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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The impacts of the fast growth of renewable energy sources (RESs) and distribution static synchronous compensators (D-STATCOMs) on unbalanced radial distribution networks (URDNs) are analyzed with three-phase power flow algorithms (PFAs). As the URDNs are unbalanced, they can experience voltage unbalance (VU). This paper proposes a novel three-phase PFA for URDNs with multiple RES and D-STATCOM device integrations. The bus number matrix (BNM) and branch number matrix (BRNM) developed in this paper make the implementation of the proposed PFA simple. These matrices are developed to store the bus numbers and branch numbers of newly created sections of the URDN. Both PQ and PV modeling of RES and PV modeling of D-STATCOM devices are effectively integrated into the proposed three-phase PFA. The accuracy of the proposed PFA has been tested on the IEEE-13 bus URDN and the results are found to be accurate with the IEEE results. Several study examples have been conducted on the IEEE-13 bus and the IEEE-34 bus URDNs with multiple integrations of three-phase RESs and three-phase D-STATCOMs. Test results indicate that these integrations improve the voltage profile, reduce the power loss and reduce the severity of the VU.

energies

A Novel Three-Phase Power Flow Algorithm for the Evaluation of the Impact of Renewable Energy Sources and D-STATCOM Devices on Unbalanced Radial Distribution Networks