PERFORMANCE EVALUATION OF THE IMPACTS OF METROLOGICAL PARAMETERS ON CRYSTALLINE AND AMORPHOUS MODULES AT MINNA, NIGERIA

Photovoltaic (PV) module performance is rated under standard test conditions (STC) i.e. irradiance of 1000 W/m², solar spectrum of Air Mass 1.5 and module temperature at 25°C. Manufacturers of photovoltaic modules typically provide the ratings at only one operating condition i.e. STC. However, PV module operates over a large range of environmental conditions at the field. So the manufacturer’s information is not sufficient to determine the actual performance of the module at field. Optimization of solar energy is affected by so many factors ranging from conversion efficiency of PV module to local metrological conditions. The research work therefore, evaluates the performance of three PV technologies using performance ratio. Metrological parameters such as solar radiation intensity, wind speed, relative humidity, and air temperature were measured simultaneously with the output electrical parameters from the three modules exposed to field test using metrological sensors and a CR1000 software-based data logging system with computer interface attached to the modules. Four years consecutives metrological and modules output data’s were collected from the modules and analyzed. The findings indicates that metrological parameters fluctuate non-linear with the modules output, under this conditions the trends as measured by the output power revealed that polycrystalline module has a better performance than amorphous module followed by mono-crystalline module in this experiment. The paper recommends the need to mitigate substandard modules entering our market through appropriate monitoring agencies and the setting of solar module laboratory for locally production of solar modules that would captures our local metrological parameters towards greater efficiency.


INTRODUCTION
Conventional fossil fuels such as oil, coal and natural gas are extensively used as the primary energy source (Khaled et al., 2021) in industry, manufacturing company and for cooking especially in developing country. However, they are limited and have an environmental risk associated with extracting, transporting and utilizing them. Approximately 66% of the global carbon dioxide and other greenhouse gases (GHG) emissions are generated from fossil sources . In contrast, renewable energy, especially solar, is available everywhere, is non-pollutant and has minimal impact on the environment, making it most suitable for the sustainable energy source (Khaled et al., 2021). The renewable energy resources are becoming the mainstream energy resource (Twidel, J. and Weir, T., 2015). Among these renewable energy resources, the solar PV is the most promising resource (Hill, R., 1999). PV energy now holds an important position in the renewable energy market. PV production has been increasing by an average of 20% each year since 2002, making it a fast-growing energy technology. The global cumulative PV installations have exceeded 21GW (Martinot et al., 2009). Over the past decade, the PV market has experienced unprecedented growth. Particularly in the over the past year, the PV market has reached a cumulative installed capacity of roughly 40 GW world-wide, with an annual added capacity of 16.6 GW (EPIA, 2011). PV installed capacity reached 102.2 GW at the end of year 2012 an addition of 31.1 GW in 2012 (Roney, 2013). PV generation systems have two major problems: the conversion efficiency of electric power generation is very low (9 -17%) especially under low irradiation conditions, and the amount of electric power generated by solar array changes continuously with weather conditions Weather parameters such as solar radiation, ambient temperature, relative humidity, wind speed, air pressure and sunshine duration are accepted as dependable and widely variable renewable energy resources (Duby et al., 2013, Ebhota andTabakov, 2022). These data play a very important role in PV systems (Faranda and Leva, 2008). Varying metrological conditions has impacts on the performance of PV modules, as metrological parameters influences the output of the solar module in the field use. Solar cell degradation is the result of various operating conditions; temperature is one of most important factors controlling outdoor electrical performance of PV module. In a similar work, Olayinka et al., (2018) show that the intensity of the sun has a significant effect on the output of solar panel, but this is been interrupted by meteorological factors interacting with solar radiation from getting to the panel. The conversion of solar energy to electrical energy through photovoltaic cells is now of great interest not only to developed nations but developing nations (Mekhilef et al., 2012). However, access to solar and other renewable energy technologies is changing the way we create and consume electricity; it seems that not everyone is getting the same level of opportunity. In Malawi, and other places in Africa, the renewable energy markets are flooded with an extraordinarily poor quality of imported solar PV equipment. The financial burden of early product failures on this disadvantaged population has the undesirable effect of constraining the rate of electrification (ESI Africa, 2016).
The success of these PV technologies in a particular environment and major factors it depends on is the reasons for these studies, therefore the main aim of this work is to evaluate the performance the of mono-crystalline, polycrystalline and amorphous modules influenced by metrological parameters, specifically irradiance, humidity, air and module temperature at Minna, Niger state-Nigeria.

Area of Study
The study area is located in the latitude 09 o 37Nʹ and longitude 06 o 32ʹE, at altitude 249 meters above level and is one of the Northern states of Nigeria that lies partially, within the semi Sahel belt of West Africa. The climate of this zone is characterized by two distinct well defined seasons, namely wet (or rainy) and dry seasons (also as Hamattern). These seasons correspond to northern hemisphere summer and winter respectively (Ezenwora et al., 2011).

Materials
The materials used for this study are solar panel with the following specifications: Monitoring stage: The performance response of the silicon PV modules to ambient weather parameters, such as solar irradiance, temperature, wind speed and relative humidity, was monitored in environment of Minna, Niger State, Nigeria, using a CR1000 software-based data logging system with computer interface.

Procedure:
The PV modules under test, and meteorological sensors, were installed on support structure at the same test plane, at surface level, to ensure adequate exposure to insolation and enough wind speed since wind speed is proportional to height. The elevation will also ensure that the system is free from any shading and protected from damage or interference by any person. The modules were tilted at latitude of Minna, Niger State, Nigeria to horizontal and south-facing to ensure maximum insolation. The global solar radiations, ambient temperature, relative humidity, wind speed and module temperature were monitored using their respective sensors incorporated in the CR1000 Campbell Scientific data logger with measurement and control module. Also data points that represent low irradiance conditions associated with late evening time from 6pm down and night measurements that might not contribute significant value to the overall data of interest were filtered out.

Data collection:
The experiment was performed for four years and data measurements were taken from 8.00am to 6.00pm each day continuously for a period of four years. The sensor was connected directly to the CR1000 Campbell Scientific data logger, while the modules were connected to the logger via a voltage divider. Instantaneous data collections were performed by the logger at an interval of 5 minutes. Data download at the data acquisition site was performed every seven days to ensure effective and close monitoring of the data acquisition system (DAS). At the end of each month, hourly, daily and monthly averages of each of the parameters-solar radiation, wind speed, ambient and module temperatures, and the output response variables (open-circuit voltage, VOC, short-circuit current, ISC, voltage at maximum power, Vmax, current at maximum power, Imax, efficiency, Eff and fill factor, FF) of the PV modules were obtained.

RESULTS AND DISCUSSION
The four years metrological data's collected and measured output electrical parameters of the three modules in a field test outside physics department of FUT, Minna, are displayed below:             Results of the first year of modules field exposure is presented in tables above it indicates monthly average variation of air temperature, wind speed, relative humidity and irradiance for the period of January to December of each year respectively. According to Skoplaki and Palyvos (2009) several factors determine the performance of a PV system and can be categorized into two: meteorological and PV system configuration parameters. The PV system configuration parameters are PV cell, PV panel orientation, storage, and self-consumption. Other configuration parameters include interconnections, inverter, and controller. For the first year of modules exposure, the wind speed peak in April recording 9.6900ms -1 having lowest value in November as 1.3617ms -1 , in the second year of modules exposure, wind speed was recorded high in the month of January (1.9948ms -1 ) and least in the month of December (0.7643ms -1 ), during the third year of modules exposure, wind speed has maximum and minimum values in February (1.9161ms -1 ) and November (0.6759ms -1 ) while in the fourth year of modules exposure, wind speed has minimum and maximum values in February and November with an amounts 0.7406ms -1 and 0.8100ms -1 respectively. Generally, the wind speed varies throughout the year except in the first year where the wind speed shows linear decreases from April to November. Literature study according to Olayinka, (2018) revealed that wind speed was inversely related to the ambient temperature, in this work the wind speed fluctuate throughout the days as ambient temperature fluctuates which confirmed Tanima et al., (2014) reports where the wind speed fluctuates across the year. Conclusively, the PV modules, overall performance varied with the wind speed and fluctuates with the output electrical characteristics. Humidity is a function of temperature as assumed by Xueyan et al., (2013). Nigeria being solar region, humidity is expected to be high however, in this research work and in the first year of the module field test, relative humidity peak in August and has lowest value in January. In the second year, of field test, relative humidity recorded highest reading in the month of August and lowest reading in the month of February. For the third year, relative humidity increase from 12.2438% in February to 81.3037% in August while in fourth year, relative humidity varied from 13.8481% as measured in January to 83.1904% measured in August. Within the four years data collection, humidity in this locality shows nearly the same pattern with two minimum values corresponding to January, February and maximum values recorded in August respectively. The performance of PV technologies in connection with humidity indicates that output electrical parameters varied with the varying humidity.
Irradiance is the energy that strikes a unit horizontal area per unit wavelength interval per unit time (Wang et al., 2008 andLiu L., 2009). The PV panel output significantly depends on solar power or solar irradiance as the solar resource is highly variable (Wang et al., 2008 andShah et ual., 2015). Analyzing the behavior of irradiance with the module output shows that irradiance fluctuate throughout the year contrary to the report of Zogou, (2011) andFouad et al., (2017) where the output of the PV module increases as the irradiation does, furthermore, studies conducted by Mondol, (2017) and Khaled et al., (2021) indicate solar irradiance have direct relationship with module current. Evaluating the performance of PV technologies due to impact of irradiance, shows that outputs electrical parameters are non-linear with the fluctuating irradiance. The main cause of the fluctuating irradiance values is cloudy situations (Wang et al., 2020) which obstruct the incidence irradiance on the PV panels.
In the first year air and module temperature varies across the  Feroz et al., (2023) and Narendra et al., (2014) where temperature and voltage are inversely related and opposed to linear increase current due to decrease band gap, udecrease open circuit voltage due to increase reverse saturation current and decreases power with increase module temperature. On the performance of PV technologies influenced by air and module temperatures and considering the view of Feroz et al., (2023) that temperature is crucial for the usage of PV modules in power generation, when module temperature rises, their performance suffers in addition, Griffith et al., (1981) reports that efficiency drops by 0.03-0.05% for every 1 °C increase in temperature without cooling. The haphazard research outcome of these PVs influenced by temperatures did not support the above findings and opposed the work of Zouine et al., (2018) where PV module output performance decreases with increasing temperature with the electrical power depend linearly on the operating temperature.

Performance ratio (PR) analysis of the three technologies
Considering tables in the first year field test, comparative performance studies of the three technologies shows that polycrystalline (Poly-cr) is more effective follow by monocrystalline (mono-cr) and then amorphous crystalline (a-cr) modules with 63%, 31% and 15% for Pmax, in relation to Voc, (a-cr) displayed high effectiveness follow by (Poly-cr) and then (mono-cr) panel with their PR as 77, 75 and 37%, where Vmax recorded 31, 24 and 17% PR for (Poly-cr), (mono-cr) and (a-cr) and Imax have 23, 15 and 7% PR for (Poly-cr), (mono-cr) and (a-cr) respectively. In the case of second year performance studies of the three modules, indicates Poly-cr has higher PR follow by mono-cr and then a-cr with 61%, 31% and 17% for Pmax, in relation to Voc, Poly-cr displayed high effectiveness follow by mono-cr