A Cloud Model-Based Optimal Combined Weighting Framework for the Comprehensive Reliability Evaluation of Power Systems with High Penetration of Renewable Energies

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2273 - 2273

Published: March 5, 2025

Reliability has long been a critical attribute of power systems that cannot be ignored. Numerous blackout events have highlighted the increasing risk outages in due to prominence high-proportion electronics and renewable energy utilization. Traditional reliability assessment methods, which typically take dozens hours assess adequacy steady-state conditions, reflect real-time performance system. Moreover, weakness identification methods can only quantify impact component while ignoring other important operational factors. To address these issues, this paper constructs three-hierarchy evaluation index system (REIS) for systems, consisting comprehensive (CREI) as top hierarchy, four primary indices middle, lots subjective objective on bottom. different calculation indices, combined weighting framework is proposed. Finally, REIS level evaluated according Wasserstein distances between CREI cloud model standard models. In case study, proposed method verified through its application grids two cities province southern China, demonstrating practicality effectiveness.

Language: Английский

Comprehensive Condition Evaluation of Distribution Transformer Considering Internal Operation, External Environment, and Load Operation for Business Expansion

Energies, Journal Year: 2025, Volume and Issue: 18(10), P. 2456 - 2456

Published: May 10, 2025

This paper proposes a comprehensive condition evaluation method for distribution transformers considering their internal operation, external environment, and load operation business expansion. Unlike the existing studies, proposed can not only comprehensively consider impacts of equipment aging, environmental influence, post-business-expansion variations on transformer’s but also effectively simplify process determining weight identifying transformer. Firstly, indicator system is established. Subsequently, each transformer calculated by using ordering relation analysis–principal component analysis (ORA-PCA) principle minimum discrimination information. Based this, an improved golden section utilized to construct criterion clouds. Moreover, model developed based cloud expectation curve method. Finally, effectiveness validated case study, sensitivity conducted expansion, providing theoretical support classification boundaries.

Language: Английский