# Increasing Photovoltaic Systems Efficiency Through the Implementation of Statistical Methods
## 4 Results
### Applying the STEM Method Results  
According to the flowchart in Figure 1, the following steps were considered:  
Step 1  
The characteristics j of the PV power plants belonging to the sets S1 and S2, respectively, are chosen:  
* Efficiency of photovoltaic panels (E), the greater, the better;
* Nominal power of a panel (P), the greater, the better;
* Tracking systems (T), the greater, the better;
* Panel surface (S), the smaller, the better;
* The specific cost of a panel (C), the smaller, the better;
* Overall losses (L), the smaller, the better. Step 2  
It chose five representative PV power plants (\(i\) = 1... 5), with the respective general characteristics:  
1. PV power plant Borzesti (Romania), 1.19 MWp--considered the reference [34], using monocrystalline PV panels;
2. PV power plant Stupini-Brasov (Romania), 20 MWp, Ref. [35] monocrystalline panels;
3. PV power plant, Ouarzazate (Morocco), 20 kW, Refs. [36; 37; 38] using HCPV technology, including tracking;
4. PV power plant Elazig (Turkey), 1 MWp, Ref. [30], using polycrystalline panels;
5. PV power plant Bisha (Saudi Arabia), 10 MWp, Ref. [39] using monocrystalline panels and a single-axis tracking system. Furthermore, the characteristics table identified in Step 1 was constructed using data extracted from the bibliography for the proposed PV plants (Table 11). Since PV Power Plant 1 was considered the reference, the following notations were assigned: 2 \(\equiv\) A, 3 \(\equiv\) B, 4 \(\equiv\) C, and 5 \(\equiv\) D.  
The PV builders provide the values for efficiency (E), the rated power of the used PV panel (P), panel surface (S), and the specific cost of a PV panel (C) in Table 11 [27; 31; 32; 33; 34; 35; 36]. In the above table for the tracking systems (T) parameter, a coefficient of 1.10 (+10%) was assigned for photovoltaic systems without tracking and 1.30 (+30%) for those with tracking because systems oriented according to the sun improve yield by approximately \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Orientation** & \multicolumn{2}{c}{**June**} & \multicolumn{2}{c}{**July**} & \multicolumn{2}{c}{**August**} \\ \hline
10\({}^{\circ}\) & 157 & 15.5 & 166 & 23.5 & 155 & 13 \\
20\({}^{\circ}\) & 156 & 14 & 166 & 23.5 & 159 & 19 \\
30\({}^{\circ}\) & 152 & 11.5 & 163 & 22 & 160 & 21 \\
37\({}^{\circ}\) & 148 & 10 & 159 & 19 & 159 & 19 \\
40\({}^{\circ}\) & 146 & 8 & 157 & 15.5 & 158 & 17 \\
50\({}^{\circ}\) & 136 & 6 & 147 & 9 & 152 & 11.5 \\
60\({}^{\circ}\) & 123 & 3 & 134 & 5 & 142 & 7 \\
70\({}^{\circ}\) & 107 & 1 & 118 & 2 & 129 & 4 \\ \hline Rang sum & & 69 & & 99.5 & & 111.5 \\ \hline
**(Rang sum)2** & & **4761** & & **9900.25** & & **12,432.25** \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Case B: The analysis (table of ranks) for June, July, and August. 30%. At the same time, a tracking system increases costs by about 10% compared to the specific cost (C), as specified in the fifth row of the table above. For the overall losses (L) parameter from Table 11, it is currently considered that these losses represent approximately 14% of the electricity produced by a PV power plant, which is equal to all the PV plants analysed. In the future, if a plant diminishes its own losses, this parameter can be adjusted accordingly. In Table 12, the matrix of characteristics Kij was calculated from the data in Table 11.  
In Table 13, the matrix/table \(a_{j}\) was built. The weight of the characteristics \(\gamma_{j}\) was calculated according to Relation-calculated according to Relation (7):  
In the end, the absolute technical level, \(\mathrm{Ha}_{\mathrm{i}}\), was calculated according to Relationships (2,3), considering the \(\mathrm{H}_{\mathrm{REF}}=1000\):  
\[\mathrm{Ha}_{\mathrm{A}}\approx 1045 \tag{9}\]