Expert transmission assisted-healing system application based on alarms and real-time measurements

• Published in: Electrical engineering Vol. 101; no. 1; pp. 279 - 290
• Main Authors: da Silva Antunes, Fábio Augusto, da Silveira, Paulo Márcio
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2019; Springer Nature B.V
• Subjects: Alarms; Avalanches; Circuit breakers; Decision making; Economics and Management; Electrical Engineering; Electrical Machines and Networks; Energy Policy; Engineering; Expert systems; Healing; Multilayers; On-line systems; Operators; Original Paper; Power Electronics; Restoration; Support systems; Assisted-healing; Self-healing; Power system restoration; Expert systems; Operation center
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-019-00777-x

Transmission system restoration is a critical task which requires agility and safety. On the one hand, the restoration proceedings, composed of numerous documents, establish the sequence and its preconditions that must be observed before the execution of each action. On the other hand, a significant amount of information, such as alarms and protection signals, fills the operator’s HMI and causes an effect known as “alarm avalanche.” The time spent to understand all of this information impacts the result of the restoration, while any erroneous preconditions assessment can undermine the restoration process. In order to conduct an efficient restoration process for power transmission systems which improves both security and agility, an online decision support system inspired by assisted-healing approach is proposed. The system is also based on the expert systems methodology through which the inputs (alarms, state of circuit breakers, protection signals, and operation proceedings) are submitted to a large set of rules (a multilayer inference engine) to be transformed into intelligible outputs for operators. These outputs instantaneously give operators the full set of conclusions necessary for decision making with the advantage of preventing misunderstandings. This paper presents an applied research whose results and simulations performed at Cemig Generation and Transmission show that it is possible to automate the processing of all these data so that operators have better information to make decisions during these critical situations.