Projects / Programmes
Stability of nuclear reactors in load follow mode of operation
| Code |
Science |
Field |
Subfield |
| 2.03.02 |
Engineering sciences and technologies |
Energy engineering |
Fuels and energy conversion technology |
| Code |
Science |
Field |
| 2.02 |
Engineering and Technology |
Electrical engineering, Electronic engineering, Information engineering |
nuclear energy, load follow, neutron transport, nuclear data, sensitivity and uncertainty analysis, nuclear reactor, machine learning, renewable energy
Data for the last 5 years (citations for the last 10 years) on
April 25, 2024;
A3 for period
2018-2022
Data for ARIS tenders (
04.04.2019 – Programme tender,
archive
)
| Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
| WoS |
1,223 |
21,321 |
17,260 |
14.11 |
| Scopus |
1,234 |
23,620 |
19,428 |
15.74 |
Researchers (15)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
31776 |
PhD Dušan Čalič |
Energy engineering |
Researcher |
2020 - 2024 |
86 |
| 2. |
39521 |
PhD Tanja Goričanec |
Computer intensive methods and applications |
Researcher |
2020 - 2024 |
92 |
| 3. |
03943 |
PhD Ivan Aleksander Kodeli |
Computer intensive methods and applications |
Researcher |
2020 - 2021 |
966 |
| 4. |
38202 |
PhD Bor Kos |
Energy engineering |
Researcher |
2020 - 2021 |
671 |
| 5. |
04538 |
PhD Marjan Kromar |
Energy engineering |
Researcher |
2020 - 2024 |
300 |
| 6. |
19167 |
PhD Igor Lengar |
Materials science and technology |
Researcher |
2020 - 2024 |
1,200 |
| 7. |
52752 |
Jan Malec |
Energy engineering |
Researcher |
2020 - 2024 |
55 |
| 8. |
25655 |
PhD Boštjan Pregelj |
Systems and cybernetics |
Researcher |
2020 - 2024 |
128 |
| 9. |
52060 |
Anže Pungerčič |
Energy engineering |
Junior researcher |
2020 - 2022 |
67 |
| 10. |
32163 |
PhD Vladimir Radulović |
Energy engineering |
Researcher |
2020 - 2024 |
244 |
| 11. |
07991 |
Slavko Slavič |
Energy engineering |
Technical associate |
2020 - 2024 |
94 |
| 12. |
27819 |
PhD Luka Snoj |
Energy engineering |
Head |
2020 - 2024 |
1,863 |
| 13. |
08557 |
PhD Andrej Trkov |
Energy engineering |
Researcher |
2020 - 2024 |
795 |
| 14. |
15742 |
Bojan Žefran |
|
Technical associate |
2020 - 2024 |
152 |
| 15. |
29546 |
PhD Gašper Žerovnik |
Computer intensive methods and applications |
Researcher |
2020 - 2024 |
232 |
Organisations (1)
| no. |
Code |
Research organisation |
City |
Registration number |
No. of publicationsNo. of publications |
| 1. |
0106 |
Jožef Stefan Institute |
Ljubljana |
5051606000 |
90,742 |
Abstract
The European Energy Roadmap to decarbonisation involves high rates of renewables along with a significant contribution from nuclear energy. With the increasing share of electricity produced by wind and solar power systems, an increasing reliance on intermittent energy sources in the Slovenian as well as European grid is expected. Correspondingly, a part of existing or more likely future Slovenian and European nuclear fleet will have to move from a base load electricity generation mode to a load-follow electricity generation mode. Adjustments of reactor core power during the load-follow operation might result in Xenon oscillations under unfavourable core conditions. Such oscillations have a period of cca. 15-30 hours and might especially trough axial power perturbance induce unacceptable power peaking factors. While there are automated systems to maintain reactor power, the control of axial power distribution is a manual operation requiring operator deep understanding of the process and adequate action. The main objective of the proposed research is to examine restrictions of the nuclear power plant load-follow operation on the nuclear aspects of the reactor core and nuclear fuel and provide effective solutions to the plant operator how to optimize plant operation. We will develop a reduced order model (ROM) methodology for the real time simulation of reactor operation with the focus on providing support for load follow operation. ROM will be connected to the developed in-depth core analysis package (In-depth Core Model – ICM), which will supply necessary data needed for the reactivity and pin power distributions. The methodology will be used to analyse complete phase space of load follow operation, i.e. phase spaces of input parameters such as load follow as well as space phase of reactor conditions. Optimal reactor operational strategies will be developed. In addition the limiting conditions of load follow operations will be determined to keep the reactor physical parameters such as power peaking factors, shutdown margin etc. within operational limits and conditions. Due to complexity of the project we will apply machine learning algorithms to explore non-conventional modes of operation or measures to mitigate Xe oscillations and couple ROM with weather predictions via feedforward control. We will evaluate all uncertainties with focus on uncertainties in calculations due to uncertainties in nuclear data. In the last part of the project we will identify and propose design features of a reactor that would be better suited to load follow operation than existing reactors. This would be of great benefit for setting up specifications and requirements for future nuclear power plants.
