Hierarchical Coordinated Automatic Generation Control Involving Distributed Energy Resources: An Aggregation Approach

The distributed energy resources (DERs) need to provide ancillary services due to their increasing penetration level in distribution networks (DNs). This paper proposes a hierarchically coordinated automatic generation control (AGC) scheme for the multi-level power grids, to facilitate the DERs to p...

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Veröffentlicht in:IEEE transactions on smart grid 2024-11, p.1-1
Hauptverfasser: Shen, Yukang, Wu, Wenchuan, Wang, Qi, Li, Yong, Li, Sun, Teng, Wei
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Sprache:eng
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Zusammenfassung:The distributed energy resources (DERs) need to provide ancillary services due to their increasing penetration level in distribution networks (DNs). This paper proposes a hierarchically coordinated automatic generation control (AGC) scheme for the multi-level power grids, to facilitate the DERs to provide AGC service, while ensuring the operational security of the host DNs. Each DN is formulated as an individual AGC participating entity to reduce the computational and communication burden of the transmission system operator (TSO). The distribution system operator (DSO) aggregates its managed DER clusters as a whole, and evaluates the equivalent aggregation dynamic model as well as the regulation capacity. The regulation capacity is evaluated using an optimization program that consider device and network constraints, and prediction uncertainties. The aggregation dynamic model is estimated based on the curve-fitting, which represents the external power response characteristics of the DN as a second-order state-space model. In addition, P-Q affine regulation strategy is employed to coordinate frequency and voltage control. The active and reactive power commands are simultaneously allocated to DER clusters to eliminate voltage violations arising from providing AGC services. Case studies conducted on a multi-level power grid verify the effectiveness and scalability of the proposed method.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2024.3493124