Economic risk analysis for the capture of a distributed energy resource using modular chemical process intensification

Abstract

Recent advances in the chemical process industry have allowed for the intensification of reactors and unit operations, by enhancing heat and mass transfer or combining multiple unit operations. Process intensification can enable chemical plants to be constructed in a more compact, modular fashion, offering improvements over conventional on-site approaches to capital construction, operations and maintenance. This modular chemical process intensification (MCPI) offers several benefits over conventional stick-built (CSB) plant construction in terms of reduced footprint, reduced energy consumption, lower cost, less waste and improved safety and quality control.However, acceptance of MCPI over CSB construction practices within the chemical industry can be impeded by the uncertain risks associated with investing in new technology. The work here documents a case study during the development of a modular chemical plant for capturing distributed energy resources within chemical production. This MCPI approach to plant construction is contrasted with a CSB approach for producing the same chemical product. Data collection tools were developed, based on a literature review, and data was collected from the technology developer to understand the process technology. Sensitivity analysis was then conducted to analyze the business rationale for the application of MCPI over CSB across several market scenarios. It was found that MCPI would be better suited for capacities up to 150 000 metric tons per year, but that improvement in payback period was needed.Additionally, for MCPI approach to achieve acceptable payback periods, efforts are needed to reduce the cost of capital equipment and compress the schedule for ramping up modular production.

Conceptual range estimation for total cost of ownership of modular process‐intensified chemical plants

“…[21,23,25] The unique scaling attributes of MCPI, in particular the strategy for numbering-up (N-U), have been a challenge for chemical facility planning, design, and construction. [37]…”

“…Estimating costs of numbering-up of modular units is relatively uncommon in the chemical process industry compared to investment cost estimation based on power law scale-up factors developed for conventional stick-built facilities. [38,39] The power law concept, termed the Learning Curve, is based on the observation that labor costs decrease when laborers repeatedly conduct routine tasks. [40,41] For example, a 20% learning curve translates into a 20% reduction in labor expense when doubling the cumulative production.…”

“…The third project involves the production of a chemical product with broad applications in the pharmaceutical, metallurgical, food, power generation, semiconductor, and other industries; additional project details are reported in Shankar Raman et al [ 37 ] This commodity chemical is often produced on site and used as a feedstock for downstream chemical processes. To protect the identity of the industry case partner, the actual chemical product is not revealed, nor is the actual production capacity or physical size of the plant; capacities are reported in the equivalent number of MCPI trains.…”