Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction

[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...

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Main Author: ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao
Format: Article
Language:zho
Published: Editorial Office of Journal of Changjiang River Scientific Research Institute 2025-06-01
Series:长江科学院院报
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Online Access:http://ckyyb.crsri.cn/fileup/1001-5485/PDF/1735794845527-1415431167.pdf
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author ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao
author_facet ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao
author_sort ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao
collection DOAJ
description [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.
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spelling doaj-art-9fb8ece4400a4e9788f7b4e3abe238fc2025-08-20T03:31:21ZzhoEditorial Office of Journal of Changjiang River Scientific Research Institute长江科学院院报1001-54852025-06-0142619420210.11988/ckyyb.20240596Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission ReductionZHOU Yan-lai, NING Zhi-hao, HE Jun-tao0State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China[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.http://ckyyb.crsri.cn/fileup/1001-5485/PDF/1735794845527-1415431167.pdfwater-carbon scheduling|impoundment scheduling|carbon emissions|non-dominated sorting genetic algorithm|cascade reservoirs
spellingShingle ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao
Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
长江科学院院报
water-carbon scheduling|impoundment scheduling|carbon emissions|non-dominated sorting genetic algorithm|cascade reservoirs
title Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
title_full Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
title_fullStr Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
title_full_unstemmed Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
title_short Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction
title_sort multi objective optimal scheduling of water carbon in cascade reservoirs during impoundment for carbon emission reduction
topic water-carbon scheduling|impoundment scheduling|carbon emissions|non-dominated sorting genetic algorithm|cascade reservoirs
url http://ckyyb.crsri.cn/fileup/1001-5485/PDF/1735794845527-1415431167.pdf
work_keys_str_mv AT zhouyanlainingzhihaohejuntao multiobjectiveoptimalschedulingofwatercarbonincascadereservoirsduringimpoundmentforcarbonemissionreduction