Experimental validation and optimization of PLC-controlled hybrid solar-diesel heating systems in extreme high-altitude climates

Integrating renewable energy technologies in severe environments presents formidable operational and thermodynamic challenges. This study investigates the performance of a large-scale hybrid solar-diesel heating system for a facility in Van (Turkiye), characterized by an extreme altitude of 2,300 m and a design outdoor temperature of -27°C. The research quantifies the thermodynamic efficiency gains of transitioning from conventional manual operation to a programmable logic controller based automated cascade control regime. A high-fidelity digital twin model was validated against a continuous 20-day spring transition window (April 23 - May 13, 2026) using empirical supervisory control and data acquisition temperature logs recorded at 15-minute intervals. Statistical validation confirmed model reliability with a mean bias error of 7.34% and a coefficient of variation of the root mean square error of 8.26%, strictly adhering to international building energy modeling calibration standards. The automated differential cascade control effectively eliminated human operational errors and inefficient boiler short-cycling. Transitioning to full automation achieved a weather-normalized reduction of 53.7% in monthly diesel fuel consumption and mitigated approximately 5.35 tons of carbon dioxide equivalent emissions per month. This research establishes a highly reproducible validation framework for hybrid industrial facilities operating under severe environmental and instrumentation constraints.