Economic analysis based on saline water treatment using renewable energy system and microgrid architecture

IF 4.3 4区 环境科学与生态学 Q2 ENGINEERING, ENVIRONMENTAL
Water Reuse Pub Date : 2023-05-17 DOI:10.2166/wrd.2023.013
N. Bhavani, K.R. Harne, Satendar Singh, Ostonokulov Azamat Abdukarimovich, V. Balaji, Bharat Singh, K. Vengatesan, Sachi Nandan Mohanty
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引用次数: 0

Abstract

Reverse osmosis desalination facilities operating on microgrids (MGs) powered by renewable energy are becoming more significant. A leader-follower structured optimization method underlies the suggested algorithm. The desalination plant is divided into components, each of which can be operated separately as needed. MGs are becoming an important part of smart grids, which incorporate distributed renewable energy sources (RESs), energy storage devices, and load control strategies. This research proposes novel techniques in economic saline water treatment based on MG architecture integrated with a renewable energy systems. This study offers an optimization framework to simultaneously optimize saline as well as freshwater water sources, decentralized renewable and conventional energy sources to operate water-energy systems economically and efficiently. The radial Boltzmann basis machine is used to analyse the salinity of water. Data on water salinity were used to conduct the experimental analysis, which was evaluated for accuracy, precision, recall, and specificity as well as computational cost and kappa coefficient. The proposed method achieved 88% accuracy, 65% precision, 59% recall, 65% specificity, 59% computational cost, and 51% kappa coefficient.
基于可再生能源系统和微电网架构的咸水处理经济分析
利用可再生能源驱动的微电网运行的反渗透海水淡化设施正变得越来越重要。该算法的基础是一种主从结构优化方法。海水淡化厂分为几个部分,每个部分都可以根据需要单独运行。MGs正成为智能电网的重要组成部分,智能电网包含分布式可再生能源(RES)、储能设备和负载控制策略。本研究提出了基于MG架构和可再生能源系统相结合的经济盐水处理新技术。这项研究提供了一个优化框架,可以同时优化盐水和淡水水源、分散的可再生能源和传统能源,以经济高效地运行水能系统。径向玻尔兹曼基机用于分析水的盐度。使用盐度数据进行实验分析,评估准确性、精密度、召回率和特异性,以及计算成本和kappa系数。所提出的方法实现了88%的准确率、65%的精密度、59%的召回率、65%特异性、59%的计算成本和51%的kappa系数。
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来源期刊
Water Reuse
Water Reuse Multiple-
CiteScore
6.20
自引率
8.90%
发文量
0
审稿时长
7 weeks
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