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Co-Simulation of an Energy Management System for Future City District Energy Systems

Authors:
  • BEST - Bioenergy and Sustainable Technologies GmbH
  • BEST - Bioenergy and Sustainable Techologies GmbH
  • BEST – Bioenergy and Sustainable Technologies GmbH

Abstract

Slides of the talk "Co-Simulation of an Energy Management System for Future City District Energy Systems"
© pixLab studios© pixLab studios
© zwoPK Landschaftsarchitektur
Co-Simulation of an Energy
Management System for Future City
District Energy Systems
IAPE’19, Oxford, United Kingdom, 15/3/2019
Andreas Moser
Daniel Muschick
Markus Gölles
BIOENERGY 2020+ GmbH
Inffeldgasse 21b
8010 Graz, Austria
Werner Lerch
Hermann Schranzhofer
Peter Nageler
Thomas Mach
Institute of Thermal Engineering
Graz University of Technology
Inffeldgasse 25b
8010 Graz, Austria
Carles Ribas Tugores
Ingo Leusbrock
AEE INTEC
Feldgasse 19
8200 Gleisdorf, Austria
© pixLab studios
Motivation
Optimal Energy Supply of City Districts
Slide 2
Necessity of
economic,
ecologic and
safe supply
Integration of renewable and
volatile energy sources
City District
Increasing complexity due to
integration into grids
(variable tariffs, electricity market)
Increased coupling
between sectors
Energy Management System (EMS)
© pixLab studios
Energy Management System (EMS)
Slide 3
Only apply the solution of the
first time step (15 min)
Repeat the optimisation after
15 minutes with new
measurements and forecasts
Moving horizon principle Model Predictive Control (MPC)
© pixLab studios
Analysed City District
Slide 4
City District Q1 + Q4a
Residential
37,823 m²
Office
37,388 m²
Commercial
17,209 m²
Planned innovative city districts
(Q1-Q20) in Graz, Austria
© pixLab studios
Default Configuration
Slide 5
Residential
Heating: 21 °C
Office
Heating : 21 °C
Cooling: 24°C
Commercial
Heating : 20 °C
Cooling : 22°C
Low-Level
Control
Desired room temperatures
within building:
© pixLab studios
Extended Configuration
Slide 6
Building Energy Hub
Co-Simulation
EMS
Low-Level
Control
Control
Day/Night Tariff
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Co-Simulation with BCVTB
Slide 7
IDA ICE
https://simulationresearch.lbl.gov/bcvtb/
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Economic Results
Default vs. Extended Configuration
Slide 8 Savings: ~ 37,000 €/a (~3%)
Simulation settings:
Period: 1/1 – 31/12/2018
High demand
Uncertain weather for prediction
∆t Co-simulation: 1 min
∆t MPC: 15 min
MPC horizon: 48 hours
Investment costs = costs/lifetime
© pixLab studios
Sankey diagram of the Energy Hub
Default Configuration
Slide 9
Simulation period: 1/1 – 31/12/2018
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Sankey diagram of the Energy Hub
Extended Configuration
Slide 10
Simulation period: 1/1 – 31/12/2018
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Exemplary Result of the Extended Configuration
Thermal Energy Storage for Re-cooling
Slide 11
Tues. 26/6/2018 Wed. 27/6/2018
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Interpretation of the Results
Default Configuration is already well designed
Extended Configuration further optimises the energy hub
Potential to reduce the size of the cooling tower
Further cost reduction!
EMS automatically discovers optimal control strategies
Thermal Energy Storage for peak load reduction
Thermal Energy Storage for re-cooling
Battery/Thermal Energy Storage for tariff shifts
Battery for Photovoltaics storage
Slide 12
© pixLab studios
Outlook
Slide 13
© pixLab studios© pixLab studios
© zwoPK Landschaftsarchitektur
Co-Simulation of an Energy
Management System for Future City
District Energy Systems
IAPE’19, Oxford, United Kingdom, 15/3/2019
Andreas Moser
Daniel Muschick
Markus Gölles
BIOENERGY 2020+ GmbH
Inffeldgasse 21b
8010 Graz, Austria
Werner Lerch
Hermann Schranzhofer
Peter Nageler
Thomas Mach
Institute of Thermal Engineering
Graz University of Technology
Inffeldgasse 25b
8010 Graz, Austria
Carles Ribas Tugores
Ingo Leusbrock
AEE INTEC
Feldgasse 19
8200 Gleisdorf, Austria
City of the Future is a research and technology program of the Federal Ministry of
Transport, Innovation and Technology. On behalf of BMVIT, it is carried out by the
Austrian Research Promotion Agency together with Austria Wirtschaftsservice
Gesellschaft mbH and the Austrian Society for Environment and Technology ÖGUT.
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