Combining intermittent renewable electricity (IRE) with carbon capture and utilisation is urgently needed in the chemical sector. In this context, microbial electrosynthesis (MES) has gained attention. It can electrochemically produce hexanoic acid, a value-added chemical, from CO₂. However, there is a lack of understanding regarding how the intermittency of renewable electricity could impact the design of a MES plant. We studied this using Aspen Plus models. A MES plant that was powered by constant grid electricity could operate from 100% down to 70% of its nominal capacity, at which point the heat exchangers and the internal geometrical design of the distillation towers became bottlenecks. The levelised production cost of hexanoic acid (LPC_C6A) was estimated at 4.0 €/kg. Switching to IRE supply increased LPC_C6A to 5.3 €/kg (for wind electricity) and 4.7 €/kg (for hybrid renewable electricity). A battery energy storage system (BESS) was deployed. The lowest LPC_C6A was found at a BESS installation of 29 GJ/h for wind electricity (5.1 €/kg) and at 12 GJ/h for hybrid renewable electricity (4.7 €/kg). In both situations, the volume flexibility of the MES plant was not improved. At the investigated market and operating conditions, coupling IRE to the MES plant was economically infeasible.

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The petrochemical industry is composed of several interconnected processes that use fossil-based feedstock for producing chemicals. These processes are typically geographically clustered and often belong to different parties. Reducing the environmental impacts of the petrochemical industry is not straightforward due to, on the one hand, their reliance on fossil fuels for energy and as a feedstock and, on the other hand, the significant level of interconnected energy and material flows among processes. Current methods for analyzing changes to existing processes cannot capture the multitude and level of interactions. The goal of this paper is to create a model of a petrochemical cluster and analyze its physical characteristics and performance. This paper addresses this goal by developing an assessment method that combines process simulations, multiplex graph analysis, and key performance indicators. The method is applied to a case study based on the petrochemical cluster in the Port of Rotterdam, resulting in a uniquely highly detailed model of a petrochemical cluster. The network analysis results show that only some of the processes are very interconnected. From the performance analysis, it can be observed that the olefins process is the most carbon-intense and has high CO₂ emissions. Additionally, the results showed the importance of considering existing interconnections when assessing the current performance of existing petrochemical clusters or the performance due to future changes to chemical processes. For instance, some changes would occur to an industrial cluster by introducing alternative carbon sources, such as biomass or CO₂.

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The petrochemical industry needs to reduce the use of fossil fuel as carbon feedstock to reduce its CO2 emissions. Several alternative carbon sources (ACSs), such as biomass, CO2 and plastic waste are being proposed to replace fossil carbon. As each of these ACS process routes has its tradeoffs, it is essential to identify the defossilization pathways that will have the most significant impact. In this work, a superstructure-based optimization approach is presented that can be used to assess defossilization pathways in existing petrochemical clusters. The small case study shows that CO₂ is a promising ACS to replace fossil fuel as the main carbon source but requires a large amount of green hydrogen and significant modifications to the existing cluster.

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The reliance of the petrochemical industry on fossil-based sources will need to be reduced by the introduction of Alternative carbon sources (ACS). Introducing ACS in a petrochemical cluster will require existing processes to be modified or replaced, potentially affecting other chemical processes within the cluster due to existing material and energy interconnections. Therefore, it is important to understand the current level of interconnections, functioning, and performance of the petrochemical cluster before introducing ACS. In this work, a representative cluster model based on the petrochemical cluster of the Port of Rotterdam was developed and considered as a case study. This model was analyzed using complex network analysis and environmental and technical key performance indicators. The selected key performance indicators (KPIs) provide insight into the performance of a petrochemical cluster, while the network properties give an understanding of the exchange of material and energy in an industrial cluster.@en

Due to the heavy dependence on fossil-fuels as raw materials, the defossilization of feedstocks in the petrochemical industry represents a challenge. A large number of possible process routes that use alternative carbon sources (ACS) like CO2, biomass, and waste are being developed for the feedstock replacement. For instance, to produce ethylene, more than 40 ACS process routes were identified. These multiple options make the selection of the promising process route a complex task. By replacing feedstocks, a process can change significantly and the impacts related to these changes in a highly interconnected industrial cluster can create cascading effects due to system interdependencies. This work aims to understand the cascading impacts in carbon flows and prices of implementing an ACS production process in an ethylene cluster. The results show that PVC will be the highest impacted and defossilizing one value-chain can have cascading effect on other value-chains as observed for PET.@en