TRANSIENCE: D4.4 – EU industrial pilot modules - ITOM - Petrochemicals

Model overview

Model purpose

The Industry Transformation Optimisation Model for Petrochemicals (ITOM Petchem) is a mathematical linear optimization model—a method to find the best solution given a set of constraints—for investment decisions in the European petrochemical production system and the utilization of capacity.

The model is used to create middle- and long-term scenarios for the future of the European petrochemical industry, depending on assumptions that influence future investments. These assumptions include market trends (e.g., future feedstock prices and demand for polymers), policy changes (e.g., climate ambition and fossil input limitations), and technological advancements (e.g., chemical recycling, and synthetic- or biomass-based production). With the given assumptions, data about the existing petrochemical production system and data about new technologies, the model results help to quantitatively illustrate a potential transformation of the European petrochemical sector, and assist in creating logically consistent narratives.

Model concept

From a mathematical standpoint, the ITOM is a linear optimization model (see technical documentation of ITOM) which optimizes the cost of the system over the whole time period, given certain equations and restrictions. The goal can be understood as illustrating an economically optimized system that fulfils the predefined demand of products. The main restriction from this standpoint is thus the predefined product demand.

The model considers spatially explicitly distributed production sites and their transport connections. The value chain is divided into a range of raw materials and feedstocks, intermediate and final products, and the model features a rich array of technologies for the production of (intermediate) products from its precursors. The driving requirement of the model is to produce an externally defined amount of final products (polymers) while externally defined parameters such as feedstock- and energy costs, and CO2 prices, all changing over the course of the scenario period. The model determines endogenously where, and by which technology the various (intermediate) products are produced in each model time period. For that production, the model uses existing brownfield production sites and capacities, and endogenously invests in retrofits or new capacities over the time period.

Key features

• Spatially explicit representation of existing base chemicals sites and capacities in EU 27+3, as well as transport routes between them (product pipelines, shipping routes)
• Model endogenous optimization of production networks across sites and steps in the value chain (feedstock, HVC, polymers)
• Includes chemical recycling technologies and a biomass-based route, as well as use of imported synthetic feedstocks
• Includes modelled regionalized polymer demand and plastic waste for chemical recycling in different sectors over time
• Includes regionalized biomass potentials for different kinds of biomass over time
• Explicit consideration and endogenously optimized usage of by-products of various production processes