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Grid Modernization – A Strategic Imperative for 2050

Advanced Energy Conference May 1, 2013

By Carl ImhoffElectric Infrastructure Sector ManagerPacific Northwest National Lab

The challenge ahead is complex The grid must meet new expectations

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Electrify transportation sector to reduce dependence on imported oil

Delivering 300GW of renewable generation by 2025

Maximize benefits of end-use efficiency and storage

Accommodate changing and responsive loads

Historical Expectations Emerging Expectations

Affordable Power

Reliable Power

Secure Power

Our electric infrastructure must continue to deliver affordable, reliable and secure power while simultaneously undergoing a major transformation

Transformation is Already Substantial

North American phasor measurement network will exceed 1200 measurement points networked by late 2013

Digital metering expected to reach 30% market share 2013, 50% by 2015.

Mainstay operational tools (minutes) now being demonstrated at SCADA rate (seconds)

Distribution automation demonstrating substantial improvements in efficiency and reliability

Demand response at the GW scale in several markets in the U.S.

Challenge: How do we capture Smart Grid benefits in current grid AND position to enable new paradigms for the grid we want in 2050?

Future Outcomes Enabled by Grid Transformation

Continued digitization across the system will lead to a “transactive” future that delivers broad optimization

Level playing field for legacy and new “smart” infrastructure

Leverages broad transparency to engage demand to help manage reliability and deliver clean generation

Enables consumers to engage their energy choices like never before

Increased strategic value of grid for public goods issues leverage “transactive management”

Energy efficiency,

Preferred fuel / generation mix etc.

Electrification of transportation

Broad use of high performance computing at local and regional levels to enable new paradigms of design and operation, delivering new levels of resilience to all hazards

Pacific Northwest Demonstration Project

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What:• $178M, ARRA-funded, 5-year

demonstration• 60,000 metered customers in 5 states

Why:• Quantify costs and benefits• Develop communications protocol• Develop standards• Facilitate integration of wind

and other renewables

Who:Led by Battelle and partners including BPA, 11 utilities, 2 universities, and 5 vendors

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PNWSG Demo Project Basics

Operational objectivesManage peak demandFacilitate renewable

resourcesAddress constrained

resourcesImprove system

reliability and efficiency

Select economical resources (optimize the system)

Aggregation of Power and Signals Occurs Through a Hierarchy of Interfaces

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PNW Region “Influence Map” – Topology

Cut Plane

Flowgate

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Regional Modeling

Alstom EMS

Alstom MMS

Future state Estimation by optimization

BPA

3TIER

Load ForecastGeneration SchedulesOutages

Renewable Generation

Forecasts

NetworkState

Gen. schedulesLoad forecasts

Transmission Zone TC Node Inputs

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High Performance Computing Opens New Paradigms of Operation

Massive Contingency Analysis: HPC improving reliability and efficiency of power systems

operations

Parallelization dramatically increases computational speed

Enables evaluation of a large number of scenarios

Revolutionizes grid operations and planning

Fast Dynamic Simulation:New model improving system

efficiency

Full topology model

Real-time performance rating

Enables improved asset management

# of processors Speedup

1024 1004

1536 1498

2048 1920

Currently running 10k processors, achieved 10,000x speed up

Parallelized Optimization Methods Enable Precise Management of Grid Complexities

WECC 230kV and above

Serial NDS is faster than CPLEX

Parallel NDS is 17 times faster

WECC 100kV and above

CPLEX no longer practical—time is divided by 10 and not converged

Parallel NDS is 160 times faster—even ignoring CPLEX pre-solve time

The bigger the problem, the better the relative performance

Key Challenge: Data to Knowledge

We need:

New networks to route data securely and efficiently

Distributed signal analysis and hardware automation

New analytic methods to extract knowledge

Simulations that run in microseconds vs. minutes, minutes vs. days

Visual analytics to aid decision making

Counter measures to advanced, persistent threats

The major challenge is in translating new real-time data into actionable knowledge that enables operation of the system in ways never before possible – ensuring unprecedented Reliability, Resilience and Efficiency.

Protected Information / Proprietary Information

Questions?

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