LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Region of Attraction Estimation for DC Microgrids With Constant Power Loads Using Potential Theory

Photo from wikipedia

The stability issues of DC power grids are attracting researchers’ attention, especially with the increasing adoption of power electronic devices and nonlinear loads. Large-signal stability analysis is required to detect… Click to show full abstract

The stability issues of DC power grids are attracting researchers’ attention, especially with the increasing adoption of power electronic devices and nonlinear loads. Large-signal stability analysis is required to detect and avoid large disturbance and destabilization, which can cause detrimental effects on DC power grids. However, the issue is still unsolved due to the complicated dynamics of large-scale power grids. This paper develops a novel method for estimation of the region of attraction (ROA) with less conservativeness using the Brayton-Moser mixed potential theory. This reliable and robust ROA estimation method provides useful insights into the stable operation of DC power grids. Moreover, this paper reveals the weak correlation between the state variables1 of branch currents and system stability. It makes it possible to reduce computational cost and lessen the curse of dimensionality by separating these state variables. The case study shows that the proposed approach can obtain a much less conservative ROA compared to traditional methods such as Lyapunov’s method.

Keywords: potential theory; power; power grids; region attraction; estimation

Journal Title: IEEE Transactions on Smart Grid
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.