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Bulk Power System Dynamics and Control V IREP2001:Onomichi GLOBAL HYBRID CONTROL OF POWER SYSTEMS. David J Hill City University of Hong Kong (on leave from Sydney University) Co-authors: Yi Guo, Mats Larsson, Youyi Wang. OUTLINE. Introduction - PowerPoint PPT Presentation
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Bulk Power System Dynamics and Control V
IREP2001:Onomichi
GLOBAL HYBRID CONTROL OF POWER
SYSTEMS
David J Hill City University of Hong Kong
(on leave from Sydney University)
Co-authors: Yi Guo, Mats Larsson, Youyi Wang
OUTLINE Introduction
Global Control Ideas
Global Transient Stability and Voltage Regulation
Emergency Voltage Control
Conclusions
GLOBAL CONTROL IDEAS
Introduction
Hybrid Models
Control Elements
Bifurcations and Global Control
Optimal Coordination and Swarming
Issues for Practical Implementation
Trends
Environmental limitsLoad growthDeregulation
All push the system harder
Mathematical Complexity
Stability margins reducing, ie more difficult dynamics (nonlinearity)
Interconnection, ie larger-scaleMore uncertainty
System structure changingNo nominal operating pointLess modelling data
Coordinated control with mixed signals, costs and actions (heterogeneity)
Specific Features of Complexity
Large-scale network structure Controls embedded, some with scope for tuning;
further design must allow for and enlist Hierarchical control structure Control actions largely determined and have diverse
timing, cost and priority Control goals are multi-objective with local and global
requirements which vary with operating state Control interacts with planning
Control Challenge
In general, we need a high-level version of distributed adaptive control which “swarms” around a complex system attacking problems as they arise, but keeping a meta-view so that other problems are not ignored
ie. “reconfigurability” built in
Hybrid Models
• dynamic state variables x• algebraic state variables ω • parameters/controls u)
Control Elements
Those existing controllers and their tunable parameters which are free to adjust for system-wide purposes
),);(,,( iiiiiii kzxUu
Bifurcations and Global Control
Power systems have benefited from bifurcation theory
Most nonlinear control methodology does not recognise bifurcations
Bifurcation Control
Avoiding the bifurcation Eliminating the bifurcation“Delaying” the bifurcationStabilisation through bifurcations
Can we control across boundaries?
What Can Modern Control Do?
Robust control
Adaptive control
Nonlinear control
Fuzzy control
Neural control
A Strategy
Bifurcation boundaries define domains of operation where dynamical behaviour is qualitatively different
Design controllers for each region and switch between them
2211 uuuu e
Optimal Coordination and Swarming
• Nonlinear, multiple controls
• Swarming via
• Optimal coordination via
ii
ie
iiiiiii
uuu
kzxUu
),);(,,(
Global Control
Global view of nonlinear systemState space segmentation into structurally stable
regions Identification of regional controllers
• local models• various control objectives• different regional controller design approaches
Combination and coordination of regional controllers, e.g. scheduling, switching, hierarchical, hybrid control
Control Algorithms
Local tunable controllers, eg robust, adaptive etc
Optimal control (hybrid systems) Staged optimisation Predictive control
Speed-gradient and passivity Structure in HJ eqn, etc
GLOBAL TRANSIENT STABILITY AND VOLTAGE
REGULATION Introduction
Dynamical Model
Local Controllers
Global Controller
Reference:
Y Guo, DJHill and Y Wang, Global transient stability and voltage regulation for power systems, IEEE Trans Power Systems, to appear.
Introduction
Transient stability and voltage regulation are required at different stages of system operation
Deal with the two problems separately, or employ a switching strategy of two different controllers which causes a discontinuity of system behaviour
Aim to design global control law to co-ordinate the transient stabilizer and voltage regulator, using heterogeneous control strategy
The global control objective is achieved with smooth and robust responses with respect to different transient faults.
SMIB Power System Model
Local Controllers
Transient controller:
Voltage controller:
A Switching Controller
(t0 is the fault occuring time, ts is the switching time)
Disadvantages:• The switching time is fixed; • Not robust with respect to different faults.
01f
2f
ttwhenutstwhenuf {u
Global Controller Design
The fault sequence is NOT known beforehand
The control law in each region is specified to be the usual type developed from model-based (nonlinear) control techniques
The global control law is the above weighted sum of local controllers type, which achieves smooth transitions between the transient period and post-transient period
The controller is globally effective in the presence of different uncertain faults; also the controller is robust with respect to parameter uncertainties
Global Controller Design
Operating region membership function:
Global Controller Design
Global control law:
Advantages:• Control action is determined by online measurement of
power frequency and voltage, which makes it unnecessary to know the fault sequence beforehand
• The controller is globally effective in the presence of different uncertain faults
• The controller inherits the properties of local controllers, i.e., it is robust with respect to parameter uncertainties
2fV1ff uuu
Simulations
Temporary fault + permanent fault: Stage 1: The system is in a pre-fault steady stateStage 2: A fault occurs at t=t0
Stage 3: The fault is removed by opening the breakers of the faulted line at t=t1
Stage 4: The transmission lines are restored at t=t3
Stage 5: Another fault occurs at t=t4
Stage 6: The fault is removed by opening the breakers of the faulted line at t=t5
Stage 7: The system is in a post-fault stateIn the simulations, t0=0.1s, t1=0.25s, t3=1.4s, t4=2.1s, t5=2.25s;
=0.04.
EMERGENCY VOLTAGE CONTROL
Introduction
System Modelling
Control Problem Formulation
Tree Search Method
Simulation Results
Other Possibilities
Reference:
M Larsson, DJHill and G Olsson, Emergency voltage control using searching
and predictive control, International J of Electrical Power and Energy
Systems, to appear.
Coordinated Control Scheme(Popovic, Hill and Wu, presented in Santorini)
Provide voltage regulation
Provide security enhancement
Control actions• reactive power compensation
• tap regulation
• load control
• FACTs
Traditionally, done one by one, trial and error
Why coordination
• minimum overall effort / cost
• maximum control effect
• better voltage profile, ie. better quality of supply
Difficulty
• Combination of dissimilar controls
Optimal scheduling of control actions
Actual control sequence accounts for• combination of dissimilar controls
• different response speeds
• different dynamic characteristics
• priority
Optimal scheduling by• economic cost
• availability of controls
When, how to take actions at each step?
Problem formulation
subject to:
(i) controls capability constraints
(ii) stability constraints
mt
mt
N
ttt RxRppxCpJ
,),,(:)(min1
Ntppp uppertt
lowt ...2,1,
)()( 1argarg tinmtinm pSpS
Optimal Scheduling (=0.2)
Model Predictive Control approach
Widespread in process control
Multivariable, nonlinear allowed naturally
Constraint handling
Future behaviour predicted for many candidate input sequences
Optimal input sequence selected by (constrained) optimization
Optimization by search
All controls are switching actions
Combinatorial optimization problem
Organize control state space in tree structure
Search tree for optimum
Combinatorial explosion
Search heuristics
Similar problem as solved in chess
computers!
Numerical example
Simulation Example (Fig 17)
CONCLUSIONS
Complex System FeaturesGlobal ControlPossibilities for Power Systems
Complex System Features
Control over wide ranges of operating conditions Nonlinearity, ie control “in the large” High dimension, ie large-scale Multiple steady-state solutions Qualitatively different behavior under different operating
conditions Lack of complete explicitly analytical description Indices flag proximity to problems, ie bifurcations ‘Elements’ of control physically based Accommodate different control objectives Optimal coordination required
Global Control
Global view of nonlinear systemState space segmentation into structurally stable
regions Identification of regional controllers
• local models• various control objectives
Optimal combination and coordination of regional controllers, e.g. scheduling, switching, hierarchical, hybrid control
Swarming type adaptive control
Possibilities for Power Systems
Power systems are increasing in complexity
Security limits have huge financial implications
Control-based expansion
Modelling, analysis, control might all need to be redone
Develop hybrid, global models and control
Develop swarming type optimal hierarchical control of all available devices
Multi-level swarming, ie devices to system levels, according to where problem is
Adaptively group up the influential and available controls of various types to attack a problem as and when it arises
Project in HK considers power electronic controls.