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Monitoring of the Smart Grid An Overview Yee Wei Law 1

Yee Wei Law 1. 2 Australian Standard: AS 60038-2000 “Standard voltages”: Transmission EHV: 275kV, 330kV, 500 kV HV: 220kV MV: 66kV Distribution LV: 11kV,

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1

Monitoring of the Smart GridAn Overview

Yee Wei Law

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Introduction to the Grid

Australian Standard: AS 60038-2000 “Standard voltages”:

TransmissionEHV: 275kV, 330kV, 500 kVHV: 220kVMV: 66kV

DistributionLV: 11kV, 22kV

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Why and what is the Smart Grid?

Three Smart Grid components◦ Transmission: Wide-area Monitoring System◦ Distribution: Distribution Automation◦ Consumption: Demand Response

Research Areas

Conclusion

Outline

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What is the Smart Grid Smart grid = envisioned next-gen power grid that is:

Intelligent(senses

overload, rerouting)

Efficient(meets demand

without more cost)

Accommo-dating

(renewable energy)

Motivating(demand response)

Quality-focused(minimum

disturbances, interruptions)

Resilient(to attacks, disasters)

“Green”(minimal

environmental impact)

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Why the Smart Grid? Ageing hardware + population growth = equipment at

limits Market deregulation (‘80s-‘90s)

Climate change◦ Distributed generation using renewable energy sources

Global cooperation (International Smart Grid Action Network including Australia)

Cost of outages in USA in 2002: $79B

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8-10% energy lost in transmission and distribution networks

Energy Management System (EMS): control generation, aggregation, power dispatch

EMS computes optimal power flow

However, SCADA-based EMS gives incomplete view of system steady state (resolution: several seconds)

Why WAMS?

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Aka synchrophasors, because time-synchronized using GPS Measures voltage and current phasors Typically 30 time-stamped samples per sec

Control of electromechanical oscillation, voltage, frequency etc.

Phasor Measurement Units (PMUs)

ABB’s RES521

Macrodyne’s 1690MiCOM P847

Phadke and Thorp’s prototype circa 1988

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Generic architecture of the WAMS

PMU PMU PMU PMU...

PDC

Application Data Buffer

Real-Time Monitoring

Real-Time Control

Real-Time Protection

Layer 1: Data acquisition

Layer 2: Data management

Layer 3: Data services

Layer 4: Applications

WAN

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Remotely and efficiently identify and resolve system problems

Enables load shifting, alleviates overload conditions Reconfigures the system after disturbances or interruptions Facilitates coordination with customer services such as

time-of-use pricing, load management and DERs Maintain equipment health

Why Distribution Automation (DA)?

Substation Distribution networkControl center

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EPRI proposed advanced DA – complete automation of controllable equipment (actuators and sensors)

Sample actuators:◦ Auto-recloser: circuit breaker that re-closes after interrupting

short-circuit current◦ Voltage regulator: usually at the supply end, but also near

customers with heavy load◦ Switched capacitor bank: switched in when load is heavy,

switched out when otherwise

Advanced Distribution Automation

RecloserVoltage regulator

Switched capacitor bank

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Static sensors:

Non-static sensors:

DA: sensors

RF temperature sensor

RF leakage current sensor

Metal insulated semiconducting (MIS) sensor for detecting hydrogen

◦ Developed by Tokyo-based HiBot

◦ Able to navigate around obstacle

◦ Laser-based sensors◦ HD camera◦ Cost & energy is a

constraint

Aerial photography (SP AusNet):

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EPRI identified two critical technologies:◦ Open communication architecture◦ Redeveloped power system for component interoperability

Urban networks: fiber opticsRural networks: wireless

DA: communication

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Wireless comm technologies for DA  CDMA2000 GE-MDS 900MHz Silver Spring

NetworksWi-Fi/IEEE 802.11 WiMAX/IEEE

802.16Interoper-ability

Open standard Proprietary Proprietary Open standard Open standard

Capacity 76.8 kbps (80-ms frame)153.6 kbps (40-ms frame)307.2 kbps (20-ms frame)

19.2 kbps (80 km)115 kbps (48 km)1 Mbps (32 km)

100 kbps 54 Mbps (802.11a)11 Mbps (802.11b)54 Mbps (802.11g)72 Mbps (802.11n)

9 Mbps

Latency Hundreds of milliseconds Tens of milliseconds Tens of milliseconds

Milliseconds Milliseconds

Interference rejection

DSSS, 2 GHz frequency band allows frequency band re-use 

FHSS, 902-928 MHz FHSS, 902-928 MHz

802.11a: ODFM, 5 GHz802.11b: DSSS, 2.4 GHz802.11g: OFDM/DSSS, 2.4 GHz802.11n: OFDM, 2.4/5 GHz*2.4 GHz band is crowded; 5 GHz less so

OFDM, 3.65-3.70 GHz

Transmission range

Nation-wide service coverage

80 km Unknown 802.11a: 120 m802.11b/g: 140 m802.11n: 250 m

20 km

Configuration Point-to-multipoint Point-to-point, point-to-multipoint

Point-to-point Point-to-point, point-to-multipoint

Point-to-multipoint

Jemena, United Energy, Citipower and Powercor SP AusNet and Energy Australia

* Note: ZigBee is not in here

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Edge over ZigBee: RF better penetration of steel structures, energy-efficient, better security

Notable vendor: Dust Networks

6LowPAN (RFC4919, RFC4944 etc.) IPv6 for low-power wireless personal area networks Edge over ZigBee: interoperability with existing IP-based

devices Routing protocol still being standardized by the ROLL

working group (Routing Over Low power and Lossy networks)

Open mesh network standards

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Keep demand curve as flat as possible (especially during summers and winters)

Ideally, everyone uses high-efficiency appliances Motivate consumers to shift their usage to off-peak hours

Demand Response

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Price-based programs◦ Dynamic peak pricing / critical peak pricing: customers notified

in advance of critical peak times (at most several days per year)

Demand Response programs

DPP = Dynamic Peak Pricing

Source: Energy Market Consulting associates, “A Report to the Ministerial Council on Energy”, 2009

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Price-based programs◦ Time-of-use pricing: different tariffs for different hours of the

day

Demand Response programs

Available from some vendors at limited locations, for example:

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Incentive-based programs◦ Direct load control (e.g. Australian water heaters)◦ Interruptible/curtailable service: reduce load during

contingencies◦ Demand bidding, emergency demand response, capacity

market, ancillary services market etc.

Reference: US Department of Energy, “Benefits of Demand Response in Electricity Markets and Recommendations for Achieving them,” report to the United States Congress, February 2006.

Enabling technology: smart meter and Advanced Metering Infrastructure

Demand Response programs

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Smart Meter and Advanced Metering Infrastructure (AMI)

Neighborhood Area Network

Home Area Network

AMI

Smartmeter

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Smart Meter and Home Area Network

In VIC, official rollout will run from 2009 to 2013

Smart meters ◦ To send meter data every 30 minutes◦ To enable remote connection/disconnection◦ To detect outage◦ To support demand response

Provide information via in-home display Provide input to smart appliances via Home Area Network (ZigBee for

Australia)

Fast charging Plug-in Hybrid Electric Vehicles (PHEV) introduce harmful harmonics – smart meters will help [Masoum et al., 2010]

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Transmission PMU placement problem Low-cost transmission line monitoring

Distribution Distribution network reconfiguration

◦ Multi-objective optimization problem: minimize real losses, regulate voltage profile, load-balancing

Resilient wireless sensor network for substation monitoring and distribution automation

Coordination of load management and demand response

Overall Security

Some research areas

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Advances in sensor and comm. tech driving Smart Grid Grid modernization stimulates multi-disciplinary research In progress:

◦ $100m Smart Grid, Smart City demo project in Newscastle

◦ Intelligent Grid: CSIRO and five universities Collaboration opportunities sought

Conclusion

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EPRI, “Sensor Technologies for a Smart Transmission System,” white paper, Dec 2009.

V. Gungor and F. Lambert, “A survey on communication networks for electric system automation,” Computer Networks, vol. 50, no. 7, pp. 877 – 897, 2006.

Y. Liu et al., “False data injection attacks against state estimation in electric power grids,” Proc. 16th ACM Computer and Communications Security, 2009.

M. Masoum, P. Moses, and S. Deilami, “Load management in smart grids considering harmonic distortion and transformer derating,” in Innovative Smart Grid Technologies (ISGT), 2010, pp. 1 –7.

B.K. Panigrahi et al., “Computational Intelligence in Power Engineering”, Springer-Verlag Berlin Heidelberg, 2010.

Select references

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Generation◦Distributed generation◦Microgrid

Transmission◦Wide-area monitoring system (WAMS)

Distribution◦Distribution automation (DA)

Consumption◦Demand response

Smart Grid components

Advanced Metering Infrastructure (AMI)