4.7 Article

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 12, Issue 4, Pages 1853-1863

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2021.3068630

Keywords

Uncertainty; Real-time systems; Optimization; Active distribution networks; Distributed power generation; Energy storage; Active distribution network (ADN); ADN management; ancillary services; distributed energy resources (DERs); energy storage system (ESS); linear optimization-based control strategy; power flexibility; stochastic optimization; uncertainty

Funding

  1. Swiss Centre for Competence in Energy Research on the Future Swiss Electrical Infrastructure through the Swissgrid
  2. Swiss Innovation Agency (Innosuisse-SCCER Program) [TSTE-01154-2020]

Ask authors/readers for more resources

This paper presents a two-stage ADN management method to deliver power flexibility to the upper-layer grid operator by updating DERs power set-points and adjusting ESS power flexibility injection. The method is tested in a real ADN located in Aigle, Switzerland.
Relying on the power flexibility of distributed energy resources (DERs) located in an active distribution network (ADN), this ADN will be able to provide power flexibility to the upper-layer grid at their point of common coupling (PCC). The power flexibility is defined as additional bi-directional active/reactive powers a resource can provide to the grid by adjusting its operating point. In this context, this paper presents a two-stage ADN management method to deliver, at the PCC, the power flexibility that the upper-layer grid operator would request minutes-ahead real-time operation. The first stage updates the power set-points of DERs considering their offer curves as well as the uncertainties stem from the short-term forecast errors of demand and renewable generation profiles. The inter-temporal constraints and losses of the grid are accounted for by exploiting a linearized dynamic optimal power flow model, whereby the first stage is implemented as a linear scenario-based optimization problem. Then, in real-time operation, relying on a linear optimization problem, the second stage adjusts the power flexibility injection of a utility-scale battery energy storage system (ESS) to mitigate the imbalance at the PCC inherent in the above-mentioned uncertainties. The performance of the proposed method is tested in the case of a real ADN located in the city of Aigle in southwest of Switzerland.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available