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Demonstration of Using Flywheels and FACTS Control for Transient
Stabilization and
Interactions with Transactive Energy Market
10th CMU Electricity Conference
April 1, 2015
Joint work with
Prof. Marija Ilic
[email protected]
Kevin Bachovchin [email protected]
Carnegie Mellon University
Milos Cvetkovic [email protected]
Massachusetts Institute of Technology
Martin Wagner [email protected]
Carnegie Mellon University
mailto:[email protected]:[email protected]:[email protected]:[email protected]
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Outline
Motivation for fast control
Transient stabilization using flywheel energy storage systems
Competitive control; cancel effect of wind disturbance
Demo on the Smart Grid in a Room Simulator (SGRS)
Interaction of flywheel control with transactive energy
market
Transient stabilization using FACTS devices Cooperative control
logic based on ectropy
Implications for SGRS numerical integration
2
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Motivation for Fast Control
Transactive energy control is a steady-state scheduling concept
Does not guarantee dynamic stability
Interest in implementing more renewable energy sources into
future power grids
Renewables introduce more uncertainty, intermittency and
unpredictability => a challenge for control design
Large sudden deviations in wind power can cause high deviations
in frequency and voltage
transient instabilities
Possible solution: fast energy storage flywheel energy storage
systems
FACTS devices 3
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Objective
4
P
PP
P
Use flywheels for transient stabilization of power grids in
response to large sudden wind disturbances
Design nonlinear power electronic control so that the flywheel
absorbs the disturbance and the rest of the system is minimally
affected
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Variable Speed Drives for Flywheels
5
Use AC/DC/AC converter to regulate the speed of the flywheel
(and hence the energy stored) to a different frequency than the
grid frequency
Controllable inputs are the switch positions in the power
electronics
Source: K. D. Bachovchin, M. D. Ilic, "Transient Stabilization
of Power Grids Using
Passivity-Based Control with Flywheel Energy Storage Systems,"
IEEE Power & Energy
Society General Meeting, Denver, USA, July 2015..
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Controller Implementation
6
Time-scale separation to simplify the control design
Regulate both the flywheel speed and the currents into the power
electronics using nonlinear passivity-based control
Source: K. D. Bachovchin, M. D. Ilic, "Transient Stabilization
of Power Grids Using
Passivity-Based Control with Flywheel Energy Storage Systems,"
IEEE Power & Energy
Society General Meeting, Denver, USA, July 2015..
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Transient Stabilization Using Flywheels
7
P
P
Want to choose set points so that the wind disturbance power
goes to the flywheel and rest of the system is minimally
affected
P
P
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Simulation Results: Flywheel
8
0 0.2 0.4 0.6 0.81230
1240
1250
1260
1270
1280
1290
time(sec)
angula
r velo
city(r
ad/s
ec)
Flywheel Speed
ref
Since the power output of the wind generator decreases during
the disturbance, the flywheel set point decreases
0 0.2 0.4 0.6 0.80.23
0.235
0.24
0.245
0.25
0.255
0.26Wind Generator Mechanical Torque
time(sec)
torq
ue(N
*m)
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Simulation Results: Power Electronics
9
The set points for the power electronic currents are chosen so
that the total current out of Bus 2 remains constant during the
disturbance
0 0.2 0.4 0.6 0.81.6
1.8
2
2.2
2.4
curr
ent(
A)
Power Electronic and Wind Currents
i1d
+iSdW
0 0.2 0.4 0.6 0.819.98
19.99
20
20.01
20.02
t(sec)
curr
ent(
A)
i1q
+iSqW
0 0.2 0.4 0.6 0.8-254
-253
-252
-251
curr
ent(
A)
Power Electronic Currents
0 0.2 0.4 0.6 0.833
34
35
36
37
t(sec)
curr
ent(
A)
i1d
i1dref
i1q
i1qref
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Simulation Results: Rest of System
10
With the control, the effect on the rest of the system is very
minimal and lasts only a short time
0 0.2 0.4 0.6 0.80.064
0.065
0.066Bus 1 Voltage: Direct Component
voltage(V
)
Vd (Control)
Vd (No Control)
0 0.2 0.4 0.6 0.81.99
1.995
2Bus 1 Voltage: Quadrature Component
t(sec)
voltage(V
)
Vq (Control)
Vq (No Control)
0 0.2 0.4 0.6 0.80.0725
0.073
0.0735
0.074
0.0745Bus 2 Voltage: Direct Component
voltage(V
)
V
d (Control)
Vd (No Control)
0 0.2 0.4 0.6 0.81.99
1.995
2
2.005Bus 2 Voltage: Quadrature Component
t(sec)
voltage(V
)
Vq (Control)
Vq (No Control)
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Linking Multi Time-Scale Simulations
11
Communication for multi time-scale simulation with ALM and fast
dynamics for generators
Source: M. R. Wagner, K. D. Bachovchin, M. D. Ilić, "Computer
Architecture and Multi
Time-Scale Implementations for Smart Grid in a Room Simulator,"
EESG Working
Paper No. R-WP-1-2014, March 2015.
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Importance of Reactive Power
Typically the market only specifies the active power set
point
However the reactive power is critically important to the
equilibria and stability of the system
12
Voltage V2 (pu)
2 (
rad)
Power Factor PF = 0.99 (Without Shunt Capacitor)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
-3
-2
-1
0
1
2
3
Manifold of Active Power Balancing Eqn at Bus 2
Manifold of Reactive Power Balancing Eqn at Bus 2
[0.9615, -0.18 rad]
[0.182, -1.27 rad]
Voltage V2 (pu)
2 (
rad)
Power Factor PF=0.2 (Without Shunt Capacitor)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
-3
-2
-1
0
1
2
3
Manifold of Active Power Balancing Eqn at Bus 2
Source: X. Miao, K. D. Bachovchin, M. D. Ilić, "Effect of Load
Type and Unmodeled
Dynamics in Load on the Equilibria and Stability of Electric
Power System," EESG
Working Paper No. R-WP-1-2014, March 2015.
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Flores Island – Market
Based on prices, market computes active power set points P* from
each component
13
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Flores Island – Dynamics
Since currently the market does not specify reactive power set
points Q*, data for Q* is randomly created
Place a voltage source inverter and the variable speed drive on
the hydro and diesel generator buses
Control the sum of the power out of the hydro and diesel
generators to match the active and reactive power set points
14
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Simulation Results – Combining Dynamics and ALM
15 0 20 40 60 80 100
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
t(min)
voltage(V
)
Wind Generator Bus Voltages
vB2d
vB2q
Stable Case: Unstable Case:
0 20 40 60 80 100-0.2
0
0.2
0.4
0.6
0.8
1
1.2
t(min)
voltage(p
u)
Wind Generator Bus Voltages
vB2d
vB2q
0 20 40 60 80 1000
5
10
t(min)
pow
er(
pu)
Reactive Power Load Consumption
0 20 40 60 80 1000
5
10
t(min)
pow
er(
pu)
Reactive Power Load Consumption
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Transient Stabilization of Interactions Using FACTS
Transient stability problem • Nonlinear dynamics • Multiple time
scales • Large regions
Unstable
Cooperative power electronics (FACTS) control • Fast thyristor
switching
• Flow control
Stable
Interactions are captured using an energy-based model •
Accumulated energy as a measure of
stability • Managing energy to ensure stability
Large scale interconnected power system
Implications for SGRS distributed integration
of differential equations
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Common Modeling Approach for FACTS Control
Create a simplified power system model
Control logic is case dependent
Loaded as test case for transients simulator
Create a structure preserving system model by combining dynamic
models of individual components
Coupling achieved through states on ports of components 𝑦𝑖 ,
𝑝𝑖
Competitive control design
Component-based approach to modeling
Module description 𝑥 𝑖 = 𝑓𝑖 𝑥𝑖 , 𝑦𝑖 , 𝑢𝑖 , 𝑑𝑖
𝑦𝑖 = 𝑦𝑖𝑗(𝑥𝑗) 𝑦𝑖𝑘(𝑥𝑘)
𝑝𝑖 = 𝑝𝑖𝑗(𝑥𝑖) 𝑝𝑖𝑘(𝑥𝑖)
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Proposed Modeling Approach
Represent components of power systems using a two-level model
which separates their internal dynamics from the dynamics of their
interactions
Internal dynamics are described using internal dynamic states
𝑥
Interaction dynamics are described using interaction variables
𝑧
Interaction variable-based
modeling
Two-level module description
𝑥 𝑖 = 𝑓 𝑖 𝑥 𝑖 , 𝑧𝑖 , 𝑃𝑖𝑘 , 𝑃𝑖𝑗 , 𝑢𝑖 , 𝑑𝑖
𝑧 𝑖 = 𝑔𝑖 𝑥 𝑖 , 𝑧𝑖 , 𝑃𝑖𝑘 , 𝑃𝑖𝑗 , 𝑢𝑖 , 𝑑𝑖
Interaction variable 𝒛 is the accumulated energy inside a
module.
M. Cvetkovic, M. Ilic, “A Two-level Approach to Tuning FACTS for
Transient Stabilization”,
IEEE PES General Meeting, July 2014.
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Proposed Cooperative Controller
Redistribute energy of disturbance
Cooperative control is expressed in terms of higher
(interaction) level dynamics
Enabled by using time scale separation between interaction and
internal level dynamics
Accumulated (stored) energy in an uncontrolled system
Accumulated (stored) energy in a system controlled by power
electronics
FACTS Generator
Generator FACTS
M. Cvetkovic, M. Ilic, “Ectropy-based Nonlinear Control of FACTS
for Transient Stabilization”,
IEEE Transactions on Power Systems, Vol. 29, No. 6, November
2014, pp. 3012-3020.
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SGRS Hierarchical Distributed Simulation of Dynamics
Aggregation od dynamics using interaction variables separates
the rate of exchange of information and the rate of internal state
computations
Interaction variable update at a slower rate n
Internal states update at a faster rate k
Interactions coming from other modules at time n
Interactions going toward other modules at time n+1
Zoom-out level
Zoom-in level
States at k+1 Interaction at n+1
M. Cvetkovic, M. Ilic, “Dynamic Simulation of Power System
Transients in Energy State Space”, in preparation.
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Response of Uncontrolled System
Short circuit at bus 3
in duration of 0.35 sec
M. Cvetkovic, M. Ilic, “Cooperative Line-flow Power Electronics
Control for Transient Stabilization”, IEEE Conference on Decision
and Control, December 2014.
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Controlled System Response
22
𝑃𝜏3 =1
𝜏3 𝑃𝜏2𝑑𝑡
𝜏2
FACTS energy has
reached zero
𝑧2 = 0
States converge to a different equilibrium
M. Cvetkovic, M. Ilic, “Cooperative Line-flow Power Electronics
Control for Transient Stabilization”, IEEE Conference on Decision
and Control, December 2014.
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Questions?
