English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper proposes a novel purely measurement-based method for estimatingdynamic load parameters in near real-time when stochastic load fluctuations arepresent. By leveraging on the regression theorem for the Ornstein-Uhlenbeckprocess, the proposed method can provide highly accurate estimation withoutrequiring any information about the power system model. Furthermore, byexploiting recursion, an online algorithm is developed to estimate the dynamicload parameters in near real-time. Simulation studies on the IEEE 39-Bus systemdemonstrate the accuracy of the model-free method, its robustness againstmeasurement noise, as well as its satisfactory performance in trackingreal-time changes of the load parameters.

Online PMU-Based Method for Estimating Dynamic Load Parameters in Ambient Conditions