A bi‐level transactive control model for integrating decision‐making and DLMP‐pricing in distribution networks

The market‐driven demand side management of distribution networks suffers from the challenge of operational security issues. This paper proposes a distribution locational marginal price (DLMP) based bi‐level transactive control model for distribution networks to manage demand side resources of nodal...

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Veröffentlicht in:IET generation, transmission & distribution Jg. 16; H. 19; S. 3814 - 3824
Hauptverfasser: Li, Biao, Wan, Can, Luo, Fengji, Yu, Peng, Sun, Mingyang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Wiley 01.10.2022
ISSN:1751-8687, 1751-8695
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Zusammenfassung:The market‐driven demand side management of distribution networks suffers from the challenge of operational security issues. This paper proposes a distribution locational marginal price (DLMP) based bi‐level transactive control model for distribution networks to manage demand side resources of nodal agents, ensuring both the network security and the agents' optimal decision. The proposed model consists of a DLMP‐pricing model at the upper level and DLMP‐based demand response (D‐DR) models at the lower level, integrating the DLMP‐pricing of the distribution network and the decision‐making of agents. The DLMP‐pricing model is constructed as the dual form of a linearized optimal power flow problem to determine DLMP related to the decision of all agents. The D‐DR model enables each nodal agent to minimize its own expenditure under the DLMP, which is established as a linear programming problem. The bi‐level model is converted into single‐level programming through replacing the D‐DR models by Karush‐Kuhn‐Tucker conditions, in which the bi‐linear items of the complementary slackness are further linearized by introducing integer variables. Consequently, the intractable bi‐level transactive control model is equivalently reconstructed as a single‐level mixed‐integer linear programming problem that can be conveniently solved. Comprehensive numerical studies validate the effectiveness of the proposed model.
ISSN:1751-8687
1751-8695
DOI:10.1049/gtd2.12549