Download Demonstration of Using Flywheels and FACTS Control for Transient Stabilization and

Demonstration of Using Flywheels and FACTS
Control for Transient Stabilization and
Interactions with Transactive Energy Market
Kevin Bachovchin
Milos Cvetkovic
Martin Wagner
[email protected]
Carnegie Mellon University
[email protected]
Massachusetts Institute of
Technology
[email protected]
Carnegie Mellon University
10th CMU Electricity Conference
April 1, 2015
Joint work with
Prof. Marija Ilic
[email protected]
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
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
Objective
 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
P
P
P
P
4
Variable Speed Drives for Flywheels
 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..
5
Controller Implementation
 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..
6
Transient Stabilization Using Flywheels
P
P
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
7
Simulation Results: Flywheel
 Since the power output of the wind generator decreases during the
disturbance, the flywheel set point decreases
Wind Generator Mechanical Torque
Flywheel Speed
angular velocity(rad/sec)
0.26
torque(N*m)
0.255
0.25
0.245
0.24
0.235
0.23
0
0.2
0.4
time(sec)
0.6
0.8
1290

1280
ref
1270
1260
1250
1240
1230
0
0.2
0.4
time(sec)
0.6
0.8
8
Simulation Results: Power Electronics
 The set points for the power electronic currents are chosen so that
the total current out of Bus 2 remains constant during the
disturbance
Power Electronic and Wind Currents
Power Electronic Currents
2.4
current(A)
current(A)
-251
-252
i1d
-253
-254
iref
1d
0.2
0.4
0.6
1.8
0
0.8
0.2
0.4
0.6
0.8
20.02
36
i1q
35
iref
1q
current(A)
current(A)
2
1.6
0
37
34
33
i1d+iSdW
2.2
0
0.2
0.4
t(sec)
0.6
0.8
i1q+iSqW
20.01
20
19.99
19.98
0
0.2
0.4
t(sec)
0.6
0.8
9
Simulation Results: Rest of System
 With the control, the effect on the rest of the system is very
minimal and lasts only a short time
0.0745
voltage(V)
0.066
voltage(V)
Bus 2 Voltage: Direct Component
Bus 1 Voltage: Direct Component
Vd (Control)
Vd (No Control)
0.065
0.064
0.2
0.4
0.6
Vq (Control)
Vq (No Control)
0.2
0.4
t(sec)
0.6
0.2
0.4
0.6
0.8
2
0.8
Vq (Control)
1.995
1.99
0
0
Bus 2 Voltage: Quadrature Component
voltage(V)
voltage(V)
0.073
2.005
2
1.995
Vd (No Control)
0.0735
0.8
Bus 1 Voltage: Quadrature Component
1.99
0.074
0.0725
0
Vd (Control)
Vq (No Control)
0
0.2
0.4
t(sec)
0.6
0.8
10
Linking Multi Time-Scale Simulations
 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.
11
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
Power Factor PF = 0.99 (Without Shunt Capacitor)
Power Factor PF=0.2 (Without Shunt Capacitor)
3
3
Manifold of Active Power Balancing Eqn at Bus 2
Manifold of Active Power Balancing Eqn at Bus 2
Manifold of Reactive Power Balancing Eqn at Bus 2
2
2
[0.9615, -0.18 rad]
1
2 (rad)
2 (rad)
1
0
0
-1
-1
[0.182, -1.27 rad]
-2
-2
-3
-3
0
0.5
1
1.5
2
2.5
3
Voltage V2 (pu)
3.5
4
4.5
5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Voltage V2 (pu)
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.
12
5
Flores Island – Market
 Based on prices, market computes active power set points P*
from each component
13
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
Simulation Results – Combining Dynamics and ALM
Unstable Case:
Reactive Power Load Consumption
10
5
0
0
20
40
60
80
100
power(pu)
power(pu)
Stable Case:
Reactive Power Load Consumption
10
5
0
0
20
40
80
100
t(min)
t(min)
Wind Generator Bus Voltages
Wind Generator Bus Voltages
1.2
1.2
1
1
0.8
vB2d
vB2q
0.6
0.4
voltage(V)
voltage(pu)
60
0.8
vB2d
0.6
vB2q
0.4
0.2
0
0.2
-0.2
0
-0.2
-0.4
0
20
40
60
t(min)
80
100
-0.6
0
20
40
60
t(min)
80
15
100
Transient Stabilization of Interactions Using FACTS
Implications for SGRS
distributed integration
of differential equations
Large scale
interconnected
power system
Transient stability problem
•
•
•
Nonlinear dynamics
Multiple time scales
Large regions
Unstable
Stable
Interactions are captured using
an energy-based model
•
•
Accumulated energy as a measure of
stability
Managing energy to ensure stability
Cooperative power
electronics (FACTS) control
•
Fast thyristor switching
•
Flow control
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
Module description
𝑥𝑖 = 𝑓𝑖 𝑥𝑖 , 𝑦𝑖 , 𝑢𝑖 , 𝑑𝑖
𝑦𝑖 = 𝑦𝑖𝑗 (𝑥𝑗 ) 𝑦𝑖𝑘 (𝑥𝑘 )
𝑝𝑖 = 𝑝𝑖𝑗 (𝑥𝑖 )
Component-based
approach to modeling
𝑝𝑖𝑘 (𝑥𝑖 )
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
Two-level module description
𝑥𝑖 = 𝑓𝑖 𝑥𝑖 , 𝑧𝑖 , 𝑃𝑖𝑘 , 𝑃𝑖𝑗 , 𝑢𝑖 , 𝑑𝑖
𝑧𝑖 = 𝑔𝑖 𝑥𝑖 , 𝑧𝑖 , 𝑃𝑖𝑘 , 𝑃𝑖𝑗 , 𝑢𝑖 , 𝑑𝑖
Interaction
variable-based
modeling
M. Cvetkovic, M. Ilic, “A Two-level Approach to Tuning FACTS for Transient Stabilization”,
IEEE PES General Meeting, July 2014.
Interaction variable 𝒛 is the
accumulated energy inside a module.
Proposed Cooperative Controller
Accumulated (stored) energy
in an uncontrolled system
Generator
FACTS
 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 a system
controlled by power electronics
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.
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
Interactions coming from other modules at time n
Interaction variable update at a slower rate n
Interaction at n+1
Zoom-out level
States at k+1
Internal states update at a faster rate k
Zoom-in level
Interactions going toward other modules at time n+1
M. Cvetkovic, M. Ilic, “Dynamic Simulation of Power System Transients in Energy State Space”, in preparation.
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.
Controlled System Response
𝑃𝜏3 =
1
𝜏3
𝑃𝜏2 𝑑𝑡
𝜏2
𝑧2 = 0
FACTS energy has
reached zero
States converge
to a different
equilibrium
22
M. Cvetkovic, M. Ilic, “Cooperative Line-flow Power Electronics Control for Transient Stabilization”, IEEE Conference on Decision and Control, December 2014.
Questions?