INTEGRATED RISK MANAGEMENT USING ARTIFICIAL INTELLIGENCE IN AN ELECTRIC POWER TRANSMISSION ENTERPRISE.

This work presents a computational tool for Integrated Risk Management in a transmission enterprise, through data integration and analysis using Artificial Intelligence (AI), statistical and Business Intelligence (BI) methods. The life cycle phases of transmission projects defined for this work are: (1) pre-auction, preparation for concession dispute; (2) feasibility, engineering and environmental licensing studies; (3) implementation, of construction of the transmission line and substations, with execution of environmental programs; 4) operation and maintenance, for the entry of the enterprise into commercial operation. The areas of interest defined for Risk Management are: (a) Environment; (b) Land ownership; (c) Implementation Engineering (Construction); (d) O&M Engineering (Operation and Maintenance); (e) Regulatory; (f) Relationship with Investors/New Businesses. The objectives of this work are: to identify possible data sources that can be associated with transmission project risks; and analyze, through the application of several methods, how these data are correlated with each other. For this, an optimized analysis of the main causes of delays in the delivery of projects, cost increases and interruption of energy transmission is carried out and, through surveys carried out by professionals from each of the defined areas of interest, previous causes that may be mapped occur throughout the life cycle of projects. Analyzes are presented in the form of dashboards, with the aim of helping managers to make more assertive decisions. Another objective is to identify unresolved issues during the implementation phase, preventing them from having any impact on the operation phase. [ABSTRACT FROM AUTHOR]