Performance evaluation and multi-objective optimization of an innovative double-stage thermoelectric heat storage system for electricity generation

As the need for renewable energy continues to grow, there is an increasing requirement to utilize systems that offer enhanced performance and efficiency. Consequently, a comprehensive investigation is conducted on a two-stage thermoelectric heat pump. The primary objective is to assess the impact of various influential factors on the overall effectiveness of the system. This exhaustive parametric study aims to provide valuable insights into the system's performance and efficiency. Subsequently, the multi-objective optimization approach considers both technical and economic goal functions. By incorporating these two aspects, the optimization process seeks to achieve the most favorable balance between technical performance and economic feasibility. This allows for a holistic assessment that takes into consideration not only the system's efficiency and effectiveness but also its economic viability in real-world applications. The best optimal solution is discovered using a variety of methods for multi-objective optimization. The optimized system is examined from both an exergy and an exergoeconomic vantage point after the best optimal solution has been identified by comparing the results of various methodologies. The outcomes demonstrate that for the multidimensional analysis of Linmap, the combination of multi-objective particle swarm optimization (MOPSO) and the linear programming technique yields the best optimal solution. The objective functions for this final optimal solution are unit cost of heating power and exergy efficiency, which are defined as 1.91 and 51.28 USD/(kWh), respectively. The results showed that the optimal current for temperature changes of 10, 20, and 30 K is 2.84, 5.53, and 8.1 respectively. Also, the optimal length and number of thermocouples were 0.0055 m, 30, and 15 m respectively in all techniques. The optimal current changes from 23.30 to 27.60 A, which indicates that the optimization technique prefers to adjust the current over other effective parameters. When the thermocouples in the first and second stages are 30 and 15 pairs, respectively, according to the design parameters of the ideal point, the system will work at its peak efficiency.