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.