smart grid and power quality: bane or boon -...

1

Smart Grid and Power Quality: Bane or Boon

June 30, 2009

PQA/ADA Conference, NY

Arshad Mansoor Vice President, Power Delivery & Utilization

2 Copyright © 2009 Electric Power Research Institute, Inc. All rights reserved. PQA/ADA Conference & Exhibition 2009

Discussion Topics

• So What is this “Smart Grid”?

• What are some Smart Grid applications?

• How would these applications impact PQ and vice versa? – An optimist view and a

pessimist view

• What should a realist (i.e., PQ Engineer) do to prepare for the future?


How to Define “Smart Grid”?

MODERN GRIDS T R A T E G Y

Intelligent Grid Coordination CommitteeFederal SmartGrid Task Force

Many Contributors Have Led to Varied Definitions


Highly Instrumented with Advanced

Sensors and Computing

Interconnected by a Communication Fabric

that Reaches Every Device

Engaging ConsumersEnhancing Efficiency & Asset UtilizationEnsuring ReliabilityEnabling Renewables & Electric Transportation

Many Definitions - But One VISION

What is The Smart Grid?


State of Smart Grid Technology

Smart Smart GridGrid

The Gartner Technology Hype Cycle


AMI ManagementSystems

WirelessData

Collection

PagingData

Collection

CIS

OMS

WMS

GIS/DPS

Wide AreaNetworks

Meter-SpecificNetworks

Data Collection Systems

Existing UtilitySystems

WebPresentation Regulators and

AgenciesInternet

Public Wireless(Paging,

GPRS, 1XRTT)

TelephoneData

Collection

Smart Meters & Other Devices

Power LineData

Collection

Usage DataRepository

PrivateWireless(WiMAX)

Asset Mgmt

MDM System

Energy Service Provider

CSR

Third Parties

Retailer

Data Exchange

Satellite

BPL

Customer

PSTNPLC/BPL

Mesh RF

Star RF

Advanced Metering Infrastructure


Is It a Boon or Bane for PQ?

Optimist View

• Additional sources of data to characterize the system power quality

• Ability to diagnose power quality issues at the extremities of the network

• Improve capability to locate faults

• Use data to assess condition of assets and predict faults

Pessimist View

• Blinded by data

• Proliferation of sensitive electronic loads (Smart Meter = Computer)

• Increasing customer complaints related to Electromagnetic Interference (EMI) from power line carriers

• Added grid complexity = (usually) increased PQ phenomena


Distribution Efficiency and Peak Demand Reduction

SectionalizersDistributed Regulators

Substation Regulators

Capacitor Banks

Communication Network

Advanced Distribution Optimization

RealtimeMetering

SectionalizersDistributed Regulators

Substation Regulators

Capacitor Banks

Communication Network

Advanced Distribution Optimization

RealtimeMetering

Progress Energy (Carolinas) Distribution System Demand Response (DSDR) Program Filing

Reduce peak demand - 247MW

Program Cost

O&M: $30.6M

Capital: $229.4M, 5 Years

Volt/Var Devices & Communication & Control Sensors Enabling Feeder Voltage Optimization



Optimist View

• Reduce voltage fluctuation

• Longer equipment life

• Reduce losses

• Reduce peak demand

• Reduce reactive var requirements

Pessimist View

• More customer complaints due to reduced voltage

• Increased susceptibility to voltage sags

• Increase losses

• Increase reactive var requirements


Integrating Distributed Resources

The Distributed Power Plant


Enabling PHEV Through Smart Charging

MainframeMainframeMainframe

Back Office Systems

MainframeMainframeMainframeMainframeMainframeMainframe

Back Office Systems

Plug-In VehicleAMI Path

Smart Charging Back EndEnergy Management, Cust ID, Billing

Non-AMI Path

Standard Interface• Utility – Auto industry

collaboration• Standardize interface

vehicle-to-grid• Open systems



Optimist View

• Reduce voltage variation by providing local system voltage support

• Increased reliability through controlled islanding

• Reduce capacitor switching transients through local var support

• Ability to provide emergency back-up power

Pessimist View

• Susceptibility of distributed resources to electrical disturbances

• Distributed resources negatively impacting operation of distribution system

• Harmonics from inverter interface


What Should a Realist (i.e., PQ Engineer) Do?

• Get ready for the future through research, development and demonstration (RD&D)– Characterize the immunity and susceptibility of smart meters, PHEV

and other smart grid technologies (remember system compatibility??)

– Educate industry on PQDIF and how large amount of data can be managed to generation actionable information

– Characterize the voltage dependency of end-use loads and develop load modes

– Demonstrate active distribution management to minimize PQ impact of distributed generation and use DG as a system resource

– Realize that added system complexity could negatively impact PQ and do our best to study and mitigate these effects proactively

Together, We Can Turn Challenges into Opportunities

Trending Network Power Quality & Reliability

Peter HofmannConsolidated EdisonJune 30, 2009

EPRI Power Quality Applications (PQA) and Advanced Distribution Automation (ADA)

2009 Conference and Exhibition


•Con Edison System Overview•Reliability and Power Quality Programs•Data & Analysis Tools•Power Quality and Reliability Trends•Looking Forward




System Overview

NY StateArea 47,214 sq mi

Peak Demand 33,939 MW

Load Density 0.72 MW/sq mi

Con EdisonArea 604 sq mi

Peak Demand 13,141 MW

Load Density 21.8 MW/sq mi

ManhattanArea 23 sq mi

Peak Demand 5405 MW

Load Density 235 MW/sq mi



27,13, 4 kV

13 kV

27, 4 kV

33,13, 4 kV

Distribution System

61 Distribution Area Substations

62 Second Contingency Networks, and 19 First Contingency Networks

2,204 Distribution Feeders

86% System is underground



Con Edison System / Manhattan System StatisticsSystem Manhattan % of System

Service Area 604 sq miles 23 sq miles 3.8 %

Population 9.22 million 1.62 million 17.6 %

Customers 3.27 million 705,165 21.6 %

UG XFMRS 35,550 9,490 26.7 %

UG Structures 264,245 59,882 22.7 %

UG Cable 93,044 miles 21,094 22.7 %

Peak Electric Demand

13,141 MW (Summer 2006)

5,404 MW 41.1 %



Area Substation – Double Syn Bus/Second Contingency Design

13.2 KV SYN BUS

20 MVAR Cap Bank 138/13.2 kV, 65MVATransformer

N.O.

N.O.

13.2 KV SYN BUS13.2 KV Fdrs.

13.2 KV Fdrs.

138 kVTransm. Fdr.



Area Substation – Network Feeder Interconnection

13.2 KV Feeders to multi- bank spot

network installationsand distributed network


13,000voltsPrimary Feeder

120/208volts

Primary Feeder120/208volts

13 kv13kv

13kv120/208volts

120/208volts

Primary Feeder

Primary Feeder

Secondary Grid

customers


Distributed Secondary Network

Spot Network



Network Distribution System



Under the Streets


• Area Substations– Double Syn Bus Design– High Available Short Circuit Current– High Side Circuit Switchers– Capacitors (10 MVAR, 20MVAR and 30MVAR banks)– Neutral Reactor

• Network – Transformers

• Integrated Ground Switch; no disconnect capability• Delta – Wye configuration• Advanced Remote Monitoring Capability


Some Network Design & Operational Features



417

12617

1,400

1,000

200

0

800

600

400

1,250

1,020

National(USA)

New York State(w/o Con Edison)

Con Edison(non-network)

Con Edison(overall)

Con Edison(network)

1,200

417

12617

1,400

1,000

200

0

800

600

400

1,250

1,020

National(USA)

New York State(w/o Con Edison)

Con Edison(non-network)

Con Edison(overall)

Con Edison(network)

1,200

0

200

400

600

800

1000

1200

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Unparalleled Reliability

Sourc e: New York S tate Publ ic Service Comm is sion

NYS

Con Edison

Inte

rrupt

ion

Rate

per

100

0 C

usto

mer

s



ReliabilityM ajor Shutdown Events

4

1

4

2

1

1

4

1

3

4

1

1

2

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

D istribut ion System

Subs tation

T ransm ission

1 96 5-1 97 5 1 9 75 -1 9 85 19 8 5-19 9 5 1 9 95 -2 00 5 20 0 5-Pre sent


• Network Reliability– Network Reliability Indexing (NRI)– Feeder & Equipment Data Bases

• FMS (Feeder Management)• CAJAC (Cable and Joints)• CINDE (Network Transformers)

– Customer Interruption Reporting

• Power Quality– PQView– SCADA (PI)

• Area Substation Data– Network Transformer Remote Monitoring (RMS)


Some Network Reliability and Power Quality Data & Analysis Tools


• Power Quality Service Center – 1993

• Cable & Splice Center of Excellence - 2003

• Distribution Engineering Equipment Analysis Center - 2007


Network Reliability and Power Quality Resources



Network Reliability Major Programs

• Accelerate Paper-Insulated Cable Replacement• Advanced replacement completion

to year 2020

• Target and replace 300 miles annually

• Replacing Thermally Sensitive Joints

• Feeder Testing




Network Transformers• New & Upgraded Transformer

Installations

• Preemptive removal based on analysis, inspection and maintenance

• Remote monitoring of temperature, pressure and oil level

• Minimize the number of transformers out of service




HARLEM

CENTRALPARK

BRONX

WASHINGTONH EIG HTS

YORKVILLE

TRIBORO

Create New Feeders• Utilize existing spare feeder positions

in substations

• Improve rapid isolation of faulted segments on feeders

• Add approximately 100 new feeders

Long-term: Split Large Networks• When load is transferred or new

substations are constructed: split large networks

• Four (4) networks will be reduced in size from load transfers when new area substations are built (2009 –2017)



Public Safety

• Stray Voltage

• Underground Structure Events

• Transformer Failure



Public Safety Major Programs

• Stray Voltage Detection

• Structure Inspection Program

• Cover Replacement Program

• Improved Cable Design

• Secondary Rebuild Program



Electric Shock Reports

151120

7052

0

40

80

120

160

200

2005 2006 2007 2008


210

11689

46130

40

80

120

160

200

2004 2005 2006 2007 2008

Public Safety Improvements

Transformer FailuresElectric Shock Report

45%

23%

48%

21%

42%

72%

26%




2494 24602033 2139

1348

0

500

1000

1500

2000

2500

2 004 2005 2006 2007 2008

Public Safety Improvements

Underground Structure Events



Network Distribution Transformer – Internal Failure Trending



Network Feeder Component Performance Trends


M an hattan O ve ra ll 198 6-200 8 O pen A u to m atic s /C u t In O pe n A utom a tics p er F eede r pe r N etw ork pe r Y ea r

1.00

1.20

1 .43

1.22

1 .23

1.21

0 .95 1.01

0.93

0.78

0.90

0 .64 0.69

0 .86

0.76 0 .80 0.84

0.93

0.85

0.86

0.68 0.70

0 .55

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1986

1987

198 8

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

200 7

2008

Ope

n A

utom

atic

s pe

r Fee

der

per N

etw

ork

per Y

ear


Network Feeder Normalized Long Term Performance Trends



• Increased Utilization of the “modified” high potential test for feeder serviceability – Reduce occurrence of “Cut In Open Automatics – CIOA”

• Increased focus on network feeder processing and restoration times during high load periods– Maintain balanced loading among feeders and prevent potential

cascading failures

Operational Enhancements to Improve Power Quality and Reliability


Operational Readiness – Information Systems




• Heads Up Display (HUD) - Intranet Based– Primary System– Secondary System– Feeder Processing– Contingency Analysis

• Automatic Email Notifications– Feeder Outages

• Open Automatics• Scheduled Outages

– Power Quality Events• Voltage Sags/Overcurrents/Reactance to Fault Calculations• Transients including magnetizing inrush

– Customer Outages• Number of Customers• Number of Structures

– Weather Events• Lightning• Rainfall

Increasing Operator Awareness of System Conditions


• Phase I – Secondary Network Monitoring at “masterpoint” spot network installations

• Phase II – Area Substation Monitoring - one power transformer– Integrate data into web based operational tools– Fault Locating– PQView enhancements

• Phase III – Expanded Monitoring at Area Substations– Integration of PQ Monitoring data with other SCADA

data– Continued PQView enhancements– Integration of microprocessor relay data


Power Quality Monitoring and Data Analysis



Phase I – Secondary Network Monitoring at “masterpoint” spot network installations



Phase II – Area Substation Monitoring - one power transformer



RMS Voltage Variation Magnitude vs Duration• 1996/1997 Data for secondary networks – 3749 Events



RMS Voltage Variation Magnitude and Duration Distribution Plots

• 2006/2007 Data for secondary networks – 3400 Events


• System Average RMS (Variation) Frequency Index– SARFI - 90– SARFI - 70

• Average frequency of specified RMS variations per site

RMS Voltage Variation Trending for Secondary Networks – Voltage Sags

SARFIN

Nxi

T= ∑



SARFI Event Rate for Con Edison System, 1996/1997 and 2006/2007

2.485

0.576

2.271

0.338

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

2.75

SARFI - 90 SARFI - 70

Even

ts P

er S

ite P

er 3

0 D

ays

1996 / 19972006 / 2007




SARFI Event Rate for Manhattan System, 1996/1997 and 2006/2007

1.991

0.567

1.527

0.246

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

2.75

SARFI - 90 SARFI - 70

Even

ts P

er S

ite P

er 3

0 D

ays

1996 / 19972006 / 2007





2006-2007 Voltage THD Histogram Showing Relative and Cumulative Frequencies for All Sites, All Voltage Measurements

0%

2%

4%

6%

8%

10%

12%

14%

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

2.75

3.00

3.25

3.50

3.75

4.00

4.25

4.50

4.75

5.00

V THD (%)

Rel

ativ

e Fr

eque

ncy

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Count of Waveshape Samples: 3,184,096

Cum

ulat

ive

Freq

uenc

y

PQView®

Steady State Trending for Secondary Networks – Harmonic Distortion

• 2006/2007 Data – 3.184M steady state samples


• System Voltage Harmonic Distortion Mean, CP95 and CP99 Indices– System Average Total Harmonic Distortion – SATHD

• Weighted average of individual circuit segment voltage THD mean values

– System Total Harmonic Distortion CP95 - STHD95– System Total Harmonic Distortion CP99 - STHD99

• CP95 and CP99 value of weighted distribution of individual circuit segment voltage THD CP95 and CP99 values

SATHDL MEANTHD

L

s ss

k

T=

⋅=∑

1 MEANTHDTHD

Ns

ii

N

mw

mw

= =∑

1

f CP L

f CP L

t s sSTHD

t s s

( )

( ).

95

950 95

95×

×=−∞

−∞

∞

∑

∑

f x

f x

s i

CP

s i

s

( )

( ).−∞

−∞

∞

∑

∑=

95

0 95




Steady State Trending for Secondary Networks – Harmonic Distortion 1996-1997 and 2006-2007 Mean Voltage THD

Values Comparison All Sites

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

Volta

ge T

otal

Har

mon

ic D

isto

rtio

n M

ean

THD

1996-1997 Average THD Values 2006-2007 Average THD Values





1996-1997 and 2006-2007 CP99 Voltage THD Values Comparison All Sites

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

Volta

ge T

otal

Har

mon

ic D

isto

rtio

n 99

th P

erce

ntile

1996-1997 CP99 THD Value 2006-2007 CP99 THD Value


1996-1997 and 2006-2007 Voltage THD Values Comparison All Sites

1.59%

2.39%

2.70%

1.87%

2.70%

3.03%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

System MeanTHD

System CP 95THD

System CP 99THD

Volta

ge T

otal

Har

mon

ic D

isto

rtio

n 95

th P

erce

ntile

1996-19972006-2007




• System RMS Voltage Magnitude CP05 and CP95 Indices– SRVMI05– SRVMI95

• Weighted average of the RMS voltage magnitude recorded measured across system during monitoring period -- low and high end of range.

05.0)05(

)05(05

=×

×

∑

∑∞

∞−

∞−

sst

SRVMI

sst

LCPf

LCPf05.0

)(

)(05

=

∑

∑∞

∞−

∞−

is

CP

is

xf

xfs


Steady State Trending for Secondary Networks – Voltage Regulation



RMS Voltage Magnitude Indices for Con Edison System, 1996/1997 and 2006/2007

96.71

%

103.7

0%

97.23

%

103.2

6%

95%

96%

97%

98%

99%

100%

101%

102%

103%

104%

105%

SRVMI05 SRVMI95

RM

S Vo

ltage

Mag

nitu

de -

Per

cent

age

Nom

inal

1996 / 19972006 / 2007

Steady State Trending for Secondary Networks – Voltage Regulation



260235

365340

323 322

422 420

474

434

281

176

0

50

100

150

200

250

300

350

400

450

500

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Customer Calls per 100,000 Customers

Customer Calls per 100,000 Customers

Customer Trends Related to Power Quality and Reliability



Customer Contacts

40

25 25

10 82 3 3 2 0 0

43

31

73

43

66

4843

28

13 1215

46

62

93

77

97

110114 115

65

82

55

0

20

40

60

80

100

120

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

EMF visits PQ Visits Off-site Assistance

Customer Trends Related to Power Quality and Reliability


• Continued focused on reliability improvements and other initiatives– Third Generation (3G) Network and Substation Design – Smart Grid– Asset Sharing

• Continued focus on Power Quality Measurement and Analysis Capability– Expand substation monitoring capabilities– Integrate microprocessor relays and other measurement devices– Integration of Power Quality data with other SCADA data


Looking Forward

smart grid and power quality: bane or boon -...

Documents