Using stochastic dual dynamic programming to design long-term operation policy of hydro-wind-solar energy systems considering multiple coupled uncertainties and end-of-year carryover storage

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS
Xiaoyu Jin , Chuntian Cheng , Shubing Cai , Lingzhi Yan , Zhipeng Zhao
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引用次数: 0

Abstract

Hydropower with reservoirs is increasingly important for balancing seasonal variability of growing variable renewable energy (VRE) through its reservoir regulation capability. However, the coupling of the seasonal variability and randomness of VRE with the stochastic nature of inflows makes it extremely challenging to manage long-term hydropower operations related to generation decisions within the current scheduling periods and future end-of-year carryover storage control. To address these challenges, we propose a stochastic dual dynamic programming-based framework for designing long-term hydro-wind-solar complementary operation policies. Inflow and VRE output uncertainties are captured by two different approaches: Markov chain and AutoRegressive Moving Average. These approaches enable the integration of stage-wise dependent randomness into the stochastic decision-making process. Model reconstruction techniques based on Disjunctive Programming are proposed to transform stage-wise nonlinear models into linear ones. Subsequently, Benders cuts families are constructed to constrain the feasible decision space related to hydropower operation and stochastic parameters, while managing the end-of-year carryover storage requirement. Case studies of a large-scale hydro-wind-solar energy system in China indicate that the proposed framework can derive effective complementary operation policies considering future reservoir storage management requirements under multiple coupled uncertainties. Real simulation results indicate that the framework can effectively enhance channel utilization by leveraging hydropower flexibility to support VRE integration, with the monthly average channel utilization rate exceeding 80 %. Besides, hydro-wind-solar complementary operation policies with varying end-of-year carryover storage requirements can be designed, with lower storage requirements trending to enhance hydropower output in a hydro-wind-solar complementary mode.
采用随机双动态规划方法设计考虑多耦合不确定性和年末结转蓄能的水能-风能-太阳能系统长期运行策略
有水库的水电通过其水库调节能力来平衡日益增长的可变可再生能源(VRE)的季节性变化,其重要性日益凸显。然而,VRE的季节性变异性和随机性与流入的随机性相结合,使得在当前调度期内管理与发电决策相关的长期水电运行以及未来年底的结转存储控制极具挑战性。为了解决这些挑战,我们提出了一个基于随机双动态规划的框架,用于设计长期的水电-风能-太阳能互补运行政策。流入和VRE输出的不确定性由两种不同的方法捕获:马尔可夫链和自回归移动平均。这些方法能够将阶段依赖的随机性整合到随机决策过程中。提出了基于析取规划的模型重构技术,将分阶段非线性模型转化为线性模型。随后,构造Benders cut族,约束水电运行和随机参数相关的可行决策空间,同时管理年终结转库存量需求。中国大型水能-风能-太阳能系统的实例研究表明,该框架可以在多个耦合不确定性条件下推导出考虑未来水库存储管理需求的有效互补运行策略。实际仿真结果表明,该框架可有效提高通道利用率,利用水电灵活性支持VRE集成,月平均通道利用率超过80% %。此外,可以设计不同年末结转蓄能要求的水能-风能-太阳能互补运行政策,在水能-风能-太阳能互补模式下,较低的蓄能要求有提高水力发电量的趋势。
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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