Reinforcing digitalisation related know how of local energy ecosystems
Project Proposal
Offering modelling, estimation and control expertise applied to smart city infrastructure for HORIZON-CL5-2021-D3 and HORIZON-CL5-2022-D3
Can act as:
Seeking expertise:
Laboratory for Renewable Energy Systems (LARES, www.lares.fer.hr/) is part of the Department of Control and Computer Engineering at University of Zagreb Faculty of Electrical Engineering and Computing. With more than 15 years of R&D experience in advanced optimal control algorithms, artificial intelligence and their practical implementations on different scales, as well as laboratory and living-lab environments LARES is experienced in research projects execution (skilled in Horizon projects) and technology transfer projects with industry partners.
Built on the premises of control theory, artificial intelligence and their applications, LARES offers its expertise in the topics of:
- cyber-physical modelling and machine learning approaches for energy-intensive systems;
- data-driven monitoring and fault detection algorithms;
- advanced control, scheduling or decision support systems for coupled physical systems.
We are interested in joining a project consortium (as partners or work package leaders) and offering the following contributions for the respective Horizon 2021-2022 calls:
HORIZON-CL5-2021-D3-02-11: dynamic building modelling, data-based monitoring, and performance assessment by using methods that utilize various data sources and reduce the gap between the assessment and actual performance and expand the evaluation with other relevant life-cycle performance indicators.
HORIZON-CL5-2021-D3-03-02: holistic energy management of systems with high RES penetration through the coordination with other energy-relevant systems such as batteries or heating and cooling system. AI based forecasting of RES power production as well as forecasting of energy demands.
HORIZON-CL5-2021-D3-03-08: Smart decision support systems, optimal sizing, and operation scheduling of complex hybrid systems with respect to household thermal and electrical demand calculated based on its dynamic performance assessment, local production and storage possibilities and energy grid conditions.
HORIZON-CL5-2022-D3-01-06: Modelling of microclimate conditions in the considered environment and development and deployment of accompanying model based and data-driven control strategies or advisory systems for maximizing the overall system performance (e.g. optimal PV positioning) and minimization of operational costs. AI based modelling of crop plant and agricultural processes, PV power production forecasting, weather forecast localization, crop yield forecasting, crop plant development modelling and soil and crop plant state predictions from short term weather forecasts.
HORIZON-CL5-2022-D3-01-08: dynamic building modelling, data-based monitoring, and performance assessment. Holistic optimization of building operation including development of sophisiticated user behavior models describing their individual flexibility to temperature changes and their impact on overall energy flexibility of the building.
HORIZON-CL5-2022-D3-02-01: Improvement of the system components reliability, advanced and automated functions for data analysis, diagnosis, maintenance and fault detection, predictive modelling, optimal control and AI for holistic optimization of system behavior including the anciliary services provision
Also, we have available fully digitalized operable living-lab skyscraper building infrastructure (zones, HVAC, PV, battery; 10.000 m2) operated via software modules implementing model predictive control of zone air temperature since 2019. All relevant data are saved with a sampling time of 1 min and available for further research.
There are existing firm ties with the institution Innovation centre Nikola Tesla (ICENT, www.icent.hr/en/), which acts as a leading constituent of the innovation ecosystem for applied research and development in the field of engineering in Croatia and broader. This creates also an opportunity to either act as or include ICENT in the consortium if deemed necessary for creating a good innovation synergy and impact.