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

N. P. G. Bhavania Saveetha School of Engineering, SIMATS, Chennai, IndiaKailash Harneb Netaji Subhas University of Technology, New Delhi, Delhi, IndiaSatendar Singhc Sharda University, Greater Noida, Uttar Pradesh, IndiaOstonokulov Azamat Abdukarimovichd Tashkent Institute of Finance, Tashkent, UzbekistanV. Balajie Vardhaman College of Engineering, Hyderabad, IndiaBharat Singhf GLA University, Mathura, UP, IndiaK. Vengatesang Sanjivani College of Engineering, Kopargaon, IndiaSachi Nandan Mohantyh Singidunum University, Belgrade, Serbia
Water Reusejournal2023en
ABI

Аннотация

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.

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