Identification of Most Significant Parameter of Impact of Climate Change and Urbanization on Operational Efficiency of Hydropower Plant

IF 0.7 Q4 ENERGY & FUELS
Priyanka Majumder, A. K. Saha
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引用次数: 2

Abstract

The operational performance of hydropower plants (HPPs) is largely affected as the output from the plant entirely depends on the rainfall and demand from consumers both of which are compromised due to the vulnerability in climatic patterns and rapid change in urbanization rate. Although, not all the parameters are equally affected and the present study aims to find the degree of impact on the various correlated parameters on which production efficiency of HPPs varies. In this aspect, a neural network concept was used as decision making tool to identify the most significant parameters with respect to change in climate, urbanization along with machine failure because as a combined effect of the first two parameters, the probability of machine failure will also increase. The result from the study provides an opportunity to mitigate the impact that can be caused as a result of climate change impact and change in rate of urbanization. According to the result it was found that Efficiency of Generators is the most significant parameter of impact of climate change and urbanization on operational efficiency of hydropower plant. The result from the scenario analysis suggested that if the A2 scenario becomes true in 2061-70 there will be a maximum decrease in the OE and if land use scenario: PR story line is found to be adopted in the future world of 2020-30 the change in OE will be the greatest (an increase of 6.056%) compared to any other scenario developed for the impact of urbanization followed by land use change scenario of the 2031-40 decade, which will be equal to an increase of 5.247% compared to the baseline.
气候变化和城市化对水电厂运行效率影响的最显著参数辨识
水电站的运行性能在很大程度上受到影响,因为电厂的产出完全取决于降雨量和消费者的需求,这两者都受到气候模式脆弱性和城市化率快速变化的影响。然而,并非所有的参数都受到相同的影响,本研究的目的是找出对HPPs生产效率变化的各种相关参数的影响程度。在这方面,神经网络概念被用作决策工具,以识别有关气候变化、城市化和机器故障的最重要参数,因为作为前两个参数的综合影响,机器故障的概率也会增加。这项研究的结果为减轻气候变化影响和城市化率变化可能造成的影响提供了一个机会。结果表明,气候变化和城市化对水电厂运行效率影响最显著的参数是发电机效率。场景分析的结果表明,如果A2场景成为真正的2061 - 70年将会有一个最大减少OE如果土地使用场景:公关故事线中发现采用2020 - 30的未来世界OE的变化将是最大的(增长了6.056%),而其他场景为城市化的影响,其次是开发的土地利用变化情况的2031 - 40的十年中,这就等于一个基线相比增长了5.247%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
22.20%
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11
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