May 24, 2024
Shoaib Khanmohammadi

Shoaib Khanmohammadi

Academic rank: Associate professor
Address: Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran
Education: Ph.D in Mechanical Engineering
Phone: 0833-8305001
Faculty: Faculty of Engineering

Research

Title
Proposed a new geothermal based poly-generation energy system including Kalina cycle, reverse osmosis desalination, elecrolyzer amplified with thermoelectric: 3E analysis and optimization
Type Article
Keywords
Poly-generation Geothermal source Optimization Thermoelectric generator
Researchers Farayi Musharavati، Shoaib Khanmohammadi، Amir Hossein Pakseresht

Abstract

One of the most appropriate approaches for enhancing the performance of the energy systems is integrating different subsystems for producing various beneficial products simultaneously. In the present study, a polygeneration system including a Kalina cycle, a reverse osmosis unit, a PEM electrolyzer, and a thermoelectric module that can generate power, fresh water, hot water, and hydrogen is examined. A thermodynamic simulation code in Engineering Equation Solver (EES) is prepared to predict the behavior of system. Using the exergy analysis different location of system with high irreversibility is determined. As the results show in the base case, the geothermal cycle condenser with 89.29 kW, reverse osmosis (RO) unit with 68.97 kW, heat exchanger 2 with 37.68 kW, and steam turbine with 22.52 kW have the highest exergy destruction rate respectively. The parametric analysis for identifying the influence of five decision variables namely steam turbine inlet pressure (P2), steam turbine back pressure (P4), vapor generator outlet pressure (P10), Kalina turbine backpressure (P13), and temperature difference of the heat exchanger (TD) is conducted. Additionally four major outputs consisting of exergy destruction rate (kW), exergy destruction cost rate ($/h), and electricity cost rate ($/h) are determined for implementing multi-criteria optimization. A tri-objective optimization to find the optimum states of the suggested system is conducted. With employing a selection method, the system arrangement with 328.2 kW of exergy destruction rate, 18.4 $/h of exergy destruction cost rate, and 12.83 $/h of electricity cost rate with determined value of decision variables is selected as final optimum state.