Gao et al. (2026) A Modified linearized orthogonal progressive optimization algorithm coordinates hydropower generation and ecological flow requirements in cascade reservoirs

Identification

• Journal: Scientific Reports
• Year: 2026
• Date: 2026-09-16
• Authors: Yuan Gao, Hui Qin, Yuhua Qu, Yang Xu, Songlin Wu, 李高歌, Zhiqiang Jiang
• DOI: 10.1038/s41598-026-69268-x

Research Groups

• Department of Hydraulic Engineering, Nanjing University of Science and Technology
• State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
• Yangtze River Basin Water Resources Committee

Short Summary

This study proposes a multi-objective optimal scheduling model for cascade reservoirs that simultaneously maximizes hydropower generation and minimizes ecological water deficits. The model integrates an improved intra-annual distribution flow method (IDFM) to estimate ecological baseflow requirements and a modified linearized orthogonal progressive optimization algorithm (MLOPOA) based on mixed-integer linear programming (MILP) to optimize the operation of cascade reservoir systems.

Objective

• Develop a multi-objective optimal scheduling model for cascade reservoirs that balances hydropower generation and ecological water deficits.
• Improve the precision of ecological baseflow estimation using an improved intra-annual distribution flow method (IDFM).
• Enhance the optimization efficiency and solution quality of the modified linearized orthogonal progressive optimization algorithm (MLOPOA) based on mixed-integer linear programming (MILP).

Study Configuration

• Spatial Scale: Cascade reservoir system from the Lower Jinsha River to the Three Gorges in China.
• Temporal Scale: Representative wet, normal, and dry years.

Methodology and Data

• Models used:
  • Improved Intra-annual Distribution Flow Method (IDFM)
  • Modified Linearized Orthogonal Progressive Optimization Algorithm (MLOPOA) based on Mixed-Integer Linear Programming (MILP)
• Data sources: Long-term records of natural inflow data, hydrological and hydraulic methods for estimating ecological baseflow.

Main Results

• The proposed model effectively balances hydropower generation and ecological water deficits in cascade reservoir systems.
• The IDFM improves the precision of ecological baseflow estimation by capturing intra-annual dynamic variability.
• The MLOPOA based on MILP enhances optimization efficiency and solution quality, reducing computational complexity.

Contributions

• This study provides a robust technical support for the sustainable operation of large-scale cascade reservoir systems.
• The proposed model addresses the conflict between energy production and ecological protection in cascade reservoirs.
• The IDFM and MLOPOA provide a framework for improving ecological flow estimation and optimization algorithms.

Funding

• National Natural Science Foundation of China (Grant No. 51979010)
• Yangtze River Basin Water Resources Committee (Grant No. YRBYWRC2020001)

Citation

@article{Gao2026Modified,
  author = {Gao, Yuan and Qin, Hui and Qu, Yuhua and Xu, Yang and Wu, Songlin and 李高歌 and Jiang, Zhiqiang},
  title = {A Modified linearized orthogonal progressive optimization algorithm coordinates hydropower generation and ecological flow requirements in cascade reservoirs},
  journal = {Scientific Reports},
  year = {2026},
  doi = {10.1038/s41598-026-69268-x},
  url = {https://doi.org/10.1038/s41598-026-69268-x}
}