r. ghasemiasl

Using Hydrogen instead of fossil fuels has grown significantly due to its high energy density and zero carbon emission during consumption. The most economical method of storing hydrogen is liquefaction. In this study, after pre-cooling by the cold energy of the PRICO and liquefied natural gas (LNG) regasification systems, hydrogen gas enters the next stage and it liquefies by a mixed refrigeration cycle. The novelty of this cycle is based on the new design of a high-efficiency hydrogen liquefaction cycle which is using the cold energy of a LNG regasification process, in turn, results in less power consumption in the compression part and also less cost of power consuming for one kilogram of liquid hydrogen compared to that for a similar cycle. Energy, exergy, and economy analyses are implemented to investigate the proposed cycle. In the proposed hydrogen liquefaction cycle with the capacity of 14 tons per hour, the specific energy consumption (SEC) 15 % and payback period 20% decreased in comparison to the similar cycle.

Optimal arrangement of turbines in wind farms is very important to achieve maximum energy at the lowest cost. In the present study, the use of Vestas V-47 wind turbine and uniform one-way wind in achieving the optimal arrangement of horizontal axis turbines in Manjil with genetic and Monte Carlo algorithms has been investigated. Jensen model is used to simulate the wake effect on the downstream turbines. The objective function is considered as the ratio of cost to power of the power plant. The results show that the Monte Carlo method compared with genetic algorithm will give a better result. Under the same conditions, the Monte Carlo algorithm will give 29% and 40% better results in terms of the number of turbines and output power, respectively. In terms of optimization, in the Monte Carlo algorithm, its fitness value is 16% less than the genetic algorithm, which indicates its better optimization.