热电厂运行和用水报告方法对热电厂用水的影响

IF 11.3 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Eric Sjöstedt, Richard Rushforth, Vincent Tidwell, Melissa Harris, Ryan McManamay and Landon Marston*, 
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引用次数: 0

摘要

热电发电占美国淡水总取水量的41%以上,因此了解发电厂取水量(WW)和用水量(WC)的决定因素对于减少该行业对日益稀缺的水资源的依赖至关重要。然而,报告的数据不一致和对热电用水的潜在决定因素的不完整分析阻碍了这种理解。我们通过引入一种新的数据过滤方法和更完整的水使用决定因素评估来解决这些挑战。首先,我们采用功率冷却比作为基于操作的数据过滤器,在保留更多原始数据的同时删除了操作上不可信的记录,优于以前的统计过滤方法。其次,我们发现不同的用水报告方法(wurm)提供的WW和WC值具有统计学上的显著差异,揭示了这一以前未被认识到的特征在报告用水记录中的重要性。第三,我们的数据驱动方法表明,传统上强调的特征(如冷却技术和总发电量)是最重要的,但在单独为WW或WC建模时,其他经常被忽视的特征可能会超过这些特征。工厂配置、冷却技术和总发电量是WW最重要的特征,而WURM、冷却技术和报告月份是WW最重要的特征。这些发现可以改善热电厂的管理、用水报告的准确性和用水建模。本研究展示了电厂运行和用水报告方法对热电厂管理的重要性,介绍了一种基于运行的数据过滤方法,并调查了预测报告取水量和用水量的特征的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of Thermoelectric Power Plant Operations and Water Use Reporting Methods on Thermoelectric Power Plant Water Use

Thermoelectric power generation accounts for over 41% of total U.S. freshwater withdrawals, making understanding the determinants of power plants’ water withdrawals (WW) and consumption (WC) critical for reducing the sector’s reliance on increasingly scarce water resources. However, reported data inconsistencies and incomplete analysis of potential determinants of thermoelectric water use hinder such understanding. We address these challenges by introducing a novel data filtering method and a more complete assessment of water use determinants. First, we applied a power-cooling ratio as an operations-based data filter that removed operationally implausible records while retaining more original data, outperforming previous statistical filtering methods. Second, we found that different water use reporting methods (WURMs) provided statistically significantly different WW and WC values, revealing the importance of this previously unrecognized feature in reported water use records. Third, our data-driven approach showed that traditionally emphasized features─such as cooling technology and gross generation─are of primary importance but can be surpassed by other, often overlooked, features when modeling WW or WC individually. The plant configuration, cooling technology, and gross generation were the most important features of WW, whereas WURM, cooling technology, and reporting month were the most important for WC. These findings can improve thermoelectric power plant management, water use reporting accuracy, and water use modeling.

This study shows the importance of power plant operations and the water use reporting methods for thermoelectric power plant management, introducing an operations-based data filtration method and investigating the importance of features for predicting reported water withdrawal and consumption.

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来源期刊
环境科学与技术
环境科学与技术 环境科学-工程:环境
CiteScore
17.50
自引率
9.60%
发文量
12359
审稿时长
2.8 months
期刊介绍: Environmental Science & Technology (ES&T) is a co-sponsored academic and technical magazine by the Hubei Provincial Environmental Protection Bureau and the Hubei Provincial Academy of Environmental Sciences. Environmental Science & Technology (ES&T) holds the status of Chinese core journals, scientific papers source journals of China, Chinese Science Citation Database source journals, and Chinese Academic Journal Comprehensive Evaluation Database source journals. This publication focuses on the academic field of environmental protection, featuring articles related to environmental protection and technical advancements.
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