5,72 m2, and peak power of 510 Wp. The technical characteristics under standard conditions of the PV modules used in this array are regrouped in Table 1. Their technology
Schema of the arrays of Sheikh-Zayed solar PV plant.
is that of micro-amorphous silicon (mc-Si) thin film. In addition, the modules are connected in series to increase the system voltage to the desired level, in order to maximize the power peak. The system is designed for a maximum rating of 1000 V, where three (3) modules are connected in series to form a series. Two (2) series connected in parallel constitute a circuit, and three circuits joined in parallel form a string. Peak power of 954,809 kWp is supplied from104 strings in the PV array (1). The DC/AC inverter, which is used in the array 1, is supplied by SMA Solar Technology (760 kW). The transformer (1600 kVA), made by CELME, intensifies the low voltage output of the inverters to a medium voltage at 33 kV. It is connected to two SMA 760 kW inverters [22]. A monitoring system is used to control the inverters and report performance parameters, system status, and weather data to a local or remote user. The data collected is averaged over 5-min intervals. These data serve to calculate hourly, weekly, monthly, and yearly performance parameters. Our study covers a period of one year from September 1, 2014, to August 31, 2015. The data used are module temperature, wind speed, solar insolation, energy generated by the PV array system (Edc), and the energy output (Eac).
Performance evaluation of PV array Performance parameters of PV array are established by the international energy agency. They are described in IEC standard 611724. As noted in the literature [16–18], the normalized
FIGURE 2
Conversion chain in the solar PV plant.
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TABLE 1
Masdar 510 PV module characteristics under (STC). PV module made of
Impp (A)
Vmpp (V)
Isc (A)
Voc (V)
Pmpp (Wp)
(mc-Si)
2,24
227,7
2,64
292
510
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indicators gather energy output, array yield, final yield, reference yield, module efficiency, inverter efficiency, system efficiency, performance ratio, capacity factor, and energy loss (array capture loss and system loss).
1. Energy generated by the PV array system (Edc) The total daily recorded value of DC power output (Edc,d) is given by the following equation: Edc;d ¼
t¼Trp X
Pdc T r
ð1:1Þ
4. Array yield of PV field (Ya) The efficiency of the PV field (Ya) is defined as the ratio between the total generated energy Edc (kWh) by the PV rows for a defined period (day, month or year) and the nominal power P0 (kWc) of the rows under the standard conditions (STC: irradiation = 1000 W/m2, ambient temperature = 25 C and AM 1.5-G reference spectrum). The daily efficiency of the PV field (Ya,d) is given by the following equation: Y a;d ¼
t¼1
The monthly DC energy generated (Edc,m) is given as: Edc;m ¼
N X
Edc;d
ð1:2Þ
d¼1
where; Tr is the recording time interval; Trp the reporting period; N the number of operating days of the plant per month; Pdc is the DC power (result of the current times the voltage). It is given as follows: Pdc ¼ V dc I dc
ð1:3Þ
Edc;d PpvðratedÞ
ð4:1Þ
The monthly efficiency of the PV field (Ya,m) is given by the following equation: X N 1 Y a;m ¼ Y a;d ð4:2Þ N d¼1
5. Final yield of the PV system or system yield (Yf) The final efficiency (Yf) corresponds to the total energy produced by the PV system Eac (kWh) per the installed nominal power P0 (kWp). This quantity represents the number of hours during which the PV field should operate at its rated power. The daily final efficiency (Yf,d) and the monthly final efficiency (Yf,m) are given by the following equations:
2. Energy output or energy fed to the utility grid (Eac)
Y f ;d ¼
ð5:1Þ
The energy generated by the PV system (Eac) is the measure of the energy across the inverter output terminals, recorded every 5-min by the data logger. The total daily recorded value of AC power output (Eac,d) is given by the following equation:
Eac;d PPVðratedÞ
Y f ;m ¼
X N 1 Y f ;d N d¼1
ð5:2Þ
Eac;d ¼
t¼Trp X
Pac T r
ð2:1Þ
6. Pv module efficiency (hpv)
ð2:2Þ
The module efficiency or energy efficiency (hpv) presents the effective energy generated by the module with respect to the available radiation. The daily PV array efficiency is given by the following equation:
t¼1
The monthly AC energy generated (Eac,m) is given as: Eac;m ¼
N X
Eac;d
d¼1
hpv;d ¼
If the AC power given as follows: Pac ¼ Vac Iac:
(2.3)
3. Reference yield (Yr) The reference efficiency (Yr) is the ratio between the total amount of solar radiation Ht (kWh/m2) intercepted by the surface of the PV solar panels and the amount of reference radiation G0 (1 kW/m2). It depicts the number of hours during which the illumination is equal to that of the reference. Yr defines the solar resource of the PV system. It is given by: Yr ¼
48
Ht G0
Edc;d 100 G Am
ð6:1Þ
where; Edc,d is the dc energy generated by the PV array system; G presents the global solar irradiation; Am presents the area of the PV module. The monthly average PV module efficiency is calculated as follows: hpv;m ¼
Edc;m 100 G Am
ð6:2Þ
7. Inverter efficiency (hinv) ð3Þ
Inverter efficiency (hinv) supposed to be higher than the module and system efficiencies. It is also called conversion efficiency,
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expressed as the ratio between the AC power generated by the inverter and the DC power produced by the photovoltaic panel system. The monthly inverter efficiency is given by the following equation: hinv;m ¼
Edc;m 100 Eac;m
ð7Þ
8. System efficiency (hsys) The photovoltaic system efficiency is related to the balance of the systems comprising the PV generator and inverter module. The monthly system efficiency can be calculated by applying the following equation: hsys;m ¼ hpv hinv
ð8Þ
9. Standardized performance index (PR) The performance ratio (PR) indicates the overall effect of the losses in the energy production of the rows of a PV system. The PR values indicate how well a PV system approaches the ideal performance under real-world operating conditions. PR is defined as the ratio between the final yield and the reference yield. It is a dimensionless quantity, given as follows: PR ¼
Yf Yr
ð9Þ
10. System losses by conversion (Ls) The losses of the system by conversion (LS) are due to the inverter conversion losses (DC-AC current) and are defined by the difference between the yield of the PV field Ya and the final yield Yf. The system losses are given as follows: Ls ¼ Y a Y f
ð10Þ
11. Array capture loss (Lc) The array capture loss (Lc) is defined by the difference between the reference yield and the array yield of the PV field. It represents the losses due to panel temperatures, wiring, partial shading, spectral losses, soiling, errors in the search for the maximum power point, conversions (DC-AC), etc. Lc is given by the following equation: Lc ¼ Y r Y a
4.51 kWh/m2/day (January) to a maximum of 7.12 kW h/m2/day (October and April) as shown in Figure 4. The seasonal daily average insolation for spring (March–May), autumn (September– November), summer (June–August), and winter (December–February) is 7.03 kW h/m2/day, 6.76 kW h/m2/day, 6.73 kW h/m2/day and 5.19 kW h/m2/day, respectively. Thus, the insolation varies according to the seasons. Indeed, the spring, summer, and autumn seasons show higher insolation compared to the winter season. Moreover, monthly wind speed variation is also illustrated in Figure 4. As seen, wind speed varies from 1.26 m/s recorded in November to 3.43 m/s noted in July. The monthly variation of PV module temperature during the studied period is illustrated in Figure 5. The module temperature varies from 26.57 C, registered in November, to 41.60 C noted in September. The monthly average variation array yield, final yield, and reference yield are depicted in Figure 6. The monthly average final yield varies from a minimum of 2.80 h/day (January) to a maximum of 4.93 h/day (October). The final annual yield is 4.26 h/day. Almost the same value as that of a Moroccan solar power station (4.4 h/day) [19]. The final annual yield found is higher than that of Egypt (3.7 h/day) [20], Spain (3.8 h/day) [21], and Ireland [16] (2.41 kWh/kWp/day). The monthly average reference yield follows the same pace as the final yield. It varies between a minimum of 4.51 h/day, recorded in January, and a maximum of 7.12 h/day registered in October, as noted in Figure 6. Moreover, the monthly average array yield has the same gait as the two cited yields (reference and final yields). It varies from a minimum of 2.89 h/day, recorded in January, to a maximum of 5.06 h/day registered in October. The yield values, recorded for the month of January, are low because of its low incident solar radiation (see Figure 4). Furthermore, the reference yield is proportional to the insolation. During the year of study, a difference between the array yield and the final yield is observed. Indeed, the final yield takes into account the DC/AC conversion losses produced in the inverter.
ð11Þ
12. Capacity factor (CF) The capacity factor (CF) is a parameter for representing the energy delivered by an electrical power distribution system. If the system delivers full rated power continuously, its CF will be unity. It is defined as the ratio of actual annual energy output to the amount of energy the PV system can deliver at its rated capacity for 24 h per day during a year. The capacity factor is given as follows: CF ¼
Y f ðannualÞ 24 365
ð12Þ
Results and discussion In the current investigation, the meteorological data and the performance of the studied array were analyzed. The monthly daily average insolation on the PV array varies from a minimum of
FIGURE 4
Variation of monthly average daily insolation and wind speed for the studied period in Nouakchott.
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Monthly average variation of the PV module temperature of Sheikh-Zayed power plant for one year of study.
FIGURE 6
FIGURE 7
Monthly variation of daily average array capture loss (Lc) and system loss (Ls) of Sheikh-Zayed power plant (array1) during one year of study.
FIGURE 8
Monthly average array yield (Ya), reference yield (Yr) and final yield (Yf ) of Sheikh-Zayed power plant during one year of study.
Monthly variation of performance Ratio of Sheikh-Zayed power plant (array1) for one year of study.
Figure 7 shows the monthly variation of the array capture loss and the system loss of Sheikh-Zayed power station plant (array 1) during one year of study. The array capture loss is greater than that of the system, which regroups all kinds of losses occurring in the solar conversion process from PV modules to the inverters. The array capture loses vary from a minimum of 1.63 h/day, noted in April, to a maximum of 2.46 h/day registered in February. Important losses are observed in summer. They are directly related to the dust deposit on the panels and to their high temperatures during this period. The system loss is relatively stable, with an average of 0.12 h per day. Precisely, it varies from 0.088 h/day to 0.32 h/day. Thus, the inverters of the PV system perform well in DCAC conversion. The average system losses, of an Egyptian solar plant, are about 0.28 h/day [20], which are higher than those found in the current study (array 1). Moreover, the system losses of a Moroccan solar plant vary between 0.14 h/day and 1.89 h/day, and the capture
losses range from 0.025 h/day to 0.76 h/day [19]. Therefore, the system losses of Morocco solar power plant are higher than those of array 1 of Sheikh-Zayed power plant. Figure 8 shows the monthly evolution of Performance ration (PR). As seen, it ranges from 0.61% to 0.71% recorded in August and November, respectively. Thus, the monthly average Performance Ratio of array 1 is 0.66%. This value is in the range of (60%– 90%) reported for the solar power plants [16]. It is lower than the performance ration of Morrocan (0.79) [19] and Djiboutian (0,84) [15] solar plant. However, it is higher than that found for an Egyptian solar plant (0.62) [20]. Generally, a PR greater than 0.8 corresponds to a system whose performance approaches the ideal performance under STC conditions. In addition, a system with a PR less than 0.7 must be suspected to failure or malfunction from system components (panels, inverters, etc.) or environmental parameters (nearby shading, an excessive dusting of panels, etc.).
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FIGURE 9
Monthly variation of the capacity factor of Sheikh-Zayed power plant (array1) for one year of study.
Figure 9 shows the monthly evolution of the daily capacity factor for one year. The capacity factor varies in the same manner as the final yield, which evolves like the generated energy Eac. The monthly average capacity factor is at its maximum in October, amounting to 20.54% where the final yield is also the highest one, in the order of 4.93 h/day. Moreover, it is low in January with a value of 11.66%, where the final yield is also low at about 2.80 h/ day. The annual average capacity factor is 17.74%. It is in the norms (0.10–0.20), as mentioned by Ayompea et al. [16]. The capacity factor in the study case of Morocco is 14.84% [19], which is lower than that found in our study. Figure 10 shows the average monthly changes in the efficiencies of the PV module and the system. The monthly average PV module efficiency ranges from a minimum of 5.61% (May) to a maximum of 6.49% (November). The monthly average system
FIGURE 10
Monthly variation of the PV System efficiency of Sheikh-Zayed power plant (array1) during one year of study.
FIGURE 11
Monthly variation of the Inverter efficiency of Sheikh-Zayed power plant (array1) during one year of study.
efficiency follows the same pace as the PV module efficiency. It ranges from a minimum of 5.46% recorded in May to a maximum of 6.32% reached in November. The monthly average inverter efficiency varies from 96.96% in January to 97.44% in October, as noted in Figure 11. This efficiency has an annual average of 97.20%. Noting that the inverter efficiency lies in the range of (95%–98%) at actual operating conditions, as reported by Ayompea et al. [16]. The annual average inverter efficiency, in the case study of Morocco, is about 96.7% [19]. It is lower than that found in our study. So, this result shows that the inverter of Sheikh-Zayed power plant (array1) is in very good working condition according to the standards and compared to other working inverters. For the current plant installed in Nouakchott, this drop in the performance ratio can be explained by certain environmental factors such as fairly high temperatures and dust. In addition, the disrespect of the optimal tiltangle of the photovoltaic panels (10 instead of 15 ), to avoid the effect of sharing the modules, has a significant effect on the reduction of the performance of the studied installation. This disrespect of the optimal tilt angle is also due to the economic gains made when buying the necessary cables to separate each row from the other. Moreover, the high temperature of the rooms, where the inverters are placed, leads to increase system losses, and consequently, the automatic shutdown of the inverter. Although these rooms are equipped with air conditioners, this does not always work (insufficient cooling load). Therefore, regular maintenance of these devices may contribute to increasing the performance of the system. It is noted that the performance index PR of the photovoltaic plant (array 1) during one year of study takes the highest value in November. Thus, during this month, the photovoltaic plant has worked well. In order to determine the effect of the meteorological conditions (insolation G, module temperature Tm and wind speed V) on the performance parameters (energy generated by the PV array system (Edc), energy fed to the utility grid (Eac), array yield of PV field (Ya), reference yield (Yr), final yield (Yf), PV module efficiency (hpv), system efficiency (hsys), inverter efficiency (hinv), 51
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ORIGINAL RESEARCH ARTICLE
TABLE 2
Statistical analysis on the effect of meteorological conditions on PV array 1 performance for November month.
ORIGINAL RESEARCH ARTICLE
Parameters
R2 (G)
R2 (Tm)
R2 (V)
Eac Edc Ya Yr Yf hpv hsys hinv
0.9536 0.9613 0.9512 1 0.9507 0.6195 0.3893 0.3883
0.8405 0.8314 0.8257 0.7933 0.8269 0.5877 0.4931 0.4948
0.4231 0.4237 0.4232 0.3598 0.4237 0.4068 0.4592 0.4605
(Eac,G) (Edc,G) (Ya,G) (Yr,G) (Yf,G) (hpv,G) (hsys, Tm) (hinv, Tm)
FIGURE 12
Variation of Eac energy as a function of insolation for 5 min step interval.
FIGURE 13
the capture losses (Lc), and system losses (Ls)) during this month, a statistical analysis was performed. The coefficient of determination of the effect of meteorological conditions on each parameter and the dominant influence parameter were determined. The results obtained are regrouped in Table 2. It is noted that the insolation G has a greater effect than the module temperature and the wind speed on Eac, Edc, Ya, Yr, Yf, hpv during this month. On the other hand, the effect of the module temperature is more important than the insolation on the hinv and hsys. The wind speed has a less important effect than the insolation and the module temperature on Eac and Edc. Indeed, it presents, a determination coefficient of 0.4231 and 0.4237, respectively. We note that the energy fed to the utility grid (Eac) varies linearly with the insolation, as illustrated in Figure 12. Moreover, the Eac energy is related to insolation according to the following relationship, presenting a high-determination coefficient (0.9536): Eac ¼ 0:654 G þ 6:59
ð10Þ
Similarly, the above energy is related to the module temperature according to a linear law as seen in Figure 13 of the form: Eac ¼ 12:2 Tm þ 375
ð11Þ
Moreover, this linear law presents a determination coefficient of 0.8405. The energy generated by the PV array system (Edc) is also influenced by the two previous meteorological parameters 52
Variation of Eac energy as a function of module temperature for 5 min step interval.
(insolation (G) and module temperature (Tm)) during November month. The energy generated (Edc) varies linearly with G and Tm as illustrated in Figures 14 and 15, respectively. The linear evolutions found have a determination coefficient of 0.9613, 0.8348, respectively. They are given as follows: Edc ¼ 0:68 G þ 6:4
ð13Þ
Edc ¼ 22:1 Tm þ 375
ð14Þ
According to these results, two models of the evolution of the Eac and Edc energies have been proposed as a function of the insolation G and the module temperatureTm during this month. They are given as: ð15Þ Eac ¼ 0:535 G þ 4:506 Tm 79:96 R2 ¼ 0:9588 Edc ¼ 0:5522 G þ 4:53 Tm 80:21 R2 ¼ 0:959
ð16Þ
These equations have a determination coefficient (R2) of 0.96. They allow evaluating the Edc and Eac energies as a function of the insolation (incident radiation) and the module temperature. Noting that these models can be improved by taking into account other meteorological parameters such as ambient temperature and humidity.
Renewable Energy Focus Volume 32, Number 00 March 2020
FIGURE 14
Variation of Edc energy as a function of insolation for 5 min step interval.
yield, final yield, and reference yield have the same pace during the year, their maximums occur in October and their minimums in January. They are proportional to incident solar radiation. The array capture loss is greater than the system loss. Indeed, the array capture loss ranges from a minimum of 1.63 h/day to a maximum of 2.46 h/day, while the system loss is relatively stable around an average value of 0.12 h per day. The monthly performance ratio varies from 0.61% in August to 0.71% in November. Its monthly average value is 0.66%. The capacity factor varies in the same manner as the final yield, which evolves like the generated energy Eac. The monthly average capacity factor is high in October (20.54%) and low in January (11.66%). The monthly average PV module efficiency ranges from a minimum of 5.61% to a maximum of 6.49%. The monthly average inverter efficiency varies from 96.96%, recorded in January, to 97.44% registered in October. The monthly average system efficiency ranges from a minimum of 5.46%, recorded in January, to 6.32% noted in November. During November month, the energy generated by the PV array Edc and the energy fed to the utility grid Eac, depend on the incident radiation and the module temperature. In addition, those energies are independent of wind speed. So, tTwo linear models, with a coefficient of determination (R2) of 0.96, have been proposed for their evaluation. They are given as: Edc ¼ 0:5522 G þ 4:53 Tm 80:21ðR2 ¼ 0:959Þ Eac ¼ 0:535 G þ 4:506 Tm 79:96ðR2 ¼ 0:9588Þ
Conflict of interest We have no conflict of interest.
References
FIGURE 15
Variation of Edc energy as a function of module temperature for 5 min step interval.
Conclusion The performance of the 954.809 kWp grid-connected photovoltaic system of a Mauritanian power station was evaluated. The impact of insolation, module temperature, and wind speed on the functioning of array 1 of this solar plant have been assessed. The analysis was performed for one-year of study, from September 1, 2014, to August 31, 2015, according to the IEC 61724 standards. Monthly variation of the daily average radiation incident on the PV array varies from a maximum of 7.12 kW h/m2/day (October and April) to a minimum of 4.51 kWh/m2/day (January). The Spring, Summer, and Autumn seasons show higher insolation than Winter season. The monthly average variation of array
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