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Machine Learning and Simulations for Asset Management at Alliander
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Gijs Molenaar
March 13, 2020
Science
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Machine Learning and Simulations for Asset Management at Alliander
Gijs Molenaar
March 13, 2020
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Transcript
Machine Learning and Simulations for Asset Management March 13, 2020,
NL-RSE Meetup Gijs Molenaar
pythonic.nl • Me! • Freelance Software/Research Engineer • MSc AI
(UvA) • PhD astronomy (South Africa)
• Public Utility company • 5.7 million client connections •
5700 FTE
None
None
The problem • Fixed budget • How to optimally distribute
budget over departments • Balance between long term and short term goals
Amsterdam • Go fully electric by 2030 • 900.000 people
• 230.000 private cars • 10 years • 2610 working days • 1000 charging stations a day?
Our solution • Build agent based simulation of company •
Run millions of simulations up to 40 years in the future • Let Reinforcement Learning agent explore and optimize problem space
What do we need? • A physical model • A
bunch of agents manipulating this model
None
None
Reinforcement Learning
Reinforcement Learning st st+1 a
Deep-Q learning Simulation agent != Reinforcent learning Agent
State • Number of connection issues Reward • function of
• Budget spend • Average waiting time for new connection • Average Waiting time for fix of broken connection Action Decision of budget split
Project structure • 3 teams: • Data Engineers • Data
Scientists • Software Engineers
None
Evaluating 2 strategies • Compute in neo4j • Compute in
NumPy + NetworkIt
None
Rpy2 R has NA values in int arrays, numpy has
NaN in float arrays
Status report • Still working on simulations • Underestimated the
effort required to get this right • Maybe too ambitious? • Useful nonetheless
Research Engineer in Corporate environment • Different setting • Requires
different mindset • More budget • A lot of politics
pythonic.nl available again! • 1 June 2020 • First getting
married in Namibia • If we don’t get Corona banned
Questions?