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.
Highlights
P OWER systems are increasingly operated closer to their capacity limits, due to technical, economic and environmental drivers
Results are organized as follows: Section V-A tests and discusses zoning methodologies’ generalities of interest for the coordinated voltage regulation (CVR) application, Section V-B investigates the applicability of the zoning methodologies in adaptive RCM, while the four paragraphs deal with the evaluation of the zoning methodologies using the proposed framework on a network with non-obvious boundaries
In pursuit of improved coordinated automatic voltage control, this paper proposed a novel generic framework to evaluate various configurations of CVR components
Summary
P OWER systems are increasingly operated closer to their capacity limits, due to technical, economic and environmental drivers. While comparative studies exist for the approaches of the second research direction [19], [27], such an analysis has not been extended to zoning methodologies This paper fills this gap and further argues that the selection of a zoning methodology affects the CVR performance, and its robustness to erroneous data and the feasibility for adaptive RCM. The main contributions of this paper are: 1) It proposes a generic framework to assess the overall performance of CVR and has the following novel key attributes: It enables zoning methodologies comparative evaluation deploying full AC load flow equations within a probabilistic analysis, effectively extending [19], [27] It can flexibly accommodate and evaluate any control implementation, e.g., [26], [30], [1], [31].
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