SYSTEMS ENGINEERINGSYSTEEMITEKNIIKAN TUTKIMUSYKSIKKÖ
Enso Ikonen
professori, säätö- ja systeemitekniikka
”Säätö- ja systeemitekniikan professuuri […]:
Alan täsmennys on säätö- ja systeemitekniikan teoria ja menetelmät sekä sovellukset, sovellukset erityisesti energiatekniikassa.”
(PYO 1.1.2010-)
Systems Engineeringhttp://www.oulu.fi/pyosys/
Systems
Engineering
Automation
Systems
Control
Theory
Process
Dynamics
Theory and Methods of
Control and Systems Engineering
Power Plant Automation
Dynamic Energy Networks
Engineering Education
Systems Engineering
Methods of control and systems engineeringhttp://www.oulu.fi/pyosys/
process control applications
power plant automation
control & systems
engineering methods & algorithms(MPC, AI/CI)
SYTE
engineering education
• Automation
Engineering
• Control System
Analysis & Design
• Advanced Methods
of Control and
Systems
Engineering
• Process Information
Systems
• Power Plant
Automation
• MSc & BSc works
• Engineering
Education
• Identification/
learning systems
• Bayesian state
estimation (KF, UKF, PF)
• Computational
intelligence (GA, SNN, SOM...)
• Model predictive
control (MPC)
• Optimization of
dynamic systems (ADP)
• Plant wide control (SOC)
• Uncertain systems
process control applications(dynamic energy networks)
power plant automation
(CFB control)
control & systems
engineering methods & algorithms
Systems Engineering
Power plant automationhttp://www.oulu.fi/pyosys/
SYTE
engineering education
• Circulating fluidized
bed combustion
(CFB)
• Once-through
boilers (OTU)
• Oxyfuel combustion
• Hybrid (solar-fossil)
plants
• Amec Foster
Wheeler Energia
cooperation
• Water distribution
• District heating
• Pulp digester
• Energy automation in buildings
• production-storage-consumption
Advanced methods applied to energy systemsRecent & on-going projects at Systems Engineering
CFB process control
CFBCON (a series of projects)
CFB power plants
dynamic modeling, control, optimization & analysis tools
HOPE (hot-loop parameter estimation)
analysis of test campaing data; state/parameter estimation
Bayesian estimation: UKF, PF
COMBO-CFB
solar-CFB hybrid
modeling, MPC,multi-objective optimization
PWC (plant wide control)
oxy/air CFB; PhD student
self-organizing control
IPCD (integrated plant & control design)
OTU-CFB; PhD student
D/RGA-methods, etc
in cooperation with Foster-Wheeler (Amec FW)
Dynamic energy networks
OPUS (Water distribution networks)
optimal pump scheduling using water towers
short-term optimization, using MDP, ADP
DINO (District heating networks)
DH dynamic modeling
model calibration & short-term operational optimization
VIRPA-B (Energy optimization in large buildings)
grocery store refrigerators as storages
shop integration & balancing power markets
modeling & optimization of storage dynamics
Samples of research
at Systems Engineering
Modelling
State estimation
Optimal control
Modeling of district heating networks
DHN modeling
hydrodynamics
pressures & flows in pipelines
pumps, valves
pseudo-steady-state
heat flow dynamics
heat propagation, delays
heat losses to ground
storages
consumer behavior
consumption predictions
local primary–secondary controls
heat production
main/peak/reserve boilers
CFB, oil burners, gas, ...
external heat sources
industrial waste heat
operation costs & constraints
’toy’ network
full Kemi
network
DHN-simulation
DH as a part of an agile energy systemApplications for DH network modelling & optimization toolbox
Boiler agility
new control specifications to controllable boilers?
improved flexibility, agility
DHN point-of-view
constraints
operation at low loads
flexibile boilers with storages
CHP
CFB (FB) circulating fluidized bed
integrated process & control design
plant-wide control
virtual power plants
flexibile boilers with hybrid constructions
boilers in an energy production netowork
DH network operational agility
tight dynamic control of production/ network/ storage/ consumer –system for..
..active loading/unloading control
..active storage control
..optimal stochastic control of unertain future consumption/production
..buffer against disturbances/ intermittant production
Fitting... .. production & consumption
using network as a storage
..renewable & local production
wind, solar surplus
intermittant
electrical-to-thermal conversions
local production
two-way heat production
...additional storage components
examination of operation with new components in DH networks
tanks, caves
storage in buildings
other (chemical, mechanical, ...)
...consumer flexibility
large consumers (commercial centers, offices, ...)
flexible consumers (street heating, swimming pools, ...)
industrial users
blocks of flats, small business
detached houses
public acceptance
...to daily operation
Hot-loop
parameter estimation
analysis of data from plant test campains
model-based state estimation
full scale physical dynamic model
PF & UKF
fuel moisture, heat transfer coeff.
a tool for data analysis
in cooperation with Amec Foster-Wheeler
HOPE example simulations
(fuel moisture vs. flue gas O2)
fixed params fixed at intervals PF
FADPnon-linear non-minimum phase CSTRoptimal control noise in product concentration
and reactor temperature + random walk in feed temperature
Plant wide control of CFBself-optimizing control (Skogestad)
Water distribution
networks
modeling of grocery store energy system (potential of participation)
energy (electricity) markets
power control reserves
balancing power
ELSPOT (day-ahead), ELBAS
energy saving vs peak shifting vs balancing power…
integrated grocery stores, renewable/own production,digitalization aspects …
Demand side managementin large buildings
COMBO-CFB
Modeling: ’tube’ model for OTU-CFB with varying tube parameters
Control: of nonlinear plant (MPC)
(Hybrid) process design based on
control aspects: minimize L2 gain -
action/disturbance
COMBO-CFB
Please visit our poster site:
• contact info, topics, papers• Kemi DH network simulations (video)• Tuira grocery store simulator (demo)