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

Increasing penetration of distributed generation (DG) has brought more uncertainty to the operation of active distribution networks (ADNs). With the reformation of the power system, increasingly more flexible loads access to distribution network through load aggregators (LAs), which becomes an effective way to solve these issues. Since LAs and ADNs are separate entities with different interests, the traditional centralized and deterministic optimization methods fail to meet the actual operational requirements of ADNs. Based on the linear power flow model, a robust optimal dispatching model of ADNs considering the influence of renewable DG’s uncertain output on voltage security constraints is established. Then, an independent optimal scheduling model for LAs is modeled based on the analysis of the composition and characteristics of flexible load in LAs. LAs and ADNs, as two different stakeholders, use a distributed modeling method to establish different economic optimization goals. The optimization problem is solved by decoupling the coupling exchanging power between LAs and ADNs into virtual controllable loads and virtual DGs. Finally, with the case study of a modified IEEE 33-bus system, the correctness and effectiveness of the proposed method are verified. The effects of the robust level and demand response incentive on the results are also analyzed.

A Distributed and Robust Optimal Scheduling Model for an Active Distribution Network With Load Aggregators