# Unstructured Data Analysis for Risk Management of Electric Power Transmission Lines +
## 5 Experiments
### Experimental Results  
Based on the content extracted from the reports of the ANEEL meetings, several relevant keywords were identified which were directly associated with 97 of the 233 risks identified by a specialist and presented during the life cycle of implementation of transmission lines (TL). The association between risks, keywords, and reports made it possible to identify the set of risks in the extracted reports and which areas or phases of the project could be refined. In addition, two equations were generated to be used as risk probability calculation parameters, with the probability of each risk occurring by the area or phase of the TL implementation project. In order to evaluate and visualize the relevance of each keyword, a word cloud was generated (Figure 3). The words displayed show a relationship between the ANEEL reportsand the risks raised by experts. The bigger the word's text size, the more times this word appeared in the weekly reports. This does not mean that more frequent words get a higher weight in the probability calculation. However, since they appeared more frequently, they would probably impact more risks than smaller ones. Figure 4 shows the number of specific risks found in reports from 2005 and 2021. As an example, a risk found was ID 1.11.01, which is described as _non-approval of the environmental study by the licensing agency_. Its causes are pending documentation for the LP request, the elaboration of the environmental study in disagreement with the guidelines defined by the environmental agency, and a record of delay in the LP issuance request deadlines. This risk is related to the environment area in the feasibility phase (Auction-LP). It was identified by crossing the following keywords: request for issuance, term of reference, elaboration of the study, and pending at the environmental agency. The year with the highest number of risks was 2013 with 79 risks. For instance, the risk _\"need to change the time of displacement of vehicles for works on roads and access roads\"_ was also related to the area of environment and the implementation phase (LI-LO). Its primary cause was the verification by the program execution team of the need to adjust the operating hours or restrict activities related to work in noise-sensitive areas such as schools, daycare centers, hospitals, or communities. The keywords that identified the risk were program execution, need for adjustments, need for alteration, and access routes. Figure 4: Number of unique risks per year. When at least one keyword from the causes of a specific risk is found in a report from a particular year, this risk is accounted for in the unique risks per year shown in this graph. It is important to note that if keywords were found on different reports for the same risk, that risk was counted only once for that particular year. Figure 3: The most relevant keywords identified in the ANEEL reports. Figure 5 shows the number of distinct risks per report. For example, the meeting reports in 2020 were presented and represented by their internal identifiers (IDs). The reports with the highest occurrences presented 21 different risks held in April in the year in question. They presented risks related to the environment, implementation, engineering, and regulatory areas. The next meeting report with 21 risks, realized in December, contained O&M engineering and regulatory risks. Based on Equation (2), the risk probability was calculated as shown in Figure 6. This shows only the risks with a probability higher than 20%. The risk identified with the highest probability of occurrence was identifier (ID) 4.04.15 with the following description: _\"not meeting the deadlines for replacing equipment already approved by ONS\"_. This risk is related to the O&M engineering area and the operation (O&M) phase, with the non-compliance causes aligning with the ANEEL guidelines in the Electric Sector Accounting Manual and the Electric Sector Asset Control Manual.