(657h) Optimal Design of Solar Systems for Decarbonizing Industrial Process Heat Applications

Decarbonizing the industrial sector is an immense challenge and is of primary importance if we hope to achieve the greenhouse gas emission reductions re­quired to meet the nation’s climate targets. The manufacturing sector accounts for about 78% of the total energy consumption of the US industrial sector [1]. In particular, industrial process heat (IPH) accounts for approximately 36% of the total energy consumption within the manufacturing sector [2]. Roughly 41% of the energy consumption of the manufacturing sector is sourced from natural gas alone [1]. Since the majority of IPH systems require moderate working temper­atures (<250 .C) [3, 4], they are well-matched for hybridization with renewable heat technologies, such as concentrating solar thermal (CST) [5], and there­fore represent significant opportunities for greenhouse gas emission reductions. However, solar technologies are not a silver bullet, as they require a significant capital investment and are highly sensitive to the geographic location of the installation.

In the last decade, solar photovoltaic (PV) technology costs have decreased from about $5.50/W in 2010 to about $1/W in 2020 [6]. Due to this signifi­cant reduction in the costs of PV and the relatively stable costs of CST (e.g., parabolic trough collectors), the question became relevant of whether PV could be more cost effective for IPH systems versus CST. In this paper, we present formal deterministic global optimization-based approaches to address this ques­tion. Specifically, we utilize a differentiable model for solar IPH hybridization [5] that was developed specifically for formal investment decision making and has been shown to be an effective tool for the optimal design of CST and ther­mal energy storage (TES) systems coupled to IPH systems. In addition to the CST and TES system models, new models for PV and battery storage were developed. We then employed these models within a comparative technoeconomic assessment based on the lifecycle savings of four IPH hybridization choices: parabolic trough CST with TES, fixed-axis PV with TES, one-axis tracking PV with TES, and one-axis tracking PV with battery storage. Three geographic locations across the US are also considered: coastal New England, Colorado’s high plains, and California’s central valley. In each location, despite the signif­icant cost reductions in PV, CST with TES is still the superior technology for solar IPH hybridization. A brief analysis of these results and opportunities for innovation in this space will also be discussed.

References
[1] US Energy Information Administration. Use of en­ergy explained: Energy use in industry, 2022. URL https://www.eia.gov/energyexplained/use-of-energy/industry-in-depth.php.
[2] US Environmental Protection Agency. Renewable heating and cooling: Renewable industrial process heat, 2022. URL https://www.epa.gov/rhc/renewable-industrial-process-heat.
[3] Shahjadi Hisan Farjana, Nazmul Huda, MA Parvez Mahmud, and R Saidur. Solar process heat in industrial systems–a global review. Renewable and Sustainable Energy Reviews, 82:2270–2286, 2018. doi: 10.1016/j.rser.2017.08.065.
[4] Parthiv Kurup and Craig Turchi. Initial investigation into the potential of CSP industrial process heat for the southwest United States. Technical report, NREL, 2015.
[5] Matthew D. Stuber. A differentiable model for optimizing hybridization of industrial process heat systems with concentrating solar thermal power. Processes, 6(7):76, jun 2018. doi: 10.3390/pr6070076.
[6] David Feldman, Vignesh Ramasamy, Ran Fu, Ashwin Ramdas, Jal Desai, and Robert Margolis. US solar photovoltaic system and energy storage cost benchmark: Q1 2020. Technical report, National Renewable Energy Labo­ratory, 2021. URL https://www.nrel.gov/docs/fy21osti/77324.pdf.