Balancing water, power, and carbon: A synergistic optimization framework for mega cascade reservoir operations

IF 9.1 1区 工程技术 Q1 ENERGY & FUELS Renewable Energy Pub Date : 2025-04-15 Epub Date: 2025-02-06 DOI:10.1016/j.renene.2025.122567
Zhihao Ning , Yanlai Zhou , Juntao He , Chun Tang , Chong-Yu Xu , Fi-John Chang
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Abstract

This study addresses the critical intersection of renewable energy production and carbon emission reduction in the context of intensified human activities and global climate change by proposing an innovative optimization framework for mega cascade reservoirs. Unlike traditional approaches that often prioritize hydropower output or carbon emissions, our framework uniquely integrates a multi-objective optimization model that simultaneously minimizes carbon emissions, mitigates flood risk, and maximizes hydropower output within the physical constraints of cascade reservoir operations. To assess the performance of various impoundment schemes, we apply the Technique for Order Preference by Similarity to Ideal Solution, demonstrating the model's versatility across different inflow scenarios using seven cascade reservoirs in the Yangtze River as case studies. Our findings reveal that, compared to practical operation scheme, the optimal scheme enhances hydropower output by 5.82 billion kW·h/a (5.32 %), increases water supply by 2.68 billion m³ (8.00 %), reduces carbon emissions by 17.31 GgC/a (14.66 %), and lowers carbon intensity by 0.63 kgCO2e/MW·h (15.22 %). This research advances theoretical frameworks for reservoir operations and offers practical implications for policymakers, enabling more informed decision-making to achieve sustainable development goals. The novel integration of water-carbon synergies within reservoir management contributes significantly to the discourse on sustainable energy systems and climate resilience.
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平衡水、电和碳:巨型级联水库作业的协同优化框架
本研究通过提出一个创新的巨型梯级水库优化框架,解决了人类活动加剧和全球气候变化背景下可再生能源生产和碳减排的关键交叉点。与通常优先考虑水电产量或碳排放的传统方法不同,我们的框架独特地集成了一个多目标优化模型,同时最大限度地减少碳排放,减轻洪水风险,并在梯级水库运行的物理约束下最大限度地提高水电产量。为了评估各种蓄水方案的性能,我们应用了理想解决方案相似性排序偏好技术,并以长江7个梯级水库为例研究了该模型在不同入流情景下的通用性。研究结果表明,与实际运行方案相比,优化后的方案可增加水力发电量58.2亿kW·h/a(5.32%),增加供水量26.8亿m³(8.00%),减少碳排放17.31 GgC/a(14.66%),降低碳强度0.63 kgCO2e/MW·h(15.22%)。该研究推进了油藏作业的理论框架,并为决策者提供了实际意义,使更明智的决策能够实现可持续发展目标。水库管理中水-碳协同效应的新整合对可持续能源系统和气候适应能力的论述做出了重大贡献。
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来源期刊
Renewable Energy
Renewable Energy 工程技术-能源与燃料
CiteScore
18.40
自引率
9.20%
发文量
1955
审稿时长
6.6 months
期刊介绍: Renewable Energy journal is dedicated to advancing knowledge and disseminating insights on various topics and technologies within renewable energy systems and components. Our mission is to support researchers, engineers, economists, manufacturers, NGOs, associations, and societies in staying updated on new developments in their respective fields and applying alternative energy solutions to current practices. As an international, multidisciplinary journal in renewable energy engineering and research, we strive to be a premier peer-reviewed platform and a trusted source of original research and reviews in the field of renewable energy. Join us in our endeavor to drive innovation and progress in sustainable energy solutions.
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