AUTHOR 1:M.KRISHNA KANTH REDDY

B.TECH III-II , E.E.E.

ANNAMACHARYA INSTITUTE OF TECHNOLOGY AND SCIENCES, KADAPA.

SMART GRID

Cost of Power Disturbances:

$25 - $188 billion per year

~$6 billion lost due to 8/14/03 blackout

Northeast Blackout – August 14, 2003

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Affected 55 million people

$6 billion lost

Per year $135 billions lost for power interruption

http://en.wikipedia.org/wiki/Northeast_Blackout_of_2003

What does the concept of Smart What does the concept of Smart Grid Grid look like?look like?

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Electrical Infrastructure

“Intelligence” Infrastructure

Smart Grid Applications

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Distributed Generation and Alternate Energy SourcesDistributed Generation and Alternate Energy Sources

Self-Healing Wide-Area Protection and IslandingSelf-Healing Wide-Area Protection and Islanding

Asset Management and On-Line Equipment MonitoringAsset Management and On-Line Equipment Monitoring

Demand Response and Dynamic PricingDemand Response and Dynamic Pricing

Participation in Energy MarketsParticipation in Energy Markets

Shared Information – Continuously Optimizing – Intelligent Responses!

Real-time Simulation and Contingency AnalysisReal-time Simulation and Contingency Analysis

Outline

• Motivation• Sensing and Measurement • Communications and Security • Components and Subsystems • Interfaces and Decision Support• Control Methods and Topologies

Wireless Mesh Networking for Wireless Mesh Networking for the Smart Grid the Smart Grid

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www.elstermetering.com

Advanced Sensing and Measurement

Advanced Metering Infrastructure (AMI)

Provide interface between the utility

and its customers: bi-direction control Advanced functionality

Real-time electricity pricing Accurate load characterization Outage detection/restoration

California asked all the utilities to deploy the new smart meter

Advanced Sensing and Measurement

Health Monitor: Phasor measurement unit (PMU) Measure the

electrical waves and determine the health of the system.

Increase the reliability by detecting faults early, allowing for isolation of operative system, and the prevention of power outages.

Advanced Sensing and Measurement

Distributed weather sensing

Widely distributed solar irradiance, wind speed, temperature measurement systems to improve the predictability of renewable energy.

The grid control systems can dynamically adjust the source of power supply.

Integrated Communications and Security High-speed, fully integrated, two-way

communication technologies that make the smart grid a dynamic, interactive “mega-infrastructure” for real-time information and power exchange.

Cyber Security: the new communication mechanism should consider security, reliability, QoS.

Experiments for Noise and Interference

• They measured the noise level in dbm (the larger the worse)

• The outdoor background noise level is -105dbm

Advanced Components and Subsystems

Advanced Energy Storage

New Battery Technologies

Sodium Sulfur (NaS)

Plug-in Hybrid Electric Vehicle (PHEV)

Grid-to-Vehicle(G2V) and Vehicle-to-Grid(V2G)

Peak load leveling

Improved Interfaces and Decision Support

The smart grid will require wide, seamless, often real-time use of applications and tools that enable grid operators and managers to make decisions quickly.

Decision support and improved interfaces will enable more accurate and timely human decision making at all levels of the grid, including the consumer level, while also enabling more advanced operator training.

Control Methods and Topologies

Traditional power system problems:

Centralized

No local supervisory control unit

No fault isolation

Relied entirely on electricity from the grid

APS: Autonomous Power System

A localized group of electricity sources and loads Locally utilizing natural gas or

renewable energy

Reducing the waste during transmission

Using Combined Heat and Power (CHP)

Diverse Energy Sources

http://powerelectronics.com/power_systems/smart-grid-success-rely-system-solutions-20091001/

Wind

Solar

Nuclear

Fossil

References1. S. Massoud Amin and Bruce F. Wollenberg,

“Toward a Smart Grid,” IEEE Power and Energy Magazine, September/October 2005.

2. M. Pipattanasomporn and S. Rahman, “Intelligent Distributed Autonomous Power Systems (IDAPS) and their Impact on Critical Electrical Loads,” IEEE IWCIP 2005.

3. R. Li, J. Li, G. Poulton, and G. James, “Agent-Based Optimization Systems for Electrical Load Management,” OPTMAS 2008.

4. J. Li, G. Poulton, and G. James, “Agent-based distributed energy management,” In Proc. 20th Australian Joint Conference on Artificial Intelligence, pages 569–578. Gold Coast, Australia, 2007.

5. http://www.smartgrid.gov/, November 2010.