Multi-objective statistical optimization of parabolic trough collector systems using Taguchi, analysis of variance and grey relational analysis methods

This study presents a statistically guided framework for multi-objective optimization of a 50 MW parabolic trough collector (PTC) concentrated solar power (CSP) plant operating under the high direct normal irradiance (DNI) conditions of Rif Dimashq, Syria. Four key design parameters namely: collector count, thermal energy storage (TES) capacity, row spacing, and tracking-axis tilt were evaluated using an integrated Taguchi design, Analysis of Variance (ANOVA), and Grey Relational Analysis (GRA) approach supported by annual performance simulations conducted in Greenius. The results showed that TES capacity was the dominant factor, contributing 96.77% of the variation in net annual electricity generation and more than 75% of the variation in field and system efficiencies. The optimal configuration (600 collectors, 6 h TES, 17.3 m row spacing, and 25° tilt) achieved an levelized cost of electricity (LCOE) of €0.1158/kWh, a net annual generation of 194,234 MWh, a field efficiency of 44.46%, and a system efficiency of 14.8%. Regression-based surrogate models developed for all performance metrics demonstrated excellent predictive reliability (R 2 = 96.15–99.36%). This framework provides an effective and computationally efficient tool for assessing design trade-offs and supporting preliminary planning and feasibility assessment of CSP-PTC plants in high-irradiance regions.