Real-time phasor simulation test-bed
for secondary voltage control of power
grids using wide-area measurements
By:
Arvin M...
2
Outline:
• Problem statement
• Secondary level Voltage Control
• Model Predictive Control
• Simulation test case
• Real-...
3
Overview of Hydro Quebec Network
Problem statement
* http://www.hydroquebec.com/fr/
Hydro Power Generation
39.5 GW
Wind ...
4
Secondary level Voltage Control
• Voltage regulation and
tracking at sensitive buses
called pilot nodes using:
– Changin...
5
Model Predictive Controller
1) State estimation based on measured output
and previous input/output set.
2) Use Identifie...
6
Simulation Test Case
• IEEE39 bus system
used as test case
• pilot buses to install
PMUs: buses 1,12 & 28
• Identify lin...
7
Real-time testbed
ePHASORsim
IEEE 39 bus
Network
ePHASORsim
IEEE 39 bus
Network
ePHASORsim
IEEE 39 bus
Network
++
MPC Co...
8
Simulation Results: Voltage Regulation
Trip generator: G3 is tripped at t=10s
0 50 100 150 200
0.85
0.9
0.95
1
1.05
V
PN...
9
Simulation Results: Voltage Regulation
Trip Line: Bus 8 to Bus 9
0 100 200 300 400 500
0.85
0.9
0.95
1
1.05
V
PN
(p.u.)
...
10
Simulation Results: Voltage Tracking
Chang Vref of Bus12 from 0.923p.u to 0.94p.u
0 50 100 150 200 250 300
0.9
0.92
0.9...
11
Conclusion and future works
• MPC controller can handle voltage regulation
and tracking at pilot buses in presence of
d...
12
Acknowledgement
• I would like to thank OPAL-RT technologies,
and specifically ePHASORsim team who
helped me to accompl...
13
Question?
of 13

NASPI-Arvin

Published on: Mar 3, 2016
Source: www.slideshare.net


Transcripts - NASPI-Arvin

  • 1. Real-time phasor simulation test-bed for secondary voltage control of power grids using wide-area measurements By: Arvin Morattab Research Directors: Prof. Ouassima Akhrif Prof. Maarouf Saad
  • 2. 2 Outline: • Problem statement • Secondary level Voltage Control • Model Predictive Control • Simulation test case • Real-time testbed • Simulation results • Conclusion and future works • Acknowledgement • Q & A
  • 3. 3 Overview of Hydro Quebec Network Problem statement * http://www.hydroquebec.com/fr/ Hydro Power Generation 39.5 GW Wind Farms 659 MW Load Area • Large amount of reactive power loss • Volnurable to faults and sudden load changes Long distance between generation and load • Based on off-line calculations and pre- defined schedules • No coordination between reactive power compensators Manual operator based voltage control in secondary level Coordinated Secondary Voltage Control
  • 4. 4 Secondary level Voltage Control • Voltage regulation and tracking at sensitive buses called pilot nodes using: – Changing Vref of exciters on the machines – Changing Vref or Qref of Static Var compensators – Switching capacitor/inductor banks – … • Consider constraints: voltage of the buses and MVAR limits • Time step of the controller: 10sec. • Settling time (for 3%) in 1min
  • 5. 5 Model Predictive Controller 1) State estimation based on measured output and previous input/output set. 2) Use Identified LTI model to relate outputs for next P future steps, to next M future values of the inputs (M≤P). In this way we will have P equation and M unknown. P and M are prediction and control horizons respectively. 3) Solve Optimization problem with respect to unknown inputs in presence of given constraints 4) Apply the first element of control signal obtained from the optimization procedure. 5) Go to step 1 for next sampling time, k+1 MPC Algorithm:
  • 6. 6 Simulation Test Case • IEEE39 bus system used as test case • pilot buses to install PMUs: buses 1,12 & 28 • Identify linear model of the system: 12 states, 12 inputs, 3 outputs • Controller designed using MPC toolbox in MATLAB Selected Pilot buses Change of Vref Change of Qref
  • 7. 7 Real-time testbed ePHASORsim IEEE 39 bus Network ePHASORsim IEEE 39 bus Network ePHASORsim IEEE 39 bus Network ++ MPC Controller refQ PNV refV refQ PNV ref PNV - + Code Generation C37.118SlaveC37.118Slave C37.118MasterC37.118Master RT RT RT 10 s 10 ms
  • 8. 8 Simulation Results: Voltage Regulation Trip generator: G3 is tripped at t=10s 0 50 100 150 200 0.85 0.9 0.95 1 1.05 V PN (p.u.) time (sec.) 0 50 100 150 200 -0.01 0 0.01 0.02 0.03 V ref (p.u.) time (sec.) 0 50 100 150 200 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 Q ref (p.u.) time (sec.)
  • 9. 9 Simulation Results: Voltage Regulation Trip Line: Bus 8 to Bus 9 0 100 200 300 400 500 0.85 0.9 0.95 1 1.05 V PN (p.u.) time (sec.) 0 100 200 300 400 500 -0.04 -0.02 0 0.02 0.04 V ref (p.u.) time (sec.) 0 100 200 300 400 500 -0.2 -0.1 0 0.1 0.2 Q ref (p.u.) time (sec.)
  • 10. 10 Simulation Results: Voltage Tracking Chang Vref of Bus12 from 0.923p.u to 0.94p.u 0 50 100 150 200 250 300 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 V PN (p.u.) time (sec.) 0 50 100 150 200 250 300 -0.02 -0.01 0 0.01 0.02 0.03 0.04 V ref (p.u.) time (sec.) 0 50 100 150 200 250 300 -0.3 -0.2 -0.1 0 0.1 Q ref (p.u.) time (sec.)
  • 11. 11 Conclusion and future works • MPC controller can handle voltage regulation and tracking at pilot buses in presence of disturbances. • A real-time validation is necessary for control algorithms such as MPC who requires time for calculations of the control input. • For larger scale networks, Centralized MPC computational burden may go beyond sample time of the controller. Decentralized MPC approach can be used as an alternative.
  • 12. 12 Acknowledgement • I would like to thank OPAL-RT technologies, and specifically ePHASORsim team who helped me to accomplish this project. • THANK YOU ALL
  • 13. 13 Question?

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