利用优化研究气候危机背景下水库的适应性运行

Nguyen Thi Thuy Hang, Hidetaka Chikamori, Cong-Thanh Tran, Tri Nguyen-Quang
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引用次数: 0

摘要

本研究调查了从 12 月到次年 6 月整个泄洪期间气候变化对越南塔莫水库性能的影响。分析了 2029-2064 年和 2064-2099 年两个时期的适应性优化运行规则。采用全球气候模型(GCM)气象研究所地球系统模型 2.0 版(MRI-ESM2-0)得出的耦合模型相互比较项目第 6 阶段(CMIP6)的三种共享社会经济路径(SSP)情景(SSP1-P2.6、SSP2-4.5 和 SSP5-8.5)的降水和温度进行流入量预测。由于流入量减少,现行运行规则几乎会导致 SSP1-P2.6、SSP2-4.5 和 SSP5-8.5 情景下两个时期的水力发电量分别减少-3.9%、0.7%、-7.6%、-6.7%、-6.3%和 7.0%,缺水量增加,缺水量与基期(1987-2022 年)相比分别增加 20.4%、6.8%、33.2%、31.3%、30.2%和 28.3%。在不同时期和情景下,通过应用非支配排序遗传算法 II(NSGA-II)优化技术,可提高发电量 7.1、7.1、7.3、6.2、6.9 和 6.8%,减少缺水量 -40.2、-42.7、-37.2、-43.4、-40.8 和 -39.0%。这种方法有可能减轻气候变化对未来水库运行的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using Optimization to Investigate the Adaptive Operation of Reservoirs under the Context of Climate Crisis

Using Optimization to Investigate the Adaptive Operation of Reservoirs under the Context of Climate Crisis
This study investigates the climate change impacts on the performance of the Thac Mo reservoir in Vietnam throughout the release duration from December to June of the following year. The adaptative optimization operating rules during two periods, 2029–2064 and 2064–2099, were analyzed. Precipitation and temperature of three shared socioeconomic pathway (SSP) scenarios (SSP1–P2.6, SSP2–4.5, and SSP5–8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) derived from the global climate model (GCM) Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2–0) were used for inflow prediction. Due to the decreased inflow, the current operating rule would almost lead to a decrease in hydropower production of two periods of SSP1–P2.6, SSP2–4.5, and SSP5–8.5 scenarios of −3.9, 0.7, −7.6, −6.7, −6.3, and 7.0% and an increase in water scarcity, with the respective amount of water deficit by 20.4, 6.8, 33.2, 31.3, 30.2, and 28.3% compared to the base period (1987–2022). The improved power production of 7.1, 7.1, 7.3, 6.2, 6.9, and 6.8% and reduced water shortage of −40.2, −42.7, −37.2, −43.4, −40.8, and −39.0% can be achieved by applying the nondominated sorting genetic algorithm II (NSGA-II) optimization technique under different periods and scenarios. This approach has the potential to mitigate climate change effects on future reservoir operations.
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