Fossil fuels are used as the primary energy source in most countries, negatively contributing to the environmental impact. Even though various technologies exist to exploit solar thermal energy in low-carbon processes, the use of solar thermal energy in the industry sector is currently minimal. The main obstacles are modeling an optimal integration and identifying its energy potential, economic feasibility and environmental benefits. The novelty of this study is the modeling of an integration of solar heat for an industrial process located in a topographically complex territory such as the Alps using the software Dymola - Dassault Systems (R). The methodology proposed is structured in several steps: (I) industrial process characterization; (II) collection of local hourly data for radiation and climatic temperature; (III) study of the position of sun and components of incident angle; (IV) comparison among three solar technologies (CPC, LFR, PTC), in terms of efficiency, IAM and heat production; (V) focus on PTC: sizing of HTF, mass flow rate, HEX; (VI) focus on PTC: dynamic modeling with Dymola - Dassault Systems (R) (HTF temperature, solar heat, solar fraction); (VII) economic and environmental impact. In this paper, the case study of a pasta factory called "Felicetti", located in the north-east of the Italian Alps, has been considered in order to investigate and evaluate the possibility of supplying solar heat for the drying process. The days of a week in June, exhibiting variable DNI, are used to demonstrate the dynamics and robust integration of the solar heat in the industrial process of pasta drying. The dynamic modelling results show that the PTC solar field can guarantee 23% of weekly energy coverage saving about 4.7 CO2/week. The economic analysis shows a pay-back time up to 9 years and a reduction of CO2 emissions up to 99 t/year.