Controlling cascading failures with cooperative autonomous agents
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Controlling Cascading Failures with Cooperative Autonomous Agents. Paul Hines Sarosh Talukdar Dong Jia Huaiwei Liao. TPP Graduate Consortium, 27 July 2005 Work supported by ABB Corporate Research & the Carnegie Mellon Electricity Industry Center. Photo: Marc O. Rieger

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Controlling cascading failures with cooperative autonomous agents

Controlling Cascading Failures with Cooperative Autonomous Agents

Paul Hines

Sarosh Talukdar

Dong Jia

Huaiwei Liao

TPP Graduate Consortium, 27 July 2005

Work supported by ABB Corporate Research & the Carnegie Mellon Electricity Industry Center

Photo: Marc O. Rieger

http://www.math.cmu.edu/~ana/Pictures/pic7.html


Some cascading failures
Some cascading failures Agents

Hines, 18-Apr-05


Blackout size cdf
Blackout size CDF Agents

Source: Talukdar & NERC/DOE data

Hines, 18-Apr-05


What is a cascading failure
What is a cascading failure? Agents

Hidden

failure(s)

Disturbance

Violation(s)

Relay

operation(s)

Blackout

Network state

transitions

Hines, 18-Apr-05


Reducing cascading failure risk
Reducing cascading failure risk Agents

  • Prevention method

    • Reduce the risk through conservative operations

      • “N-1” security

      • Imposes additional dispatch costs

  • Control method

    • Reduce the risk through improved control systems

      • Give the grid “good reflexes”

Hines, 18-Apr-05


One approach
One approach… Agents

Hidden

failure(s)

Disturbance

Interrupt the CF

sequence here from a central location

Violation(s)

Relay

operation(s)

Blackout

Network state

transitions

Hines, 18-Apr-05


Another approach
Another approach… Agents

Hidden

failure(s)

Disturbance

Interrupt the CF

sequence here froma central location

Violation(s)

Relay

operation(s)

Blackout

Network state

transitions

Hines, 18-Apr-05


A new approach
A new approach… Agents

Hidden

failure(s)

Disturbance

Interrupt the CF

sequence here

using distributedautonomous agents

Violation(s)

Relay

operation(s)

Blackout

Network state

transitions

Hines, 18-Apr-05


Rationale for using distributed agents
Rationale for using distributed agents Agents

  • Information

    • No need for global knowledge

    • Reduced “seams” problems

  • Speed

    • Computation & action co-located

  • Robustness

    • Distributed solutions tend to be more resistant to failures

Hines, 18-Apr-05


Problem statement
Problem statement Agents

  • Improve the grid control system by

    • eliminating power system network violations at minimum social cost before a cascading failure results

    • using only distributed autonomous agents capable of shedding local load and generation.

Hines, 18-Apr-05


Solution method spatial decomposition
Solution method – Agents Spatial decomposition

Autonomous

Hines, 18-Apr-05


Solution method incremental work
Solution method – Incremental work Agents

  • Allow each agent to work iteratively to remove the violations that it is aware of

  • Model Predictive Control:

    • Calculate a plan

    • implement a portion of the plan

    • update the plan

    • implement a portion of the plan

  • Allow for cooperation among agents

Hines, 18-Apr-05


Operators Agents

u

x

Power Network

Bus 1

Measurement

hardware 1

Load/gen controller 1

Bus n

Load/gen controller n

Measurement

hardware n

Hines, 18-Apr-05


Operators Agents

x

u

u1

Power Network

δ1

Measurement

hardware 1

Load/gen controller 1

agent 1

+

un

δn

Measurement

hardware n

Load/gen controller n

agent n

+

Communication

Network

Hines, 18-Apr-05


Solution method cooperation
Solution method -- Cooperation Agents

  • Definition:

    • The sharing of useful information.

  • Many methods exist, we use the following:

    • When agents calculate a solution:

      • Compare that solution with those neighbors who appear to require control actions

      • If a discrepancy exists:

        • exchange important measurements

        • recalculate

        • repeat no more than 3x

Hines, 18-Apr-05


Verification method
Verification method Agents

  • Perform repeated simulations using IEEE networks and random double contingencies

  • Adjust the amount of communication (the size of the internal neighborhood)

Hines, 18-Apr-05


Typical result
Typical result Agents

Branch outages 8,40rl=2, re=10

Hines, 18-Apr-05


Control error
Control error Agents

Control error

Hines, 18-Apr-05


Control error vs communication
Control error vs. communication Agents

Local neighborhood radius

Hines, 18-Apr-05


Conclusions
Conclusions Agents

  • It is possible to control cascading failures using a flat network of distributed autonomous agents

  • Cooperation can vastly improve solution quality and/or reduce the amount of communication required

  • Improving the grid control system should allow operators to make better tradeoffs among conflicting objectives

    • (Dispatch costs, reliability, protection, network investment)

Hines, 18-Apr-05


Related policy issues
Related policy issues Agents

  • Where network authority is inherently distributed (>100 independent control areas in US eastern interconnect) a distributed solution has many advantages over centralized solutions.

  • While it is technically possible to control cascading failures, incentives for investment in such technologies are not always aligned with the costs.

Hines, 18-Apr-05


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