#Meet the D-HYDROFLEX team: CARTIF

Today our blog series hosts a short interview with CARTIF team.

Welcome all. We are delighted to have you with us. CARTIF is the D-HYDROFLEX partner who is responsible for the algorithms’ development, predictive maintenance testing, energy production forecasting and hybridization via VPP.

Cr. P. S.: Thank you for inviting us.

Before getting into deeper discussion, would you like to first introduce yourselves to our readers?

Cr.: Yes, of course. My name is Cristina Vega, and I am a researcher at CARTIF, a technology center in Valladolid, Spain. I work as a project manager, project coordinator of new proposal projects related with the industry 4.0.

P.: My name is Paula Hernamperez, and I am a researcher at CARTIF. I work as a project manager, data analyst and as an operational researcher, mainly in the renewable energy resources field.

S.: I’m Sergio Rodríguez Carro, from Zaragoza, a mechanical industrial engineer currently pursuing my PhD in thermal systems hybridization and optimal control at the University of Valladolid. I work as a researcher in the Energy Division of CARTIF, where I actively participate in several European projects in the field of energy model control and optimization.

Q: Please describe CARTIF’s role on the project?

P.: CARTIF team is in charge of the development and integration of the decision support toolkit for hybrid hydro power plants.

S.: This includes designing and implementing algorithms for fault detection, predictive maintenance, energy and hydrogen production forecasting, water flow modeling, and environmental indicators analysis.

Cr.: Data will encompass system variables and accelerometer data registered in the different HPP elements. Normal-behavior model will be designed using statistical or machine learning based techniques.

P.: CARTIF also coordinates the development of other project toolkit algorithms.

Q: What are the main challenges of your work on the project, and how do you tackle them?

S.: – One of the main challenges of our work on the project is ensuring the reliability and efficiency of the developed algorithms. To achieve this, we employ rigorous research methodologies and conduct exhaustive tests in simulated and real environments. The replicability in different geographical areas and market set ups is definitely a challenge.
In D-HYDROFLEX, there are 6 demo sites in Poland, Romania, Spain, France and Greece. P.: For me, I would say that the main challenge, is the coordination of the work performed. We are a lot of partners, 18 companies and up to 45 hardworking people, all of us working in our own field of expertise each. But, you know, you need to more or less understand what people is talking about anytime, in case they have any issue you need to help them with… even when you have no idea of what they are talking about (smiling).

Q.: Cristina, what are your thoughts?

Cr.:  The big challenge in the beginning of each project, is to understand all the team, how works the process, where the project takes place. And after this, important is to start the process of collecting information and data.

The problems are related to the fact that the enterprises don’t have data, they can’t share it outside the company, descriptions are not available, the real problem to be solved is not very well defined. It may take a long time until we can have good files to start working on.

The person in charge of obtaining information, the main contact between partners, have to be all the time pending to receive the information on time, and prepare a GANTT of interferences between the due dates defined in the project. It happens that we miss some information and the work needs to be performed on time.

Q.: You raise an interesting issue. Data sharing among partners.

Cr.: I believe it is a big challenge in many projects. Not all partners are consciences about the requirements for developing models of predictive maintenance. The developers need a lot of information about their production lines. It is needed the knowledge of an expert in the field to obtain a good analysis of the data available. The data available to be shared out of the plants, (another challenge) have to be enough and with high quality to obtain good models.

Q: What are your expectations from the project? What impact will the project have on the energy ecosystem?

S.: My expectations for the project are high. I strongly believe that D-HYDROFLEX will not only contribute to advancing scientific and technological knowledge in the field of hybrid hydroelectric plants but will also have a significant impact on the European energy ecosystem. Successfully implementing our decision support tools can drive the adoption of more sustainable and efficient solutions, accelerating the transition to a cleaner and more resilient energy future.

Cr.: The reduction of the wasted time. If we can detect when in a HPP can appear a defect, it is possible to schedule the maintenance, avoiding a stop in the worst time of production.

It is important to have the machineries ready for work, especially with this kind of production plants that depends a lot on the environment… they can’t start producing energy when they want.

Q.: Paula?

P.: My expectations for the project? I hope we are able to cover the hydro power plants needs with the toolkit we are developing. We are in constant contact with the demonstrators participating in the project to understand the main point we need to take into consideration. I am highly confident we will get good results.

Q: Sergio? Please, one last comment for the innovation perspective in the renewable energy research.

S: Well, innovation in this field of science, like almost everything in life, is crucial because we face complex challenges such as maximizing energy efficiency, minimizing emissions, and effectively managing resources like water and hydrogen. In addressing these challenges, we must think beyond conventional solutions and explore new strategies and approaches. For instance, in our D-HYDROFLEX project, we’re combining hydroelectric technologies with hydrogen storage and production systems to create more flexible and efficient hybrid plants. This requires innovation in control algorithm design, infrastructure management, and complex system integration.

Thank you all three for being with us today.

Cr. P. S.: It was our pleasure.

Learn more on D-HYDROFLEX toolkit here.

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