Research group for optimal planning and control of electric power systems with a high share of RES

Submitted by moderator_US on Thu, 08/20/2020 - 10:45
Photo of the research group
University
Faculty/school/department
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split
Size of the team
number of researchers number of supporting staff number of PhD students
4
3
2
Composition of Joint Unit of Research, if relevant

Electrical engineering – power engineering

PI
PI name
Damir Jakus
PI bio

Damir Jakus researcher ID: G-4696-2017

Contact person and e-mail
Contact person
Boris Ljubenkov
Contact person e-mail
Short description of research profile
  • 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 methods and deep neural networks 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.
Publications

Representative publications

Čađenović, Rade; Jakus, Damir; Sarajčev, Petar; Vasilj, Josip  Optimal Distribution Network Reconfiguration through Integration of Cycle-Break and Genetic Algorithms.  // Energies, 11 (2018), 5; 1278, 18
Sarajčev, Petar; Jakus, Damir; Vasilj, Josip; Vodopija, Stipe  Application of genetic algorithm in designing high-voltage open-air substation lightning protection system.  // Journal of electrostatics, 93 (2018),  43-51
Sarajcev, Petar; Jakus, Damir; Vasilj, Josip Introducing novel risk-based indicator for determining transmission line tower's backflashover performance.  // Electric power systems research, 160 (2018),  337-347
Sarajčev, Petar; Jakus, Damir; Jolevski, Danijel  Transformer insulation coordination using volt– time curve and limit–state surface formulation.  // International journal of electrical power & energy systems, 90 (2017),  256-266
Vasilj, Josip; Sarajčev, Petar; Jakus, Damir  Estimating future balancing power requirements in wind–PV power system.  // Renewable energy, 99 (2016),  369-378
Technology Expertise

For the realization of the above objectives and activities, the existing laboratories at the Department of Power Engineering (laboratory A246 and B309) will be used. These laboratories will be equipped with computer and laboratory equipment (protection relays of different generations, measuring equipment,…) and specialized software packages for the analysis and simulation of power systems (MATLAB, PowerFactory, GridLAB, OpenDSS, PowerCAD, WinDIS, EMTP, Anaconda, etc. .). In the next five-year period, a significant upgrade of laboratory equipment is planned, which would be financed through other financial sources, and the procurement of the same will complement the existing laboratory computer and software resources. Through the VIF financing program, small value equipment will be procured: measuring equipment of small value, laboratory consumables, maintenance of licenses for various software packages,…