# Dynamic Thermal Rating and Development of Renewable Energy Zones in Sicily
## 4 Methodology
### Application of Dynamic Thermal Rating to Sicilian Transmission Grid
#### 4.2.3 Identification of Critical Lines  
After implementing the algorithm proposed by IEEE, a methodology was developed to identify the set of locations where the Dynamic Thermal Rating simulations should be performed. Specifically, the following steps were taken:  
* Identification of all municipalities crossed by each REZ;
* Classification of the municipalities in each REZ based on their potential for thermal exchange to identify the hot spot municipalities;
* Once the hot spot municipalities had been identified, Dynamic Thermal Rating simulations were carried out for the municipalities crossed by each REZ in these locations. To classify the municipalities of each REZ, software owned by Terna called Sisnet was used, which shows the layout of the entire Italian transmission network. In each Renewable Energy Zone, the following municipalities are present:  
* REZ A: Mazara del Vallo, Campobello di Mazara, Castelvetrano, Partanna;
* REZ B: Marsala, Misilicemi;
* REZ C: Trapani, Pacco, Misilicemi, Erice, Buseto Palizzolo, Custonacci, Castellammae del Golfo;
* REZ D: Castellammae del Golfo, Alcamo, Partinico;
* REZ E: Troina, Cerami, Capizzi, Mistretta, Castel di Lucio, Regalbuto;
* REZ F: Gela, Butera, Licata, Acate, Vittoria. To determine the hot spot municipalities in each REZ, the following methodology was used based on the climate analyses mentioned in the previous paragraphs:  
* For each municipality in the REZ, the climatic class for each month of the year was calculated;
* Each municipality was assigned a score, called the \"hot spot score\" (X), which is calculated as follows:  
\[\mathrm{X_{m}}=\sum_{1}^{12}\mathrm{X_{m,month}} \tag{9}\]  
where \(\mathrm{X_{m,month}}\) is a number corresponding to the value of the climatic class of the municipality for the month in question. It is important to clarify that the meteorological stations used for these climatic analyses may be different from those used for the analysis of the region as a whole. This choice was made to ensure the most accurate results possible. For the analysis of each REZ, only the meteorological stations available in the vicinity of the REZ were used, while for the global and regional analysis, the stations that ensured equal availability of meteorological data over the whole region were used. The DTR simulations performed consider the meteorological conditions observed on 19 April 2024. This choice is consistent with the fact that the network overloads from which the REZ were identified were simulated under the meteorological conditions of 19 April 2024. Another important point to highlight is that the proposed results consider not only the thermal limit of conductor annealing but also the thermal limit due to the presence of other network elements, such as current and voltage transformers. Figure 3 illustrates the results of the simulations and compares them with the corresponding current capacity currently in use. It can be observed that the results obtained refer to the hypothetical network scenario of 19 April 2024, characterized by high energy production from renewable sources. In all the sites studied, it was possible to simulate a significant increase in the current carrying capacity of the lines without reaching conductor  
annealing conditions and while respecting the current limits imposed by network elements (such as current and voltage transformers). In addition, since the analyses were carried out in the hot spots of the various Renewable Energy Zones, the installation of a few DTR devices in these municipalities should ensure an overall increase in the permissible power flows across all the lines of each REZ. This section presents the results of the comparison between the following:  
* Overloads simulated on WinCreso, under n-1 network conditions on 19 April 2024;
* Overloads following the implementation of Dynamic Thermal Rating on the same lines, under the same network conditions. An important clarification is made: the overloads have been expressed in terms of active power [MW], assuming, for simplicity, a power factor of 1.