Techno-economic optimization of a new waste-to-energy plant for electricity, cooling, and desalinated water using various biomass for emission reduction

Hai T 1 , Ma X 2 , Singh Chauhan B 3 , Mahmoud S 4 , Al-Kouz W 4 , Tong J 5 Show all authors , Salah B 6

Affiliations 

  • 1 School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, Guizhou, 558000, China; School of Information and Artificial Intelligence, Nanchang Institute of Science and Technology, Nanchang, China; Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia. Electronic address: haitao@sgmtu.edu.cn
  • 2 Department of Logistics Management and Engineering, Nanning Normal University, Nanning, 530023, China. Electronic address: drxyma@nnnu.edu.cn
  • 3 Department of Mechanical Engineering, GLA University, Mathura, (UP), India. Electronic address: bhupendradce@gmail.com
  • 4 College of Engineering and Technology, American University of the Middle East, Kuwait
  • 5 Department of Logistics Management and Engineering, Nanning Normal University, Nanning, 530023, China. Electronic address: 977344011@qq.com
  • 6 Department of Industrial Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh, 11421, Saudi Arabia. Electronic address: bsalah@ksu.edu.sa
Chemosphere, 2023 Oct;338:139398.
PMID: 37406939 DOI: 10.1016/j.chemosphere.2023.139398

Abstract

A newly developed waste-to-energy system using a biomass combined energy system designed and taken into account for electricity generation, cooling, and freshwater production has been investigated and modeled in this project. The investigated system incorporates several different cycles, such as a biomass waste integrated gasifier-gas turbine cycle, a high-temperature fuel cell, a Rankine cycle, an absorption refrigeration system, and a flash distillation system for seawater desalination. The EES software is employed to perform a basic analysis of the system. They are then transferred to MATLAB software to optimize and evaluate the impact of operational factors. Artificial intelligence is employed to evaluate and model the EES software's analysis output for this purpose. By enhancing the flow rate of fuel from 4 to 6.5 kg/s, the cost rate and energy efficiency are reduced by 51% and increased by 6.5%, respectively. Furthermore, the maximum increment in exergetic efficiency takes place whenever the inlet temperature of the gas turbine rises. According to an analysis of three types of biomasses, Solid Waste possesses the maximum efficiency rate, work output, and expense. Rice Husk, in contrast, has the minimum efficiency, work output, and expense. Additionally, with the change in fuel discharge and gas turbine inlet temperature, the system behavior for all three types of biomasses will be nearly identical. The Pareto front optimization findings demonstrate that the best mode for system performance is an output power of 53,512 kW, a cost of 0.643 dollars per second, and a first law efficiency of 42%. This optimal value occurs for fuel discharge of 5.125 and the maximum inlet temperature for a gas turbine. The rates of water desalination and cooling in this condition are 18.818 kg/s and 2356 kW, respectively.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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