Determining the Efficiency of the Energy Storage Unit of Solar Chimney Power Plants with Artificial Intelligence

The biggest drawback for solar energy systems is the lack of performance during non-sunlit hours. While this can be overcome by integrating energy storage units into the systems, the initial investment cost and maintenance costs are disadvantages. Solar chimney power plants, a type of solar energy system, have a simple structure consisting of a collector, chimney, and turbine and operate solely on the principle of generating electricity by accelerating heated air upwards. The system's feasibility was demonstrated with the first prototype, Manzanares, which serves as the reference pilot plant in this study. Solutions are obtained after the validation and mesh-independent solution steps of the model created with the 3D CFD model. For real-world simulation, a discrete ordinates (DO) solar ray tracking algorithm is implemented in the analysis, assuming turbulent flow. Solar radiation enters the system through the translucent collector and reaches the ground. Solar radiation reaching the ground can be stored for heat transfer to the system air during non-sunlit hours using energy storage materials. Due to the system's structure, using storage materials in the ground is quite easy, and even using water with high heat capacity is possible. This study discusses the appropriate amounts of artificial intelligence-based energy storage systems for use on the ground. Solutions to increase energy storage efficiency and reduce performance degradation throughout the day are discussed. In particular, comprehensive recommendations are offered for maximum 24-hour performance.