2024 : 12 : 4
Shoaib Khanmohammadi

Shoaib Khanmohammadi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Engineering
Address: Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran
Phone: 0833-8305001

Research

Title
Thermodynamic and economic analyses and multi-objective optimization of harvesting waste heat from a biomass gasifier integrated system by thermoelectric generator
Type
JournalPaper
Keywords
Thermoelectric Waste heat recovery system Biomass Organic Rankine cycle Dimensionless parameters
Year
2019
Journal ENERGY CONVERSION AND MANAGEMENT
DOI
Researchers Shoaib Khanmohammadi ، Morteza Saadat ، Abdullah Al-Rashed ، Masoud Afrand

Abstract

Thermoelectric waste heat recovery systems (WHRSs) can be used appropriately to recover wasted heat from various industrial processes. In the current work, new thermodynamic modeling was developed to harvesting waste heat from an integrated system includes an externally fired gas turbine and a biomass gasifier by three thermoelectric WHRSs. The biomass system consisted a gas turbine cycle, an organic Rankine cycle (ORC) and a domestic water heater were first thermodynamically modeled, and then effects of adding thermoelectric WHRSs to different locations of the system were investigated. It is observed that first law efficiency of the system (η1) will become 17.11% (an increase of 0.35%) if the total output heat from the stack enters WHRSs. The efficiencies of the system can be increased from 16.76% to 17.93% by placing a WHRS on the condenser of ORC. Moreover, the operating parameters have a significant effect on the integrated system efficiency; the influence of increasing αGE on the efficiencies is in contrast to the effect of enhancing αcond. In addition, an economic assessment of integrating WHRSs with the biomass gasifier integrated system is conducted and the conditions are indicated under which the proposed system is profitable. Furthermore, the results of genetic algorithm based multi-objective optimization shows that with the use of γDU =2 and γL,ORC = 30 defined thermal efficiencies are at their optimum state.