Thermoecology-based performance simulation of a Gas-Mercury-Steam power generation system (GMSPGS) - Gonca, Guven; Genc, Ibrahim (PERGAMON-ELSEVIER SCIENCE LTD, 2019)
In this study, thermo-ecology based performance investigations for a combined system consists of Brayton gas cycle, Rankine mercury cycle and Rankine steam cycle, which is called Gas/Mercury/Steam power generation system (GMSPGS), are carried out depending on the most used performance characteristics such as power generation, density of power generation, destructed exergy, second law efficiency (exergetic performance efficiency) with respect to destructed exergy and power generation, ECOP and EFECPOD. The impacts of system design and operating parameters for gas cycle part, mercury cycle part and steam cycle part on the performance characteristics are parametrically examined in detailed. The used parameters are inlet temperature and pressure of the air, mass flow rate of the air, pressure ratio, equivalence ratio, turbine speed, residual gas fraction (RGF), mercury temperature of the gas-mercury heat exchanger (GM-HEX), low-pressure mercury turbine (LPMT), medium-pressure mercury turbine (MPMT), high-pressure mercury turbine (HPMT), steam temperature at the mercury-steam heat exchanger (MS-HEX), the pressures of low-pressure steam turbine (LPST), medium-pressure steam turbine (MPST), high-pressure steam turbine (HPST), open feed water heater (OFWH) and condenser (COND). The results demonstrated that the performance specifications are substantially affected by the component properties. Beside the theoretical model examined in the paper, a data obtained from artificial neural networks (ANNs) is also presented to model the system. It is shown that a limited number of parameters is enough for good approximations.
Keywords: Gas-Mercury-Steam combined system; Exergy; ECOP; EFECPOD; Thermo-ecology; ANN model; ORGANIC RANKINE-CYCLE; WASTE HEAT-RECOVERY; IRREVERSIBLE MILLER CYCLE; ARTIFICIAL NEURAL-NETWORK; BRAYTON-CYCLE; THERMODYNAMIC ANALYSIS; REGENERATIVE BRAYTON; EFFICIENCY OPTIMIZATION; COGENERATION SYSTEM; MATHEMATICAL-MODEL; Thermodynamics; Energy & Fuels; Mechanics