HVDC Power Injection

8/20/2019 HVDC Power Injection

1/10

1160 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 28, NO. 2, MAY 2013

Damping of Inter-Area Oscillations in MixedAC/DC Networks Using WAMS Based

Supplementary Controller Robin Preece , Student Member, IEEE , Jovica V. Milanović , Fellow, IEEE , Abddulaziz M. Almutairi , Member, IEEE ,

and Ognjen Marjanovic , Member, IEEE

Abstract— The paper presents a supplementary VSC-HVDC

Power Oscillation Damping (POD) controller based on widearea measurement signals (WAMS). The controller is designedas Multi Input Single Output (MISO) using a Modal LinearQuadratic Gaussian (MLQG) methodology in order to targetcritical inter-area electromechanical modes. The approach hasbeen tested on a large (16 machine, 68 bus) test network incorpo-

rating parallel HVDC/AC transmission and has shown improveddamping compared to a traditional Power System Stabilizer

(PSS) based controller structure utilizing local signals. The designprocess has incorporated the effects of wide area signal transmis-

sion delays. Variation in these signal delays and the complete lossof signals has been also investigated to establish the robustness of

the WAMS based controller and its sensitivity to loss of signals.Extension of the controller to incorporate reactive power modu-lation has been investigated, as has variation in available activepower modulation capacity. The proposed controller performance

has been assessed through small and large disturbance analysis.

Index Terms— Electromechanical modes, Linear Quadratic

Gaussian (LQG) control, power oscillation damping, VSC-HVDC.

I. I NTRODUCTION

E LECTRICITY transmission networks of the future areexpected to incorporate large numbers of HVDC lines,leading to many instances of HVDC operation in parallel with

AC lines. Worldwide interest in large renewable generation

sources, often either offshore or long distances from traditional

load centers is increasing. Moreover, in many cases planning

consent for new overhead lines is becoming increasingly

dif ficult to obtain, discouraging AC network reinforcements

as too lengthy and costly. HVDC systems with higher power

transfer capacities per line, feasible lengthy subsea installations

and no technical line length limitations provide an attractive

alternative [1]. In the U.K., this is especially true with two

Manuscript received January 09, 2012; revised February 28, 2012 and May15, 2012; accepted June 30, 2012. Date of publication August 15, 2012; date of current version April 18, 2013. This work was supported in part by the Engi-neering and Physical Sciences Research Council (EPSRC) and in part by Na-tional Grid Plc. Paper no. TPWRS-00030-2012.

R. Preece, J. V. Milanović, and O. Marjoanovic are with the School of Elec-trical and Electronic Engineering, The University of Manchester, Manchester M60 1QD, U.K. (e-mail: [email protected]; [email protected]).

A. M. Almutairi is with the College of Technological Studies, PAAET,Kuwait.

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TPWRS.2012.2207745

planned HVDC links to operate in parallel with the existing

grid. These links will help to facilitate the increased power

transfer from the north to the south of the country when large

renewable generation capacity is connected [2].

A further benefit of HVDC that is largely unused in practical

installations is that of power oscillation damping (POD). With

fast acting power electronics within the converter stations it is

possible to rapidly vary power flow through the HVDC line.

The potential for power injection control at non-generator buses

(where HVDC systems are typically installed) has attracted re-

cent interest and it has been shown that HVDC systems can be

used with POD controllers to damp inter-area electromechan-

ical oscillations [3]–[7].

This paper first presents a traditional Power System Stabi-

lizer (PSS) based design for the supplementary HVDC POD

controller with local signal input. Following this a more robust

Wide Area Measurement Signals (WAMS) based controller

is designed using a targeted novel modal Linear Quadratic

Gaussian (MLQG) methodology.

LQG POD controllers have been applied to both centralized

generator control [3], [4] and fast acting FACTS devices suchas Thyristor Controlled Series Capacitors (TCSCs) [5]–[7]. The

paper shows that the novel MLQG controller design is effec-

tive with an HVDC application. This design approach utilizes

multiple global network signals subjected to transmission de-

lays but controls only the HVDC line active power injection.

The MLQG approach enables targeted damping only of the crit-

ical inter-area system modes, leaving local modes unaffected.

Through this design, vastly improved post-disturbance system

stability is observed.

The simplicity and transparency of this design approach

distinguishes this controller from other existing multivariable

synthesis techniques. Controller tuning is completed simply

and effectively by applying nonzero weights only to thosetargeted modes requiring supplementary damping. This is far

easier than the case of standard LQG, requiring participation

analysis and complex weightings, and approaches, where

weighting functions must accurately model the uncertainties to

ensure the practical robustness of the controller.

II. MODAL LINEAR QUADRATIC GAUSSIAN CONTROL

The LQG control design is a cornerstone of modern optimal

control theory and its advantages led to widespread research

into it use in power system damping [3]–[7]. However, the de-

sign approach is rarely straightforward, especially within large

power systems where many generators participate in the critical

0885-8950/$31.00 © 2012 IEEE


2/10

PREECE et al.: DAMPING OF INTER-AREA OSCILLATIONS IN MIXED AC/DC NETWORKS 1161

modes which require additional damping. In these situations,

the controller tuning process can become prohibitively complex.

Specifically, the issues arise surrounding the correct selection of

system states upon which to target controller action.

Participation factor analysis is required to identify the electro-

mechanical states involved in targeted system modes. Weight-

ings can then be assigned to these states. However, if these states

are involved in other targeted modes (or modes that do not re-quire altering), the damping of these modes will also be affected,

sometimes adversely. This results in a complex and time con-

suming tuning process in which it is often not possible to obtain

exact target damping factors. These complexities and problems

can be overcome through the novel use of a modal representa-

tion of the control design problem discussed below.

Consider the following linearized state-space plant (power

system) model [8] described by (1) and (2):

(1)

(2)

where w is process noise and v is measurement (sensor)

noise. They are usually assumed to be uncorrelated zero-mean

Gaussian stochastic processes with constant power spectral

density matrices and respectively. The LQR control

problem, in the modal formulation [9], is to devise a feedback

control law, which minimizes the cost function (3):

(3)

where and are appropriately chosen weighting matricessuch that and , and is

a real matrix which provides mapping between system modal

variables and state variables as in (4):

(4)

where modal variables are directly associated with system

modes ( where ). The real transformation ma-

trix is obtained using Real Schur Decomposition [10] and

relates to the matrix of right eigenvectors as .

The weighting matrices and are commonlyconstructed

as diagonal. Values of the diagonal elements of are set in order

to penalize the corresponding controller’s outputs from high ac-tions. Values of the diagonal elements of are set in order

to penalize the corresponding modal variables when deviating

from their steady-state values. Each diagonal element in

is directly associated with a modal variable and hence with

the corresponding mode . A higher value of modal weight

corresponds to a higher effort by the controller to stabilize the

corresponding mode. In order to focus on adding damping to the

modes of interest only, these modes will be given some weights

in while the other modes’ weights are set to zero. In this

way, control effort of the designed LQR is directed towards the

modes of interest only, by shifting them to the left in the com-

plex plane, while keeping locations of other modes unaltered.

The LQR controller gain is computed by solving the asso-

ciated algebraic Riccati equation (ARE), based on cost function

(3), and the final LQG feedback control law can be written as

(5):

(5)

where is an estimate of the states obtained using Kalman

filter, described by (6):

(6)

where is a constant estimation error feedback matrix. The

optimal choice of is that which minimizes

. It is calculated by solving the ARE associated with the cost

function (7):

(7)

In this paper, the weighting matrices and are tuned

using the loop transfer recovery (LTR) procedure at plant input

[8]. The Kalman filter is synthesized such that the loop transfer

function , where is the plant transfer func-

tion, approaches the LQR loop transfer function

. The tuning parameters of Kalman filter are

calculated as in (8) and (9):

(8)

(9)

where and refer to the nominal model, is any positive

definite matrix and is a constant.Full recovery of robustness is achieved as . Care is re-

quired as full recovery would lead to excessively high gains and

therefore deteriorates the nominal performance of the true noise

problem. For non-minimum phase systems, which is a common

case in power systems, only partial recovery can be achieved

[8].

The closed-loop dynamics of the LQG controller can be de-

scribed by (10):

(10)

and the transfer function of the LQG controller, from to , isthen given by (11):

(11)

The novel modal LQG (MLQG) controller provides many

benefits of the traditional LQG approach:

• Participation factor analysis is no longer required as LQR

weightings directly correspond to system modes.

• It is simple to address the damping of several modes by

providing non-zero weightings to all modes requiring ad-

ditional damping.

• Exact damping factors can be achieved if desired through

fine tuning of the weightings.


3/10


Fig. 1. Injection model for an HVDC line in parallel with an AC line.

• All untargeted modes are left completely unaffected by

the controller, allowing local controllers to maintain good

damping.

A full comparison between the traditional and modal LQG

controller designs is presented in [9].

III. HVDC MODELING

HVDC system modeling can range in complexity from full

detail models which include valve switching to simple models

which are only acceptable when the HVDC system is remote

and has no significant impact on the stability analysis [11]. Thisresearch is concerned with electromechanical oscillations and

so the operation of the power electronics within the HVDC con-

verter stations is neglected. As such, the converter stations are

represented simply as sinks and sources of active and reactive

power [12].

A. Injection Modeling

The method employed to model the HVDC system is injec-

tion modeling [13]. The model complexity is determined by the

level of detail required for the studies being performed. Concep-

tually, the HVDC converter stations are replaced by equivalent

generator buses connected to the AC system across a reactance

, representing the converter transformer. Hence, the equiva-

lent injection model for an HVDC line in parallel with an AC

transmission line is given by Fig. 1.

The voltage and angle at the equivalent generator buses are

varied to produce the desired power flow into and out of the

HVDC system as dictated by (12) and (13). This method can be

used to produce both voltage source conversion based HVDC

(VSC-HVDC) and line commutated conversion based HVDC

(LCC-HVDC) dynamic system models [14]:

(12)

(13)

B. VSC-HVDC Injection Model Development

The more recently operationally viable VSC-HVDC pro-

vides some benefits over its more established counterpart

LCC-HVDC, and is seeing an increase in popularity. Its

smaller footprint, decreased harmonic injection and reactive

power injection capabilities were previously compromised by

higher losses and lower operating capacities [15]. However

modular multi-level converters (MMC) have reduced these

losses to levels comparable with LCC systems and many

VSC-HVDC projects are currently under construction.

The internal current control loop of the VSC is modeled as

ideal for the system stability studies, meaning the active and

TABLE IACTIVE POWER IMPORTED I NTO NETS FROM SURROUNDING AREAS

WITH NO HVDC LINK I NSTALLED

reactive power control reference setpoints are met instantly.

Converter station controllers are or integral regulators

with clamped anti-windup. These controllers and the DC line

dynamics (modeled as a -section) are utilized to determine

the expected flow into and out of the VSC-HVDC system with

full description given in [14] and [16]. A common control

scheme is used with one converter maintaining the DC voltage

and the other regulating active power flow. Reactive power control is independent at each converter station. Additional

signals, and , are available to vary the active and

reactive power reference setpoints and modulate power flow

for stabilizing purposes.

IV. TEST SYSTEM

A 16-machine, 68-bus network is chosen as the test system

for the studies, shown in Fig. 2. This represents a reduced order

equivalent model of the New England Test System (NETS)

and the New York Power System (NYPS). Five separate areas

are present: NETS consisting of G1–G9, NYPS consisting of G10–G13, and three further infeeds from neighboring areas

are represented separately by G14, G15 and G16. All gener-

ators are represented by full sixth order models. Generators

G1–G8 are under slow DC excitation (IEEE-DC1A) while G9

is equipped with a fast acting static exciter (IEEE-ST1A) and

PSS. The remaining generators (G10–G16) are under constant

manual excitation. Power system loads are modeled as constant

impedance. Full system details, generator and exciter parame-

ters are given in [17] with PSS settings for G9 taken from [18].

All simulations are performed within the MATLAB/Simulink

environment making use of modified MATPOWER [19] to

perform initial load flows.

With loading as given in [17], the NYPS area is heavilyimporting power from the surrounding areas due to an active

power demand of 8.57 GW but generation of just 5.86 GW.

Details of the active power import across inter-area ties are

given in Table I. The infeed from the G16 area (along two

lines) is largest, accounting for over half the total active power

import into NYPS.

A VSC-HVDC link is introduced between the NYPS and

G16 areas to support this power infeed. The link is installed

in parallel with the most heavily loaded tie line, from bus 18

to bus 50. Normal operating capacity for the HVDC link is se-

lected as 400 MW. At this capacity, active power infeed from

the G16 area to NYPS through AC tielines is reduced com-

pared with those given in Table I: MW,

and MW. Import from area G14 is also


4/10


Fig. 2. 16-machine, 68-bus test system. Separate areas (NETS, NYPS, G14, G15, G16) shown with inter-area ties highlighted. VSC-HVDC link shown.

TABLE III NTER -AREA ELECTROMECHANICAL MODE DETAILS FOR TEST SYSTEM WITH STANDARD LOADING

slightly reduced with import from NETS largely unaffected. De-

tails about the VSC-HVDC line parameters and controller gains

are included in the Appendix.

Small signal analysis of the linearized system including the

VSC-HVDC reveals that with standard loading, as given in

[17], four poorly damped oscillatory inter-area electro-mechan-

ical modes are present which would benefit from improved

damping. These modes are detailed in Table II. All these

modes have damping factors, , below 5% which is considered

unsatisfactory in terms of control design objectives [18]. The

VSC-HVDC link is operating at 400 MW capacity with zero

reactive power injection . All local electro-mechan-

ical modes are adequately damped with .

V. POD CONTROLLER DESIGN

The general control overview for the 16-machine, 68-bus

network is shown in Fig. 3. For all designed supplementary

HVDC POD controllers, output was limited to just one signal,

. This signal is sent to the converter station regulating

active power injection. In this study this is the inverter con-

nected at bus 50. POD controller input signal transmission

delays are experienced only for wide area, or global, signals as

is discussed below.

A. SISO PSS Structure

1) Design Methodology: The initial design process for the

VSC-HVDC POD controller followed that of a conventional

Fig. 3. Test network control overview.

Fig. 4. PSS based SISO POD controller for HVDC.

PSS. This has been used previously with HVDC power mod-

ulation [20]–[23] and has been shown to be effective at modal

damping. The design consists of a washout filter, lead-lag blocks

and gain, as shown in Fig. 4. Controller parameters are depen-

dent upon the modes of interest to be damped.


5/10


TABLE IIIR ESIDUE A NGLES FOR MODES OF I NTEREST FOR HVDC PSS POD DESIGN

The residue based tuning method is used [24]. First, the

angles of the residue values, (of the open loop transfer

function between controller output and controller input), cor-

responding to the critical eigenvalues are assessed. In this case

the controller output will be the HVDC modulation reference,

, and the controller input is selected as a local signal,

the active power transfer into bus 50 from bus 18 through

the parallel AC transmission line, . The phase com-

pensation required by the PSS is then calculated simply as

(to shift the eigenvalue further into the

left half of the complex plane with no change in frequency). Pa-

rameters for the lead-lag blocks are then determined according

to the required phase compensation desired.

Shown in Table III are the residue angles and required PSS

compensation angles for the four poorly damped inter-area

modes. As the lead-lag block is tuned for a specific compensa-

tion angle at a specific frequency [24] it is clearly not possible

to optimally tune the PSS for multiple modes.

Tuning is carried out for the inter-area mode for which the

magnitude of the residue value suggests greatest modal control-

lability will occur given the controller input signal [11]. Residue

magnitude values are also shown in Table III, normalized for the

largest value. As Mode 1 is most controllable, tuning is carriedout for these modal characteristics at a standard VSC-HVDC

operating capacity of 400 MW. Final controller parameters are

given in the Appendix.

2) Small Signal Analysis: The improvement in modal

damping with the PSS based SISO POD controller installed

is shown in Fig. 6. As a local input signal is selected, it is as-

sumed that there is no transport delay associated with receiving

the signal . Similarly, it is assumed that the POD

controller is located at the VSC-HVDC converter station con-

trolling active power regulation, and no output signal transport

delays are modeled.

Very slight improvement is seen in all inter-area modes,

though only Modes 1 and 2 cross the 5% damping thresholdwith damping coef ficient increasing to 7.08% and 5.44%,

respectively. All local modes remain damped with .

The small signal analysis performed suggests that the PSS-

based POD has limited influence upon the critical inter-area

electromechanical oscillations present within the test network.

This may be in part due to limited modal observability [11]

within the local input signal . This is a problem that

can be overcome through use of global signals within a multiple

input control structure.

B. MISO Modal LQG Controller Design

To allow targeted damping of oscillatory electromechanicalmodes, MLQG was selected as the controller design approach.

Selection of inputs to the controller is determined through a

full modal observability assessment for the network [11]. The

number of required signals depends upon the number of crit-

ical modes requiring additional damping and the observability

of these modes within the available system signals. Networks

containing a large number of PMUs will be able to exploit these

available signals to gain a highly accurate representation of the

network’s oscillatory nature following disturbances. Within thisstudy, active power flow through lines from bus 45 to bus 51

, bus 68 to bus 18 , bus 65

to bus 17 , and from bus 67 to bus 42

were determined to display greatest observability of

the critical Modes 1 to 4, respectively.

A MISO MLQG power oscillation damping controller was

designed, as described in Section II, for the standard operating

conditions with a VSC-HVDC operational capacity of 400 MW.

Controller inputs are as described above and controller output

was limited to .

Often when performing LQG control design it is necessary to

perform initial model order reduction to avoid ill conditioningwhen solving high order matrix Riccati equations [6]. This

problem was not experienced and so controller design was

carried out using the full linearized system model.1) Incorporating Signal Delays: As remote signals are

assumed to be sent through pre-existing communications links

(and not dedicated signal transmission hardware), delays be-

tween the instant of measurement and the signal reaching the

controller are experienced. Dependent upon various factors,

including distance and communication protocols, these delays

can be in the range of a few hundreds of milliseconds [25]. In

the simulations performed, global network signals are assumed

to have associated transport delays of 500 ms. These signal de-

lays are modeled as 2nd order Padé approximations [26] duringmodel linearization and controller design. As with the PSS

based POD controller, it is assumed that the POD controller

is located at the VSC-HVDC converter station and no output

signal transport delays are modeled.

The introduction of delays to the controller input signals af-

fects the LTR process during the design of the LQG controller.

The degree of recovery achieved can be assessed through

comparison of the singular value plots for both and

. With parameters , , , and set to

fixed values as given in the Appendix, the LTR procedure was

completed for , shown in Fig. 5. Increasing

beyond 100 provides no further discernable improvement in

recovery in the frequency range of interest. Fig. 5 demonstrates

that with the signal transport delays included, full recovery of

the robustness properties of is not possible, even

for large . For the rest of the design process, was fixed

at 1, providing a compromise between optimal recovery of

robustness properties and unacceptably high filter gains.

2) Small Signal Analysis and Controller Reduction: Small

signal analysis on the closed loop system (of Fig. 3) demon-

strates the improvements seen in damping of all critical

inter-area modes. This is shown in Fig. 6 where it can be

seen that all critical modes now achieve damping greater than

5%. Modes 1 to 4 are now damped with values of 19.39%,

15.93%, 14.09%, and 11.63%, respectively. This is not onlygreatly improved over the “no POD” case but also over the


6/10


Fig. 5. LTR process at plant input with varying valueswith delayed controller input signals.

Fig. 6. Modal placement with no POD, PSS-based POD, full order MLQGPOD, and reduced order MLQG POD (dashed line signifies 5% damping).

modal placements for the PSS-based POD controller. With the

targeted modal damping from the MLQG controller affecting

solely the inter-area Modes 1 to 4, all local modes remain

unaffected and adequately damped with .

The designed MISO MLQG controller as defined by (11) is

of 182nd order, equal to the full linearized system model order.

It is desirable to reduce this in order to decrease the online com-

putational burden of the controller whilst still maintaining the

improved critical mode damping.The balanced Schur reduction method [27] was applied to the

controller, implemented within MATLAB. The limiting factor

upon the level of reduction permitted was chosen as the degra-

dation seen in the damping of critical modes through the use of

the reduced order controller. Allowable degradation was set at

5% of the full order controller values for each critical mode.

With this methodology, the MLQG POD controller was reduced

to 28th order. Small signal analysis of the closed loop system

with the reduced order controller provides values of 18.90%,

15.43%, 14.34%, and 11.70% for Modes 1 to 4, respectively,

also shown in Fig. 6.

The small signal analysis performed is dependent upon the

linearization of the nonlinear power network and elements such

as the signal transmission delays. Furthermore, the improve-

ment in inter-area mode damping is “ideal” and based on the

LQR state feedback control eigenvalue placement (which as-

sumes full state knowledge). The true performance and robust-

ness of the designed controller is dependent upon the Kalman

filter state estimator and is, therefore, most readily assessed

through transient simulations.

VI. CONTROLLER TRANSIENT PERFORMANCE

A. Variation in System Operating Conditions

Large disturbance transient studies have been performed for

two cases. These are:

Fig. 7. For base case, settling times for NYPS inter-area AC infeeds.

Fig. 8. For outage case, settling times for NYPS inter-area AC infeeds.

1) The base case, theoperating point for which the controllers

have been designed. System loading and generation is

as previously described. The VSC-HVDC is operating at

400-MW capacity with zero reactive power output. Alllines are in service. The system is subjected to a 100-ms

self-clearing fault at bus 38 at a time of 0.5 s.

2) The outage case. Still with standard loading, the line be-

tween bus 18 and bus 49 is removed from service. This line

provided a path for some of the power flow from the G16

area to NYPS. As a consequence, power flow through the

line from bus 18 to bus 50 is increased. VSC-HVDC oper-

ational capacity is increased slightly to 450 MW to aid this

transmission, still with zero reactive power injection. The

system is then subjected to a 100-ms fault near to bus 1 on

the line from bus 1 to bus 30, at a time of 0.5 s, cleared by

disconnecting the line.These transient studies were performed for the case with no

POD controller installed, with PSS-based POD, and with the re-

duced order MLQG POD including signal delays. VSC-HVDC

modulation was limited to 100 MW.

1) Transient Results and Discussion: Settling times were

recorded from the point of fault clearance to the time at which

the power deviation was within 1% of the steady state value

(or 1 MW, whichever was greatest). These times are shown

for the NYPS inter-area AC infeeds (as detailed in Table I) in

Figs. 7 and 8.

Looking first at the base case (Fig. 7), the inter-area infeed

power flows demonstrate the considerably improved modal

damping of the MLQG controller. All infeeds settle in less than12 s, compared with 23 s with the PSS-based POD controller

installed, and 31 s with no damping controller.

With the outage case (Fig. 8), the settling times of the AC

NYPS infeeds show the robustness of the MISO MLQG con-

troller to varying operating point. The improved performance

over the PSS-based controller is still pronounced with all ties

settling within 19 s (compared to 33 s for the PSS-based POD

and 40 s when no POD controller is used).

Plots of the active power injected at bus 9 from bus 8 through

the AC infeed and the active power injected at bus 50 by the

VSC-HVDC are shown in Figs. 9(a) and 10(a). These show that

despite the separation between the point of control (the VSC-

HVDC link between buses 18 and 50) and a relatively distant

inter-area tie (bus 8 to bus 9), damping is still vastly improved.


7/10


Fig. 9. For base case: (a) Active power injected at bus 9 (NYPS) from bus8 (NETS), and (b) Active power injected at bus 50 by VSC-HVDC inverter station. : fault occurs, : fault cleared, PSS POD power modulation evident, : MLQG POD power modulation evident.

Fig. 10. For outage case: (a) Active power injected at bus 9 (NYPS) from bus8 (NETS), and (b) Active power injected at bus 50 by VSC-HVDC inverter station. : fault occurs, : fault cleared, PSS POD power modulation evident, : MLQG POD power modulation evident.

This is still evident forthe outage case, demonstrating the ability

of the MLQG controller to perform well as operating conditions

change.

The plots of the active power injected by the inverter,Figs. 9(b) and 10(b), present the control action of the various

POD controllers. The forced modulation of active power flow

through the VSC-HVDC link is used to stabilize the network.

With no POD it can be seen that the VSC-HVDC returns to

its steady state power injection setpoint rapidly. This can also

be seen to occur with the MLQG POD controller following

the disturbance at 0.5 s (labeled t1). It is not until 500 ms after

the fault instant (at ) that the controller input signals

display a disturbance and the HVDC active power modulation

begins. The active power modulation of the PSS POD using

signals with no delay is evident as soon as the fault is cleared

(at ).

Further investigation has been made into the effects of

varying operating conditions including generator and key tie

Fig. 11. Deterioration in damping of critical modes by MLQG controller withincreasing signal delay.

line outages with both the PSS-based POD and MLQG POD

controller, available in [28]. It should be noted that the MLQG

controller significantly outperformed the PSS-based controller

across wide ranging operating scenarios.

B. Variation in Wide Area Signal Delay and Loss of Signals

The use of wide area measurements has been demonstrated as

enabling a better, more robust controller design. These signals

are becoming more prevalent in modern power systems, pro-viding reliable real-time data which can improve many aspects

of system performance. However, these signals will often be

sent through pre-existing satellite communication links (as ded-

icated hard-wired links may prove prohibitively expensive) and

as such are potentially subject to increased delay or even com-

plete loss. If faster communication channels (e.g., fi ber optic

links) are available then the shorter associated delays should be

included in the controller design stage. However, controller per-

formance will only improve as signal delays shorten [9].

The effects of signal latency and mitigation techniques for

use with WAMS based controllers has been a topic of much in-

terest. Readers are directed towards [29]–[34] for comprehen-sive analyses of these effects and novel mitigation techniques

to improve controller performance in the presence of signal la-

tency. For the novel MLQG controller, the effects of increased

signal delays and the complete loss of signals have been investi-

gated in order to demonstrate the controller’s robustness to these

problems.

The controller’s local signal to the VSC-HVDC converter sta-

tion is assumed to be hard-wired and not subject to these issues.

In addition to the results investigating the robustness of the con-

troller to varying system operating conditions, the MLQG con-

troller has also been tested to determine the robustness to vari-

ation in signal delay and complete loss of input signals. Fig. 11

shows the deterioration seen in the damping of all critical modesas the delays are increased to 1100 ms for the base case oper-

ating point. There is a gradual degradation in controller perfor-

mance as the signals are delayed for longer than the 500 ms

assumed during the design process.

Table IV details the maximum permissible delay tolerances

beyond which the MLQG controller will exhibit worse perfor-

mance than with the PSS-based POD controller, or no POD con-

troller, installed. These delays can increase to 766 ms (53.2%

higher than the already pessimistic 500 ms assumed) before the

controller displays worse performance than the PSS-based POD

controller taking local signals. With respect to the complete loss

of signals, this has been tested for the loss of up to two of the

four input signals. As the signals selected all contain some in-

formation about all the critical modes, there is some redundancy


8/10


TABLE IVMLQG CONTROLLER SIGNAL DELAY TOLERANCES

TABLE VDAMPING FACTOR OF CRITICAL MODES WITH LOSS OF I NPUT SIGNALS

Fig. 12. Active power injected at bus 9 (NYPS) from bus 8 (NETS) for basecase operating point with and signal failures.

within them. The damping of the four critical modes for the var-

ious cases is shown in Table V.

The shaded cells represent the cases when the modal damping

factor drops below that seen with the local PSS-based POD con-

troller installed. It is evident, for example, that the loss of input

signal always results in the damping factor of Mode 3 being

heavily reduced to less than 5%. This signal was initially se-

lected for the high observability of Mode 3, so this result is

not unexpected. Damping factors can be seen to still be higher than with the PSS-based POD installed for the majority of cases

when signals fail.

Even with the (unlikely) loss of two input signals, the MLQG

controller can often maintain relatively high damping factors

on some modes. Looking at case 5 (highlighted in Table V),

even though damping of Mode 2 has dropped to “lower than

PSS POD” levels, the damping of the remaining low frequency

modes are still in the range of 8.87%–9.60%. Due to this fact,

the transient performance of the controller is still highly com-

petitive, with all infeeds settling within 16 s for the base case

scenario when signals and are lost. The oscillationspresent

on the tie line between buses 8 and 9 are shown in Fig. 12, the

robustness of the MLQG controller to the failure of wide area

signals is clearly visible with the oscillations quickly damped.

Fig. 13. Active power injected at bus 9 (NYPS) from bus 8 (NETS) for basecase with and without reactive power modulation.

C. Incorporating Reactive Power Modulation

The studies presented have been concerned with the modu-

lation of active power flow through the parallel VSC-HVDC

link in order to stabilize post-disturbance system oscillations.

One of the stated advantages of using VSC-HVDC over classic

LCC-HVDC is the availability of “four quadrant” operation of

the converters, allowing the generation or consumption of reac-

tive power at each converter station.The MLQG design approach can be readily extended to in-

clude multiple controller outputs into a MIMO structure. In ad-

dition to the single signal, signals at each con-

verter station were incorporated and the MLQG controller de-

sign was completed once more.

Fig. 13 shows the oscillations present on the tie line between

buses 8 and 9 for the base case operating scenario both with, and

without, reactive power modulation included. It can be seen that

the additional reactive power modulation provides very limited

improvement in the system response (just 0.4 s improvement in

settling time).

With little benefit achieved, it is unlikely that VSC-HVDC

reactive power output would be modulated for power oscillationdamping purposes. Perhaps more probable would be the use of

fast reactive power modulation to ensure quickly stabilized bus

voltages at the points of interconnection with the VSC-HVDC

link during the post-disturbance oscillations.

D. Variation in Modulation Capacity

The simulations presented within this paper have assumed

a generous allowance of 100 MW for power oscillation

damping (equating to 25% of the VSC-HVDC link operating

capacity for the base case scenario). This modulation capacity

is the same for both designed POD controllers.

In a practical installation, the limit of available modulationcapacity will be determined by the system operator. The bene-

fits of reserving this capacity for modulating purposes following

system disturbances must be compared with the costs of re-

ducing the power transfer capability through the HVDC link.

Converter ratings will set the upper bound on possible power

transfer. As the required modulations in active power are rela-

tively slow (typically about 1 Hz), DC voltage limit violations

should not be an issue provided the converter regulating DC

voltage has been designed to be suitably fast.

The effect of limiting the modulation capacity (from the pre-

viously considered 25%) to 10% and 5% has been investigated.

Fig. 14 shows the oscillations between buses 8 and 9 and the

controlled variations in the power injected by the inverter station

for the base case with varying limits on modulation capacity


9/10


Fig. 14. (a) Active power injected at bus 9 (NYPS) from bus 8 (NETS) and (b)Active power injected at bus 50 by VSC-HVDC inverter station for base caseoperating point with differing modulation capacity limits.

with the initially designed MLQG controller (varying only ac-

tive power injection).

It can be seen that the settling time for this line increases

slightly as less capacity is reserved for POD action. The same

result is true of the PSS-based controller. With the exception

of the line 18–50 (which always sees improved settling times

with the PSS POD due to the local signal selection), restricting

the capacity reserved for POD to just 5% with the MLQG con-

troller still results in improved settling times over the PSS-based

POD controller operating with 25% modulation capacity. For

the MLQG controller 10% modulation capacity results in key

tie line settling times increasing by 1.9–2.7 s (to a maximum of

14.1 s); and 5% modulation capacity results in key tie line set-tling times increasing by 2.7–4.7 s (to a maximum of 16.1 s);

when compared with the initial 25% modulation capacity.

An idea of the likely availability of this modulation capacity

can be sourced from the publicly available data on the usage

of the 1 GW Britned HVDC link between July and December

2011 [35]. This data is taken for an HVDC link which does not

reserve capacity for modulation. During this six month period

(ignoring periods with no power transmission): 73.8% of the

time at least 5% link capacity was spare; 70.6% of the time at

least 10% link capacity was spare; and 63.1% of the time at least

25% link capacity was spare.

It is clear that there will be periods when large amounts of

HVDC link capacity may be available for active power modu-lation for system stabilizing purposes. At these times it would

be advisable to more fully exploit the damping capabilities of

the HVDC link as higher modulation capacities result in faster

system settling times. This may require flexible modulation

limits dependent upon system operating conditions.

VII. CONCLUSIONS

A MISO Modal LQG power oscillation damping controller

for VSC-HVDC lines has been shown to be effective at

damping inter-area electromechanical oscillations within a

large heavily meshed network. Furthermore, it has been shown

that even when accounting for transmission delays on wide

area controller input signals, the MISO controller is able to

vastly outperform a standard PSS based SISO POD controller

dependent upon local signals. Furthermore, the effects of

variation in the transmission delays of the wide area signals

the MLQG controller receives has been demonstrated. Not

only can the controller tolerate delays over 50% longer than

designed for, but it can even continue to outperform the PSS

based controller with the loss of half of its wide area inputs. It

has been shown that the addition of reactive power modulationat each VSC-HVDC converter station offers little benefit with

respect to improved system settling times. The damping of

power oscillations is dominated by the active power modulation

through the HVDC link.

Furthermore, the effects of limiting the capacity available for

active power modulation have been demonstrated. The MLQG

controller performance was reduced as the capacity reserved for

POD controller action is also reduced; however the controller

maintained superior performance compared with the PSS-based

controller. Analysis of operational data for the Britned link

shows the availability of modulation capacity and suggests

that use of fl

exible controller limits may be advantageous infully exploiting the VSC-HVDC link’s ability to stabilize the

network. This paper has shown that active power modulation of

HVDC lines is effective at damping multiple inter-area modes

within a large, heavily meshed network. Also, the MLQG

control methodology has been shown to be implementable with

a VSC-HVDC application. The targeted damping of critical

electromechanical oscillatory modes afforded by the MLQG

POD controller design may be of particular interest in large

power systems where very selective additional damping is

desired.

Finally, It should be pointed out that although use of an LQG

controller synthesis approach cannot intrinsically guarantee ro-

bustness properties [36], robust controller performance can still be achieved. Conversely, the use of controller synthesis tech-

niques that guarantee the robustness of the controller can only

ensure this robustness within the bounds of the defined uncer-

tainties. If these uncertainties are poorly formalized then the

controller’s practical ef ficacy may not match its intended math-

ematical performance. In either case, the performance and sta-

bility of the final controller must be thoroughly assessed through

multiple means (including nonlinear simulations) in order to es-

tablish its true robustness.

APPENDIX

HVDC SYSTEM AND CONTROLLER DATA

VSC-HVDC Line Parameters (on 600-MVA HVDC base):

VSC-HVDC Controller Parameters:

SISO POD Control Parameters (on 100-MVA base):

Fixed Parameters during LTR Tuning:


10/10


R EFERENCES

[1] J. Arrillaga, Y. H. Liu, and N. R. Watson , Flexible Power Transmis- sion: The HV DC Op tions. Chichester, U.K.: Wiley, 2007.

[2] National Grid Electricity Transmission plc, Offshore Development In-formation Statement, Sep. 2010. [Online]. Available: http://www.na-tionalgrid.com.

[3] D. Dotta, A. S. e Silva, and I. C. Decker, “Wide-area measurements- based two-level control design considering signal transmission delay,”

IEEE Trans. Power Syst., vol. 24, pp. 208–216, 2009.[4] T. Michigami, M. Terasaki, N. Sasazima, K. Hayashi, and T. Okamoto,“Developmentof a newadaptiveLQG system generatorfor high-speeddamping control techniques of power system oscillation,” Elect. Eng.

Jpn., vol. 142, pp. 30–40, 2003.[5] A. C. Zolotas, B. Chaudhuri, I. M. Jaimoukha, and P. Korba, “A study

on LQG/LTR control for damping inter-area oscillations in power sys-tems,” IEEE Trans. Control Syst. Technol., vol. 15, pp. 151–160, 2007.

[6] K. M. Son and J. K. Park, “On the robust LQG control of TCSC for damping power system oscillations,” IEEE Trans. Power Syst. , vol. 15, pp. 1306–1312, 2000.

[7] A. M. D. Ferreira, J. A. L. Barreiros, J. W. Barra, and J. R.Brito-de-Souza, “A robust adaptive LQG/LTR TCSC controller applied to damp power system oscillations,” Elect. Power Syst. Res.,vol. 77, pp. 956–964, 2007.

[8] S. Skogestad and I. Postlethwaite , Multivariable Feedback Control: Analysis and Design. Chichester, U.K.: Wiley, 1996.

[9] A. Almutairi, “Enhancement of power system stability using wide areameasurement system based damping controller,” Ph.D. dissertation,Univ. Manchester, Manchester, U.K., 2010.

[10] G. H. Golub and C. F. V. Loan , Matrix Computations. Baltimore,MD: The John Hopkins Univ. Press, 1989.

[11] P. Kundur , Power System Stability and Control . London, U.K.: Mc-Graw-Hill, 1994.

[12] P. E. Bjorklund, K. Srivastava, and W. Quaintance, “Hvdc light mod-eling for dynamic performance analysis,” in Proc. PSCE ’06 , 2006.

[13] H. F. Latorre, M. Ghandhari, and L. Söder, “Active and reactive power control of a VSC-HVdc,” Elect. Power Syst. Res., vol. 78, pp.1756–1763, 2008.

[14] R. Preece and J. V. Milanovic, “Comparison of dynamic performanceof meshed networks with different types of HVDC lines,” in Proc. IET

ACDC , London, U.K., 2010.[15] N. Flourentzou, V. G. Agelidis, and G. D. Demetriades, “VSC-based

HVDC power transmission systems: An overview,” IEEE Trans. Power Electron., vol. 24, pp. 592–602, 2009.

[16] R. Preece, A. M. Almutairi, O. Marjanovic, and J. V. Milanovic,“Damping of electromechnical oscillations by VSC-HVDC active power modulation with supplementary WAMS based modal LQGcontroller,” in Proc. IEEE PES General Meeting , Detroit, MI, 2011.

[17] B. Pal and B. Chaudhuri , Robust Control in Power Systems. NewYork: Springer, 2005.

[18] G. Rogers , Power System Oscillatio ns. Norwell, MA: Kluwer, 2000.[19] R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “MAT-

POWER: Steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Trans. Power Syst., vol.26, pp. 12–19, 2011.

[20] C. Zheng, X. Zhou, and L. Ruomei, “Dynamic modeling and transientsimulation for VSC based HVDC in multi-machine system,” in Proc.

PowerCon ’06 , 2006.[21] Y. Pipelzadeh, B. Chaudhuri, and T. C. Green, “Wide-area power os-

cillation damping control through HVDC: A case study on Australianequivalent system,” in Proc. IEEE PES General Meeting , 2010.

[22] H. Jingbo, L. Chao, W. Xiaochen, W. Jingtao, and T. S. Bi, “Designand experiment of heuristic adaptive HVDC supplementary dampingcontroller based on online Prony analysis,” in Proc. IEEE Power En-

gineering Society General Meeting , 2007.[23] D. V. Hertem,R. Eriksson,L. Soder, andM. Ghandhari, “Coordination

of multiple power flow controlling devices in transmission systems,”in Proc. IET ACDC , London, U.K., 2010.

[24] J. V. Milanovicand S. K. Yee, “Roadmap fortuning power systemcon-trollers,” in Proc. 3rd IASTED Int. Conf. Power and Energy Systems,Marbella, Spain, Sep. 2–4, 2003.

[25] R. Majumder, B. Chaudhuri, and B. C. Pal, “Implementation and testresults of a wide-area measurement-based controller for damping in-terarea oscillations considering signal-transmission delay,” IET Gen.,Transm., Distrib., vol. 1, pp. 1–7, 2007.

[26] J. Lam, “Model reduction of delay systems using Pade approximants,” Int. J. Control , vol. 57, pp. 377–391, 1993.

[27] M. G. Safonov and R. Y. Chiang, “A Schur method for balanced-trun-cation model reduction,” IEEE Trans. Autom. Control , vol. 34, pp.729–733, 1989.

[28] R. Preece, A. M. Almutairi, O. Marjanovic, and J. V. Milanovic, “Ef-fectiveness of a supplementary MLQG power oscillation damping con-troller installed at an HVDC line within a meshed network,” in Proc.Cigre Int. Symp.: The Electric Power System of the Future , Bologna,Italy, 2011.

[29] J. W. Stahlhut, T. J. Browne, G. T. Heydt, and V. Vittal, “Latencyviewed as a stochastic process and its impact on wide area power system control signals,” IEEE Trans. Power Syst., vol. 23, pp. 84–91,2008.

[30] W. Hongxia, K. S. Tsakalis, and G. T. Heydt, “Evaluation of timedelayeffects to wide-area powersystem stabilizer design,” IEEE Trans.

Power Syst., vol. 19, pp. 1935–1941, 2004.[31] B. Mirkinand P. O. Gutman, “Robust output-feedback model reference

adaptive control of SISO plants with multiple uncertain, time-varyingstate delays,” IEEE Trans. Autom. Control , vol. 53, pp. 2414–2419,2008.

[32] B. Chaudhuri, R. Majumder, and B. C. Pal, “Wide-area measurement- based stabilizing control of power system considering signal transmis-sion delay,” IEEE Trans. Power Syst., vol. 19, pp. 1971–1979, 2004.

[33] R. Majumder, B. Chaudhuri, B. C. Pal, and Z. Qing-Chang, “A unified

Smith predictor approach for power system damping control designusing remote signals,” IEEE Trans. Control Syst. Technol., vol. 13, pp.1063–1068, 2005.

[34] N. R. Chaudhuri, S. Ray, R. Majumder, and B. Chaudhuri, “A new approach to continuous latency compensation with adaptive phasor power oscillation damping controller (POD),” IEEE Trans. Power Syst., vol.25, pp. 939–946, 2010.

[35] National Grid Transmission, “Metered Half-Hourly ElectrictyDemands: July–December 2011,” 2011. [Online]. Available:http://www.nationalgrid.com.

[36] J. Doyle, “Guaranteed margins for LQG regulators,” IEEE Trans. Autom. Control , vol. 23, pp. 756–757, 1978.

Robin Preece (S’10) received the B.Eng degree in electrical and electronic en-gineering in 2009 from the University of Manchester, Manchester, U.K., where

he is currently pursuing the Ph.D. degree.

Jovica V. Milanović (M’95–SM’98–F’10) received the Dipl.Ing. and M.Sc.degrees from the University of Belgrade, Yugoslavia, the Ph.D. degree fromthe University of Newcastle, Australia, and his Higher Doctorate (D.Sc. de-gree) from The University of Manchester, Manchester, U.K., all in electricalengineering.

Currently, he is a Professor of electrical power engineering and Director of External Affairs in the School of Electrical and Electronic Engineering at TheUniversity of Manchester (formerly UMIST), Visiting Professor at the Univer-sity of Novi Sad, Novi Sad, Serbia, and Conjoint Professor at University of Newcastle, Newcastle, Australia.

Abddulaziz M. Almutairi (S’06–M’11) received the B.Sc. degree from KuwaitUniversity, Kuwait, the M.Sc. degree from the University of North Carolina atCharlotte, and the Ph.D. degree from the University of Manchester, Manchester,U.K., all in electrical engineering.

Currently he is an Assistant Professor of electrical power engineering in theCollege of Technological Studies, PAAET, Kuwait.

Ognjen Marjanovic (M’08) received the First Class honors degree from theDepartment of Electrical and Electronic Engineering, Victoria University of Manchester, U.K., and the Ph.D. degree from the School of Engineering, Vic-toria University of Manchester, U.K.

Currently he is a Lecturer in the School of Electrical and Electronic Engi-neering at The University of Manchester, U.K.

Documents

HVDC Power Injection