Affiliation:
1. Department of Electrical Engineering, Khwopa College of Engineering, Bhaktapur 44800, Nepal
2. Department of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel 45210, Nepal
3. Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, Porsgrunn N-3918, Norway
4. Centre for Renewable Energy Systems Technology (CREST), Loughborough University, Loughborough LE11 2HN, UK
Abstract
Despite there are significant advancements in modern power systems, blackouts remain a potential risk, necessitating efficient restoration strategies. This paper introduces an innovative concept for power system restoration, focusing on balancing active and reactive power while ensuring voltage stability. For instance, this paper employs an agglomerative clustering technique, which partitions the power system into segments with balanced reactive power, facilitating swift restoration postblackout. Central to this methodology is the use of the line stability factor, which assesses the voltage stability of individual lines, identifying the system’s stronger and weaker sections based on voltage stability levels. This paper demonstrates the effectiveness of the proposed methodology through case study analysis, comparing voltage stability levels across agglomerative clusters and their geographical locations. The power system is divided into two stable partitions, considering the number of black-start generators, available reactive power, and voltage stability levels. This partitioning reveals that the clusters formed by the agglomerative method are inherently stable, suggesting enhanced system stability, dependability, and availability during the restoration phase following a blackout. In addition, this paper discusses the potential causes of blackouts, offering insights into their prevention, and finishes with a novel clustering methodology for power systems, considering reactive power and voltage stability. This method facilitates the parallel restoration of the system’s independent partitions, significantly reducing restoration time; it addresses critical challenges and outcomes, underscoring the methodology’s potential to revolutionize blackout recovery processes in modern power systems.