Uma Estratégia Cognitiva de Recuperação de Redes Elétricas no Contexto do Smart Grid
Creators: name: Calhau, Flávio G.
Publisher: name: Zenodo
Year: 2019
Subjects: Smart Grid
Network Reconfiguration
Cognitive Management
Reconfiguration Algorithm
HATSGA
Case-based Reasoning
Autonomic Computing
Dynamic Reconguration
Scalable Reconguration

description: Electrical Power Supply Distribution Networks have become very attractive due to automation process and electronic devices incorporation, which allows distance maneuvers. The reconguration process consists of changing distribution network topology by closing or opening interconnection keys. Also, such process focuses on supporting decision making, planning and/or real-time control of electric network operation aiming to minimizing active power losses, load balancing, fault isolation, voltage level improvements and maintaining continuity of user services. The task of managing and taking decisions to change the electrical network topology is a complex task due to the diversity of conguration possibilities. In this context, Autonomic Management Systems (AMS) are being investigated as a feasible solution to the grid reconguration problem. Thus, we expect that management human intervention can be replaced by autonomic solutions, preferably, dynamically generated. This thesis proposes the use of Case-Based Reasoning (CBR) coupled with HATSGA algorithm for the fast reconguration of large distribution power networks. The suitability and the scalability of the CBR-based reconguration strategy using HATSGA algorithm are evaluated. The evaluation indicates that the adopted HATSGA algorithm computes new reconguration topologies with a feasible computational time for large networks. The CBR strategy looks for managerial acceptable reconguration solutions at the CBR database and, as such, contributes to reduce the computational time of reconguration using HATSGA. This suggests CBR can be applied with a fast reconguration algorithm resulting in more efficient, dynamic and cognitive grid recovery strategy.
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