The manufacturing industry is the second largest emitter of CO2, with the cement industry being one of the main contributors (7-8 % of the global emissions). Carbon capture and utilization (CCU) technologies are promising decarbonization solutions for the cement industry, addressing both fossil fuel-related (40 %) and process-derived emissions (60 %). Within a cement plant, producing synthetic natural gas (SNG) from captured CO2 is particularly suitable, as it is sufficient to fully replace solid fuels in the rotary kiln. On the other hand, the use of zero-carbon fuels, such as green ammonia, is also recognized as a promising approach for decarbonization. In this work, a superstructure was developed to explore alternative routes for producing SNG and green ammonia from CO2 and N2 in cement plant flue gas, respectively. The routes were modelled in Aspen Plus® V14, and their economic viability was assessed. Currently, the most promising route, at a cost of 109 €/tonne of flue gas, involv... [more]

Industrial decarbonization has heightened interest in electrifying major chemical processes, but existing planning methods typically assume fixed electricity prices and overlook how industrial power use affects the grid. This work introduces a grid-aware optimization framework that captures two-way interactions between industrial electricity usage and the power flows within the grid. We use the DC Optimal Power Flow (DC-OPF) model to generate Locational Marginal Prices across refinery demand levels and embed a surrogate reflecting the relationship between the power demand and the prices into an operational optimization problem for a partially electrified refinery. The surrogate model is embedded within the optimization problem using disjunctive reformulations and off-the-shelf packages such as OMLT (Optimization and Machine Learning Toolkit). In a case study considering an oil refinery with installed electric boilers, electrolyzers, H2 storage, and post-combustion carbon capture infras... [more]

Decarbonization of hydrogen-intensive industrial clusters is essential to meet the European Union's net-zero targets. Although hydrogen can replace fossil-based feedstocks and fuels in refineries and chemical industries, its production remains largely dependent on natural gas. Therefore, cost-effective and low-emission supply routes require a system-level approach that integrates regional resources, technologies, and industrial demand. This study applies a multi-objective optimization framework to design a low-carbon hydrogen supply system for Galicia (northwestern Spain), addressing two gaps in regional energy system modeling: model transferability across regions and integration of social criteria beyond techno-economic assessment. The model quantifies trade-offs between total system cost and greenhouse gas emissions, and an employment indicator is integrated via post-processing using TOPSIS. The results show that meeting 100% of the projected 2030 demand (105 kt H2/a) yields a single... [more]

CO2-to-methanol process is an attractive option to simultaneously reducing the anthropogenic CO2 while producing value-added chemicals. In this work, two distinct CO2-to-methanol process routes specifically, single step and dual step are evaluated based on their economic and environmental performance. First, a multiobjective optimization (MOO) framework is formulated to develop the optimal process configurations. Three conflicting objectives including methanol production rate, total annual cost (TAC) and carbon intensity of methanol are considered. For this MOO, the elitist non-dominated sorting genetic algorithm (NSGA-II) is employed to get the Pareto front. From the Pareto front, a balanced compromise solution is identified by the technique for order of preference by similarity to ideal solution (TOPSIS) with entropy information as weighting criteria. Then, the comparative performance analysis is conducted across the Pareto front. At the TOPSIS-selected configuration, the single step... [more]

Achieving net climate neutrality will likely require negative-emission technologies such as Direct Air Capture (DAC). Potassium hydroxide (KOH) absorption is one of the most mature DAC approaches, but it can cause significant emissions due to natural-gas-based thermal regeneration. Electrochemical regeneration methods, such as electrolysis and electrodialysis, have recently been proposed as alternatives, yet their relative performance and environmental impacts remain unclear. We present a comparative cradle-to-gate life cycle assessment (LCA) of three KOH-based DAC configurations: (i) the established Ca-looping thermal regeneration, (ii) the electrolysis regeneration (DAC-ELY), which co-produces hydrogen, and (iii) the electrodialysis regeneration (DAC-ED). The results show that, expectedly, electricity demand dominates life cycle impacts across all configurations. With the current German electricity mix, the established DAC has the lowest overall impacts, while DAC-ELY and DAC-ED exhi... [more]

Power-to-X (PtX) technologies play a central role in renewables-based energy systems by enabling the conversion of renewable electricity into multiple energy carriers. However, due to the multiple energy conversion stages inherent to such energy systems, they often suffer low system efficiencies and high operational costs. In this context, waste product utilization offers significant potential for improving system performance. Directly integrating waste product utilization into energy system operational problems, however, is computationally challenging, as it requires high model granularity to capture waste product characteristics and introduces additional complex constraints.This work proposes a method to integrate waste heat utilization into operational optimization problems, aiming to improve the overall performance of PtX energy systems. Detailed process models, together with pinch analysis, are used to generate surrogate models for the thermal (by-)products and their associated te... [more]

Trinidad and Tobago emits 11.3 metric tonnes of CO2-eq per capita per year, making it one of the highest per capita per year greenhouse gas (GHG) emitters globally. An estimated 87% of these emissions are linked to the industrial sector, including power generation. This study aims to reduce the national environmental impact of the power generation and waste disposal sectors, with the goal of reducing the country's reliance on natural gas and promoting sustainable power generation via waste-to-energy (WTE) pathways. This work seeks to implement a mixed-integer linear programming (MILP) framework, along with techno-economic analysis (TEA) and life-cycle assessment (LCA) to determine potential sustainable objectives with respect to T&T's power system. The study implements supply chain optimisation considering single objective optimisation (SOO) with life-cycle (LC) endpoint externalities included. The key constraint of the system was the production of sufficient electricity to sustain the... [more]

The development of energy technologies with low CO2 emissions is increasingly important for achieving the United Nations Sustainable Development Goals. In this context, power plants based on the Allam-Fetvedt Cycle appear promising because this cycle (introduced in 2012) features inherent CO2 capture. In this context, its association with biogas as fuel enables its application as a Bioenergy with Carbon Capture and Storage (BECCS) system. This study evaluates the technical, energetic, and economic feasibility of an Allam-Fetvedt Cycle power plant fueled by biogas. The methodology is based on detailed process simulations performed using Aspen Plus® v14. Two biogas production scenarios were assessed: Case 1 and Case 2, corresponding to the processing of 8 and 24 million tons of sugarcane per year, respectively. The economic analysis indicated a high capital investment, primarily in the Air Separation Unit (ASU) and the Balance of Plant (BOP). Nevertheless, a significant reduction in the... [more]

The aviation sector is difficult to decarbonize due to limits on aircraft electrification, making sustainable aviation fuel (SAF) a critical near-term solution. This study integrates Aspen-based process modeling with game-theoretic optimization to design a multi-agent SAF production network comprising coal gasification and CO2-assisted natural gas reforming for syngas production, and Fischer-Tropsch (FT) synthesis for SAF production. Techno-economic parameters from Aspen simulations inform an agent-based model in which agents maximize their net present value subject to capacity and demand constraints. Three decision-making frameworks are compared: (i) social welfare optimization, (ii) cooperative bargaining - symmetric (equal bargaining power) and asymmetric (bargaining power weighted by agents' competitiveness outside cooperation), and (iii) competitive equilibria modeled as generalized Nash equilibrium. The results show that social welfare maximization excludes coal and yields the hi... [more]

Biogas offers a promising biogenic carbon source for renewable methanol, but differences in CH4/CO2 ratio across feedstocks and possible upstream CO2 handling can shift syngas stoichiometry away from the methanol synthesis target range. This work quantifies how biogas composition and reformer operation influence the stoichiometric number (SN) and the associated conditioning requirement needed to meet methanol synthesis targets. A steady-state Aspen Plus® model of an integrated biogas-to-methanol process is used as the analysis framework. A base-case operating point is defined, followed by parametric evaluation of biogas CH4/CO2 ratio, reformer temperature, reformer pressure and steam-to-methane (S/C) ratio. The studied CH4/CO2 ratio range covers CO2-rich to CH4-rich cases that may occur across sites and upgrading levels. The resulting SN shifts are tracked and converted into a quantitative correction requirement to maintain the methanol design target (SN = 2.01). Temperature determines... [more]

The unprecedented expansion of Artificial Intelligence is adding increasing electricity demand to Europe's power system. While incumbent plans pursue a net-zero future by 2050, they fail to consider the implications of large-scale AI-based data centres. In this study, a spatially explicit optimisation model is developed to assess how hyperscale data centres may reshape energy infrastructure investment, and emissions trajectories, across different AI demand growth scenarios. The results indicate that, after 2030, AI capacity deployment increasingly shifts toward regions with the ability to expand nuclear and gas-based generation, as firm and flexible power sources are essential for supporting the deployment of high-capacity AI data centres. By 2050, AI-driven electricity demand under high growth scenarios may reach up to 450 TWh, corresponding to 7% of total Europe's demand, with installed AI capacity reaching approximately 85 GW. This additional load leads to an increase of nearly 25 M... [more]

Cost reduction of green ammonia production is critical to advancing the hydrogen-ammonia economy, as ammonia capable of cost-effective storage and transportation is a promising hydrogen carrier and energy carrier to alleviate the intermittency and geographical limitations of renewables. Optimisation and techno-economic assessment based on rigorous model are essential to accurately investigate techno-economic feasibility and fully explore optimisation potential. This work estimates the levelized cost of ammonia (LCOA) of an integrated system including a hydrogen generation process employing Proton Exchange Membrane (PEM) water electrolysis, a nitrogen generation process from flue gas recovery, and an ammonia synthesis process based on Haber-Bosch Process. To enhance the reliability of LCOA, detailed equipment sizing and costing is conducted according to stream data from rigorous modelling in Aspen Plus. A novel optimisation strategy is proposed to enhance the computational robustness by... [more]

The increasing deployment of variable renewable energy (VRE) is essential for achieving a sustainable society; however, its inherent variability poses challenges for maintaining a stable electricity supply. Vehicle-to-grid (V2G) technology enables bidirectional electricity exchange between electric vehicles (EVs) and the power grid and can enhance the utilization of renewable electricity by charging EVs during periods of VRE output curtailment. This study developed a regional V2G system model and evaluated its potential through energy flow simulations and life cycle assessment (LCA). The model explicitly considered hourly operation schedules of individual EVs, the spatial distribution of V2G infrastructure, and minimum output constraints of thermal power generation. The number of EVs is assumed to increase to up to 10, 000 units. In the energy flow simulations, EV charging and discharging were calculated on an hourly basis over one year. LCA was conducted to assess greenhouse gas (GHG)... [more]

Human activities have already transgressed several planetary boundaries, yet energy system models remain largely focused on greenhouse gas mitigation, reflecting their original purpose of addressing climate change. Recent integrations of Planetary boundary-based Life Cycle Assessment into Energy System Optimisation Models show that even cost-optimal low-carbon pathways systematically violate multiple planetary boundaries, indicating that supply-side decarbonisation alone is insufficient for absolute environmental sustainability. At a 2050 horizon, where energy supply is largely decarbonised and technologies are assumed mature, further impact reductions through techno-economic optimisation become limited, positioning final energy demand as a key remaining lever for restoring feasibility under planetary constraints. To address this gap, we ex-tend an Energy System Optimisation framework coupled with a Planetary Boundary framework by explicitly treating final energy demand as a decision v... [more]

European industry accounts for approximately 20% of total European CO2 emissions, with heat demand representing one of the largest energy consumers. Solar thermal collectors offer an efficient renewable alternative to fossil fuels to cover the heat demand. However, due to the temporal mismatch between the solar thermal generation and process heat generation a thermal storage is needed to maximize the renewable utilization. This article presents a novel optimization framework for integrating an ideal heat storage with solar thermal systems in multiperiod heat exchanger network synthesis. We derive an analytical approach to optimize the heat storage by using physical insights from Pinch Analysis: heat can only charge the storage below the lowest pinch point in a given period and discharge above the highest pinch point. We show both how to do it for a storage of infinite size and of finite size, and that the infinite size storage is much more efficient to solve. The approach is validated... [more]

Early-stage system-level assessment of emerging technologies is essential for achieving climate neutrality and a circular economy; however, such assessments are often constrained by the lack of representative life cycle inventory data. In thermal energy systems, performance strongly depends on scale, making direct application of laboratory- or bench-scale experimental data potentially misleading in life cycle assessment (LCA). This study investigates the influence of experimental scale on system-level evaluation using a zeolite-based thermal energy storage (TES) system as a case study.LCAs were conducted using performance data from laboratory-, bench-, and pilot-scale experiments and compared with predicted commercial-scale performance derived from numerical simulations. The TES system stores waste heat via water vapor desorption from zeolite and generates pressurized steam using a moving-bed with indirect heat exchanging system. Heat recovery ratios of 36%, 50%, and 61% were obtained... [more]

Heavy-duty road transport remains a challenging sector to decarbonize, as full electrification of long-distance trucking is currently constrained by limitations in energy density and charging infrastructure. Alternative fuels such as hydrogen, biodiesel, and e-fuels are thus gaining increasing attention. In parallel, the cement industry is a major source of unavoidable, process-related CO2 emissions, offering an opportunity to use captured industrial CO2 as a feedstock for e-fuel production. This study evaluates the production of e-methanol and Fischer-Tropsch (FT) diesel from captured CO2 at an Austrian cement plant as a base case. Several system configurations are analyzed, including different electricity supply options across Europe and the use of biogenic versus fossil CO2. An integrated framework combining process simulation, techno-economic analysis, and life-cycle assessment is applied to compare both fuel pathways. Results show that the climate impact of e-fuels is highly depen... [more]

The rapid expansion of AI data centers is straining electricity grids alarmingly, forcing data center planners to navigate two-pronged challenges: (1) lengthy interconnection queue delays undermining immediate grid access, and (2) volatile electricity prices that spike dramatically during high demand events. This convergence forces planners to reconsider traditional grid-only strategies. While behind-the-meter (BTM) generation offers a solution, existing research lacks comprehensive frameworks for identifying technology portfolios under combined uncertainties of grid access delays and market volatility. This study develops a two-stage stochastic optimization framework with binary capacity constraints co-optimizing data center location and BTM energy portfolios under these challenges. The model evaluates conventional (gas turbines), renewable (solar, wind, batteries), and emerging technologies (hydrogen fuel cells, small modular reactors) across four progressive scenarios spanning emiss... [more]

Recent geopolitical disruptions and extreme weather events have underscored the importance of resilience in global energy supply chains, particularly for import-dependent economies pursuing ambitious energy transition targets. These events have exposed the limitations of supply chain designs focused solely on cost minimization that lack the flexibility and redundancy required for secure operation under stress. As energy systems evolve toward higher shares of variable renewable energy and increased demand uncertainty, episodic manual re-planning becomes inadequate, highlighting the need for modeling frameworks that integrate predictive modeling, optimization, and control to enable intelligent and adaptive supply-chain design and operations under uncertainty. This work presents a comprehensive data-driven modeling and optimization framework for adaptive energy supply-chain networks under evolving demand. The framework integrates three layers: (i) a machine-learning model for demand forec... [more]

The aviation sector represents one of the most pressing challenges in the energy transition due to its strong reliance on energy-dense liquid fuels and established fuel infrastructure. Sustainable Aviation Fuel (SAF), particularly from agricultural residues, offers a near-term mitigation pathway; however, large-scale adoption is shaped by policy mandates, infrastructure expansion, market price formation, and passenger demand responses. These coupled dynamics are difficult to capture using aggregate or equilibrium-based models. This study develops an agent-based model to analyze SAF transition pathways and applies it to India's civil aviation system. Results show that SAF adoption emerges from the coordination between infrastructure entry, cost learning, and market responses rather than mandate ambition alone. Even moderate mandates fall short of intended adoption levels without timely infrastructure expansion, while aggressive mandates become infeasible under binding supply and price c... [more]

"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]

This study aims to compare different pathways for achieving CO2 emission reductions during the production of methanol and, subsequently, formaldehyde, i.e., its major derivative. An equation-oriented model of the formaldehyde sector is developed, incorporating a superstructure of various transition pathways including feedstock switching (biomass, biogas, waste), process electrification (Power-to-X), and CO2 capture. The OSMOSE tool is used to evaluate the superstructure and compare the alternative production pathways on the basis of thermodynamic, environmental, and economic key performance indicators for future scenarios (2025 and 2050). Furthermore, to cope with the limitations of predefined pricing scenarios, a parameter sweep is performed, exploring a broader set of economic conditions and seeking to identify the zones of economic optimality associated with each configuration through the solving of a Mixed-Integer Linear Programming cost minimization problem, while generalizing the... [more]

The transition toward low-carbon ammonia production increasingly relies on highly efficient routes for renewable hydrogen generation, with Solid Oxide Electrolysis (SOE) representing a particularly promising solution. SOEs, operating with steam at elevated temperatures, offer intrinsic thermodynamic advantages and are attractive when integrated with processes that can effectively utilize or supply high-grade heat. This context opens the possibility for advanced energy coupling between hydrogen production and the exothermic ammonia synthesis process. This work investigates such an energy integration strategy by simulating a small-scale ammonia plant where hydrogen is produced through an SOE system thermally coupled to the ammonia synthesis loop. Specifically, high-grade heat available in the Haber-Bosch (HB) reactor outlet is recovered via a "Heat Recovery Steam Generator" (HRSG) to provide a substantial fraction (55 wt%) of the steam required by the electrolyzer. The assessment demonst... [more]

Refineries are major sources of direct CO2 emissions, primarily from steam generation, fluid catalytic cracking, and hydrogen production. This study develops a superstructure optimization framework to evaluate the economic and environmental viability of retrofitting existing refineries with small modular nuclear reactors (SMRs) for cogeneration of heat and electricity. A multi-period mixed-integer quadratically constrained program is formulated, simultaneously minimizing the present cost of retrofitting and CO2 emissions over the time horizon. This problem is solved to generate a Pareto frontier via the e-constraint method. Two cases are analyzed for a medium-scale refinery, considering 1) inflexible operation under average annual electricity prices and 2) flexible operation under hourly prices with the possibility of installation of storage devices. Compared to a benchmark without SMRs in the superstructure, allowing their installation leads to reduced costs at lower or comparable emi... [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]