"Green" hydrogen production via polymer electrolyte membrane (PEM) electrolyzers must overcome significant energy penalties and high costs to become competitive in renewables-based energy systems. Adaptive operating strategies for PEM electrolyzers-by dynamically adjusting current density, pressure, and temperature-have demonstrated efficiency improvements in simple energy systems. However, their effectiveness in the context of complex power-to-X energy systems featuring variable downstream synthesis processes remains unclear. This work shows that integrated optimization of PEM electrolyzer operating parameters in conjunction with downstream methanation processes (MP) delivers substantial system-wide efficiency and cost benefits under dynamic hydrogen demand and pressure conditions. To demonstrate this, an equation-oriented process model of a PEM electrolysis system is embedded within a higher-level energy system model to compare sequential optimization (where the electrolyzer adapts t... [more]

Heat pumps offer the possibility of reducing CO2-emissions in the chemical industry. However, the integration of heat pumps, especially in non-continuous processes, faces several challenges. Energy storage facilitates a way to enhance heat integration by providing a continuous supply of heat flows. By doing so, the question arises as to whether this implementation should be applied to the process or to the utility level. At the process level, there is usually more freedom, as one is not bound by the existing temperature levels of the utility system, which are mostly difficult to retrofit. Therefore, this study presents an approach that generates heat integration concepts at the process level based on two different criteria. These criteria influence which process streams are grouped for a storage implementation and therefore influence the heat integration. The aim is to maintain the heat flows as continuous as possible by integrated heat storages. Finally, the possible heat integration... [more]

The reduction of CO2-emissions in the chemical industry is essential to meet European climate targets. Particularly, the reliance on fossil fuels for process heat supply is a key factor for CO2-emissions. Electrically driven compression heat pumps are a promising option to reduce fossil fuel consumption by upgrading low-temperature waste heat to a higher temperature level, provided that low-carbon electricity is available. However, the integration of heat pumps into chemical utility systems remains a challenge due to economic constraints and the high complexity associated with site-wide heat integration and retrofit of existing structures. This work presents a mixed-integer linear programming (MILP) approach for the optimization of utility systems with integrated heat pumps. To address computational complexity, candidate utility temperature levels are pre-selected, and feasible heat pump coefficients of performance (COP) are precomputed. The framework is applied to both greenfield and... [more]

This study presents the modeling and operation optimization of an adsorption heat storage to improve the supply of renewable heat to a house. The system configuration is an open system with water being carried by an air flow and adsorbed on zeolite 13X beads in a packed bed. A numerical model is developed based on mass and energy balances, using a Langmuir adsorption isotherm and a Linear Driving Force (LDF) mass transfer equation. The model is implemented in Pyomo and solved with the NLP solver IPOPT. A sensitivity analysis on the discretization parameters is performed to choose a good compromise between accuracy and computational time. The chosen model is then validated against experimental data from the literature, with a mean absolute percentage error less than 5%. The dynamic optimization of the operation of the system to satisfy a heat demand is then performed. The trajectory for the inlet fluid velocity is optimized in several heat demand scenarios. The results show that this nu... [more]

Behind-the-meter generation from variable renewable energy is a potential pathway for new data centers to obtain power more quickly and more sustainably than interconnecting to existing electrical grids. Energy storage is needed to accommodate the variability of wind and solar energy across multiple timescales. Hydrogen from electrolysis and ammonia made from this hydrogen can be used as fuel for dispatchable power generation while offering lower $/MWh storage costs than batteries. In this work, we analyze the economics of using hydrogen, and/or ammonia along with batteries in hybrid energy storage systems to enable data centers to be powered by 100% renewables. We perform this analysis using an optimization model for the selection, sizing, and coordinated hourly operation of constituent energy storage technologies toward minimizing the levelized cost of energy (LCOE). The model uses an hourly resolution scheduling horizon of five years to account for hourly, seasonal, and interannual... [more]

Green hydrogen constitutes a strategic energy vector for achieving the Sustainable Development Goals (SDGs 7, 9, 12, and 13) due to its high energy density, flexibility for renewable energy storage, and direct emission-free operation. However, its production critically depends on the supply of high-purity water, which is unsustainable in the context of a projected 40% global water deficit by 2030. Given that more than 97% of available water is saline, integrating desalination processes with electrolysis constitutes an essential strategy for transitioning toward circular economy models in water resource management. This work presents the conceptual design, detailed modeling, and optimization of an integrated process for the sustainable production of green hydrogen from saline water. The system couples a desalination technology (Solar Distillation) with two electrolysis technologies (AEL and SOEC), modeled through physicochemical, electrochemical, and thermodynamic principles. The object... [more]

When designing and planning Green Hydrogen Supply Chains (GHSCs), sustainability considerations are increasingly recognized as essential, particularly in light of decarbonization goals and climate policy targets. Existing research has largely focused on economic and environmental however, social sustainability aspects remain significantly underexplored. This work aims to develop a mathematical programming model to design a GHSC, considering simultaneously economic and social aspects. Solar PV, wind power, and PPA (wind) as energy sources are integrated, while transportation options include the construction of new pipelines, compared to the use of existing highways for trucks carrying liquefied or compressed hydrogen to deliver hydrogen to an oil refinery. The model is applied to a case study conducted in the Brazilian state of Bahia, where different social indicators will be explored, characterizing the case study context while allowing generalization to other contexts. Results allow u... [more]

The ecological transition demands innovative frameworks to reduce industrial resource consumption and environmental impacts. Industrial ecology, particularly through Eco-Industrial Parks (EIPs), provides a promising pathway by enabling exchanges of materials, energy, and water between firms. However, the deployment of EIPs is limited by the lack of standardized industrial profiles and transferable modeling approaches. This study develops a generic framework for representing industrial actors as standardized input-output black-box models, consolidating data on resource consumption, energy demand, by-products, and waste streams. These profiles are structured into a harmonized database to support resource-exchange analysis and scalable optimization across diverse contexts. Complementary mappings of processes and resources, as well as energy and heat demand profiles, enhance the feasibility of identifying synergies such as heat cascading and material reuse. The framework is designed to int... [more]

The increasing popularity of electric vehicles (EVs) leads to an expected rise in the quantity of end-of-life lithium-ion batteries (LIBs) that require efficient management. This paper presents a State Task Network (STN) based optimization model to analyze and optimize the supply chain for LIBs, allowing for the selection of optimal processing routes, facility locations, capacities and reintegration of recovered materials, as well as analyzing the possible trade-offs between different end-of-life management strategies. Based on available data from the literature, the model is demonstrated with the LIB supply chain considering both primary production and different end-of-life strategies for spent LIBs (recycling and reuse). The case study reveals that mechanical pretreatment followed by hydrometallurgical recycling is the optimal pathway and it outperforms the linear supply chain in both costs and emissions. The cost optimal solution opts for more centralized collection and disassembly,... [more]

This document includes the configuration design codes and the data produced from the simulation of Magnetic Inductive Swing Adsorption. Furthermore, the document also consists of the surrogates produced for the optimisation study. This reduces the installation of IDAES/Pyomo/PETSc in a new conda environment.

This document provides supplementary material supporting the Conference Paper “A Multi-Objective Optimisation and Superstructure-Based Decision-Support Tool for Regional Low-Carbon Hydrogen Roadmaps: Methodology and Application to a region of Spain”.

It includes additional methodological details, input data, model assumptions, and extended results that complement the analyses presented in the main manuscript.

Digital supplementary information for the ESCAPE36 conference paper titled: High Performance HPs Using Tailored Refrigerants

SUPPORTING INFORMATION for the work "Particle Swarm Optimization for simultaneous design and optimization of heat pumps considering Mixed Integer problems", submited to ESCAPE 36.

This document provides the Supplementary Material for the study titled: Virtual Plant–Model Pair as a Step Towards Real-Time Optimization of a Simulated Moving Bed System. The work has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

This document contains digital supplementary material for the article “An Extended Superstructure Formulation for Non-Isobaric Flowsheet Synthesis”, submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

Supplementary material for: Generative AI for the optimal design of seawater desalination processes (ESCAPE 36, Sheffield, June 2026)

This document provides digital supplementary material related to the article “Development of a methodology for heat pump-based heat integration in batch processes” which has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

This document compiles the digital supplementary material associated with the article entitled “Optimizing Steam Flux for Energy Efficiency in Ammonia Recovery during Sodium Carbonate Production”, published in the peer-reviewed proceedings of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). It presents the effects of variations in steam pressure and temperature on the system’s temperature and mass flow rate.

This document contains digital supplementary material (assessment of sustainability promotion potential) related to the article entitled “Methodology to assess the integrity of Water and Energy Integration Systems (WEIS) models using the ThermWatt computational tool”, which is part of the peer reviewed conference proceeding of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). The present content has been adapted from the PhD thesis entitled "Simulation and Optimisation of Water and Energy Integration Systems (WEIS): An Innovative Approach for Process Industries".

This document contains digital supplementary material (detailed model description, parameters for different case studies and additional figures) related to the article "Optimization of Site-wide Heat-Integrated Utility Systems with Heat Pumps using MILP" which is submitted to the peer reviewed conference proceeding of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36).

This document contains the supplementary material for the paper titled “A Comparative Analysis of Sequential Active Learning Approaches: Statistical Design of Experiments versus Bayesian Optimisation”, submitted to the ESCAPE36 conference for consideration.

This supplementary material contains tables and figures with the data necessary to replicate the results described in the manuscript.

The source code contains a run_experiments.sh script, which can be used to replicate the results described in the manuscript.

Nitrogen-based fertilisers are pivotal for global food security, yet their production is a notable source of greenhouse gas emissions. Urea, a vital fertiliser with significant market presence—19% in Europe and 33% globally—is produced through an energy-demanding process reliant on fossil fuels. This study introduces a ’Green’ Urea plant concept, aimed for implementation in Ravenna, Italy, harnessing exclusively renewable energy sources to foster agricultural sustainability. With a production capacity of 1,300 tonnes per day, this facility neighbours Italy’s first carbon capture and storage (CCS) facility at Ravenna. The core of the proposed methodology is the synthesis of green ammonia. Seawater Reverse Osmosis-Polymer Electrolyte Membrane Electrolysis (SWRO-PEM) and Pressure Swing Adsorption (PSA) yield the necessary hydrogen and nitrogen feedstocks. An enhanced Haber-Bosch process utilising a Ru-based catalyst, facilitating lower operational conditions (500◦C and 100 bar) for the af... [more]

Algal biomass production, mineralization, and chemical conversion as promising carbon dioxide utilization processes are compared with regard to economic as well as environmental factors. The production of the chemicals methanol, dimethyl ether, and dimethyl carbonate is selected as the most viable alternative among all options. The integrated production of the proposed chemicals is evaluated for a wide range of trade-offs between economic potential and environmental impact by applying multi-objective superstructure optimization. The results indicate that direct hydrogenation of CO2 to methanol with subsequent dehydration to dimethyl ether is on the verge of profitability (including capture cost) while achieving a positive net CO2 consumption of ca. 68% of supplied CO2 when direct and indirect emissions are accounted for; and 85% when only direct emissions are considered.