A transmission expansion model for dynamic operation of flexible demand
Peer reviewed, Journal article
Published version
Permanent lenke
https://hdl.handle.net/11250/2757419Utgivelsesdato
2020Metadata
Vis full innførselSamlinger
- Publikasjoner fra CRIStin - SINTEF Energi [1614]
- SINTEF Energi [1731]
Originalversjon
10.1016/j.ijepes.2020.106252Sammendrag
This paper proposes a model to include investments in demand flexibility into traditional transmission expansion problems under uncertainty. To do so, a dynamic power flow model is proposed. The model is solved via applying a value function approximation in form of a neural network on the operational problem, allowing to yield a result for the non-convex investment problem. Additionally, robust sets are applied and linearized to deal with uncertainty and decrease computational complexity. In similar manner, Karush Kuhn Tucker conditions are used to transform a tri-level into a bi-level problem. Case studies for systems of varying complexity show the convergence of the algorithm as well as that flexible resources can be used as a cost-effective substitute for transmission lines in grid expansion.