# Quantification of the Benefits for Power System of Resilience Boosting Measures
## 5 Case Studies
### Contingency Forecasting in Operational Planning Mode (OP1)  
This case study is an example of contingency forecasting application to a real emergency wet snow scenario occurred in The North of Italy on 5-7 February 2015. The forecasts of the weather variables of interest (ambient temperature, wind speed intensity and direction, precipitation rate) are elaborated on 4 February 2015 for the subsequent 72 h, and for each of the 11381 points of the forecasting geospatial mesh.  
By applying the forecasts of weather variables to the grid model, it is possible to get the geospatial distributions of the stress variables of interest (wind and snow loads) for each hour belonging to the 72 h forecasting period: Figure 7 shows the action on line components (expected values of the mechanical tension, the sleeve thickness and the load on cross-arms) for the 10 h of the forecasting period, highlighting the OHL spans with the highest values of stress variables.  
In 10 h ice sleeves reach about 100 mm thicknesses, making the mechanical tension on some OHLs approach to 100 kN which is the rated tensile strength for a typical 22.8 mm conductor used for 132 kV lines. The records of the real emergency event indicate that first 132 kV lines were damaged at hour 12, which confirms a good agreement with the tool outputs.  
The critical lines (i.e., the ones which most contribute to the total failure probability) at hours 8, 10, and 15 reported in Table 4 belong to the same geographical area where the largest number of collapsed  
Figure 7: Ice thickness in mm (**top right diagram**), mechanical tension (**top left diagram**) and mechanical load on tower equipment in kN (**bottom left diagram**) in the first 10 h of the forecasting interval.  
lines were recorded (areas of Parma, Modena, Bologna). At hour 28, 24 lines at 132 kV show a failure probability higher than 90%.  
In hours 8 and 10 the lines with the highest failure probabilities are located in the countryside south of Bologna city; in hour 15 the affected lines still south of Bologna get closer to the city. Adverse weather conditions persist causing large sleeve thicknesses on conductors and high mechanical tensions close to the rated tensile strength around hours 30-40, which is also highlighted by actual records: in fact, after hour 35 various 132 kV lines connected to substations in the provinces of Bologna, Parma and Modena were damaged and their repair times were higher than 3 h. Simulations confirm that the lines with very high failure probabilities are around Parma, and between Modena and Bologna [23].  
Starting from the list of critical components at hour 15 (see Table 4), RELIEF generates a set of 71 single and multiple contingencies which most contribute to the total operational risk. This set includes 6 \"N-1\" branch contingencies, 15 \"N-2\", 20 \"N-3\", 15 \"N-4\", 6 \"N-5\", and 1 \"N-6\" common mode multiple branch contingencies, and 8 multiple dependent busbar contingencies.  
The assessment of the relevant risk indicators shows that the higher risk contingencies and seven out of the ten most likely outages are N-k common mode contingencies: under extreme weather conditions multiple outages are more probable than single outages and contribute to the larger part of the Loss Of Load (LOL) risk. This fact demonstrates the limits of conventional N-1 criterion and the advantages of applying the contingency forecast criterion. The total LOL risk at hour 15 is equal to 14.6 expected lost MW.