Decarbonisation Technology - November 2024 Issue

Dene business objective and system scope Objectives: Production throughput, revenue, costs, asset utilisation, asset availability Scope: Equipment, process, plant site, enterprise supply chain

Model the appropriate detail Dierent parts of the system can be modelled at dierent levels of detail

Simulate all required scenarios Dierent redundancy levels, storage capacities, system congurations, alternate operation/maintenance strategies

Analy s e and compare simulation results

Identify best scenario, option or alternative, based on business objective Provide insights on C apex /O pex vs system performance trade-os

Figure 1 Aspen Fidelis workflow from objectives to results

weather patterns as well as other sources of uncertainty. Aspen Fidelis is a commercial software system for de-risking capital projects, as described above. It explores multiple system configurations during conceptual design and improves the design by performing reliability, availability and maintenance (RAM) analysis. This could include alternative conversion technologies (such as CO₂ to chemicals), alternative feedstocks, power reliability options, storage options, and the like. Creating design flexibility supported by ‘nested’ models with different levels of detail is the strength of this system. Through this analysis, subsystems initially identified as the highest project risk can be modelled in higher granularity. Once the plant is operational, Fidelis can drive asset performance management to identify critical equipment and events. Figure 1 shows how the software helps to detangle capital projects. Performance analysis to debottleneck sustainability projects One of the most beneficial areas of risk analysis is to understand opportunities and challenges associated with sustainability projects. Understanding risk levels and how to mitigate them can bring confidence to project owners and lenders alike. In the following sections, we will review some examples of sustainability projects that can be de-risked using Aspen Fidelis.

capture process. Several flue gas streams (for example, from a boiler, gas turbine, and tertiary sources) are combined and sent to a carbon capture unit for amine absorption. We assume a nominal capacity of 419.6 t/y for the plant. If we assume 9.6t/y reduced capacity due to unplanned downtime, the system must deliver the remaining 410 kt/y performance with a probability of 85% or more. From a reliability and risk point of view, the question is whether the current design can meet the performance targets and if not, what can change to meet or exceed the expected performance? For this hypothetical process, Aspen Fidelis simulated 100 different scenarios over a lifecycle period of 20 years. The main criterion was tons of captured CO₂ per year. The software reported a best-case scenario capture of 408 kt/y and identified a list of culpability. To redress the reduced capture rate, spare equipment (in this case pumps) needed to be considered. After adding spare pumps to the model and running the scenarios again, the system would capture at least 410 kton/y with a probability of 88% (identified with a red dot on Figure 3 ). Here we have simplified the model and process flow diagram. However, there are other nuances involved in designing a new carbon capture plant, including pipe flows, storage tanks, dynamic behaviour of the system, and total cost. The Fidelis model incorporates all these uncertainties to predict the future performance of the system and what actions can be taken today to ensure meeting process targets.

Carbon capture projects risk analysis Let us assume a rigorous model of a carbon