Liu et al. (2026) Scenario-adaptive scheduling of cascade hydro-wind-solar-pumped storage systems driven by hydrological variability

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-10-11
• Authors: Lu Liu, Chao Ma, Muhan Li, Zexing Deng
• DOI: 10.1016/j.jhydrol.2026.136585

Research Groups

• State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, China
• School of Civil Engineering, Tianjin University, China

Short Summary

This study develops a scenario-adaptive scheduling framework for cascade hydro-wind-solar-pumped storage systems to improve bundled power delivery reliability under hydrological variability. It demonstrates that optimal scheduling windows vary significantly with runoff scenarios and that pumped storage capacity is crucial for system reliability.

Objective

• To develop a scenario-adaptive scheduling framework for cascade hydro-wind-solar-pumped storage complementary systems (CHWSPCS) to determine optimal scheduling window selection under varying hydrological conditions and uniform bundled power delivery.

Study Configuration

• Spatial Scale: Middle reaches of the Yalong River, China (case study for verification).
• Temporal Scale: Monthly cumulative-runoff quantiles for scenario distinction; multi-day scheduling windows (e.g., 3-15 days); daily delivery profile.

Methodology and Data

• Models used: A coordinated operation model for CHWSPCS, incorporating long-term reservoir boundaries, shared-reservoir pumped storage, transmission limits, and a daily delivery profile. Optimization results are analyzed using a tolerance-based hierarchical rule (prioritizing delivered energy, then Loss of Load Probability (LOLP), then curtailment rate (CR)).
• Data sources: Monthly cumulative-runoff quantiles (used to distinguish high, normal, and low-runoff scenarios), concurrent wind and photovoltaic inputs.

Main Results

• The proposed strategy effectively coordinates hydropower, wind, photovoltaic, and pumped storage units, significantly improving the reliability of bundled power delivery across diverse hydrological scenarios.
• Abundant inflow can increase hydropower curtailment and planned-delivery shortfalls under constrained release and transmission, despite supporting greater delivery. Limited inflow emphasizes inter-day water allocation and coordination with variable renewable generation.
• With a 1.0% delivered-energy tolerance, optimal scheduling windows for alpha (high-runoff flood-season) scenarios are 3–5 days, while for beta (low-runoff non-flood) scenarios, they range from 3 to 15 days across months.
• Reducing pumped-storage capacity from 1200 MW to 600 MW for a repeated 7-day delivery increases the median Loss of Load Probability (LOLP) by 1.323–2.053 percentage points.

Contributions

• Development of a novel scenario-adaptive scheduling framework that explicitly links scheduling-window selection to hydrological conditions and reservoir flexibility for cascade hydro-wind-solar-pumped storage systems.
• Quantification of the impact of hydrological variability (runoff scenarios) on optimal scheduling window lengths for bundled power delivery.
• Demonstration of the critical role of pumped storage capacity in enhancing the reliability of bundled power delivery in such complementary systems.

Funding

• Not specified in the provided text.

Citation

@article{Liu2026Scenarioadaptive,
  author = {Liu, Lu and Ma, Chao and Li, Muhan and Deng, Zexing},
  title = {Scenario-adaptive scheduling of cascade hydro-wind-solar-pumped storage systems driven by hydrological variability},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136585},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136585}
}