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

Southwest China possesses substantial hydropower potential and abundant solar resources. To harness these renewable resources effectively, extensive photovoltaic (PV) facilities and cascaded hydropower stations have been strategically constructed in mountainous regions, culminating in the development of hybrid energy systems (HES) that combine hydro, PV, and pumped-storage. Nevertheless, the current research on HES scheduling often neglects the transmission congestion in the local grid to which HES is connected. This oversight results in avoidable curtailment of solar power, load shedding, and water spillage. Hence, this paper introduces a robust optimization model for HES scheduling. The primary objectives are to enhance the integration of renewable energy sources, mitigate water spillage, minimize peak-valley differences in multiple external grids, and alleviate transmission congestion within the HES-connected grid. To validate the effectiveness of this approach, both a modified IEEE 6-bus system and a real-world case study from the Yalong River region in Southwest China are employed. Numerical results illustrate that by involving the HES in local grid congestion management, a substantial reduction in PV generation curtailment and water wastage is achievable, with minimal impact on peak load management in multiple external grids.

Robust Scheduling of a Hybrid Hydro/ photovoltaic/Pumped-Storage System for Multiple Grids Peak-Shaving and Congestion Management