Temperature Measurement of a Solar Panel for Optimum Energy Storage

Abstract

With the arrival of the new millennium, debates on the planet's energy future have intensified. According to the ever-increasing needs of the population and the consequences that this have in the medium term, one of the answers to this debate is the energetic transition from fossil energy to cleaner and renewable energy such as photovoltaics. The input parameters of a solar panel for energy creation are the temperature and solar iradiation. The latter will define the energy efficiency of photovoltaic cells.

This paper proposes an analysis of the influence of temperature on energy storage optimization. After the presentation of the functioning of stand alone PV panels, a solution to the influence of temperature will be presented theoretically and experimentally: the technology of hybrid PV thermal panels. The results obtained show the efficiency of this type of system in improving the efficiency in the transformation of solar energy.

Keywords: Photovoltaïc pannel, Storage battery, Stand alone PV system, photovoltaic thermal.

Introduction

Nowadays, the population is sensitive to its environmental impact. It efficiency, government subsidies and it accessibility make solar energy very attractive to the general public. In addition, the energy required to manufacture a photovoltaic panel is reimbursed within 1 to 3 years, depends of the site's exposure to sunlight. Those arguments explain the increase in solar energy production worldwide past years. Those characteristic make solar energy very attractive, but above all, this solution presents a major constraint: its intermittent nature in the supply of energy [1].

Generally, a photovoltaic (PV) panel owner can expect to be able to meet the energy consumption of his home on a sunny day. However, in case of reduced energy consumption, the production of the PV panels may be too high, the excess will then be injected into the electrical grid. Similarly, during a night period, the production of solar energy may not compensate the home's electricity consumption [1].

Figure 1 : Operating principle of a Photovoltaic pannel

It is to overcome this constraint that the stand-alone PV system has been set up. This system is a PV panel coupled with an energy storage solution that is there to absorb fluctuations in energy production.

This is in this context that this paper is situated: optimizing a stand-alone photovoltaic system, but first of all it is important to describe how the system work.

A photovoltaic panel figure 1. is composed of several photovoltaic cells connected in series and in parallel. Those cells are made from two layers of silicon. The lower layer is doped with Boron (P type) to create a positive potential and conversely the upper layer is doped with Phosphorus (N type) atoms to create a negative potential. The solar rays (photons) absorbed by the upper layer will initiate an electromotive force due to the physical photovoltaic phenomenon. The voltage generated by a single cell is generally between 0.3V and 0.8V.[2] The inputs factors affecting its performance are the materials used, solar irradiation and temperature.

Energy storage is the preservation of an amount of energy for future use. This is at the heart of today's challenges, both in terms of optimizing energy resources and facilitating access to them. It makes it possible to adjust energy production, consumption and limiting losses. In the stand alone PV system it is achieved through a electrochemical storage : a battery. This solution makes it possible to compensate the fluctuating nature of solar energy production, during periods of solar irradation the battery is loaded while at night the energy stored can be returned [5].

Stand Alone PV system

The synoptic Figure 2. shows schematically the elements and the functioning of the system, the purpose of the study being the influence of temperature, so the electrical diagram is not detailed in this paper. The interest of this diagram is to understand that the electrical power generated by the PV panel does not provide the same output according to two scenarios : - Production > Consumption: The energy produced is used to charge the battery, if the battery is full, the current is then redirected to the electrical grid or it can be used to heat water for example.

Production < Consumption: The energy stored on the battery is then used to complete the electricity needs of the supllied system.[3]

Figure 2 : Schematic view of the system

As detailed above, in this system, there are various input parameters that influence efficiency. In the following section, we will define the varying parameters of this system in order to understand the influence of temperature..

The first input variable is the solar iradiation, it defines the electrical power that the PV panel will be able to deliver. Its value is set at 1000W/m², which is the standard value for a test. It is important to note that this value does not correspond to the received terrestrial radiation which is on average 340W/m²[1].

Concerning the choice of the battery, according to the work of Mr.DEKKICHE in 2008 [4] and Mr.Benamara in 2012 [5], the litthium-ion system is perfectly adapted. Indeed, we can see that this type of battery has a very good charge/discharge efficiency around 90%, which is very important for our application. In addition, its percentage of self-discharge (≈2%) per month is very low, which is another important advantage. For all these reasons, we choose to use the Litthium-ion battery for the study of this system. As it is expensive, Litthium-ion batteries are not yet very often used on the market for this type of application. In the following part, the reflection will focus on optimizing the production of electrical power and therefore the quantity of stored energy.

Temperature influence on PV effeciency

The efficiency of a photovoltaic panel depends on the output power delivered. The latter is related to the voltage (U) as well as the current (I) (Power=Umax*Imax). Those two physical quantities are highly temperature dependent. In fact, when the temperature increases, the current will tend to rise while the voltage will drop Figure 3 [6].

Figure 3 : Current-Voltage output curve characteristics of the PV module with different temperatures [6]

The maximum output power that can be obtained will therefore be the best ratio between current and voltage. This means that this optimal point fluctuates a lot since the current decreases as the voltage increases. Several calculation methods such as MPPT [3] (Maximum Power Point Tracking) can be used to determine this point in order to constantly obtain the maximum power according to external parameters. These results, which can be found in many experiments, testify to the harmful nature of temperature on the performance of a PV panel. At this point the dilemma is the following, to increase the efficiency it is necessary to increase the power which depends on the solar iradation. A solar panel absorbs only 6 to 20% of the rays, the rest is converted into heat which in turn will reduce the efficiency of the system [7]. To overcome this constraint and achieve an optimal operating mode, it is essential to control the panel temperature. The combined system of photovoltaic thermal (PV/T) solution compensates for efficiency losses. This technology consists of using heat transfer fluid to recover the heat from the refracted rays as well as the heat released by the joule effect. This system allows not only to cool the PV cells and thus improve their efficiency but also to transform the heat initially considered as a loss in heat energy usable for the system provided (e.g. hot water for a house) [8].

Several vectors can be used, in particular water or other liquids (figure 4. [9]) with a thermal efficiency of 45% to 65%. Gases such as air are also used because they are less expensive to use but have a lower efficiency about 45% [10].

Figure 4 : Schematic figure of a PV/T system [9]

Experimental model

The objective of this experimental study is to compare the efficiency between a liquid and a gaseous heat transfer fluid in order to determine if the price difference of the technology is justified by performance. In order to judge the performance of both systems, the output analysis data will be: -Thermal efficiency: it is a ratio experimentally determined from the temperature difference between the fluid and that on the surface of the PV cells.

-Electrical efficiency: it is the quotient between the maximum theorical electrical power that the panels can provide and the measured power at the output [10].

The multiplication of these two performance factors will give us an overall system performance coefficient.

Figure 5 : PV/T air system

The first system tested Figure 4 uses water with some additive as a carrier, its thermal conductivity is 4180 J.KG1.K-1. The second system Figure 5 works with air 1007 J.KG1.K-1, the properties of these two fluids shows that water is presumably a more efficient vector.

Table 1 : Input factors

In order to compare the two technologies as well as possible, the tests are carried out in order to vary the different input variables. Table 1 presents these factors : solar radiation A, environmental temperature B (fixed at 25°C) and PV cells temperature D. The concentration factor C corresponds to a percentage concentration of the solar rays to simulate a PV panel whose inclination is more or less perfect with regard to the incident rays of the sun, the value 1 corresponds to a nonoptimized positioning with regard to the radiation, the value 2 so 100% of concentration of the rays will be taken for this study.

Design of experiment

The objective of the design of experiment is to identify the most significant factors and the possible interactions between them.

Table 2 : Results of the different runs

The Table 2 is a summary of all the input and output Data. It shows the reponse of the outputs, so the percentage on efficiency of the two systems according to the combination of input factors.

Table 3 : Results of the ANOVA

The anova shows us the impact of the different factors but above all how significant are those factors in our model. The P-values that is less than 0.05 indicate that the model is significant. For the different factors and interactions, when the P-value is greater than 0.1 it indicate that the terms is not significant. The AD interaction in this case is not significant, it can be explain because the values are randomly generated. So the experimental part can still be done anyway.

Table 4 : Fits statistics

The R² is an indicator for judging the quality of a simple linear regression. It measures the adequacy between the model and the observed data. The he R² of 0.97 means that the equation of the regression line is able to determine 97% of the point distribution. In addition, the difference between the Adjusted R² and the predicted R² is less than 0.2. We can conclude that this model can be used.

Data analysis

The simulation results show the strong interaction between these different parameters. As expected for a given ambient temperature (=25°C), the temperature of the PV Cells increases as the intensity of solar radiation increases. This strong interaction has a direct impact on the responses of both systems

Table 5 : Response of the two systems

		PV cells temperature (°C)
	Solar radiance (daW/m²)	0	152
	25	49.38%	50.99%
	125	53.20%	53.79%
	25	52.68%	54.29%
	125	56.51%	57.09%

It can be seen that for a zero temperature of the PV cells the global efficiency increases with the amount of solar radiation. This increase is to be expected, it is the very principle of the photovoltaic effect. However, we cannot conclude whether one system is more efficient than the other since temperature does not have an influence at this stage.

For a very high temperature of the PV cells, the increase in efficiency is noted. As explained above, temperature reduces the electrical efficiency of the system, but it is the hybrid thermal system that shows all its meaning since this constraint becomes an advantage on the overall efficiency.

Concerning the conclusion in relation to these results, an increase in the efficiency of the system is visible when the temperature increases and so when the thermal system comes into operation. On the other hand, the increase is too small to affirm a real benefit, and also the difference in efficiency between the two heat transfer fluids is too small to determine which system is the most appropriate. It should be noted, however, that these data were generated randomly and therefore do not reflect actual real life conditions.

Figure 6 : Efficiency of both systems as a function of cell PV temperature and solar radiation

Conclusion

A solution for Temperature measurement of a solar panel for optimum energy storage has been presented in this paper. The stand alone PV panel system has been developed in order to understand the challenges of such an optimization, indeed the critical point of this problematic is in the optimization of the energy production efficiency which consequently increases the amount of stored energy. The MPPT method was presented to explain how to optimize electrical efficiency. But the influence of temperature still remains a major constraint. In fact, the increase in electrical production leads to an increase in temperature and therefore a decrease in electrical efficiency. The PV hybrid thermal panel solution was therefore presented. This system allows to recover the thermal energy released as well as to cool the PV cells. This sytem has demonstrated in the first more theoretical part it efficiency in relation to the increase of the overall efficiency in terms of energy stored. In this last experimental part, the aim was to determine whether a liquid heat transfer fluid is more efficient than a gaseous one. We found that the air PV/T system seems less efficient than the liquid system. In addition, since the design of air systems is easier to manufacture and is only 2% to 4% less efficient, it is the most promising concept.

References

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