GRID DATA Program Introduction - ARPA-E · Analysis for a Smart and Resilient Grid PI: Prof. Pete Sauer Non-Wire Methods for Transmission Congestion Management through Predictive

Generating Realistic Information for the Development of

Distribution And Transmission Algorithms

GRID DATA Program Introduction

Tim HeidelProgram Director

Advanced Research Projects Agency – Energy (ARPA-E)

U.S. Department of Energy

GRID DATA Kickoff Meeting

Denver, CO, March 30-31, 2016

Emerging Grid Challenges

1

– Increasing wind and solar

generation

– Decentralization of generation

– Aging infrastructure

– Changing demand profiles

– Increasing natural gas generation

– Cybersecurity threats

‣ All of these challenges require

new tools for faster, better,

more robust grid optimization.

Responsive Demands

- Scheduling large loads (eg. industrial loads)

- Mobilize large numbers of small assets

Power Flow Controllers

- AC Power Flow Controllers

- High Voltage DC Systems

Energy Storage Optimization

- Scheduling energy flows

- Coordination of diverse storage assets

Transmission Topology Optimization

- Optimal line switching

- Corrective switching actions

‣ Advances in power electronics, computational technologies, and

mathematics offer new opportunities for optimizing grid operations.

New Opportunities for Grid Optimization

2

CD-PAR CAD Image

115kV, 1500A Prototype (2-5 Ω)

Continuously Variable Series Reactor

50uH (<150 lbs) Prototype

Distributed Series Reactor

3

ARPA-E GENI Optimization Projects (2012-2015)

4

AC-Optimal

Power Flow

Stochastic

Optimization

Distributed

Optimization

Optimal

Forecasting &

Dispatch of

Demand

Transmission

Switching

Energy

Storage

Optimization

Fast

voltage/transi

ent stability

calculations

Grid

Optimization

Toolkit

Advanced Computing Cost Reductions & Performance Gains

New Optimization Methodologies & Advanced Solvers

PMU-Based

State

Estimation

Fully leveraging GENI

successes will require new

Optimal Power Flow (OPF) tools…

5

But GRID DATA is not focused on

OPF algorithm development…

Primary Technical Targets (from GENI Funding Opportunity Announcement)

SCALABILITY: Capable of managing large dynamical systems (>10,000 nodes)

VALIDATION: Real-world datasets supplied by transmission operators or utilities.

FEASIBILITY: Consideration of sensing, communications, computational, and

actuation (ramp and dispatch) challenges for implementation in “real-time” markets.

FAILSAFE: Designs where a safe, “dumb” operation occurs in the event of local or

wide- area failure or attack.

GENI Program Targets

6

Exemplary GENI Modeling Results

7

Boston University & PJM

(Topology Control)

• PJM day-ahead + real-time simulations based on

historical data (2010, 2013, 2014).

• Generation economics.

• Must-run, maintenance and outage schedules.

• Load profiles and forecasts.

• Reserve requirements.

• Operational power flows (inc. historical topology).

• Interchange with neighboring regions.

• Transmission constraints and contingencies.

• > 13,000 nodes (up-to 100k for breaker node), >

18,000 branches, > 6000 single and multi-element

contingencies.

• Benchmarked both DA and RT market results against

historical data (nodal prices (major trading hubs),

dispatched generation mix, congestion costs and

congestion patterns).

Caltech & Southern

California Edison

(Distributed AC-OPF)

• SCE distribution systems

• 6 feeders (4KV, 12KV)

• ~15,000 buses

• <10% error compared with

substation measurements

Challenges with Requiring Real Datasets

‣ Realistic, large-scale datasets are extremely valuable but also difficult,

time consuming and expensive to collect, prepare, and use.

– Every team must negotiate unique data agreement.

– Base cases from ISO/utilities usually do not converge (substantial

cleaning always required).

‣ Data typically cannot be published in any form.

– Very difficult to independently verify/replicate results.

– Results may reflect quality of data more than quality of algorithms.

‣ ISOs/utilities have limited bandwidth to devote to R&D.

– Very few teams can put together credible project plans up front.

– High barrier to entry for those not already in power systems field.

8

Public Benchmark Power System Models

‣ Existing datasets are not adequate

‣ There are too few of them

‣ They are too small

‣ They are not representative of real systems

‣ They are incomplete

‣ They are too easy

Public OPF test systems are drawn from:

• IEEE Power Flow, Dynamic and Reliability,

MATPOWER, Edinburgh, EIRGrid, Other Publication

Test Cases

There are approximately 35

widely available public datasets. IEEE 30 bus.

9

Public OPF test systems are drawn from:

• IEEE Power Flow, Dynamic and Reliability,

MATPOWER, Edinburgh, EIRGrid, Other Publication

Test Cases

There are too few existing public datasets

• Compare against another data intensive field,

computer vision:

• Caltech 101: 9146 images

• Caltech 256: 30,607 images

• LabelMe: 106,739 images

• OPF is solved each year: 1 hour snapshots for a

year = 8,760 datasets for a single system.

IEEE 30 bus.

Images from Caltech 256.

There are approximately 35

widely available public datasets.

10

Existing public datasets are too small

• Real transmission networks are 5,000-50,000 buses.

• Almost all test cases comprise less than 4,000 buses.

Eastern Interconnection Transmission

Network (100kV+ only) Distribution of public test case sizes

11

Not representative of real systems (Examples)

‣ Extremely large (typically unobserved) voltage drops

‣ Low base voltages and an overabundance of voltage control capacity

‣ Lines with non-physical negative resistances (due to undocumented

network reductions).

‣ Lines with non-zero MW thermal emergency ratings, zero MW normal

ratings.

‣ All generators of each type have equivalent characteristics (and cost

curves).

‣ Identical subnetworks are repeated multiple times.

‣ Lists of contingencies, emergency (short term) equipment ratings,

protection system details, generator ramp rates and real and reactive

capability curves, transformer tap settings, capacitor bank locations and

settings, phase shifting transformer characteristics, energy storage

capacity, line switching capabilities, and flexible demand are more often

than not omitted.

Existing public datasets are incomplete

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• To have any hope of replicating

a real-world OPF problem,

dataset must (at a minimum)

include:

• Generator capabilities

• Generator costs

• Thermal line limits

• Most existing test sets lack

information on these key features.

Right: Datasets listed.

Spaces with “-” indicate

missing information from

the dataset.

C. Coffrin et al.NESTA: The Nicta Energy

System Test Case Archive, arXiv preprint

arXiv:1411.0359v1 (2014) 13

Existing Datasets Are Too Easy (?)

‣ In theory, to find a global solution

can take a time exponential in

the size of the network.

‣ In practice, existing solvers

and/or heuristics find solutions to

the existing test sets that are

extremely close to globally

optimal solutions very quickly.

– Line thermal and generator limits

are set to large non-binding values.

– Generators assigned quadratic cost

curves, often with the same

coefficients Low optimality gaps indicate that heuristics

are extremely close to the global optimum

(red). Surprisingly, the potential gains from

line switching are provably low (blue).

14C. Coffrin et al. NESTA: The Nicta Energy System Test Case Archive, arXiv

preprint arXiv:1411.0359v1 (2014)

Network Connectivity

Line Thermal Limits

SS Generator Characteristics

Generator Cost Curves

Time Series Load Data (by bus)

Contingency Lists

Bus shunt/transformer tap settings

Normal/Emergency Ratings

Dynamic Generator Characteristics

Maintenance Outages

Automated Local Controls

Protection Settings/Coordination

Power Market Design Details

Operator actions (intuition)

GRID DATA Program Objective

Accelerating the development, evaluation, and adoption of new grid

optimization algorithms will require more realistic, detailed public datasets.

GRID DATA:

Increasing

Complexity &

Completeness

Current

datasets

15

GRID DATA:

Increasing

Realism

“Realistic

but not

Real”

Two Pathways to New Datasets

Real Data

- Start with real data, then anonymize,

perturb topologies and change

sensitive infrastructure asset data as

necessary.

- Risks:

- Requires extremely close collaboration

with ISOs such that infrastructure is not

reconstructable and can be publically

released.

- Datasets may no longer well represent

real data.

- Real data is often messy, incomplete.

Open-access, large, realistic,

validated datasets

Synthetic Data

- Generate via expert input,

geographic/road data and data mining.

- Generate new random graph methods

for transmission networks.

- Devise statistical metrics (moments of

capacity distributions, degree

distributions of networks); validate

against real data.

- Risks:

- Validation metrics may be incomplete or

misleading. (Leading to lack of realism.)

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New Model Repositories Needed

17

Existing mechanisms for

sharing and collaboratively

developing, reviewing

models are limited.

New Model Repositories Needed

18

‣ Enhance research repeatability (and transparency) by enabling the

collaborative maintenance and version control of models.

‣ Researchers need to be able to easily contribute and share new models

with the community.

‣ Open source software development community has enabled highly

productive, widely distributed, technical collaboration involving

thousands of individuals.

Project Categories

GoalsDuration 2016-2018

Projects 7

Total

Investment$11 Million

Program

DirectorDr. Tim Heidel

GRID DATA ProgramGenerating Realistic Information for the Development

of Distribution And Transmission Algorithms

Development of large-scale, realistic,

validated, and open-access electric power

system network models with the detail

required for successful development and

testing of new power system optimization

and control algorithms.

• Transmission, Distribution, and Hybrid Power System Models & Scenarios

• Models derived from anonymized/obfuscated data provided by industry partners

• Synthetic models (matching statistical characteristics of real world systems)

• Power System Model Repositories

• Enabling the collaborative design, use, annotation, and archiving of R&D models

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Power System Network Model Requirements

‣ Teams may choose to address any specific OPF application(s).

‣ Any method(s) may be used to create test systems (using real-world data

or purely synthetic approaches).

‣ Teams may choose to address (i) transmission/bulk power systems, (ii)

distribution systems, or (iii) hybrid transmission and distribution systems.

‣ Required and optional model details were specified in the FOA.

‣ Detailed plan for validation with technical success/fail criteria required.

‣ Models must be publicly releasable and must not contain CEII data.

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Transmission

At least one small network model having between 50 and 250 electrical

buses required and at least one large network model having > 5,000

buses. (Larger test systems may not consist of repeated duplicates of

smaller systems.)

Distribution

At least one model with at least 3 independent feeders originating at

one or more substations, corresponding to a minimum of at least 5,000

individual customers.

Scenario Creation Requirements

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‣ Scenario sets must be designed with temporal resolutions and time-

coupling suitable for solving one or more specific OPF problems.

‣ Any method(s) may be used to create power system scenarios (using

real-world data or purely synthetic approaches).

‣ Teams must generate at least a full year of time-coupled physically

feasible scenarios with at least hourly granularity. (Teams are strongly

encouraged to use the shortest feasible time step between scenarios (5

minutes, 15 minutes, etc.)).

‣ Scenarios must represent a range of difficulty to OPF optimization

algorithms. Teams are also encouraged to develop infeasible scenarios

(to test the ability for OPF algorithms to identify infeasibility quickly).

‣ Required and optional scenario details were described in the FOA.

‣ Teams must have a detailed plan for validation with technical success/fail

criteria to ensure scenarios are sufficiently representative of a range of

real-world power system operating conditions.

Repository Creation Requirements

‣ The repository must be completely open (including international access),

giving researchers the ability to upload modified versions of existing

models and designate relationships between different models (i.e.

version control) as well as provide annotation and/or comments on

specific models (similar to, for example, GitHub).

‣ The repository should be able to accommodate different kinds of power

system models (not just ones suitable for OPF control and optimization).

‣ The repository should have the ability to scale the repository to archive

an arbitrary number of power system models.

‣ Teams have proposed a self-funding mechanism with potential to extend

well beyond ARPA-E’s development funding.

‣ Teams are required to establish a set of standards for models and a clear

self-governance model for the repositories.

‣ The teams must design a plan for active curation of power system

models in the repositories.

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GRID DATA Project Portfolio

23

Power System Models & Scenarios Model Repositories

T Transmission Models

D Distribution Models

H Hybrid Models

T

PI: Prof. C. DeMarco

T

PI: Prof. T. Overbye

H

PI: Dr. H. HuangPIs: Dr. B. Hodge

& Dr. B. Palmintier

D

T

PI: Prof. P. Van Hentenryck

PI: Dr. M. Rice

PI: Dr. A. Vojdani

23

GRID DATA Program Participants

24

Lead Organizations

Subs/Team Members

CIT

GridBright

Avista

ASU

NRECA

PJM

MIT

PNNL

VCU

CAISO

University of

Wisconsin

Columbia Univ

University

of Michigan

UISOL

UIUC

LANL

Cornell

ANL

GE/Alstom

ComEd

GAMS

NREL

Additional ARPA-E Performer Presentations

25

OPEN 2012

OPEN 2012

OPEN 2012

Cyber-Physical Modeling and

Analysis for a Smart and

Resilient Grid

PI: Prof. Pete Sauer

Non-Wire Methods for

Transmission Congestion

Management through Predictive

Simulation and Optimization

PI: Dr. Henry Huang

Micro-Synchrophasors for

Distribution Systems

PI: Dr. Alexandra von Meier

Additional ARPA-E Performer Presentations

26

IDEAS

OPEN 2015

OPEN 2015

Coordinated Operation of Electric And Natural Gas Supply Networks: Optimization Processes And Market DesignPI: Dr. Alex Rudkevich

High Performance Power-grid Optimization (HIPPO) for Flexible and Reliable Resource Commitment Against Uncertainties

PI: Dr. Feng Pan

Global-Optimal Power Flow (G-OPF)

PI: Prof. Hsiao-Dong Chiang

Bigwood Systems Inc.

Kickoff Meeting Objectives

27

Research

Teams

Industry

Experts

Gov’t

PMs

ARPA-E

Knowledge

Cross-disciplinary

learning about issues

and opportunities

Learning and

industry insights for

researchers & gov’t

Summary of program

goals

Relationships

Potential collaborations

between research

teams

Industry engagement to

improve and gain

access to research

outcomes

Future development

opportunities within

industry and gov’tCommunity

Datasets

making an

impact in the

worldideas

x

xx

incomplete team

uncertain value

poor implementation

Ideas alone are often not enough

Low yield

28

Datasets

making an

impact in the

world

ideas+ value (Techno-economic analysis)

+ team (Stakeholder engagement)

+ implementation (Skills and Resources)

ARPA-E Tech-to-Market tries to improve yield

29

GRID DATA Kickoff Meeting Objectives

30

‣ Discuss GRID DATA objectives (especially first year goals)

‣ Provide critical feedback on approaches and applications.

‣ Explore partnership opportunities and potential synergies.

‣ Brainstorm strategies for maximizing GRID DATA impact

‣ Discuss ARPA-E OPF competition vision

Agenda: Wednesday Morning

31

Start Time

Institution/Presenter Project Title

DAY 1

8:00 Eric Rohlfing (ARPA-E) Welcome and Introductions

8:15 Tim Heidel (ARPA-E) GRID DATA Program Introduction

9:00 Richard O’Neill (FERC) Generating Good Test Problems

9:20 Yonghong Chen (MISO) Bridging a Gap: The Role of and Challenges for GRID DATA

9:40 Networking Break

GRID DATA Model Development

10:10 Wisconsin (GRID DATA)EPIGRIDS: Electric Power Infrastructure & Grid Representation in Interoperable Data Set

10:30 Michigan (GRID DATA)High Fidelity, Year Long Power Network Data Sets for Replicable Power System Research

10:50 UIUC (GRID DATA) Synthetic Data for Power Grid R&D

11:10 PNNL (GRID DATA)Sustainable Data Evolution Technology (SDET) for Power Grid Optimization

11:30 NREL (GRID DATA)SMARtDaTa: Standardized multi-scale Models of Anonymized Realistic Distribution and Transmission data

11:50 Discussion Moderator: Marija Ilic

12:20 LUNCH

Agenda: Wednesday Afternoon

32

Start Time

Institution/Presenter Project Title

DAY 1

12:20 LUNCH

13:20GRID DATA BREAKOUT SESSION #1:

Model Validation

14:40 Networking Break

15:10 BREAKOUT SESSION #1 Reports

OPF Competition

15:40 Tim Heidel (ARPA-E) OPF Competition Introduction and Overview

16:10 PNNL (OPF Competition) ARPA-E Power Grid Optimization Competition Design

16:55 Discussion

17:15POSTER SESSION

Agenda: Thursday Morning

33

Start Time

Institution/Presenter Project Title

DAY 2

8:30 Tim Heidel (ARPA-E) Welcome and Recap

8:40 Patrick Panciatici (RTE)Realistic data for challenging problems; an internal TSO R&D perspective

9:00 Tao Hong (UNC Charlotte) Lessons learned from organizing energy forecasting competitions

GRID DATA Repository Development

9:20 PNNL (GRID DATA)Data Repository for Power system Open models With Evolving Resources (DR POWER)

9:40 GridBright (GRID DATA)A Standards-Based Intelligent Repositorty for Collaborative Grid Model Management

10:00 Discussion Moderator: Carleton Coffrin

10:20 Networking Break

10:50GRID DATA BREAKOUT SESSION #2:

Data Formats and Accelerating Adoption

12:05 LUNCH

13:00 BREAKOUT SESSION #2 Reports

Agenda: Thursday Afternoon

34

Start Time

Institution/Presenter Project Title

DAY 1

OPEN FOA 2012 Projects

13:30 CIEE (OPEN 2012) Micro-Synchrophasors for Distribution Systems

13:50 UIUC (OPEN 2012)Cyber-Physical Modeling and Analysis for a Smart and Resilient Grid

14:10 PNNL (OPEN 2012)Non-Wire Methods for Transmission Congestion Management through Predictive Simulation and Optimization

14:30 Discussion Moderator: Terry Oliver

14:50 Networking Break

OPEN FOA 2015 & IDEAS Projects

15:20Newton Energy Group

(OPEN 2015)Coordinated Operation of Electric And Natural Gas Supply Networks: Optimization Processes And Market Design

15:40 PNNL (OPEN 2015)High Performance Power-grid Optimization (HIPPO) for Flexible and Reliable Resource Commitment Against Uncertainties

16:00 Bigwood Systems (IDEAS) Global-Optimal Power Flow (G-OPF)

16:20 Discussion Moderator: Josh Gould

16:45 Final Discussion Program Director Wrap-up

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www.arpa-e.energy.gov

Tim Heidel

Program Director

Advanced Research Projects Agency – Energy (ARPA-E)

U.S. Department of Energy

[email protected]