Showing 4 results for Microturbine
Peyman Maghsoudi, Pedram Hanafizadeh,
Volume 16, Issue 1 (3-2016)
Abstract
In this paper, multi objective genetic algorithm is applied to optimize one type of recuperator in a 200 kW microturbine by considering two key parameters such as recuperator efficiency and cost. ε-NTU method is selected for the recuperator efficiency and pressure drop calculation. The recuperator total cost consists of capital cost, operational cost and maintenance cost. A plate-fin heat exchanger with offset strip fin for counter and cross flow arrangements is chosen for optimization. Fin pitch, fin height, fin offset length, cold stream flow length, non-flow stream length and hot stream flow length are considered as six design parameters. NSGA-II (Non-dominated Sorting Genetic Algorithm) is conducted to maximize recuperator efficiency and minimize its total cost. Results of the optimization are presented as a set of designs, called ‘Pareto-optimal solutions’. The results reveal the confliction between the two objective functions. It can be concluded that any change in the geometry of the recuperator increasing the efficiency also increases the total cost and vice versa. Finally, the optimal designs are compared together based on non-dominated sorting concept and the final optimal designs are obtained.
F. Rashidi, H. Rashidi,
Volume 19, Issue 2 (2-2019)
Abstract
In this paper, using a thermodynamic rules, a multigeneration energy system with an initial stimulus of microturbine has been modeled. Then, using the concept of exergy and applying economic and environmental functions, exergy efficiency and total cost rate are calculated as two objective functions. Due to the contradiction of the objective functions, a multiobjective firefly algorithm is used to optimize the system. To accelerate the process of optimization and to prevent algorithm capture in local optimizations, new algorithms have been added to the innovative algorithm. The result of applying the algorithm on the multigeneration energy system will result in a set of Pareto-optimal solutions, indicating the compromise between the target functions. A fuzzy decision making based on max-min approach is used to select the desired solution between the Pareto-optimal solutions. In order to evaluate the efficiency of the proposed optimization algorithm, the results of this algorithm are compared with two particle swarm optimization algorithms and multi-objective genetic algorithm. Based on the results of system optimization, the exergy efficiency can increase up to 69%. Also, considering the total cost rate of the system as the only target function, this can be reduced to 572$/h.
M. Nozari, S. Tabejamaat, M. Aghayari, H. Sadeghzade,
Volume 20, Issue 7 (6-2020)
Abstract
Combustion chamber has a crucial role in gas turbines and has a significant effect on the pollution and efficiency of them. Due to the complicated flow in combustion chambers because of high turbulence intensity, flow mixing, and flame behavior, prediction of the performance of such chambers is very complicated. There is a vital need for experimental investigations to study and understand the flame behavior in combustors. This experimental study was performed using a can type combustion chamber and LPG fuel at atmospheric conditions. First, stability curve, temperature distribution in the combustion chamber, and its exit plane in 6 flow conditions and then flow behavior were evaluated. The pollution at the outlet was obtained in different conditions and equivalence ratios. The results show that the flame tends to go downstream of the combustion chamber when the fuel mass flow rate increases (or in other words, by increasing the equivalence ratio) in constant air mass flow rate and finally exits from the chamber. By increasing the air mass flow rate in constant fuel mass flow rate, CO pollution is increased, and NOx pollution is decreased.
Aref Sohrabi, Seyyed Mahdi Mirsajedi,
Volume 24, Issue 12 (11-2024)
Abstract
This study investigates the combustion of hydrogen-methane mixtures in the annular combustion chamber of a C30 microturbine. The primary objective is to evaluate the impact of premixed methane-hydrogen combustion on pollutant emissions and outlet temperature in an annular combustion chamber. Simulations were performed using a partially premixed combustion model and the k-ε turbulence model, employing the Probability Density Function (PDF) approach for chemical reaction modeling. To ensure a detailed analysis of pollutant emissions, comparisons were conducted at a constant turbine inlet temperature. The results indicate that adding hydrogen to methane increases NOx emissions due to the higher flame temperature compared to pure methane, even at constant turbine inlet temperatures. However, this blend can reduce fuel consumption by up to 35%. Additionally, a fuel mixture of 60% methane and 40% hydrogen results in a 61% reduction in CO2 emissions. The study further revealed that, owing to the premixed nature of the fuel-air mixture, the annular geometry, and the swirling flow pattern within the combustion chamber, a fuel blend containing 30% hydrogen can lower NOx emissions to 16.1 ppm—significantly less than the 46 ppm reported in previous studies. Moreover, increasing the hydrogen fraction in the fuel reduced CO emissions by 16%. These findings demonstrate that annular combustion chambers with premixed flows and hydrogen-methane fuel blends have considerable potential for reducing pollutant emissions and optimizing fuel consumption
