*3.2. System Description and Meteorological Data*

This paper focuses on the optimal design of large-scale PV power plants connected to the electric grid. The optimisation process was carried out using HGWOSCA and SCA techniques. The proposed methodology supports PV plant configurations for both central and string topologies and the arrangement of the components within the installation area. Moreover, it considers a list with different types of PV modules and inverters and their specifications as candidates to design the PV power plant, as illustrated in Tables 5 and 6. The actual meteorological data, such as solar irradiance, wind speed, and ambient temperature, are also considered. The optimisation process in this methodology aims to determine the number of PV modules connected in series and parallel, the number of PV module lines per row, the distance between two adjacent rows, the tilt angle of the PV module, the orientation of PV modules that can be installed vertically or horizontally, the optimum PV module and inverter, from a list of possible candidates. Two objective functions, namely the minimum LCOE and maximum annual energy, were considered. Furthermore, the effect of the annual PV module reduction coefficient on PV plant performance was determined.

**Table 5.** Photovoltaic (PV) modules specifications at standard test condition.



**Table 6.** Inverters specifications at standard test condition.

### 3.2.1. System Description

The architecture of PV plants is composed of several hundreds of PV modules that produce DC power depending on the meteorological parameters (solar radiation and temperature) [64] and inverters that permit the conversion from DC to AC power and ensure the maximum power extraction from the PV modules [65]. The generated power is injected directly into the electric network at the point of common coupling by using step-up transformers [66].

In PV plants, PV modules are connected in series (*Ns*) to form a string. These strings are rationalised and connected in parallel (*Np* ≥ 1) to form a PV array. In the case of central inverters topology, several hundreds of PV modules are connected to one inverter, and junction boxes need to be used through the DC main cable before leaving for the inverter. In string inverter topology, one string is connected directly to one inverter, and junction boxes need not be placed in the installation field.

The PV arrays within the available area are arranged in multiple rows. Each row consists of multiple lines of PV modules. The number of lines per row is equal to *Nr*. Considering the shading effect, the inclined adjacent rows are installed with space in between. The tilt angle (β) of PV modules is constant during the PV plant lifetime.

The universal transverse Mercator coordinate (UTM, X: east, Y: north) system was used to model the PV power plant area. Several PV modules vary from one row to another, as the row length varies on the basis of the installation area shape.

#### 3.2.2. Selected Site

The Djanet village is located in the South East of Algerian Sahara in the province of Illizi, and it is characterised by a hot desert climate according to longitude 9.28◦ E, latitude 24.15◦ N and an altitude of 1030 m. Djanet village electrification is still dominated by diesel generation (DG). The delivery of fuel leads to an increase in the cost and the maintenance of the units. However, a PV plant grid connected with a capacity of 3 MW was installed in 2015, and its extension is expected to reach 7 MW to supply the village and decrease the units of DG.

#### 3.2.3. Meteorological Data

The performances of PV modules depend on solar irradiation, ambient temperature, and wind speed. These data have been recorded to step times of semi-hourly and hourly. Solar irradiation is expressed in Watts per square meter (W/m2). Ambient temperature is in degrees Celsius (◦C). Wind speed is in m/s. Figures 2 and 3 show the daily assessment of the meteorological characteristics. The semi-hourly data of solar irradiance and ambient temperature are observed as more accurate than the hourly data. That is because the peak values of the solar irradiance and ambient temperature may not be recorded in the hourly data. This happens because the data only records point values for every hour, while within a period of time the meteorological data may have significant fluctuation. Thus, semi-hourly data is more precise and accurate compared to hourly data measurements.

**Figure 2.** Irradiance data. (**a**) Hourly average time. (**b**) 30 min average time.

**Figure 3.** Temperature data. (**a**) Hourly average time. (**b**) 30 min average time.

To determine the energy generated by the PV power plant, knowledge of the solar irradiance profile during the year is required. The solar irradiation for hourly and semi-hourly (i.e., 30 min-average) data of the selected location are plotted in Figures 4 and 5. As we can see, the radiation intensity remained high over the year. It is observed that the maximum value of solar irradiance is reached in

March. As for the minimum value of irradiance, this is recorded in June. Each vector represents the same size for 1 year, where the one for semi-hourly step is equal to 17,520 data and the one for hourly step is equal to 8760 data. The climatic conditions of the location are as follows: high solar irradiance potential; ambient temperature with a maximum average of (29.7 ◦C) in summer; and the sky is mostly clear during the whole year.

**Figure 4.** Hourly solar irradiance over the year (W/m2).

**Figure 5.** Solar irradiance over the year (W/m2).
