Design optimization and control approach for a solar-augmented industrial heating

Abstract

Process level integration of solar energy could give an economically feasible solution if the industrial process allows its practical integration. The solar-augmented industrial process behaves as a complex system influenced by uncertainty of solar radiation, variability of demand temperature and process time schedule as well as possibility of thermal stratification in the storage. Addressing these issues to reach the most economical solution has two dimensions to it. First, the solar thermal system needs to be optimally designed. This requires the development of a performance criterion that will deliver maximum solar energy to the industrial process, avoid large variations of energy in the storage, and meet investment constraints. Second, the identified optimal system should be dynamically controlled to enable uniform heat distribution and efficient auxiliary heat utilization. This paper presents a holistic design optimization and control approach for a solar-augmented industrial process to facilitate decision support. The proposed solution is designed and optimized for a dyeing industrial process case study that resulted in a 5.7 year payback period, 56.3% solar fraction, and 252.2 tons equivalent carbon emission reduction. Furthermore by implementing dynamic control, about 12.4% increase in solar gain that led to a 5.6% reduction in payback period is identified.