Operational constrained nonlinear modeling and identification of active distribution networks

• Published in: Electric power systems research Vol. 168; pp. 92 - 104
• Main Authors: Conte, F., D’Agostino, F., Silvestro, F.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-03-2019; Elsevier Science Ltd
• Subjects: Active distribution networks; Computer simulation; Distributed generation; Dynamic equivalents; Electricity distribution; Equivalence; Grey box modeling; Interoperability; Mathematical models; Modelling; Networks; Nonlinear systems; Observability (systems); Operators; Simulation; Grey box modeling; Active distribution networks; Dynamic equivalents
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2018.11.014

•This paper proposes equivalent models of active distribution networks (ADN).•Equivalent models allow TSOs to expand the system observability.•The proposed model is able to take into account the prior knowledge of an ADN.•The model can be easily adapted to different configurations of the ADN.•The approach is validated by a simulation study on a Benchmark MV Active Network.
This paper proposes a methodology for the identification of equivalent models of active distribution networks. Due to the increasing installation of distributed generation plants, distribution networks are acquiring an “active” role in the management of the overall power system. In this context, equivalent modeling is becoming essential for allowing transmission system operators to expand the system observability and improve the interoperability with distribution system operators. The present paper proposes a nonlinear model and an identification procedure able to take into account the prior knowledge of a given active distribution network. The result is an equivalent model, which can be easily adapted for reproducing the dynamical behavior of the network with different configurations. The proposed approach is validated through a simulation study on a Benchmark Medium Voltage Active Network.