The Experts below are selected from a list of 1344 Experts worldwide ranked by ideXlab platform

Souvik Bhattacharyya - One of the best experts on this subject based on the ideXlab platform.

  • studies on a two stage transcritical carbon dioxide heat pump cycle with flash intercooling
    Applied Thermal Engineering, 2007
    Co-Authors: Souvik Bhattacharyya
    Abstract:

    Abstract Simulation studies on a two-stage flash intercooling transcritical carbon dioxide heat pump cycle are presented. Sub-critical and super-critical thermodynamic and transport properties of carbon dioxide are calculated employing an exclusive precision property code based on recently published correlations. Results exhibit that flash intercooling technique is not economical with CO2 refrigerant unlike NH3 as the refrigerant. COP is considerably lower than that of the single cycle for a given gas cooler and evaporator temperature. There is no optimum inter-stage pressure as well. However, a marginal increase in COP occurs as inter-stage pressure decreases from the classical estimate of geometric mean of gas cooler and evaporator pressure. It is observed that incorporation of desuperheating of vapour in the intercooler almost doubles the mass flow rate in the second stage which can be attributed to the large flashing that occurs in the intercooler; this increase depends on the discharge temperature from the first stage and mass flow rate of refrigerant flow in the evaporator. Compressor Isentropic Efficiency shows marginal influence on system performance.

  • Optimization of two-stage transcritical carbon dioxide heat pump cycles
    International Journal of Thermal Sciences, 2007
    Co-Authors: Souvik Bhattacharyya
    Abstract:

    Optimization studies of two-stage transcritical carbon dioxide heat pump cycles, incorporating options such as flash gas bypass, flash intercooling and Compressor intercooling, are presented based on cycle simulation. Sub-critical and super-critical thermodynamic and transport properties of carbon dioxide coded and then integrated with the simulation code for further analyses. Results exhibit improvement in performance by adopting optimal operating conditions. The optimum interstage pressure, thus obtained, deviate from the classical estimate of geometric mean of gas cooler and evaporator pressure. It is observed that the flash gas bypass system yields the best performance among the three two stage cycles analyzed. Internal heat exchanger effectiveness and Compressor Isentropic Efficiency shows marginal influence on the system performance. Internal heat exchanger effectiveness shows marginal influence on the system performance while Compressor Isentropic Efficiency shows an about 10% variation in COP. However, optimum gas cooler pressure and optimum intermediate pressure are only marginally affected. Based on the cycle simulations, correlations of optimum gas cooler pressure and inter-stage pressure in terms of gas cooler temperature and evaporator temperature are obtained. This would be useful as a guideline in design of such systems.

Ibrahim Dincer - One of the best experts on this subject based on the ideXlab platform.

  • a new integrated heat pump option for heat upgrading in cu cl cycle for hydrogen production
    Computers & Chemical Engineering, 2017
    Co-Authors: M Almahdi, Ibrahim Dincer, Marc A Rosen
    Abstract:

    Abstract A potential cascaded vapor compression heat pump is proposed to address the high temperature heat demand in the copper chlorine (Cu-Cl) thermochemical cycle for hydrogen production. The configuration studied is a cuprous chloride CuCl vapor compression heat pump cascaded with a biphenyl (C 6 H 5 ) 2 heat pump. Such cascaded heat pumps is meant to upgrade heat from nuclear power plants with a heat input temperature of approximately 300 °C or industrial waste heat to meet the Cu 2 OCl 2 decomposition reactor heat demand. Energy and exergy analyses are performed to understand the performance of the heat pump. It is determined that the CuCl-biphenyl heat pump exhibits a high coefficient of performance for certain operating conditions relating to the Compressor Isentropic Efficiency and the excess CuCl feed temperature. The base energetic and exergetic coefficient of performances of the CuCl-biphenyl heat pump are 1.76 and 1.15 respectively.

  • multi objective optimization of a combined heat and power chp system for heating purpose in a paper mill using evolutionary algorithm
    International Journal of Energy Research, 2012
    Co-Authors: Pouria Ahmadi, A Almasi, M Shahriyari, Ibrahim Dincer
    Abstract:

    SUMMARY The present study deals with a comprehensive thermodynamic modeling of a combined heat and power (CHP) system in a paper mill, which provides 50 MW of electric power and 100 ton h−1 saturated steam at 13 bars. This CHP plant is composed of air Compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. The design parameters of this cycle are Compressor pressure ratio (rAC), Compressor Isentropic Efficiency (ηAC), GT Isentropic Efficiency (ηGT), CC inlet temperature (T3), and turbine inlet temperature (T4). In the multi-objective optimization three objective functions, including CHP exergy Efficiency, total cost rate of the system products, and CO2 emission of the whole plant, are considered. The exergoenvironmental objective function is minimized whereas power plant exergy Efficiency is maximized using a Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost is performed. The results show that at the lower exergetic Efficiency, in which the weight of exergoenvironmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergoenvironmental objective. In addition, with increasing exergy Efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases. Copyright © 2010 John Wiley & Sons, Ltd.

  • thermodynamic and exergoenvironmental analyses and multi objective optimization of a gas turbine power plant
    Applied Thermal Engineering, 2011
    Co-Authors: Pouria Ahmadi, Ibrahim Dincer
    Abstract:

    Abstract The present study deals with a comprehensive thermodynamic and exergoeconomic modeling of a Gas Turbine (GT) power plant. In order to validate the thermodynamic model, the results are compared with one of the largest gas turbine power plants in Iran (known as Shahid Salimi Gas Turbine power plant). Moreover, a multi-objective optimization is performed to find the best design variables. The design parameters considered here are air Compressor pressure ratio ( r AC ), Compressor Isentropic Efficiency ( η AC ), gas turbine Isentropic Efficiency ( η GT ), combustion chamber inlet temperature ( T 3 ) and gas turbine inlet temperature (TIT). In the multi-objective optimization approach, certain exergetic, economic and environmental parameters are considered through two objective functions, including the gas turbine exergy Efficiency, total cost rate of the system production including cost rate of environmental impact. In addition, fast and effective non-dominated sorting genetic algorithm (NSGA-II) is applied for the optimization purpose. The thermoenviroeconomic objective function is minimized while power plant exergy Efficiency is maximized using a power full developed genetic algorithm. The results of optimal designs are obtained as a set of multiple optimum solutions, called ‘the Pareto optimal solutions’. Moreover, the optimized results are compared with the working data from the case study. These show that by selecting the optimized data 50.50% reduction in environmental impacts is obtained. Finally, sensitivity analysis of change in objective functions, when the optimum design parameters vary, is performed and the degree of each parameter on conflicting objective functions has been determined.

  • exergoenvironmental analysis and optimization of a cogeneration plant system using multimodal genetic algorithm mga
    Energy, 2010
    Co-Authors: Pouria Ahmadi, Ibrahim Dincer
    Abstract:

    In the present work, a combined heat and power plant for cogeneration purposes that produces 50MW of electricity and 33.3kg/s of saturated steam at 13bar is optimized using genetic algorithm. The design parameters of the plant considered are Compressor pressure ratio (rAC), Compressor Isentropic Efficiency (ηcomp), gas turbine Isentropic Efficiency (ηGT), combustion chamber inlet temperature (T3), and turbine inlet temperature (TIT). In addition, to optimally find the optimum design parameters, an exergoeconomic approach is employed. A new objective function, representing total cost rate of the system product including cost rate of each equipment (sum of the operating cost, related to the fuel consumption) and cost rate of environmental impact (NOx and CO) is considered. Finally, the optimal values of decision variables are obtained by minimizing the objective function using evolutionary genetic algorithm. Moreover, the influence of changes in the demanded power on various design parameters are parametrically studied for 50, 60, 70MW of net power output. The results show that for a specific unit cost of fuel, the values of design parameters increase, as the required, with net power output increases. Also, the variations of the optimal decision variables versus unit cost of fuel reveal that by increasing the fuel cost, the pressure ratio, rAC, Compressor Isentropic Efficiency, ηAC, turbine Isentropic Efficiency, ηGT, and turbine inlet temperature (TIT) increase.

Pouria Ahmadi - One of the best experts on this subject based on the ideXlab platform.

  • multi objective optimization of a combined heat and power chp system for heating purpose in a paper mill using evolutionary algorithm
    International Journal of Energy Research, 2012
    Co-Authors: Pouria Ahmadi, A Almasi, M Shahriyari, Ibrahim Dincer
    Abstract:

    SUMMARY The present study deals with a comprehensive thermodynamic modeling of a combined heat and power (CHP) system in a paper mill, which provides 50 MW of electric power and 100 ton h−1 saturated steam at 13 bars. This CHP plant is composed of air Compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. The design parameters of this cycle are Compressor pressure ratio (rAC), Compressor Isentropic Efficiency (ηAC), GT Isentropic Efficiency (ηGT), CC inlet temperature (T3), and turbine inlet temperature (T4). In the multi-objective optimization three objective functions, including CHP exergy Efficiency, total cost rate of the system products, and CO2 emission of the whole plant, are considered. The exergoenvironmental objective function is minimized whereas power plant exergy Efficiency is maximized using a Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost is performed. The results show that at the lower exergetic Efficiency, in which the weight of exergoenvironmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergoenvironmental objective. In addition, with increasing exergy Efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases. Copyright © 2010 John Wiley & Sons, Ltd.

  • thermodynamic and exergoenvironmental analyses and multi objective optimization of a gas turbine power plant
    Applied Thermal Engineering, 2011
    Co-Authors: Pouria Ahmadi, Ibrahim Dincer
    Abstract:

    Abstract The present study deals with a comprehensive thermodynamic and exergoeconomic modeling of a Gas Turbine (GT) power plant. In order to validate the thermodynamic model, the results are compared with one of the largest gas turbine power plants in Iran (known as Shahid Salimi Gas Turbine power plant). Moreover, a multi-objective optimization is performed to find the best design variables. The design parameters considered here are air Compressor pressure ratio ( r AC ), Compressor Isentropic Efficiency ( η AC ), gas turbine Isentropic Efficiency ( η GT ), combustion chamber inlet temperature ( T 3 ) and gas turbine inlet temperature (TIT). In the multi-objective optimization approach, certain exergetic, economic and environmental parameters are considered through two objective functions, including the gas turbine exergy Efficiency, total cost rate of the system production including cost rate of environmental impact. In addition, fast and effective non-dominated sorting genetic algorithm (NSGA-II) is applied for the optimization purpose. The thermoenviroeconomic objective function is minimized while power plant exergy Efficiency is maximized using a power full developed genetic algorithm. The results of optimal designs are obtained as a set of multiple optimum solutions, called ‘the Pareto optimal solutions’. Moreover, the optimized results are compared with the working data from the case study. These show that by selecting the optimized data 50.50% reduction in environmental impacts is obtained. Finally, sensitivity analysis of change in objective functions, when the optimum design parameters vary, is performed and the degree of each parameter on conflicting objective functions has been determined.

  • Thermo-economic-environmental multiobjective optimization of a gas turbine power plant with preheater using evolutionary algorithm
    International Journal of Energy Research, 2011
    Co-Authors: H. Barzegar Avval, A. R. Ghaffarizadeh, Pouria Ahmadi, Mohammad Hassan Saidi
    Abstract:

    In this study, the gas turbine power plant with preheater is modeled and the simulation results are compared with one of the gas turbine power plants in Iran namely Yazd Gas Turbine. Moreover, multiobjective optimization has been performed to find the best design variables. The design parameters of the present study are selected as: air Compressor pressure ratio (rAC), Compressor Isentropic Efficiency (ηAC), gas turbine Isentropic Efficiency (ηGT), combustion chamber inlet temperature (T3) and gas turbine inlet temperature. In the optimization approach, the exergetic, economic and environmental aspects have been considered. In multiobjective optimization, the three objective functions, including the gas turbine exergy Efficiency, total cost rate of the system production including cost rate of environmental impact and CO2 emission, have been considered. The thermoenvironomic objective function is minimized while power plant exergy Efficiency is maximized using a genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost has been performed. In addition, the results showed that at the lower exergetic Efficiency in which the weight of thermoenvironomic objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of Pareto Frontier with the lower weight of thermoenvironomic objective. © 2010 John Wiley & Sons, Ltd.

  • exergoenvironmental analysis and optimization of a cogeneration plant system using multimodal genetic algorithm mga
    Energy, 2010
    Co-Authors: Pouria Ahmadi, Ibrahim Dincer
    Abstract:

    In the present work, a combined heat and power plant for cogeneration purposes that produces 50MW of electricity and 33.3kg/s of saturated steam at 13bar is optimized using genetic algorithm. The design parameters of the plant considered are Compressor pressure ratio (rAC), Compressor Isentropic Efficiency (ηcomp), gas turbine Isentropic Efficiency (ηGT), combustion chamber inlet temperature (T3), and turbine inlet temperature (TIT). In addition, to optimally find the optimum design parameters, an exergoeconomic approach is employed. A new objective function, representing total cost rate of the system product including cost rate of each equipment (sum of the operating cost, related to the fuel consumption) and cost rate of environmental impact (NOx and CO) is considered. Finally, the optimal values of decision variables are obtained by minimizing the objective function using evolutionary genetic algorithm. Moreover, the influence of changes in the demanded power on various design parameters are parametrically studied for 50, 60, 70MW of net power output. The results show that for a specific unit cost of fuel, the values of design parameters increase, as the required, with net power output increases. Also, the variations of the optimal decision variables versus unit cost of fuel reveal that by increasing the fuel cost, the pressure ratio, rAC, Compressor Isentropic Efficiency, ηAC, turbine Isentropic Efficiency, ηGT, and turbine inlet temperature (TIT) increase.

  • Optimization of Combined Cycle Power Plant Using Sequential Quadratic Programming
    Heat Transfer: Volume 1, 2008
    Co-Authors: Mohammad Reza Meigounpoory, Pouria Ahmadi, Ahmadreza Ghaffarizadeh, Shoaib Khanmohammadi
    Abstract:

    The thermal-economic optimization of a combined cycle power plant (CCPP) which can provide 140 MW of electrical power is discussed in this paper. The CCPP is composed of a gas turbine cycle (including, air Compressor, combustion chamber, gas turbine), heat recovery steam generator (HRSG), steam turbine, condenser system, and a pump. The design parameters of such a plant are Compressor pressure ratio (rAC ), Compressor Isentropic Efficiency (ηAC ) gas turbine Isentropic Efficiency (ηGT ), and turbine inlet temperature (T3 ), pinch difference temperature (ΔTpinch ), steam turbine inlet temperature (Ta ), steam turbine Isentropic Efficiency (ηST ), and pump Isentropic Efficiency (ηPUMP ). The objective function was the total cost of the plant in terms of dollar per second, including sum of the operating cost related to the fuel consumption, and the capital investment for equipment purchase and maintenance costs. The optimal values of decision variables were obtained by minimizing the objective function using sequential quadratic programming (SQP). The effects of change in the demanded power and fuel price on the design parameters werestudied for, 100, 120, and 140MW of net power output.Copyright © 2008 by ASME

Norbert Müller - One of the best experts on this subject based on the ideXlab platform.

  • using water vapor as refrigerant in multistage variable speed turbo Compressor to improve seasonal energy Efficiency ratio of air conditioning
    International Journal of Air-conditioning and Refrigeration, 2011
    Co-Authors: Qubo Li, Demiss A Amibe, Norbert Müller
    Abstract:

    An air conditioning system using water as refrigerant (R718) that compresses water vapor with multistage stage variable speed axial Compressor with intercooling between stages by water injection is considered. Four stage compression with flash intercooling resulted in 50% improvement of coefficient of performance (COP) at full load compared to conventional refrigerants like R134a. The energy Efficiency of an air conditioning unit is specified by seasonal energy Efficiency ratio (SEER). SEER is defined as the ratio of cooling output of an air conditioner measured and electrical energy consumption as per AHRI 210/240 during cooling season. The SEER is computed after determining the evaporator cooling capacity and the electrical energy demand of the Compressor at each bin temperature using assumed Compressor Isentropic Efficiency, mechanical Efficiency and electrical Efficiency and multiplying by the weight of each bin temperature to determine the total for the cooling season. As a result of multistage compression, best part load performance of water as a refrigerant and operation of Compressor near design point at part load due to variable speed drive, 50%–60% improvement in SEER is obtained compared to the best available in the market using conventional refrigerants such as R134a with single stage compression.

Qubo Li - One of the best experts on this subject based on the ideXlab platform.

  • using water vapor as refrigerant in multistage variable speed turbo Compressor to improve seasonal energy Efficiency ratio of air conditioning
    International Journal of Air-conditioning and Refrigeration, 2011
    Co-Authors: Qubo Li, Demiss A Amibe, Norbert Müller
    Abstract:

    An air conditioning system using water as refrigerant (R718) that compresses water vapor with multistage stage variable speed axial Compressor with intercooling between stages by water injection is considered. Four stage compression with flash intercooling resulted in 50% improvement of coefficient of performance (COP) at full load compared to conventional refrigerants like R134a. The energy Efficiency of an air conditioning unit is specified by seasonal energy Efficiency ratio (SEER). SEER is defined as the ratio of cooling output of an air conditioner measured and electrical energy consumption as per AHRI 210/240 during cooling season. The SEER is computed after determining the evaporator cooling capacity and the electrical energy demand of the Compressor at each bin temperature using assumed Compressor Isentropic Efficiency, mechanical Efficiency and electrical Efficiency and multiplying by the weight of each bin temperature to determine the total for the cooling season. As a result of multistage compression, best part load performance of water as a refrigerant and operation of Compressor near design point at part load due to variable speed drive, 50%–60% improvement in SEER is obtained compared to the best available in the market using conventional refrigerants such as R134a with single stage compression.

  • multi stage variable speed turbo Compressor for enhancing seasonal energy Efficiency ratio of air conditioners using r718 as refrigerant
    Volume 5: Industrial and Cogeneration; Microturbines and Small Turbomachinery; Oil and Gas Applications; Wind Turbine Technology, 2010
    Co-Authors: Demiss A Amibe, Qubo Li, Norbert Mu Ller
    Abstract:

    An air conditioning system using water as refrigerant (R718) that compresses water vapor with multistage stage variable speed axial Compressor with intercooling between stages by water injection is considered. Four stage compression with flash intercooling resulted in 50% improvement of coefficient of performance (COP) at full load compared to conventional refrigerants like R134a. The energy-Efficiency of an air conditioning unit is specified by seasonal energy Efficiency ratio (SEER). SEER is defined as the ratio of cooling output of an air conditioner measured and electrical energy consumption as per AHRI 210/240 during cooling season. The SEER is computed after determining the evaporator cooling capacity and the electrical energy demand of the Compressor at each bin temperature using assumed Compressor Isentropic Efficiency, mechanical Efficiency and electrical Efficiency and multiplying by the weight of each bin temperature to determine the total for the cooling season. As a result of multistage compression, best part load performance of water as a refrigerant and operation of Compressor near design point at part load due to variable speed drive, 50–60% improvement in SEER is obtained compared to the best available in the market using conventional refrigerants such as R134a with single stage compression.Copyright © 2010 by ASME