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1. Application Of AI
Technologies In NPP
22.11.2024 | Belgrade
Peter Kertys, Maroš Bubán

2. Our Power Plants (11/2024)
31x
2x
2x
Installed
capacity
1 653 MW
2 474 MW
2 MW
SE production
share
8.14%
91.85%
0.01%
4129 MW

3. 3
Inhouse LLM Chat
Maintenance
Blowndown
loss
HPHE
degradation
Internal
consumption
Production
prediction

4. Inhouse
LLM Chat
6 monthsimplementation
Userseager to cover more topics
8 topic areas + 4 custom prompt built in progress

5. Inhouse LLM Chat
5
Information
aggregator
Company data
User required
training & GDPR
Enterprise
secured solution
Own indexes
Area specific
validation
SSO
Own vector indexed DB
Multi-stage prompt architecture in
background
Login required
Feedback notification
20% employee utilization
2 stage search engine for no/SQL DB
In house built FE & BE
Cost management

6. Selector
Agent
Question
Agent
Summariz
ation
Agent
Service Desk
Agent
Corporate
documenta
tion Agent
Intranet
Agent RAG evaluation
Multiple models
Different data
sources
Prepare data for user
response
Decision for domain
agent selection
Question request
Vector DBs
Architecture

7. Blowndown
loss
Data collection & quality check
Reportprototype
Modelcalibration

8. 8
Reduced costs
Better monitoring
& interpolated
values
Enhanced
process
Operator training
Data quality
check required
Continouos
monitoring
SMS notification
Improved computation
Chemistry system integration
Power BI report
Operator reaction & calibration
Regression models, computation &
simulation based on weather forecast
& river level
12h update
Blowndownloss – sulfates & potasium

9. 9
Concentration
of salts in
water and in
the circuit
Weather
forecast
Hronriver
water level +
prediction
Excel Delta Lake
Web
scrapping
Flows,T of
CCW,
Weather
PI system
1 h 24 h 1x/12h in 5m gr. 1x/12h in 5m gr.
1x/12h v 5m gr.
Density
calculation
12 h
Blowndown
loss - control
room1 h
Batch processing
Architecture

10. Internal
consumption
1yr reference metering & calibration
1yr usage at NPP Jaslovské Bohunice
+0,5MW during specific conditions

11. Int. consumption – impeller blade angle
11
Higher energy
production
Reduced own
consumption
Internal operation
manual change
Training
Hourly update
Data quality check
Additional rule
engine w/o safety
impact
Total integration into OT
Scaling for Mochovce
Integration with other circuit
balancing projects
Potential for full automation
Power BI report with optimal set-up
Additional temperature + prediction
EMAIL + SMS notification
Integrated Wet bulb temperature
forecast, optimization model for
temperature & impeller blade angle
combinations on historic data
Transfer function from temperature
into circulation water

12. Delta Live
Tables
BQDV, CCW
operational
data
PI system
Weather
forecast
Delta Lake
4 h
1 h
Rotation of
the blades
report
Power BI
Alerts
Local SMS
gateway
Email
Email
SMS
1 h
Wet bulb temperature
–
precalculated data
Data transformation
Architecture
Calculation
Data quality check

13. Questions
Peter Kertys
peter.kertys (at) seas.sk
Maroš Bubán
maros.buban (at) seas.sk