关键词: 水碳调度, 蓄水调度, 碳排放, 非支配排序遗传算法, 梯级水库

Abstract:

[Objectives] This study aims to optimize water-carbon coordinated scheduling during reservoir impoundment to improve power generation and storage rate, and to reduce greenhouse gas emissions in reservoir operation. [Methods] Given that current studies on cascade reservoir impoundment scheduling have not yet incorporated carbon reduction objectives, this study proposed a multi-objective water-carbon scheduling model for cascade reservoirs during impoundment period based on the carbon emission factor method.An early storage strategy for cascade reservoirs was developed,and three objectives—minimizing flood control risk,maximizing power generation,and minimizing greenhouse gas emissions—were established.The Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) was employed to derive optimal scheduling schemes for the impoundment period.[Results] A case study was conducted on a cascade system comprising six reservoirs in the middle and lower reaches of the Jinsha River and the Three Gorges Reservoir.The results showed that the three scheduling objectives on the Pareto frontier formed a spatial surface distribution,reflecting nonlinear competitive relationships among the objectives.Compared to the current scheduling scheme,the optimal scheduling scheme—while occupying 0-4.92% of the flood control storage capacity—achieved a 0.65%-3.60% increase in multi-year average power generation (by 0.723-4.026 billion kW·h/a), a 6.45%-22.43% reduction in multi-year average spilled water volume (by 1.582-5.503 billion m³/a), an 8.33%-9.85% decrease in multi-year average greenhouse gas emissions (by 38.55-45.63 Gg CO₂ e/a), and a 9.49%-11.44% reduction in carbon emission intensity (by 0.39-0.47 kg CO₂ e/MW·h). Typical year scheduling analyses were conducted for a wet year (2020) and a dry year (2022). In the wet year, the selected scheme with the minimum flood risk increased power generation by 3.341 billion kW·h/a and reduced direct GHG emissions by 39.53 Gg CO₂ e/a without increasing flood risk compared to the current scheme. In the dry year, the scheme with the maximum power generation raised the final storage level of the Three Gorges Reservoir by nearly 2 meters, increased available water by 1.794 billion m³, and reduced direct greenhouse gas emissions by 15.32 Gg CO₂ e/a, while meeting the minimum ecological flow constraints during the impoundment period. [Conclusions] This study develops a multi-objective scheduling model for cascade reservoirs during the impoundment period and analyzes the nonlinear synergy and competitive relationships between carbon emissions and traditional water resource utilization benefits. The NSGA-Ⅱ optimization solutions significantly improv the long-term average power generation and storage rate while reducing greenhouse gas emissions without compromising flood control standards. Scheduling analyses for both wet (2020) and dry (2022) years demonstrate that the proposed model is well-suited to different hydrological scenarios, achieving a balance between carbon reduction goals and traditional reservoir functions such as flood control, storage, power generation, and drought resistance. This research provides technical support for implementing coordinated water-carbon scheduling of cascade reservoirs during the impoundment period.

Key words: water-carbon scheduling, impoundment scheduling, carbon emissions, non-dominated sorting genetic algorithm, cascade reservoirs