Abstract
This work studies the economic feasibility of using a hybrid solar energy system to satisfy the thermal demand in industrial processes. From an artificial intelligence perspective, a modeling and computational optimization methodology was developed for the design of a hybrid solar thermal plant. Modeling is applied to satisfy the needs of a pasteurization process in the region of Jalisco, Mexico. Scenarios with four different types of fossil fuels used in the backup system were analyzed. According to the optimization results, all the backup fossil fuel scenarios demonstrate economic viability. Furthermore, the present value studies indicate that under the appropriate climatic conditions, for the four auxiliary fuel scenarios, the optimization methodology can produce economically attractive configurations of the solar thermal plant for investors. The presented methodological procedure can be easily adapted and used to analyze the financial competitiveness of other solar thermal technologies for the industrial heat generation.
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