Korupcijska kaznena djela protiv službene dužnosti - s analizom prijedloga njihovih izmjena

Rad obuhvaća elaboraciju primjedba međunarodne zajednice odnosno GRECO-a na pojedina korupcijska kaznena djela te implementaciju tih primjedba u prijedloge izmjena korupcijih kaznenih djela protiv službene dužnosti koja se smatraju korupcijom u užem smislu odnosno kaznenog djela zlouporabe obavljanja dužnosti državne vlasti iz članka 338. KZ, protuzakonitog posredovanja iz članka 343. KZ, primanja mita iz članka 347. KZ te davanja mita iz članka 348. KZ. Problematizirani su i prijedlozi izmjena kaznenog djela zlouporabe položaja i ovlasti iz članka 337. KZ, koje se ne smatra kaznenim djelom koje čini korupciju u užem smislu, ali predstavlja korupcijsko kazneno djelo i jest korupcija u širem smislu. Prikazano je kaznenopravno uređenje korupcijskih kaznenih djela u zakonodavstvima Francuske i Slovenije te je komparirano u glavnim crtama s pozitivnopravnim uređenjem korupcijskih kaznenih djela prema hrvatskom Kaznenom zakonu. Temeljem provedene komparativne analize predložene su određene promjene koje bi trebalo provesti u pojedinim kaznenim djelima

Data-Driven Thermal Modelling for Anomaly Detection in Electric Vehicle Charging Stations

The rapid growth of the electric vehicle (EV) sector is giving rise to many infrastructural challenges. One such challenge is its requirement for the widespread development of EV charging stations which must be able to provide large amounts of power in an on-demand basis. This can cause large stresses on the electrical and electronic components of the charging infrastructure - negatively affecting its reliability as well as leading to increased maintenance and operation costs. This paper proposes a human-interpretable data-driven method for anomaly detection in EV charging stations, aiming to provide information for the condition monitoring and predictive maintenance of power converters within such a station. To this end, a model of a high-efficiency EV charging station is used to simulate the thermal behaviour of EV charger power converter modules, creating a data set for the training of neural network models. These machine learning models are then employed for the identification of anomalous performance.Comment: Published in: 2022 IEEE Transportation Electrification Conference & Expo (ITEC

Advanced control methods for power converters in distributed generation systems and microgrids

The twenty-two papers in this special section focus on flexible control of power converters which serve as interfaces between the distributed generation (DG) units and the legacy alternating current (ac) grid or the ac or direct current (dc) microgrid (MG), is the key to realization of high penetration of renewable energy in a safe and stable fashion. When connected to the ac legacy grid, these power converters need to provide ancillary services such as frequency and voltage support, harmonic compensation, as well as synthetic inertia emulation. Another emerging solution is to interface the DG units with the ac legacy grid through an intermediate entity called anMG. MG can be based either on ac and dc architecture and can work in both stand-alone and grid-connected modes. Since it is responsible for multiple power converters, an MG has higher operational flexibility than individual units.However, due to a lack of stiff voltage reference source and natural inertia, control of MGs is generally more challenging than control of individual grid-connected power converters