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The efficiency of many processes strongly depends on their thermodynamic reversibility, i.e., proximity to equilibrium throughout the process. In thermochemical cycles for water and/or carbon dioxide splitting, thermochemical air separation, and thermochemical energy storage, operating near equilibrium means that the oxygen chemical potential of the solid and gas phases must not differ significantly. We show that approaching this ideal is possible in thermal reduction only if the reaction step occurs at a specific, reaction coordinate- and material-dependent temperature. The resulting thermal reduction temperature profile also depends on the ratio of gas and solid flows.

Photoelectrochemical (PEC) and solar thermochemical (STCH) water-splitting represent two promising pathways for direct solar hydrogen generation. PEC water-splitting integrates multiple functional materials and utilizes energetic electrons and holes generated from sunlight to produce hydrogen and oxygen in two half-reactions, while STCH water-splitting couples a series of consecutive chemical reactions and uses absorbed heat from sunlight to generate hydrogen and oxygen in two full reactions. In this Focus Review, the basic operating principles, sunlight utilization, device architecture, reactor design, instantaneous and annually averaged solar-to-hydrogen (STH) conversion efficiency, and the operating conditions and constraints of both pathways are compared. A side-by-side comparison addresses some common sources of confusion and misinterpretation, especially in the evaluation of STH conversion efficiencies, and reveals distinct features and challenges in both PEC and STCH technologies. This Focus Review also addresses materials and device challenges in PEC and STCH for cost-competitive hydrogen generation.

Presentation of the results of a study conducted in the Gipuzkoa region (north of Spain) in which the socioeconomic factors of 23 municipalities were analysed in order to see which was their impact on the waste generation and on the food waste patterns. This presentation was given in the Waste Management Europe conference in Bergamo (Italy) on June 21st 2022.

Los sistemas Business Intelligence (BI) permiten el acceso y el analisis de la informacion para mejorar y optimizar los procesos de toma de decision tanto en agilidad como en rendimiento de sus resultados. En el presente articulo se presenta el proceso de implantacion de un BI para la Revista DYNA. Dicha implantacion responde al interes de la revista de aumentar su factor de impacto (IF o Impact Factor) en las principales listas de impacto de revistas cientificas. La herramienta desarrollada permite la identificacion de areas, campos, autores, revisores, etc. prioritarios y favorece el apoyo de la toma de decisiones a la hora de aceptar o rechazar trabajos, estimar el impacto que pueden llegar a tener los mismos, apostar por tematicas, etc. Palabras clave: Business Intelligence, Inteligencia de Negocio, Cienciametria, Mejora del factor de impacto

Solar thermal-driven thermochemical H2O and CO2 splitting offers a carbon-neutral path to produce feedstocks for synthetic fuel production such as hydrogen or synthesis gas. This paper assesses research outcomes for perovskite materials in two-step thermochemical cycles. Experimental, computational and thermodynamic studies are summarized and critically discussed, identifying key attributes for future research. In addition to the critical review, a fast method for the classification of effective thermochemical properties (oxygen vacancy formation enthalpy and entropy) in a wide range of operational temperatures is provided. These properties together with a high-grade of sintering resistance and fast kinetics are the main characteristics required to maximize the solar-to-fuel efficiency of the process. The discovery of optimum material compositions for this application could be effectively achieved by a combination of machine learning, DFT, experimental testing and system modelling, and will require an extensive international research effort. If successful, this could lead to the ultimate development and practical application of thermochemical cycles for fuel production.

To achieve further substantial reductions in the cost of concentrating solar-thermal power systems, recent efforts have been directed towards changing the working fluid in the receiver, adopting new approaches to thermal energy storage, and incorporating higher-efficiency power cycles. In this study, we present a novel CSP system configuration under development in ASTRI research program in Australia, incorporating a tubular sodium receiver, a high-temperature phase-change material storage unit, and a supercritical CO2 power block. The model is implemented using the SolarTherm framework in the Modelica language, and simulated using Dymola software. The novel system was compared to a ‘reference’ system with a molten salt receiver, two-tank storage, and subcritical steam Rankine cycle. For verification, the reference system was also modelled using the System Advisor Model software, and differences of 1% in annual receiver output and 2% in net electrical output were achieved when comparing Modelica and SAM simulations, despite difference operating strategies and time resolution. The results of the analysis of the novel system showed an improvement of annual solar-to-electricity efficiency to 19.6%, up from 15.6% for the reference system. This was achieved as a result of higher power cycle efficiency, despite the reduction in optical and receiver efficiencies resulting from the higher working fluid temperature. The ASTRI system was economically optimised for financial performance using 2012 as the basis year, and reached a minimum levelised cost of electricity of 11.42 ¢AUD/kWh for a solar multiple of 2.2 and storage capacity of 8–9 h at the location of Alice Springs, Australia.

Scholars, managers, and policy makers are increasingly interested in the potential of servitization to enhance the innovation capabilities for manufacturing companies, among others. Collaboration within the supply chain appears to play a relevant role in the transition to service provision because of its relational character. Combining these elements in the same model, this study sheds light on the relationship between innovation capabilities and integration levels, both internally and externally with customers and suppliers, considering the level of servitization in different firms. Using partial least squares structural equation modeling (PLS-SEM) on a sample of Basque manufacturing companies, this study reveals significant differences between manufacturing companies with low- and high-level services regarding the impact of customer integration on product innovation capability. The same result was not found for other supply chain dimensions—internal and supplier integration. These findings can be related to the prominent role of customer relationships and contacts in developing innovation capabilities in manufacturers’ services considered by some previous research. In addition, by analysing the different dimensions of supply chain integration separately, internal integration was found to be an enabler of external integration.

We present, for the first time, a dynamic model of a 1-MWth thermochemical syngas production plant based on non-stoichiometric CeO 2 . This work aims to provide a simulation tool to assess plant performance under realistic solar conditions. We propose a route to produce a continuous syngas flow rate without requiring syngas storage, an optimisation method to achieve maximum solar-to-fuel efficiency, and a control strategy to maintain plant operation at optimal conditions. An extensive evaluation of the effect of dynamic and off-design performance on plant operation is also discussed for both discontinuous and continuous production of syngas. When a heat-recovery strategy is implemented, a maximum efficiency of 9.24–9.03% in Geraldton (WA) can be obtained, respectively. The thermochemical syngas production plant was also evaluated at another nine locations in Australia. The maximum solar-to-fuel efficiency of 9.68% was obtained in Alice Springs (NT), while in Melbourne (VIC) was 6.14%. These results demonstrate that previous steady-state calculations overestimated the values of the solar-to-fuel efficiency. This is due to an inability to accommodate the effect of essential variables such as: plant size and location, variation of the direct normal irradiance, heliostat field operation, and thermal inertia in solids, gases, reactors and storage tanks. Ultimately, this work demonstrates the need for the development of dynamic and off-design models to evaluate more accurately the potential of solar-driven fuel-production processes.

Digitalisation, servitisation, and sustainability are keywords for the current and future development of the manufacturing industry. However, their interaction in the context of an organisation and its supply chain is unclear. This study examines how digital product–service innovation (PSI) or digital servitisation affects sustainability, considering the triple bottom line perspective, as well as identifies the underlying causes. Moreover, this study analyses the role played by supply-chain strategic collaboration, both internal and external to the company, in digital PSI and sustainability. Using a multiple-case study methodology and B2B market perspective, four companies belonging to the capital goods industry were analysed. Our findings indicate that digitalisation is leveraging both basic and advanced services in their impact on economic and environmental sustainability dimensions, while the results are limited in social sustainability. In addition, supply-chain integration is relevant for digital PSI. Internal integration is required for both basic and advanced services, while external integration is especially important in advanced services. We conclude by emphasising that companies should acquire digital capabilities to develop defensive and offensive business strategies that ultimately affect sustainability.

In recent times, new learning methodologies known as student-based methodologies have been introduced to simplify the learning process for the students and facilitate the acquisition of skills for them. Among them, problem based learning (PBL) and project-based learning (PjBL) are widely used methods in the world of education. Real case solving (RCS) is a variant of the PBL where students solve real cases through the application of the PBL methodology. RCS seems to be a relevant approach for educators, but it has an apparently limited implementation degree at the academic level. This article presents the successful implementation of four different RCS approaches in the lecturing process in five different classes in the engineering degree of University of Deusto. The initiative has been analyzed both quantitative and qualitatively, the overall performance and success rate of the students were compared with the ones acquired from conventional teaching methods. The results were found to be promising, demonstrating a significantly better performance than the traditional teaching methodologies. The successful results encouraged the university to continue working further in this direction.

In order to reduce the energy cost while improving the process operation, a study which aims to analyze the influence of the operational parameters variations and determine the optimal operating conditions of a pilot multi-effect desalination system (MED) at CIEMAT-Plataforma Solar de Almeriia (PSA) has been performed. An equation-based object-oriented mathematical model of the experimental MED plant, implemented using the modeling language Modelica and previously developed, calibrated and validated, has been adapted to carry out this study. Firstly, an energetic and exergetic analysis of the process under nominal conditions has been carried out, revealing the key sources of energy and exergy consumption. On the one hand, the thermal energy contained in the mass outflows are the main responsible source of the high energy consumption, on the other hand the entropy generation and the heat exchanged with the environment are the responsible of the exergy degradation. Secondly, a study on the influence of the operational parameters shows that the production of the real plant under nominal conditions is far from the maximum simulated values and some operational parameters have not a great influence in the process with respect to the rest. Finally, using a genetic optimization algorithm implemented in the modeling tool, a optimization process taking into account different energy and exergy performance criteria, sets optimal operational set points.

In this paper, we present a new method to determine the optimal design conditions of a supercritical CO2 recompression Brayton cycle with dry cooling based on plant location. These power cycles are gathering high interest in concentrated solar thermal power technologies, which are most likely to be deployed in arid areas where dry cooling is a strategic choice. However, the usual high ambient temperature associated with these locations affects negatively the cycle performance. The key selection of two design parameters, the recompression fraction and the compressor inlet temperature, can minimise this negative effect. The method presented here allows the adjustment of these two parameters maximising the annual generation of electricity and cycle efficiency simultaneously. The optimisation process analyses the drop in the cycle performance due to the yearly variation of ambient temperature at the specific location. To reduce the computational effort required, polynomial regressions extrapolate the results from a reduced set of design-point and off-design cycle simulations in a wide range of ambient and compressor inlet temperatures. As an example, the method is applied to three different locations demonstrating the existence of optimal design conditions and justifying the need to adjust these two key parameters for each specific location.

Concentrating solar thermal power plants rely in thermal energy storage systems in order to provide a stable power supply. However, they might not been able to meet power plant demands, mainly because of their storage sizes which are restricted due to economic reasons. One way of mitigating this effect is to control in an optimal way the charging and discharging processes. For the design and validation of advanced control strategies, an accurate dynamic model is essential. For this reason, a dynamic thermal energy tank model intended to be used in concentrating solar thermal power plant models is presented in this paper. The developed tank model is validated in charging and discharging processes and also at rest state in order to validate thermal losses dynamics. Simulation results are compared against experimental data from the CIEMAT-PSA molten salt testing facility.

Many commercial solar thermal power plants rely on indirect thermal storage systems in order to provide a stable and reliable power supply, where the working fluid is commonly thermal oil and the storage fluid is molten salt. The thermal oil - molten salt heat exchanger control strategies, to charge and discharge the thermal storage system, strongly affect the performance of the whole plant. Shell-and-tube heat exchangers are the most common type of heat exchangers used in these facilities. With the aim of developing advanced control strategies accurate and fast dynamic models of shell-and-tube heat exchangers are essential. For this reason, several shell-and-tube heat exchanger models with different degrees of complexity have been studied, analyzed and validated against experimental data from the CIEMAT-PSA molten salt test loop for thermal energy systems facility. Simulation results are compared in steady-state as well as transient predictions in order to determine the required complexity of the model to yield accurate results.

Big Data Analytics (BDA) has the potential to improve demand forecasting, communications and better manage supply chain resources. Despite such recognised benefits and the increase of BDA research,...

La denominada Industria 4.0 o cuarta revolucion industrial promueve, entre otros, el uso de los sistemas de inteligencia de negocio o Business Intelligence (BI) para el manejo de grandes cantidades de datos provenientes de entornos Big Data. Los sistemas BI contemplan tanto aplicaciones, infraestructura y herramientas, como las mejores practicas que permiten el acceso y el analisis de la informacion para mejorar y optimizar los procesos de toma de decision tanto en agilidad como en rendimiento de sus resultados. El presente articulo presenta un caso de implantacion de un sistema BI en un entorno industrial alimentario con caracteristicas Big Data en la que se combinan informaciones de diversas fuentes para ofrecer informacion que mejore la toma de decisiones de los mandos. La conclusion de esta implantacion es que el proceso de integracion de informaciones de diversas fuentes (Data Integration - DI) mediante herramientas BI permite una toma de decisiones ademas de intuitiva, mucho mas fundamentada y agil que favorece la mejora de los resultados empresariales.

In this work, a study of the effect of the plant location in the hydrogen production plant based on ceria thermochemical cycle is presented. This study consists of the analysis of the annual performance of a 1 MWth continuous hydrogen production plant in ten locations along Australia. The analysis was performed by using the model developed by the same authors and presented in SolarPACES 2017 [1]. Overall, the results showed that locating a plant in a sunny area can increase the solar-to-fuel efficiency in around 4% within the locations under investigation. Oppositely to previous works, this work demonstrates that the optical losses together with the annual DNI distribution play the most critical role into obtaining the highest possible efficiency in a solar driven hydrogen production plant.

The solar reforming of methane can reduce the fossil fuel consumption in the mining industry. To study how the variability of the solar resource impacts on the reforming process and how to minimize this impact on the mineral process, a dynamic model of a solar reforming plant is presented. This work aims to provide a simulation tool to assess plant performance under realistic solar conditions. A plant design with syngas storage has been developed and tested. The work ends with the study of the effect of the size of the solar field and the storage capacity on annual simulations for a specific scenario.

This paper presents a new dynamic model to study the transient thermochemical behavior of a double-effect absorption heat pump (DEAHP). It has been designed according to the experience with an experimental DEAHP totally integrated into a solar-assisted multi-effect distillation (MED) plant set up at CIEMAT – Plataforma Solar de Almeria (PSA). The non-linear first-principles model was implemented using the equation-based object-oriented Modelica modeling language and is based on a mathematical formulation that describes the main heat and mass transfer phenomena in this kind of facilities. A modular and hierarchical modeling methodology has allowed a graphical modeling development. Submodels that wrap the different physical phenomena are interconnected between them, thus making a three level deep hierarchy. All the submodels have been calibrated and validated with experimental data. The numerical predictions show a good agreement with measured data.

A large part of the scientific community efforts is focused on improving efficiency and reducing costs of desalination processes. For that, this work presents a methodology to find optimal operation strategies, based on genetic algorithms and a highly customizable dynamic solar desalination model set, of any system’s configurations according to several criteria. This methodology has been tested in a solar-gas hybrid configuration modeled in this work. Test results show that the methodology can improve the distillate production by 20% with respect to the initial case, when optimization criterion is to maximize production, or can increase the distillate production by 14%, only with 10% increase of the thermal energy from gas boiler consumption, when optimization criteria are to maximize distillate production and minimize thermal energy consumption from gas boiler.

Digital capabilities play a relevant role in servitisation strategy for manufacturing companies. Using logistic regression models with a sample of more than 2000 Spanish manufacturing companies, this paper studies the relationship between digital capabilities and servitisation within Spanish industries. This research considers both manufacturing and connecting digital capabilities, along with, training and software skills. The findings can be used by companies and policy makers to boost servitisation. Advanced manufacturing technologies (AMT) are not found to have a positive or significant impact on servitising, except when combined with the use of digital capabilities for internet-based marketing. Significant space also exists for improvements in staff training in information and communication technologies (ICTs) because of their potential contribution to product-service innovation. Finally, the relationship between firm size and servitisation indicated by previous research is confirmed.

Some companies improve their production performance using manufacturing or operations models. In the last decade these models have come to be known as &ldquo, X&rdquo, production systems (XPS), or company-specific production systems. XPS systems have been oriented mainly to implement lean manufacturing and continuous improvement principles, but have shown little progress in terms of sustainability principles. The emergence of databases (DBs), big data, and business intelligence (BI) systems have enabled the creation of system panels to measure performance and manage business processes. These panels also allow assessment of the implementation of the principles, methods, and tools of the XPS. The effectiveness of these systems requires sufficient IT infrastructure and an acceptable quality of data, but the key performance indicator (KPI) panels of XPSs often lack consistent and acceptable data. In other cases, the IT infrastructure does not cover the needs of the personnel managing the operations, which limits the progress of XPSs. This paper documents the positive experience of one company in jointly auditing and improving data quality and IT infrastructure, which better aligned its XPS with sustainability objectives. It explores, using an empirical case study where the researchers were actively involved, the possibility of complementing the KPI panel system of XPS assessment systems with the principles of sustainability, data quality, and IT infrastructure. The paper describes the development and testing of an assessment tool based on those principles, and offers a number of results that may benefit similar small- and medium-sized companies (SMEs).

This chapter focuses on product customization through modularization, to avoid intense rivalry in mass-production-oriented sectors. Companies achieve cost reductions along with product range broadening to keep up with customer needs and co-create value with the customer. This approach has a big impact on the current business model of the company. The purpose of this chapter is, firstly, to provide a model for supporting managers in the decision-making process to decide when and how to develop this kind of servitization strategy and, secondly, to illustrate its application to a business case in the Spanish bicycle industry.

In this work, we explore for the first time the viability and the annual performance of a solar plant which combines a sodium receiver, phase-change material (PCM) storage and supercritical CO2 (sCO2) power block. The simulation results suggest that the system is thermodynamically and economically viable, reducing the levelized cost of electricity (LCOE) compared with a conventional CST plant based on molten salts. The paper presents a new dynamic model of the novel plant configuration which is used for performing a storage sizing study obtaining the best plant investment.

This paper presents a dynamic model of a solar-assisted multi-effect distillation (MED) plant, carrying on with the previous work “Dynamic modeling and performance of the first cell of a multi-effect distillation plant” (de la Calle et al., 2014). The dynamic model has been designed according to the experience with an experimental solar thermal desalination system erected at CIEMAT-Plataforma Solar de Almeria (PSA). The mathematical formulation based on physical principles describes the main heat and mass transfer phenomena in this kind of facilities. The model was implemented using the equation-based object-oriented Modelica modeling language. Based on a modular and hierarchical modeling, different specific-phenomenon submodels have been developed. They have been interconnected between them, thus making a three level deep hierarchy. All the submodels have been calibrated and validated with experimental data. The numerical predictions show a good agreement with measured data.

This work characterized the research community of supply chain analytics (SCA) with respect to coauthorship, a special kind of collaboration. A characterization of coauthorship in terms of researchers’ countries, institutions and individuals was elaborated, so three different one-mode networks were studied. Besides, the SCA research community is characterized in terms of Supply Chain Management (SCM) research streams. Coau- thorship among researchers working on different streams is also analyzed. Metrics that depict the importance of the network nodes were studied such as degree, betweenness and closeness. This study found out an intense collaboration between USA and countries such as China, India, United Kingdom and Canada. Researchers from Canada and Ireland are better situated (central) in the network, although they have not published a considerable amount of papers. The presence of cliques and the small-world effect were also observed in these networks. In terms of research streams, more research on SCA located at the Strategic Management, Technology-focused and Logistics streams was found. The most common links between research streams are on the one side, Technology-focused with both Strategic Management and Logistics and on the other side Strategic Management with both Logistics and Organizational behavior. SCA researchers are rarely working with a focus on Marketing. This study contributes to the SCA literature by identifying the most central actors in this area and by characterizing the area in terms of SCM research streams. This study may contribute to the development of more focused research incentive pro- grams and collaborations.

Annual performance simulations provide a valuable tool for analysing the viability and overall impact of different concentrating solar power (CSP) component and system designs. However, existing tools work best with conventional systems and are difficult or impossible to adapt when novel components, configurations and operating strategies are of interest. SolarTherm is a new open source simulation tool that fulfils this need for the solar community. It includes a simulation framework and a library of flexible CSP components and control strategies that can be adapted or replaced with new designs to meet the special needs of end users. This paper provides an introduction to SolarTherm and a comparison of models for an energy-based trough system and a physical tower system to those in the well-established and widely-used simulator SAM. Differences were found in some components where the inner workings of SAM are undocumented or not well understood, while the other parts show strong agreement. These results help to validate the fundamentals of SolarTherm and demonstrate that, while at an early stage of development, it is already a useful tool for performing annual simulations.

This paper describes a model to simulate the thermal transient behavior of the first cell of a solar-assisted multi-effect distillation (MED) plant. It has been designed according to the experience with an experimental solar thermal desalination system erected at CIEMAT-Plataforma Solar de Almeria (PSA). The non-linear first principles model has been developed using the object-oriented Modelica language. It includes two submodels corresponding to the effect and the preheater of the first cell of the MED plant. Both submodels have been calibrated and validated with experimental data. The numerical predictions show a good agreement with measured data.

The use of Salinity Gradient methodologies to recover part of the osmotic energy in the brine of multi-effect distillation (MED) systems is explored here. Measurements from a membrane-based Pressure Retarded Osmosis laboratory system have been used to estimate the energy that would be recovered from this brine, when a source of low-salinity water is available locally (such as industrial or municipal wastewater). This methodology has been evaluated for a specific case study (72 m3/d solar/gas MED system) at different temperatures.

The performance of a double-effect LiBr–H 2 O absorption heat pump connected to a solar multi-effect desalination plant has been analyzed experimentally. A detailed study of the main operation problems has been carried out in a first experimental campaign with the aim of identifying new control strategies to improve the behavior of the system at stationary nominal conditions, as well as to increase its thermal efficiency. An improved control strategy is proposed to deal with the identified problems and has been validated in a second experimental campaign. Results of these experiments have shown an improvement of the heat pump performance when the refrigerant flows continuously between the low-temperature generator and the condenser. By avoiding intermittent water flow, it is easier to keep LiBr solution levels in both generators constant, gas consumption is lower, it takes less time to reach steady state and a higher average coefficient of performance is reached.

This article describes a temperature control structure designed for the interior of a solar hydrogen reactor based on a two-step ferrite-redox technology. Until now, this temperature has been controlled by manual selection of the heliostats to be focused on the receiver targets. However, the strong system dependency on operating conditions suggests that the procedure be automated in order to ensure the desired setpoint change response. The aims are to maintain the desired temperatures and to make the setpoint switch as fast as possible, keeping plant conditions within the margins of safety. The scheme proposed includes a procedure for selecting the heliostats to be focused on the reactor by using a simple model of the solar field and a gain scheduling control system which changes the control tuning parameters to deal with the varying dynamics observed during the process. Real experiments show the promising results of this work.

The water deficit in the Mediterranean area is a known matter severely affecting agriculture. One way to avoid the aquifers’ exploitation is to supply water to crops by using thermal desalination processes. Moreover, in order to guarantee long-term sustainability, the required thermal energy for the desalination process can be provided by solar energy. This paper shows simulations for a case study in which a solar multi-effect distillation plant produces water for irrigation purposes. Detailed models of the involved systems are the base of a predictive controller to operate the desalination plant and fulfil the water demanded by the crops.

This paper presents a preliminary control scheme for a molten salt – thermal oil heat exchanger. This controller regulates the molten salt mass flow rate to reach and maintain the desired thermal oil temperature at the outlet of the heat exchanger. The controller architecture has been tested using an object-oriented heat exchanger model that has been validated with data from a molten salt testing facility located at CIEMAT-PSA. Different simulations are presented with three different goals: i) to analyze the controller response in the presence of disturbances, ii) to demonstrate the benefits of designing a setpoint generator and iii) to show the controller potential against electricity price variations.

The promising advances in research in two-step solar hydrogen production from water have increased interest in producing hydrogen with this technology. In this framework, the Hydrosol II Project pilot plant for producing continuous solar hydrogen from water using a ferrite-based redox technology was erected at the CIEMAT-Plataforma Solar de Almeria. Two reactors allow the oxidation and reduction steps to be performed in parallel, which, sequentially switched, make hydrogen production quasi-continuous. A dynamic model of a solar hydrogen production plant has been developed based on experience with this pilot plant. As it was designed as a control algorithm test platform, for practical control issues, some simplifications have been assumed to make the model suitable. The new model includes both a solar field model and a processing plant model and is able to simulate the concentrated solar power received by the reactors and the thermal and chemical reactor behavior. The solar field model and plant thermal behavior were calibrated and validated with experimental data. The numerical predictions show good agreement with measurement data.

This article presents the work-in-progress of dynamic modelling works of hydrogen generation in Hydrosol3D project. This project has been based on the results of the Hydrosol II project where a pilot plant at the Plataforma Solar de Almeria (CIEMAT) with the aim of producing continuously hydrogen was set up. The hydrogen is produced from water and concentrated solar radiation, based on a two step cycle process. In this process different chemical reactions occur, with an important dependence of the temperature inside the reactors. Several dynamic models for simulation and control system design are been developed currently and its progress is presented in this work-in-progress article. The mathematical models of the different subsystems are presented and first simulation results are commented.