September: María Isabel Roldán Serrano (DLR)
María Isabel Roldán Serrano is a project manager at the Institute for Low CO2 Industrial Processes at the German Aerospace Center. She completed her PhD at the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT-PSA) in the field of design of high-temperature solar reactors using CFD simulations. She then worked as a Senior Simulation Engineer for Robert Bosch Automotive Steering GmbH and moved to the German Aerospace Center as a project manager in 2020. We spoke to Mabel about her research and her motivation.
Interview:
What are you currently working on?
María Isabel Roldán Serrano: Currently, I am involved as subproject leader within the framework of the European project "SINNOGENES” in the analysis and integration of an optimal decarbonisation concept in sea-buckthorn processing plants. For that purpose, our team develops an optimisation tool that couples design and operation to select the most appropriate configuration for the decarbonisation of the selected industrial process by integrating renewable sources, energy-conversion components and storage systems. In the project, 6 demonstration plants for the integration of storage systems in different environments and energy demands are planned and I am coordinating the activities related to the demonstration plant in Herzberg, Brandenburg, for decarbonizing the production facility of the company Sanddorn GmbH.
Additionally, I lead the internal project “Coal Phase out Atlas” in which different DLR Institutes work together for the techno-economic and environmental evaluation of the conversion of existing coal power plants worldwide into thermal storage power plants.
What is your personal motivation?
María Isabel Roldán Serrano: Since I finished my degree in Chemical Engineering, my main motivation has been the development of sustainable and environmental-friendly industrial processes to offer a small contribution in the energy transition towards a model based on renewable sources. My further academic education and professional experiences have been focused on that aim.
What kind of challenges are you facing in the near future?
María Isabel Roldán Serrano: The selection of an optimal decarbonization concept needs to be focused on the minimization of the investment and operational costs as well as on the CO2 emission reduction. The techno-economic and environmental analysis of new concepts is an important aspect to be included in each study. Therefore, I am implementing a new tool developed within the framework of a collaboration between different DLR institutes in order to integrate the economic analysis to the process design.
Additionally, I am starting national and international collaborations for the development of new project ideas based on the application and improvement of the methodologies and tools developed in our group that allow the selection of optimal decarbonization concepts for industrial processes.
If you could make a wish for something for your research, what would you wish for?
María Isabel Roldán Serrano: The decarbonization of industrial processes and electricity generation require raising the awareness of regional communities for the capabilities offered from local renewable sources. For that purpose, it is important to promote financial instruments for small and medium-size companies that allow their collaboration with research institutes as well as the development and integration of demonstration plants. In this way, new technologies can be applied and their business case tested.
Where do you see your discipline in 5-10 years?
María Isabel Roldán Serrano: For the achievement of the European goal of climate neutrality by 2050, the decarbonization of industrial processes and electricity generation are key activities, since the industry sector accounts for about 20 % of GHG emissions in Germany. Therefore, the development of efficient methodologies that aim the selection of optimal decarbonization concepts according to the location of the industrial site with waste heat recovering are going to gain importance. These methodologies need to include different modelling levels and adapted optimization algorithms that allow a detailed analysis of several configurations minimizing the computational time.
Additionally, since these concepts are based on the integration of different renewable sources, energy-conversion components and storage technologies, an adapted smart control for a short-term time horizon is required. For that purpose, the development of AI models trained with real-time data are an important requirement to optimize the system operation and minimize the process energy demand. Therefore, in general, advanced modelling methods will reduce time and costs to achieve an industrial-process decarbonization.
ORCID: 0000-0002-0663-6048