Thermoeconomical, wind assessments and environmental analysis of compressed air energy storage (CAES) integrated with a wind farm by using RSM as a machine learning optimization technique - case study - Denmark

In this research, thermodynamic modeling and economic evaluation of a new wind power plant were discussed. A new wind power plant was designed by combining CAES, gas turbine units and wind turbines. Using the optimization method, the feasibility of setting up an optimal wind power plant in different cities in Denmark was discussed. EES thermodynamic software was used to model the wind power plant and the response surface method were used to optimize. The wind power plant in its most optimal state can reach an ERTE of 24.659 % and a cost rate of 185.213 $/h. The optimal results showed that the optimal number of wind turbines for setting up a wind farm is 11. The highest exergy destruction as well as the cost rate of the wind power plant is related to the wind farm and the gas turbine, respectively. A case study for setting up a wind farm concerning the climate change analysis of six cities SSkagen, Alborg, Arhus, Roskilde, Odense, and Copenhagen was conducted in Denmark. Then, the ability of the wind power plant to supply the electricity needed by the population of the studied cities was investigated. The wind farm performance in the mode of using wind farm electricity and not using wind farm electricity for CAES unit and electricity generation was investigated. The results showed that when the electricity required by the CAES unit is supplied from the power grid, the gas turbine can help the instability of the wind farm and provide the power needed for peak consumption.