Projects | Damir ‧ Jakus

FLEXSYS

Fri, 10 Oct 2025 00:00:00 +0000

Global power systems are undergoing a profound transformation driven by the imperative of decarbonization and the transition toward sustainable, low-carbon energy models. In this context, renewable energy sources (RES) – particularly solar power plants and wind farms – are experiencing significant growth, raising their share in global electricity generation, together with hydropower, to over 30%. Although essential for reducing greenhouse gas emissions, these variable sources introduce a range of technical challenges related to production fluctuations, grid stability, demand management, and overall system cost-effectiveness.

The FLEXSYS project addresses these challenges by exploring innovative solutions for the systematic and coordinated management of flexibility resources at the power system level. The project’s main objective is to ensure the stable integration of RES through the application of advanced models and control strategies for flexibility resources, with particular focus on technologies such as battery energy storage systems, electric vehicles, pumped-storage hydropower plants, and large consumers such as PEM electrolyzers. FLEXSYS includes theoretical modeling, the design of hybrid converters and control algorithms based on model predictive control (MPC) and artificial intelligence/machine learning (AI/ML) methods, as well as multi-level optimization. The developed solutions are validated through simulations, Hardware-in-the-Loop testing, and experimental validation on real system platforms. The project results aim to contribute to a more resilient, sustainable, and efficient energy system, supporting European decarbonization and security-of-supply objectives.

Project Objectives:

The project is focused on the development of innovative scientific and technological solutions in the field of flexibility management in power systems with a high share of renewable energy sources. The key objectives include:

Development of accurate and computationally efficient models of flexibility resources such as battery energy storage systems, supercapacitors, electric vehicles (V2G), pumped-storage hydropower plants, and controllable demand (O1),
Implementation of advanced control strategies based on Model Predictive Control (MPC) and artificial intelligence/machine learning (AI/ML) methods, including forecasting tools for key variables such as renewable generation, demand, and electricity prices (O2),
Development of optimization models for microgrid management and flexibility modeling in transmission and distribution networks (O3),
Design and prototyping of a hybrid power converter integrating multiple energy sources and enabling application in V2G systems (O4),
Analysis of dynamic stability and transient phenomena in systems with high RES penetration using EMT simulations and machine learning methods (O5),
Validation of developed solutions through simulations, Hardware-in-the-Loop (HIL) testing, and real-world experimental validation (O6),
Dissemination of results through scientific publications, conferences, technical reports, and open-access tools (O7).

Project Leader: prof. Damir Jakus

Project Value: 238.050 €

Project Duration: 10/2025 - 10/2029

Funding Source: Funded by the European Union - NextGenerationEU

LuminiH2

Mon, 01 Jan 2024 00:00:00 +0000

Opis istraživanja

Projekt LUMINIH2 sastoji se od više dijelova pri čemu je cilj realizacija laboratorijskog modela i prototipa mikromreže te laboratorijskog modela i prototipa elektromotornog pogona na vodik čime će se objediniti korištenje različitih tehnologija obnovljivih izvora energije (OIE) i vodika, s vlastitim razvijenim sustavom upravljanja i monitoringa. Također, cilj je stvoriti napredni model\algoritam za dijagnostiku i monitoring komponenata vodikovih tehnologija i ostalih komponenti podsustava (kompresor, energetski pretvarači, FN sustav, vjetroagregat, baterijski spremnik), što će omogućiti održavanje stabilnosti i pouzdanosti sustava.

Predloženi projekt sastoji se od više dijelova pri čemu je cilj realizacija laboratorijskog modela i prototipa mikromreže te laboratorijskog modela i prototipa elektromotornog pogona na vodik s vlastitim razvijenim sustavom upravljanja i monitoringa. Laboratorijski model podrazumijeva numeričke i simulacijske realizacije sustava, dok prototip obuhvaća fzički model sustava. Navedeni laboratorijski modeli i prototipovi su osnova za implementaciju različitih modela\algoritama upravljanja i monitoringa za čiju je izradu nužno istražiti i razviti različite softverske modele. Također, cilj je stvoriti napredni model\algoritam za dijagnostiku i monitoring komponenata vodikovih tehnologija i ostalih komponenti podsustava. Kroz projekt će se osigurati evaluacija laboratorijskih modela i prototipova te sustava upravljanja i monitoringa.

Očekivani rezultati

Krajnji korisnici ovog projekta su sve fzičke i pravne osobe koji trebaju kontinuiranu opskrbu električnom energijom na izoliranim elektroenergetskim lokacijama. To uključuje pojedince, kućanstva, tvrtke, industrije ili čak zajednice koje se nalaze u ruralnim ili udaljenim područjima koja nisu povezana s glavnim elektroenergetskim mrežama. Ova tehnološka rješenja koja kombiniraju OIE i vodikovu tehnologiju mogu pružiti održivu i pouzdanu električnu energiju za krajnje korisnike koji inače nemaju pristup konvencionalnoj elektroenergetskoj mreži. Ovo uključuje udaljena sela, otoke, planinska područja ili druga mjesta koja su izvan dosega konvencionalne infrastrukture.

Advance-RES

Sat, 30 Dec 2023 00:00:00 +0000

Research description

Trends in the development of electric power systems indicate the fact that the period of the next 5 years will mark the period of generating units based on RES. To ensure safe and reliable operation of the power system in such operating conditions, significant investments in capital equipment at the power system level, or the development of advanced methods of power management and control that will avoid or reduce these costs are necessary. Given these trends, the focus of the research group will be on the development of advanced methods of optimization and machine learning and their application in the planning and management of power plants with a high share of RES. For this purpose, the goals of the research group will be directed in several directions:

Optimal planning and operation of transmission and distribution networks with a high share of RES. In this part, the activities are related to:
- Development of methods for optimal extension planning of transmission/distribution networks with a high share of RES,
- Development of methods for the optimal operational management of power networks to increase grid hosting capacity under the current network state,
- Analysis of the different sources of flexibility to create conditions for the energy transition of the classic power system to RES-based systems.
Optimal microgrid management. In this part, the activities include:
- Application of model-predictive control methods for optimization of microgrid operation and creation of conditions for participation in the ancillary services market,
- Application of machine learning methods to develop generic approaches for optimal microgrid management.
Application of machine learning and deep learning methods in power equipment diagnostics and relevant power system parameter forecasting. Activities in this section include:
Development of methods for forecasting important market/power system parameters such as day-ahead / intra-day load forecasting, forecasting the production of wind farms / PV power plants, forecasting hydrological conditions at the level of individual basins, etc.
- Development of methods based on machine learning and Bayesian statistics for forecasting and classification of equipment condition in power facilities.
- Development of methods based on machine learning for the analysis of transient stability and power system fault classification.
- Development of machine learning-based methods for the classification of power system faults.
Formation of laboratory for microgrid and real-time power system simulation:
- Procurement of equipment for microgrid development through other founding sources The equipment will be used to test the developed algorithms and methods and implement advanced microgrid management strategies;
- Procurement of equipment for real-time simulation of power system operation, which would examine the possibility of implementing the developed algorithms and analyze the effects of their application.

Expected results

It is anticipated that advanced methods and algorithms will be developed for the optimal planning, operation, and management of electric power systems (EPS) with a high share of renewable energy sources (wind farms and solar power plants). To this end, the development and simulation of network models at the national, regional, and local levels, encompassing different voltage levels, are expected. These models will enable the analysis of various challenges in integrating new production, consumption, and storage technologies into existing EPS, as well as proposing solutions. Additionally, methods for forecasting consumption and renewable energy production at different time scales relevant to the functioning of the electricity market are planned to be developed.

MsEVP

Sat, 30 Dec 2023 00:00:00 +0000

Developed transport infrastructure is considered to be an extremely important factor in the sustainable and balanced development of any country. Trends in traffic and the automotive industry are following technological developments and requirements related to environmental protection and greenhouse gas emissions reduction, and as a result, electric vehicles are increasingly being used instead of motor vehicles. Advances in battery development, energy efficiency, vehicle materials, design itself and better aerodynamics bring electric vehicles into almost everyday use. The development of new technologies, especially in the field of batteries, allows a very short time to charge vehicles, but the main obstacles to the mass use of electric vehicles in road transport are still high cost and underdeveloped charging network in some countries. As with motor vehicles, the basic problem stems from the fact that traffic congestion at rest will not be solved by increasing traffic in motion, but changes in infrastructure are necessary to ensure optimization of both traffic at rest and traffic. The result of the conducted research and development will be a smart-grid charging station for electric vehicles within the construction of a rotary parking system whose main goal is to optimize traffic at rest and traffic in motion. The system called Markoja Smart EV (Smart Electric Vehicle) - MsEVP involves the development of hardware and software components:

Charging station for electric vehicles (created by connecting smart parking systems and vehicle power supply systems); Application for full management of the MsEVP system (by owners and users).

The goal of the project is to develop a smart grid charger for electric vehicles within the construction of a rotary parking lot, which is managed by the platform owner and the end user through the application. Rotating parking takes up space as two parking spaces for vehicles, and by placing the vehicle vertically in several levels they accept up to 16 vehicles, depending on the size of the garage. By integrating EV power technology to each parked vehicle - a solution is obtained that allows vehicles to be charged while parked where the space occupied by vehicles is significantly less than the space required for horizontal parking of an equal number of vehicles. The aim of the project is to gain knowledge and practical experience by cooperating with a scientific research institution in research and development of innovative products. In addition, the project will explore the possibilities of applying innovative technical solutions related to the optimal power supply of rotary parking for electric vehicles and the possibility of using a flexible charging method to support the power grid operation.

GridS

Fri, 30 Dec 2022 00:00:00 +0000

Project Summary

GridS is a project focused on researching the potential of implementing the innovative concept of microgrid management. This involves advanced management techniques that could be applied globally. The project is a collaboration between Rita Solar D.O.O., Iri D.O.O., and the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture (FEESB) in Split.

General Project Goal

The goal of this project is to develop technology and active systems for electricity distribution that facilitate the integration of distributed generation plants, enable dynamic electricity delivery termination, and introduce priority delivery of ICT technology and smart-grid energy solutions. The purpose of the project is to explore technology for managing electricity production and consumption using predictive algorithms and to validate this technology in a relevant environment.

The project includes the development of the following systems:

A system for integrating various renewable electricity sources into a single manageable energy source (integrator/aggregator)
An electricity delivery system with consumption control and dynamic power limiting
An advanced distributed control system that maintains system stability and ensures priority electricity delivery