Abstract
Hierarchically structured automatic voltage control (AVC) architecture has attracted increased interest as networks operate closer to their capacity limits. Hierarchical AVC enables wide-area coordinated voltage regulation (CVR). Due to the inherent complexity of the task, it is based on reduced control models, i.e., simplified models of the system suitable for voltage control. It is a fact however that a single reduced control model (static RCM) cannot be optimal for all network configurations and operating conditions. In pursuit of an improved CVR, this paper investigates the applicability of zoning methodologies in adaptively determined RCM. It further argues that the selection of a zoning methodology affects not only the CVR operation, but also its robustness to erroneous data and proposes a comprehensive generic framework for evaluating its performance. Lastly, it extends and evaluates several zoning-based control model reduction methodologies: namely, hierarchical clustering employing two different proximity metrics, spectral rm k-way and fuzzy rm C-means, on both static and adaptive schemes.
Original language | English |
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Pages (from-to) | 2736-2746 |
Number of pages | 11 |
Journal | IEEE Transactions on Power Systems |
Volume | 30 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Sept 2015 |
Keywords
- Adaptive control model reduction (adaptive-RCM)
- automatic voltage control (AVC)
- coordinated voltage regulation (CVR)
- erroneous data
- graph theory
- pilot nodes