Wide-Area Monitoring and Control of Power Systems using

Wide-Area Monitoring and Control of

Power Systems using Real-Time

Hardware-in-the-Loop Simulations

Matthew Weiss

Thesis advisor: Dr. Aranya Chakrabortty

7/28/2016

1

Introduction

2

• Power grids are envisioned to be come green and smart in the coming decades.

• PMU measurements and PMU technology are becoming much more common.

• Relatively little effort has been made to explore how synchrophasors can be used for automatic feedback control over a wide geographic area.

• Local PSS and AVR control commonly in use today.

• In this research,

• A breakdown of methodology used to create a functional and accurate reduced-order model is presented.

• The model is validated and contingencies regarding renewable energy are explored and a major problem identified.

• Two wide-area controller designs are presented using PMU measurements. • A hardware-in-the-loop test-bed is presented for implementation of these control

schema in a real-world setting for performance validation. • It is concluded that wide-area control schema presented here are successful in

stabilizing otherwise unstable power-system conditions!

Thesis Outline

3

• Identification of Power System Models using Synchrophasors

• Impacts of Wind Penetration

• Wide-Area SVC Control Design

• Wide-Area PSS Design using LQR

• Hardware-in-the-Loop Implementation

• Wide-Area Control using Cloud Computing

Identification of Power System

• How can synchrophasor measurements be used to construct a reliable dynamic-equivalent model?

• How does the implemented model react to different types of contingencies?

4

WECC and its Geography

5

• The Western Electricity Coordinating Council (WECC) is a large power system on the west coast of United States.

• The WECC 500 kV power system is divided into five coherent generation areas interconnected by long transmission lines.

• This leads to the emergence of slow “inter-area” power oscillations in the range of 0.1 Hz to 1 Hz.

Reduced-Order Topology

6

Five-machine equivalent of WECC

• A reduced-order equivalent of the WECC 500 kV system can be constructed.

• A pilot bus is selected from each area based on the following criteria: The bus must have a PMU

installed

All generators within that area must lie electrically behind this bus.

• The area behind the pilot bus is represented by an aggregated synchronous generator (ASG)

Aggregate Machines

7

• The ASG is modeled as a second-order damped oscillator

described by the swing equations:

• Each pilot bus is connected to adjacent pilot buses through

long transmission lines.

• In the steady state, each ASG is represented in the network

by its Thevenin equivalent.

• Estimation of all system parameters will be done using PMU

data.

PMU Data Modes

8

Model Parameter Calculations

9

•From this data it is possible to derive :

•Tie line impedances •Inter-area impedances •Inertias •Damping values

Model Validation

• RSCAD software was used to realize a model of WECC.

• Real-Time-Digital-Simulators (RTDS) was used to run RSCAD models in real-time with a 50 micro-second time-step.

• Real-time application will be of utmost importance later in this research

10

Model Parameters

• Calculated Values Intra-area Impedance

Inter-area Impedance

Machine Inertia

Machine Damping

• Easily Derived Data Values Pre-fault Inter-area Voltage Phase Angle

Post-fault Inter-area Voltage Phase Angle

Pre-fault Voltage

Post-fault Voltage

• Needed but not Provided Values Machine Power Rating

Machine Power Generation

Load Placement in System

Effective Shunt Capacitance

11

Line Reactance

•Station 3 Ended up Negative in Least Squares Calculations.

Real bus contains significant capacitance Real bus represents a very heavy load Without capacitance, voltage sag occurs

•In the model, it wasn’t possible to use this value.

Capacitor added at Station 3 Value tuned such that bus voltage was correct Intra-area impedance substituted with another stations value

12

Bus Voltage Tuning

•Voltages only of secondary interest

System voltage may vary locally Voltage has little effect on overall power flow Just needs to be close, defined as within 2% error

•Voltages tuned by varying the PV bus voltage inside the machines.

13

Fault Power Flow Matching

•Most pilot buses exhibit a large, instantaneous phase angle and power flow change.

Station 1 - Station 2 is the exception Station 4 - Station 5 is very large. Almost 25 degrees. Station 5 is a loss of generation fault location in the real world power system

•This can’t be recreated by adjusting the governor load reference setting due to slow dynamics.

Resistive loads added or dropped to recreate instantaneous power changes, and thus phase angle changes. Resistance value calculated to appropriately add or subtract net power injection at each pilot bus

14

5 10 15 20 25 30

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Time (seconds)A

ngle

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es)

Angle Between Area 4 and Area 3

Real Transient Response

Phase Angle Tuning

• Resistive Loads insufficient to match steady-state phase angles

• Steady-state phase angle values matched by adjusting machine Pm reference points.

• These points change when the fault occurs in the model. Allows slower, non instantaneous phase

angle adjustment Exact steady-state phase angle matching

possible

15

5 10 15 20 25 30

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Model Transient Response

Inertias and Damping Values

•Calculated values produced one strange result

Angle between Station 1 and Station 2 had a very high frequency component. Original Station 1 Inertia was skeptically insufficient This value was changed such that the transient responses shared slow-mode frequencies with PMU data.

16

5 10 15 20 25 3016

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Time (seconds)

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Model Transient Response

Transient Response Validation

17

Plots of PMU data compared against transient response of WECC model in RSCAD Reduced-order model then used for various contingencies.

Contingencies

18

•Increase in intra-area line impedance Line trips Change in generation location

Renewable energy sources located further from Station

Lines intra-area Impedance increased until marginal stability was observed.

Some buses more sensitive to increases than others

Model excited with impulse fault on all 5 pilot buses and phase angles recorded

•Decrease in aggregate inertia Inertia-less renewable sources displacing synchronous machines 90% of inertia eliminated from each machine, one at a time. Model excited with loss of generation fault and phase angles recorded

Line Loss Contingency

19

Effects of line loss are demonstrated here in these four plots along with data regarding underlying frequencies and damping values.

Inertia Loss Contingency

20

Effects of inertia loss are demonstrated here in these four plots along with data regarding underlying frequencies and damping values.

Thesis Outline

21







Wind Power in the US

• Wind power generation increasing in the US

• Oil and coal prices rising

• Great for the environment

For this trend to continue, prevalent issues regarding renewable energy integration need to be solved

PRESENT PAST FUTURE

Wind Availability vs. Use

• Wind located far from US population centers Population lies along East and

West coasts of US Midwest lightly populated and

wind abundant Most population in low wind areas

• Poses issues for US power grid

Stability issues Local area control insufficient in

some cases Long distance transmission

challenges present

Wide-area control a solution for this problem!

Wind in WECC

• Expected to increase in Southern California

– Area 4 represents this area

• 500MW of wind added to RSCAD model

– DFIG turbine model

24

Wind and Bus Inertia

25

Wind Simulation Results

• WECC model faulted with a four-cycle line-to-ground fault on all five pilot buses simultaneously

– Phase angles between pilot buses recorded and plotted for two cases

• WECC with 500MW wind penetration on area 4

• WECC with no wind penetration

26

Wind Simulation Plots

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Wind Bus Sweep

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Model transient response was observed when 700MW of wind was placed on different pilot buses in WECC

Summary of Wind Simulations

• Wind increases severity of power swing on model

– Increase in intra-area line impedance

– Decrease in bus aggregate inertia

• RSCAD simulation shows this phenomenon

– Poorer damping, higher residue values

• Next question. How to counteract this?

29

Thesis Outline

30







SVC in the WECC

• Need a way to combat system destabilization due to wind penetration – Must exist in real-world – Must increase damping

• SVC offers a solution – Typically regulates

immediate bus voltage – Device regulates via

reactive power control, allowing control of phase angles

31

SVC Location

• Real-world SVC exists geographically and topologically halfway between Areas 4 and 5.

• Geographically local to planned increases in wind penetration.

32

SVC Parameters

• One 117 MVAR variable inductive element

• Two 91 MVAR switchable capacitive elements

• Droop typically 1-10% in Industry. 4% was used.

33

SVC Controls Basics

• Input is a per-unit local bus voltage measurement – Filtered – Relative to reference – Droop of 4%

• Output controls inductive reactor elements and capacitive reactor switches – Passes through PI controller – PI controller will be tuned

34

SVC PI Tuning

• System very complex, unknown, even in model – Even more unknown in real-world or with

wind/SVC added to model

– Exact system identification based tuning methods impractical

• Zeigler-Nichol’s method used – Great for unknown/complex systems

– RSCAD allows necessary tests/data collection

35

Zeigler-Nichol’s RSCAD

• Process:

– Controller input, VPU, disconnected

– Step input applied to controller

– Resulting change in per-unit voltage collected in RSCAD

– Collection data shows SVC Process Reaction Curve

36

SVC Step Response

• RSCAD Data shown below for Process Reaction Curve

– Lag time, L measured

– Rise time, T, measured

– Change in amplitude, A, measured

37

SVC Local Control Results

38

Data collected from RSCAD when a four-cycle line-to-ground fault was applied to area three. Just a comparison of SVC, no WAC implementation.

Input to Controller

• Must be a measure of some quantity in power system – Rotor angles of generators

– Speed deviations of generators

– Machine output power

– Branch power flows/phase angles

• Chose inter-area phase angles – Generators in model are fictitious

– Model tuned around phase angle recreation, not voltage recreation

– Pilot buses exist in real-world, with PMUs installed

39

Selection of an Input Signal

• Must be robust to changes in steady-state operating point

• Need to devise a test to search for robustness

• Test devised to randomly vary steady-state point – Test shall randomly vary power injection on each

bus • Vary governor load-reference at each bus

• Vary wind penetration at area 4

40

RSCAD Impulse Responses

• Each case was tested for an impulse located on additional control input of the controller

– Resulting phase angle responses were recorded

41

0 10 20 30-0.1

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Angle

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ngle

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Modal Data

42

Modal Variance

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Variance Results

• Controller input must be robust to changes in system steady-state

• Finding this by observing variance in mode residue

• Phase angles three and four show much less variation than one and two – Also in closer proximity to controller, more realizable

in real-world scenario

Mode Phase 1 Phase 2 Phase 3 Phase 4

1 2.9410 1.8491 0.0648 0.0487

2 0.8818 0.4235 0.2351 0.1941

44

Wide-Area Control Structure

• Use of both phase angles three and four as inputs – Requires three data sources

from three buses

• Output is reactive power injection between buses four and five – Limited by SVC operational

limits

• Goal is to reduce inter-area oscillation intensity and increase damping – Tests will be conducted to

observe and quantify controller performance 45

Controller Overview

• Supplementary controller composed of several parts

• Input to be phase angle measurements

• Output to lead to PI controller input, which leads to reactive SVC elements

• Composed of a Low-Pass filter, Lead-Lag filter, and Washout Filter in series for each slow-mode. – Two branches for each phase angle input

46

Controller Transfer Function

47

Data Required

• Frequency, Residue, and Damping for both modes across both angular inputs. – Gained from RSCAD and ERA

• Impulse applied to power system

• Data collected

• Data analyzed with ERA

• Different than base paper’s method

– Used to calculate controller parameters

Angle Mode Frequency Residue Damping

3-4 1 1.2478 45.5570 0.2719

3-4 2 1.9131 42.2355 0.2099

4-5 1 1.2784 41.0623 0.2763

4-5 2 1.7526 64.0806 0.2813

48

Low Pass Filter

49

Lead-lag Filter

50

Washout Filter

51

Total Transfer Function

• Controller consists of two parallel transfer functions for each phase angle input

– Two phase angle inputs

• One for each modal frequency

– Four total transfer functions in parallel

– Displayed on next slide.

52

Controller Transfer Function

53

Recap of Wide-Area Controller

54

Controller Tests

• Compare performance of power system both with and without supplementary wide-area controller

– Default SVC case

– One angle input

– Two angle inputs

• Fault applied on area 3

• Wind on area 4

55

Controller Test Plots

56

Controller performance with two, and then three pilot buses transmitting data were compared against the baseline case with no wide-area controller.

Power System Transience

• ERA used to find damping reduction of primary slow-mode frequencies

• More sufficiently damped

Phase Angle

Mode 1 Baseline

Mode 1 Controller 1

Mode 1 Controller 2

1 0.3653 0.3311 0.3426

2 0.6006 0.7816 1.0000

3 0.2166 0.3747 0.2856

4 0.2774 0.3001 0.4143

Phase Angle

Mode 2 Baseline

Mode 2 Controller 1

Mode 2 Controller 2

1 0.1923 0.1616 0.1674

2 0.2213 0.2762 0.2840

3 0.2763 0.3589 0.2856

4 0.1472 0.2151 0.4029

57

SVC WAC on Other

Operating Points

58

Controller Conclusion

• Improvements in power system stability – Improvements in three of four phase angles, with

large improvements in geographically close angles

• Real-world applicable – SVC exists in real-world

– Pilot buses exist in real-world

– PMUs exist in real-world

• Further tests desired to include hardware contingencies and implementation – Up to now, model and controller are both in RSCAD

– It is desired to create PMUs, and controller using real-world equipment

59

Thesis Outline

60







LQR Wide-Area Control

• Base model used was reduced-order five-machine WECC equivalent model.

• We next design a linear quadratic regulator state feedback controller

u(t) = Kx(t)

• Gain matrix K computed offline

• Excitation system voltage used as control input

• Bus angle, frequency, and voltage used for estimating machine states.

61

State-Space Equations

• Each machine i represented by three orders of differential equations

62

State-Space Equations

• Arranged in matrix form:

• Partials taken, not shown here

• State Space formed

• Initial conditions taken from WECC in RSCAD 63

Wide-Area Control

• Transform into via use of the PSS stabilizer input on each machine.

• Choice of matrix K will minimize:

• For our design, R was I3n

• Selection of Q was more challenging.

64

Relative Angles

• Product XTQX is a problem because X contains absolute angles.

65

Selection of Q Matrix

• Q was chosen such that the product XTQX contained only relative angles.

66

K Matrix Issue

• The feedback matrix K will have the same issue as Q.

• Define: Rearranged as:

• Controller output equates to:

• Only if: We force this: 67

State-Space Impulse

Comparison • Alteration of K Matrix could influence

controller performance.

• A brief test done simply in MATLAB verifies alteration of matrix is negligible.

68

Creating an Unstable Test

Case • To test the controller’s performance, a case

was created in WECC that was unstable.

• K matrix was recomputed around new operational point:

69

Test of Unstable Case

70

Controller Performance Test

71

Controller performance in damping a transience was compared against baseline model with lack of control.

Feedback of Just Local

Voltage State Variables

72

All terms in the feedback matrix K were zeroed out except for terms responsible for local voltage feedback. This was compared against the full K matrix controller implementation.

Feedback of Just Local

Frequency State Variables

73

All terms in the feedback matrix K were zeroed out except for terms responsible for local frequency feedback. This was compared against the baseline model with no control.

Standard PSS on WECC

74

A PSS was applied to each aggregate machine and compared against performance of the Wide-Area LQR Controller. Note the issue of applying a ‘double’ PSS here.

Unstable Baseline Case for

LQR and SVC

75

• To further test performance, another case was created in WECC that was unstable even with PSS.

• K matrix was recomputed around new operational point:

Controller Performance

Conclusion

76

Case unstable with PSS was tested with both SVC-based WAC and LQR-based WAC. Both wide-area control methods were capable of damping this unstable system!

Thesis Outline

77







Hardware-in-the-loop

Implementation • Hardware architecture

RTDS: Software component

GTAO: low-level analog signals

PMUs: analog data collection

PDC: PMU/computer interface

RTAC: hardware controller

GPS: universal timestamp

• Design Capabilities

Integration of hardware controllers

Includes hardware measurement devices

Built-in software simulators such as RSCAD

Real-time operation

PMU2

PMU3

PMU1

PDCGTAO

CardRTDS

GPS

To Computer

RTAC

78

RTDS & GTAO Card

GPS

RTAC

PMU SEL487

PMU SEL421

PDC SEL3373

Controller in Hardware

79

Controller Differences

• Model tested for two cases

– WAC in software in RSCAD exclusively

– WAC brought into hardware, and created in RTAC

• Fault applied to bus 3 of duration eight cycles from line to ground

• Controller output recorded for both cases

80


• Differences come from many sources

– Measurement errors

– Analog noise

– Discretization errors

– System delays

• Fourth order discrete transfer function

• Time constant of 16.67ms

• Theoretical transfer function delay of 67ms

81


• Delay found to be 75 milliseconds

– 67 ms from discrete transfer function

– 8 ms from network delays or other delays in system

82


83

Performance of RSCAD-based SVC-WAC compared against a hardware implementation using the RTAC.

Controller Performance 2

• Mode damping compared using ERA Phase Angle Mode 1 in

Software Mode 1 in Hardware

Mode 1 No Controller

1 0.3426 0.3408 0.3653

2 1.0000 1.0000 0.6006

3 0.2856 0.3162 0.2166

4 0.4143 0.3193 0.2774

Phase Angle Mode 2 in Software

Mode 2 in Hardware

Mode 2 No Controller

1 0.1674 0.1721 0.1923

2 0.2840 0.2872 0.2213

3 0.2856 0.3162 0.2763

4 0.4029 0.3498 0.1472

84

Summary of HIL Set-up

• Controller functions in a hardware laboratory setting – 67ms of delay present innately

– Graphically, controller performance shows no degradation

– Damping values comparable and show little degradation

• HIL controller can still provide adequate damping to the WECC model

85

Thesis Outline

86







Wide-Area Monitoring and

Control • Validate the distributed applications for wide-area

monitoring and control through the cyber-physical distributed cloud computing test-bed

87

PMUs and Cloud Computing

88

RTDS 152.14.125.32/33/232

Lab Computers 152.14.125.109/

10.0.0.X

PMU1 10.0.0.3

PMU2 10.0.0.4

PMU3 10.0.0.5

PMU4 10.0.0.6

PMU5 10.0.0.7

PMU6 10.0.0.8

GTAO

Rib

bo

n c

able

s

Netgear Switch

Eth

ern

et

cab

les

BEN port

BEN

VLAN904

GTNET 10.0.0.9

VM1 VM2

VM3 VM4

VM6

Control Signals

Internal Fiber Optic Cable

VM5

ExoGENI Oakland, CA Rack Site

Co

ntro

l Signals

PM

U d

ata

PMU based WAMS at NCSU

Comparison of Control

Signals

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Control Signals from ExoGENI Control Signals from RSCAD

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t1 t2

1sec

t1-t2 = 0.2sec

Comparison of LQR


90

Performance of RSCAD-based LQR-WAC compared against a cloud-computing implementation using the ExoGENI Network.

PMU Lag Contingency

91

One PMU in the Hardware-ExoGENI test-bed was delayed by eight milliseconds, or roughly half a cycle. The resulting destabilization that occurs is presented.

ExoGENI Packet Loss

Contingency

92

A loss of packets between t=6.5 and t=9.5 was injected into the test-bed and the resulting disturbances recorded during transience.

Conclusions

• A working wide-area, reduced-order model of WECC was created

• Wind penetration studies revealed need for improvements in power system stability improvements.

• We developed SVC-based and PSS-based wide-area controllers that were capable of damping otherwise unstable WECC power system model under various operating conditions.

• Hardware-in-the-loop and cloud-in-the-loop test-beds demonstrated controller functionality in simulated real-world settings and equipment.

93

Future Works

• Update the WECC Model

• Series FACTS devices not possible currently due to fictitious lines

• Issues regarding performance loss or total failure of controller when delay or PMU mismatch is observed

• PSS is currently hypothetical. How to implement on an aggregate of machines

94

Works Cited

95

Questions?

96

Documents

Wide-Area Monitoring and Control of Power Systems using