PTQ Q2 2022 Issue

Process Book) used for operations, process control, and reliability. In addition to the ubiquitous lagging indi - cators, such as unit/site energy indices, effective EnMS use leading KPIs that are operating handle/degradation focused and prioritised on energy or $ gap to poten - tial. These leading KPIs include reflux ratios, key tem - peratures, pressures, fouling/degradation impact on exchanger heat recovery/compressor efficiency. They were originally developed in a standardised (Excel) variable table with regression based SMART targets that track key constraints like product quality. Effective EnMS accountability requires a mix of central and units roles, usually with a central coordinator, site-wide tools, and functions for utility systems, furnaces, compres - sors and responsibilities for each process area. Daily, weekly, monthly, quarterly meetings and reports include a significant $/day total energy gap and the top notable contributors at the unit/equipment area levels to drive operations and maintenance or project initiation needed to close the gaps, which should be tracked by the normal refinery initiative management processes. Q Have completed energy efficiency projects delivered expected energy and CO 2 savings? A Romain Roux, Decarbonization & Consulting Director, Axens, In the frame of energy efficiency studies performed by Axens Horizon, we have frequent feedback on the results of implemented energy efficiency solutions, especially for quick wins and budget-friendly solutions. Results are as expected within a margin of accuracy that depends on the accuracy of the basic data. Some solutions we would like to highlight include: ● Low Capex projects for optimisation of complex heat exchange networks by re-routing of streams ● Optimisation of distillation column operating conditions ● Upgrade of heaters fuel/air control system ● Implementation of air preheaters in furnaces Among the solutions creating a higher return on investment, we got several opportunities to switch two heat exchangers within a heat exchange network (CDU, coker, visbreaker). The two heat exchangers were iden - tified thanks to Pinch analysis developed explicitly for revamping applications. A Ken Chlapik, Market Manager - Low Carbon Solutions, JohnsonMatthey, For decades Johnson Matthey has been involved in energy efficiency projects with its customers to help reduce the level of energy used per unit production of syngas. For example, in the refinery hydrogen market, we have worked with industrial gas companies over the last 20 years to set new levels of efficiency that are 20-30% lower than on-purpose refinery hydrogen plants. This has been done utilising unit technologies and cat - alyst developments to not only improve year one per - formance but also extend that efficient performance for long lifecycles beyond the typical refinery major turn - around cycle.

Axens,; PhilippeMège, Head of Digital Service Factory, Axens, Digital transformation of the refining and chemical industry is now playing a crucial role in energy effi - ciency improvement and associated GHG emission reduction. Digitalisation in view of remote performance monitoring is a major aspect of today’s unit operation management and optimisation. The main advantages of digital tools are first to reduce the delay between the client’s request for unit monitoring or troubleshooting and the technology provider’s answers, and to open up access to customised unit optimisation tools. Implementing Software as a Service, accessible to our customers 24/365 and fed by process and lab data through an automatic and near real-time transfer, has been the first step of our digital transformation and paved the way for a new paradigm for technical services. For such fast-track implementation, supported by licensor and catalyst experts, operator involvement to automate data transfer while addressing all potential concerns related to cybersecurity, data ownership, and lifecycle is minimum. For operators, access to appropriate alerts, data anal - yses, and optimisation tools are success factors in fast decision-making in increasing overall unit profitability. Typical examples of client expectations that can be addressed through remote performance monitoring are: unit performance prediction while changing operating conditions; comparing actual performances with nor - malised ones; catalyst end-of-cycle prediction to antic - ipate turnaround or get the most from the catalyst; or even proposing continuously the best set of operating conditions for a given set of performance targets, such as yields optimisation, utilities reduction, and cycle length extension. Reliability of the projections is ensured through advanced data analysis algorithms with a preliminary data reconciliation step using, for instance, principal component analysis (PCA) and robust regression meth - odologies such as partial least squares (PLS) or Theil- Sen estimator. Other available tools are very accurate and continu - ously update shift vector generation, which can become a major help for the planning department. The generation of synthetic data thanks to machine learning is another example of either densifying lab - oratory data or generating new models to foresee a product’s properties based on existing process data and unit performances and acting as an on-line analy - ser. Improving operation survey quality at no extra cost becomes a key adoption factor. A Tom Chupick, Principal Consultant – Carbon and Energy Management, Petrogenium, After developing/supporting/auditing a few dozen energy management systems (EnMS) globally, the main learnings relative to integration and accountabilities help drive sustainability. The foundation is consistent with Iso-50001, but improved sharing and replication of best practices and tools is required. Sites with effective inte - gration have built EnMS into the same user interface (PI

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