Computing the feasible operating region of active distribution networks: Comparison and validation of random sampling and optimal power flow based methods

Abstract The feasible operating region (FOR) indicates the operation points that an active distribution network can achieve at the interconnection point with the transmission grid when operating flexible assets within it; without disturbing the stability of the grid itself. Even though the concept i...

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Bibliographic Details
Main Authors: Daniel A. Contreras, Krzysztof Rudion
Format: Article
Language:English
Published: Wiley 2021-05-01
Series:IET Generation, Transmission & Distribution
Subjects:
Online Access:https://doi.org/10.1049/gtd2.12120
Description
Summary:Abstract The feasible operating region (FOR) indicates the operation points that an active distribution network can achieve at the interconnection point with the transmission grid when operating flexible assets within it; without disturbing the stability of the grid itself. Even though the concept is not new, many novel methods to compute the FOR efficiently have been proposed in recent years, resulting in two main schools of thought: random sampling (RS) and optimal power flow (OPF) methods. Both approaches have their merits, yet no wide‐ranging analysis regarding scenarios in which each method could be best applied has been done so far. This paper focuses on performing such a comparison; however, capability charts of flexibility providing units and grids are usually modelled as irregular convex polygons, requiring some adaptation of the RS‐methods to allow for a proper comparison of the resulting feasible operating region. Correspondingly, new methods to adapt the extraction of random samples from generic capability charts are proposed in the paper. Using models of two radial distribution grids, both OPF‐ and RS‐based methods are compared and validated. Results show that RS methods are adequate for assessing small grids, especially with the proposed improvements, while OPF‐based methods excel in larger grids.
ISSN:1751-8687
1751-8695