http://hdl.handle.net/10366/138522 2026-07-20T08:11:50Z http://hdl.handle.net/10366/172113 [EN]The energy transition has created opportunities towards decarbonization. While renewable energies are abundant, they are non programmable resources. Hydrogen can be the bridge between the rewewable energy and the chemical and power industries. However, its difficult transportation calls for its transformation into more handy chemicals such as ammonia or methane as energy carriers. This book presents all the steps from the hydrogen production to its storage in the form of chemicals and their use within a decarbonized and defossilized industry. 2026-05-01T00:00:00Z http://hdl.handle.net/10366/172112 [EN]The decarbonization of energy-intensive industries is essential to achieve global greenhouse gas emission reduction targets. Steel production, responsible for approximately 7% of global CO emissions, requires innovative low-carbon alternatives. One promising option is the use of renewable electricity and green hydrogen in the Direct Reduced Iron (DRI) process. In this study, an integrated energy system to supply renewable electricity and hydrogen to a DRI-based steel plant is analyzed. The proposed network combines two renewable power generation technologies (solar photovoltaic and onshore wind) with three complementary storage solutions (batteries, compressed hydrogen, and Liquid Organic Hydrogen Carriers (LOHCs)). A mathematical optimization framework is developed to determine both the optimal sizing and operational strategy of the system. The methodology is applied to the provinces of mainland Spain as a case study. Results highlight the critical role of integrating multiple generation and storage technologies to ensure a continuous supply of electricity and hydrogen. They also reveal a strong dependence on geographical location for design and technology selection, driven by variations in renewable resource availability. The energy cost per ton of steel is estimated at 500–600 €/t. It exceeds five fold current costs but is expected to decline significantly with future technology improvements. Hence, these integrated renewable systems are regarded to be a technically feasible and economically competitive option in the future. Overall, it represents a key enabler for the deep decarbonization of the steel sector. 2026-06-01T00:00:00Z http://hdl.handle.net/10366/172110 [EN]Energy storage is a critical component in the transition to a renewable based energy system. To face this challenge, Power-to-X technologies are gaining increased attention. This study investigates the conversion of surplus electricity from wind and solar sources into hydrogen, and subsequently into methane, utilizing existing natural gas infrastructure for efficient storage, transport and conversion into electricity. The process consists of two main stages: first, the production of methane using Power-to-X technologies during periods of excess renewable energy production. Second, the generation of electricity during peak demand, with CO2 captured for reuse in methane synthesis creating a closed carbon loop. This integrated system repurposes combined cycle power plants, developing a Power-to-Methane-to-Power (PtMtP) configuration. Two alternative combustion approaches are evaluated: oxy-combustion (OC), which simplifies CO2 purification and air combustion or ordinary combustion or conventional combustion (CC), which requires more complex purification methods such as amine absorption or pressure swing adsorption (PSA). Results indicate that CC with CO2 capture via amine absorption is the most profitable process, especially when it is assumed that the oxygen produced by the electrolyzer is sold. For a 400 MW CCPP, the electricity production cost ranges from 650 to 750 $/MWh when the income from oxygen sales is neglected. However, if it is assumed that the market can absorb the full output of electrolytic oxygen, the production cost decreases to between 450 and 550 $/MWh. 2026-06-01T00:00:00Z http://hdl.handle.net/10366/172109 [EN]Hydrogen is proposed as a fuel for maritime decarbonization, but its storage is challenging. Liquid Organic Hydrogen Carriers (LOHCs) offer a solution for storing hydrogen under ambient conditions enabling to reuse oil infrastructure. The dehydrogenation module, coupled with a Solid Oxide Fuel Cell, is modeled using a first-principles model. Detailed three-phase reactor modeling accounts for heat, mass and momentum and represents relevant phenomena in LOHCs reactors. Two different stages are set: process design and operation. In the first stage, unit design parameters and operating conditions are considered and several objectives are proposed. Additionally, several reaction technologies are suggested (mixed-integer formulation). With equipment defined, operation is optimized. Expensive high-complexity models hinder optimization. Hence, Machine Learning algorithms and specifically Bayesian Optimization (BO) can be leveraged for LOHCs optimization. Process design involves the optimization of a mixed-integer, single (SO) and multiobjective (MO) constrained formulation. Then, SO and MO constrained optimization are carried out for operation. To handle integers, adapted kernels and multiple acquisition function optimizers are used. These strategies perform comparably or better than approaches ignoring integers. Then, these are encouraged for an effective mixed-integer optimization. Design stage reached a trade-off with 1990 $/kW and 5.95 l/kW equipment investment and volume respectively and 37.49% efficiency. Detailed reactor models differ significantly from simplified baselines showing the need to accurately represent these units. Then, operation MO was carried out. Pareto Front was built with several operational points. Thus, the use of LOHCs for hydrogen storage in maritime sector is explored and promoted. 2026-04-01T00:00:00Z http://hdl.handle.net/10366/172108 [EN]The reduction of CO2 emissions is crucial for controlling global warming. Within the carbon capture, utilization, and storage (CCUS) initiative, chemical production is appealing. Methane stands out due to its extended use and compatibility with the current natural gas infrastructure. Since CO2 emissions are highly distributed, a scale analysis of e-methane production is essential. This work presents a scale study of carbon capture and hydrogenation to produce methane. Three technologies for carbon capture (absorption, adsorption, and membrane separation) and two reactor designs (isothermal multitubular, and adiabatic multibed) are analyzed and three different scenarios are proposed: continuous, semi-modular, and modular. Module units are based on a 1.3 MW electrolyzer housed in a sea container. Adsorption is the most profitable carbon capture technology. The optimal operational scenario varies with the amount of CO2 treated. Prices for methane produced range from 40 to 60 $/million BTU for continuous scenario, from 40 to 55 $/million BTU for semi-modular scenario and from 50 to 70 $/million BTU for modular scenario. Although the prices are not competitive, they can be reduced considering the carbon credits and, in addition, these processes prevent CO2 emissions into the atmosphere and ensure methane availability for energy storage or as an energy carrier system. 2025-06-01T00:00:00Z http://hdl.handle.net/10366/172107 [EN]The reduction of GHG emissions is clearly bounded to an increase in the use of renewable resources. Hence, the use of energy carriers such as hydrogen seems crucial to reduce the fluctuations in the power generation. However, the physico-chemical properties of hydrogen hinder its transportation and storage. Alternatives such as LOHCs are regarded as a promising option to improve them. The selection among the available LOHCs systems and the process optimization are some of the key points to enhance the deployment of this storage technology. In this work, a systematic two-step design methodology is proposed. First, a prescreening stage is developed to select the best LOHCs candidates considering the economy, safety and environmental of hydrogenation and dehydrogenation processes. In a second step, the optimization of the most promising LOHCs systems from the first stage is carried out. N-ethylcarbazole and indoles mixture systems resulted to be the most promising options from the first stage of the methodology to be used for hydrogen storage. Hence, both processes are optimized. Surrogate models are developed to represent the hydrogenation and dehydrogenation reactors. Although trickle bed and slurry reactor designs were considered for both tasks, the optimization results suggest the use of slurry reactors over trickle beds due to better catalyst use. However, the trickle bed technology presents numerous advantages and it cannot be discarded yet for LOHCs applications. The hydrogen storage costs ranged between 1.30–2.34 $/kg H2 for different plant capacities. The dehydrogenation stage, and specifically the dehydrogenation reactors and the heating agent used, resulted to have a major impact on it. Thus, this methodology allows to identify the most promising LOHCs options and to design its process, analyzing the challenges for its deployment. 2025-06-01T00:00:00Z http://hdl.handle.net/10366/169667 [EN]This work presents a two-stage optimization procedure for the conceptual design and operation of A-frame dry cooling systems for concentrated solar power facilities. First, the optimal geometry of the A-frame including sizing, number of fans and blade geometry, and unit parameters such as pipe length, configuration and number is determined. Finally, the operation of the system over a year for minimum energy consumption is computed. The geometry problem is formulated as a mixed-integer non linear programming (MINLP) problem. A tailor-made branch and bound algorithm is used to solve the complex non-linear programming sub-problems. The second problem consists of a multi-period MINLP. A fixed geometry is used to evaluate the usage of fans over time. The solution suggests an apex angle of 63°, one row of 75 pipes of 13.5 m long with a diameter of 3.3 mm, and 4 fans are used but they only operate at full capacity during summer. This design allows reducing the energy required by 20% by using the appropriate pipe configuration and number. The unit consumes around 4% of the energy produced by the CSP plant that serves. It is a promising result that can be affected by plant layout and ground availability. 2018-01-01T00:00:00Z http://hdl.handle.net/10366/168230 [EN]The operation performance of air-coolers in concentrated solar power plants decays due to particulate deposition on heat transfer surfaces. The deposition process can be seen as a stochastic phenomenon. A modelling approach is proposed to capture the uncertainty and the effect of extreme events, such as sandstorms, affecting the performance of plants located in dry places through dust or sand deposition on the air coolers. A case study of a concentrated solar power plant located in Dubai is analysed. Sandstorms generate acute and drastic fouling of the air coolers, and this is modelled as a stochastic process using historical aerosol dispersion data. Ten scenarios are generated by sampling the probability distribution of sandstorms occurrence and intensity. The optimal operation (cleaning schedule and airflow profiles) of the air coolers is established using Benders decomposition to solve the resulting large-scale mixed integer non-linear programming problem. The results of the stochastic scenarios demonstrate that substantial savings of $ 0.6 M − $ 2.7 M per year are achieved by the optimal operation. Cost is minimized by a combined reactive and proactive cleaning policy which accounts for the frequency, intensity and seasonal variability of sandstorms, in addition to the variability on local radiation and weather conditions. 2020-01-01T00:00:00Z http://hdl.handle.net/10366/168228 [EN]This work presents a parametric programming framework for the optimal design and operation of systems with performance loss over time. A two-stage procedure is proposed. The unit is designed for the operating conditions just before maintenance. In a second stage, a multiperiod problem is solved for the optimal the operation of the unit over time including cleaning costs. The minimum operating cost as a function of the cycle length determines the operating cycle and the unit design. The methodology is applied to A-frame cooling systems under fouling conditions, where fouling affects the pressure drop and the global heat transfer coefficient. The sigmoidal deposition profile results in an optimal cycle time of 8 years. This design allows reducing the energy required to around 4% of the energy produced by the concentrated solar power plant. It is a promising result that can be affected by plant layout and ground availability. 2019-01-01T00:00:00Z http://hdl.handle.net/10366/163046 [EN] This work presents the development of a reduced order compartment model for a counter-current spray dryer. The compartment model is formulated using adaptable compartments and introducing the use of correlations based on dimensionless groups. These correlations can capture the mean residence time they but are unable to reproduce the variance of the entire residence time distribution (RTD). Limitations are also observed in the evaluation of internal fluxes. The application of these correlations to a specific zone requires the inclusion the geometrical modifications in any part of the unit. A small internal modification in one geometry not only modifies a zone, but also influences the remaining regions so that the zones cannot be independently scaled-up. The methodology is complemented with an analysis of the RTD showing that most of the dispersion generated takes place in the bottom cone. 2022-01-19T00:00:00Z http://hdl.handle.net/10366/163043 [EN]We optimized the operation of the process thatreforms biogas with CO 2 and/or steam for the production ofmethanol using a mathematical optimization approach. Theraw biogas is cleaned up before reforming. Part of the biogas isused to provide energy for the process. Next, the unreactedhydrocarbons and CO 2 are removed. Subsequently, syngascomposition may be adjusted, using either water gas shiftreaction or membrane-pressure swift adsorption. Finally,methanol is synthesized. The process is modeled using massand energy balances, chemical and phase equilibria, and rulesof thumb. The problem is formulated as an NLP problem with simultaneous heat integration for the optimal biogas compositionand methanol production. Two objective functions are considered: a simplified production cost and an environmental onedeveloped based on carbon footprint. Biogas is expected to have around 50−52% of CH 4 and 45−47% of CO 2 , depending on theobjective function. The production cost of methanol is $1.75/gal, for a plant size that uses 10% of the potential biogas to beproduced in Madrid, Spain, with an investment of $46 MM. 2016-05-18T00:00:00Z http://hdl.handle.net/10366/162154 [EN] Methanol and ammonia emerge as two of the most important energy carriers in a new decarbonized society. In this work, a systematic assessment of the power generation based on these chemicals is performed using two different alternatives: direct utilization as green fuels in fuel cells or as carriers for hydrogen. Despite the need for a previous stage for hydrogen production, the use of these chemicals as hydrogen carriers demonstrates higher efficiencies (around 40%), mainly due to the higher degree of maturity of the hydrogen fuel cells. This is reflected in the cost of electricity for the different alternatives with around 700 €/MWh for hydrogen carrier options and about 1200 €/MWh for the direct utilization as green fuels. Compared to hydrogen, the use of methanol or ammonia has a higher electricity production cost. However, future improvements in the efficiency of fuel cell units could convert these fuels is competitive options. In addition, for different scenarios combining transportation and power generation, methanol and ammonia emerge as technically and economically feasible alternatives, especially for distances over 3000 km. Consequently, both hold a pivotal role in addressing the challenges associated with hydrogen within a future energy systems characterized by high renewable penetration. 2024-11-01T00:00:00Z http://hdl.handle.net/10366/162151 [EN] Methanol is one of the most important chemical compounds, as it is the basis for producing a wide variety of derivatives. Its production through fossil sources such as natural gas in countries like Mexico is not entirely viable due to the fluctuations in the availability of this resource. The use of renewable sources to produce methanol represents an interesting area of opportunity to reduce the dependence on a single raw material. This work proposes the design of the methanol supply chain in Mexico using residual materials, finding a solution with the best compromise between profit, social impact, and CO2 emissions. The solution with the best compromise corresponds to a profit of 7,334,100 USD/y, a marginalization index of 2592.536 and CO2 emissions of -0.021 Mt/y. This solution has 8 different types of raw materials, 18 process plants and the use of three processing technologies: gasification, anaerobic digestion, and catalysis from CO2. 2024-09-01T00:00:00Z http://hdl.handle.net/10366/162148 [EN] The defossilization of household heating systems is one of the paramount goals of renewable energy, where pellets are regarded as a promising option. A multiscale techno-economic analysis is performed to determine first the raw material yield to pellets as well as estimating CAPEX and OPEX as a function of the biomass processed. Next, the location of the facilities is evaluated in the agricultural counties of Castilla y León through the formulation of an MILP facility location problem, including economic, social, and environmental objectives. The lignocellulosic materials considered are pinewood, eucalyptus wood, corn stover, and switchgrass. For substituting the natural gas-powered boilers in towns with over 500 inhabitants, 860,000 t/yr of pellets will be necessary. 98.1% substitution is achieved deploying 13 pellet plants, 11 based on pinewood and 2 on corn stover, representing 26.4% of the resources available and it is necessary to invest 164.8 M€ with an annual profitability of 133.0 M€. The emissions substituting these boilers are reduced by 94.8%. Switchgrass is studied separately as it is not currently grown in Castilla y León, although, its introduction would decrease the OPEX from 127.5 €/t to 63.9 €/t while the social and environmental impact is adversely affected. 2024-07-01T00:00:00Z http://hdl.handle.net/10366/162145 [EN] Renewable ammonia can be the path to decarbonization of food, chemicals, and the transport system. While lately, electrochemical hydrogen and air separation are gaining support, biomass-based ammonia can provide an alternative to contribute to green ammonia deployment with possible synergic with the current ammonia facilities. Different processing paths have been considered, depending on the wet content of the biomass. Wet biomass yield to ammonia is low, but it is more interesting as a waste management procedure. Biomass gasification has attracted most of the attention and results in promising ammonia production prices using technologies already in the toolbox of the process industry. The combination of ammonia and urea production solves one of the most significant challenges in biomass-based ammonia, the released CO2. These integrated facilities allow for the full utilization of biomass in the green chemical industry. 2024-06-01T00:00:00Z http://hdl.handle.net/10366/162121 [EN] This work introduces a compartment model based on a discreteelement method (DEM) model. The DEM model determines the residence times(RTs) of particles in the active (in contact with air) and passive zones. Theextracted RT is combined with the heat and mass transfer models into acompartment model, where particles are modeled by employing a populationbalance. Heat and mass transfer models contain efficiency coefficients that aremodeled with surrogates generated from a reduced set of experiments. Theresulting surrogate models are validated with additional experiments in anindustrial facility. It accurately reproduces the heat and mass transfer in the dryer(±10% of relative error in temperature prediction) and provides a guess of thedistribution of the properties of the particles (e.g., moisture content andtemperature) across particle sizes and locations within the dryer. 2024-03-01T00:00:00Z