Optimizing the Performance of Parabolic Trough Solar Collectors Using the Grey Wolf Algorithm

The current study proposes a Grey Wolf Optimizer method for parabolic trough solar collector (PTSC) design optimization. The hunting and leadership styles of Grey Wolf packs serve as models for the Grey Wolf Optimizer (GWO). Compared to other swarm-based algorithms, GWO has a number of advantages. It does not require derived knowledge during the first search and is very flexible to different optimization situations. Its ability to avoid local optima is further improved by the fact that it requires few initial settings. Thermal and energetic efficiency, which are crucial performance indicators for PTSCs, are the selected objective functions. The PTC receiver tube's inlet and outlet diameters, as well as the inlet temperature, are design factors. To enhance PTC performance without raising expenses, the volume of the PTSC material is maintained constant throughout the optimization process. In this work, mathematical programming models were formulated using a multi-objective optimization strategy. MATLAB was used to create and implement these models. Both thermal and exergetic efficiencies are effectively maximized by the suggested optimization strategy. Researchers in the field who want to examine and improve PTSC performance can easily use the optimization model. Researchers can quickly choose their preferred optimal locations for the study and construction of PTSCs by using the Pareto fronts that are currently in use.