Modeling for the Smarter Grid–TransCARE software provides probabilistic Trans reliability Current...

© 2016 Electric Power Research Institute, Inc. All rights reserved.

Roger C. Dugan Sr. Technical Executive

EPRI, Knoxville, TN

Presented at

“Tools for the Smart Grid”

BNL/ISGAN Workshop on Modeling Simulation and More

April 14-15, 2016

Modeling for the

Smarter Grid

2 © 2016 Electric Power Research Institute, Inc. All rights reserved.

EPRI is at the Forefront of Advancing Computer Tools

and Methods for Supporting Utility Grid Planners

Utility grid planners require improved computer tools

– To assess benefits and impacts of solar PV, storage and other DER

There have been advancements in commercially-available

tools within the last decade but gaps remain

– For both transmission grid tools and distribution system analysis tools

– Combined simulation of transmission and distribution

This presentation gives and overview of recent and

continuing research


Topics Addressed in this Presentation

Transmission grid performance with renewables

Probabilistic approaches to planning

– Planners are accustomed to static, deterministic analysis

– Utility planners are often uncomfortable with probabilistic methods

Renewable DER naturally requires probabilistic approaches

Modeling Storage for distribution planning

Quasi-static time series analysis

PV system modeling

DMS modeling

Dynamics analysis for microgrids


Transmission Grid Tool Research


Overview: Distributed Resources & Renewables

Integration to the Bulk System

DOE SUNRISE

Dist PV Integration Assessment

Resource Reliability Capability

Integrated Grid Framework

Forecast Value & Integration

Reserve Determination

System Flexibility Adequacy

Feeder Hosting Capacity

Models for Reliability Analysis & Composite Load Levels

Production Simulation

Model Development

& Testing

Flexibility Analysis/ Adequacy

Utility Threat Identification

Feeder Clustering & Characteri-

zation

Strategic Plan Development

Operational Simulation Tools & Analysis


Issue: Maintain bulk system operational reliability with large

penetration of non-synchronous resources

Key Recent EPRI R&D Results

– DER Ride-Through Req. White Paper / IEEE P1547 Facilitation

– Reliability Contributions White Paper

– Analysis of voltage and frequency performance of BES with DER

– Comparison of various modeling approaches for DER in bulk system studies

Current Work

– DER modeling in BES studies

– Transmission ‘hosting capacity’

– Frequency response with high levels of variable generation

Value

• Understanding implications of

high penetrations of distributed PV

• Bases for planning strategies for high

penetration futures

PV Systems Equivalent Representation


Various approaches to model

active distribution systems

• Minimum level of modeling detail

• Data needs

• Automation of creation of

equivalent models


Various approaches to model

active distribution systems

• Minimum level of modeling detail

• Data needs

• Automation of creation of

equivalent models

Representative active distribution system (ADS) data

1. Bottom-up construction of

detailed ADS

2. Bottom-up construction of

equivalent ADS by clustering of DERs

5. Change of equivalent

impedance in equivalent ADS

4. Satisfactoryvalidation of equivalent

ADS performance?

Validated equivalent ADS with multiple

voltage levels

No

6. Highestvoltage level of unmeshed ADS

reached?

Yes

No

Equivalent ADS of certain voltage level(s)

Yes

7. Connect equivalent ADS to

detailed ADS of next higher voltage level

3. RMS simulation of detailed and equivalent

ADS and comparison of results

HV

MV

eHV

Load

MV

Load LVRT

PF100

LV

LV

Load

PF100

aRCI NEW

NEW

LVRT

NEW

PF100 LVRT

PF095 NEW

PF100 aRCI

NEW

PF100

PFPOW

PF100

NEW

HV

HV

HV HV

eHV

Load

HV

CHP / Bio

Wind

Photovoltaic

Class

Class specifies

the fault behviour

Primary voltage active distribution system equivalent

Secondary voltage

active distribution

system equivalent

n

2

3

4

Measurement

location

1

Fvl

vrrecov

FvhVt3Vt2Vt1Vt0

Fvl

frrecov

FvhVt3Vt2Vt1Vt0

:

:

Pext

Pref

Pdrp

Vt

It

Qref

Freq_ref

Freq

Ddn Pdrp

11 + sTg

11 + sTg

FvhFfh

FvlFfl

+

++

+

+

+

+N

N

D

D

Ipmax

0

Iqmax

Iqmin

XC

fdbd

0.01

QmxQref

QmnV0 V1

Dqdv

Ipcmd

Iqcmd

Ip

Iq

It = Ip + j Iq

Q Priority (Pqflag =0)Ipmax = ImaxIqmin = -IqmaxIpmax = (Imax2-Iqcmd2)1/2

P Priority (Pqflag =1)Ipmax = ImaxIqmax = (Imax2-Ipcmd2)½

Iqmin = -Iqmax

-

+


Evaluation of DER Impacts

on Transmission Performance

• DER aggregation for bulk system

studies and modeling guidelines

• Interconnection Recommendations

based on system studies

Distributed Energy Resource Impacts on Transmission


DOE SUNRISE Strategic

Planning for Distributed PV

• Strategic plan & operational impact

analysis tools for integrating PV

• Southern Company & TVA

• Voltage, Frequency, Flexibility, and

Operating Reserve Impacts

Feeder Hosting Capacity

Models for Reliability Analysis & Composite Load Levels

Production Simulation

Model Development

& Testing

Flexibility Analysis/ Adequacy

Utility Threat Identification

Feeder Clustering & Characteri-

zation

Strategic Plan Development

Operational Simulation Tools & Analysis


Transmission Performance Impacts of Distributed PV

Impact on Voltages :

Delay in voltage recovery

Degradation of load power factor

Change in Active/Reactive

Power Margins

Impact on Frequency:

Reduction in system inertia due

to change in generation mix

PV drop out due to large voltage

disturbance (as per IEEE 1547)


Risk Based Planning

Recent EPRI R&D Results

– Load, Dispatch, & Outage

Uncertainty tool provides Planning

case /probabilities

– TransCARE software provides

probabilistic Trans reliability

Current Work

– Develop grid resiliency

assessment framework

Risk-based planning tools treat

uncertainties to ensure reliability

and economic investment

Illuminate value of transmission

Risk-Based Planning

• TransCARE analysis software

• Load, Dispatch, & Outage uncertainty

model for setting planning cases

• EISPC Risk-Based Planning primer,

application, & R&D gaps whitepaper 7

,250

8,0

00

8,7

50

9,5

00

10

,25

0

11

,00

0

11,7

50

12,5

00

13,2

50

14,0

00

14,7

50

15,5

00

16,2

50

17

,00

0

17,7

50

18,5

00

19,2

50

20,0

00

20,7

50

21,5

00

1

10

100

1000

0

800

1,600

2,400

3,200

4,000

4,800

5,600

6,400

Region Load (MW)

Frequency of Occurence

Renewable Output (MW)

100-1000

10-100

1-10

HILF

Events

Average

System

Conditions

HILF

Events


Scenario Builder Tool to Determine Trans. Planning Cases

across Uncertainties

Gen. & Trans.

Outage Data

Load Variation

(Weather)

Load Variation

(Economic)

Wind & Solar

Variability

Hydro Variability

Demand

Response

Network Model,

Gen. Merit Order &

Dispatch Price

Various Load/Gen.

Dispacth Scenarios

(with probability)

Monte Carlo Draw

Gen. & Trans.

Outages


Integration of Wind/PV

Forecasts into Operations

• Evaluation of Wind/PV Forecast

accuracy and value in operations

• Methods to integrate forecasts into

key operations functions

• Use of Probabilistic Forecasts

Managing Uncertainty in Operations with high VG

Applications of Stochastic

Optimal Power Flow

• Determine operating reserves based

on uncertainty in wind/solar forecasts

• Advanced operational simulation tools

to investigate system operations

• Applying at CAISO and engaging

vendors

0

1000

2000

3000

4000

7/2/20 0:00 7/2/20 12:00 7/3/20 0:00 7/3/20 12:00 7/4/20 0:00

MW

Comparison of Load Following Up Requirements

Dynamic LFU(Load+Wind&Solar) Static LFD LFU_Load Dynamic LFU-Wind+Solar

0

500

1000

1500

2000

2500

3000

3500

7/2/20 0:00 7/2/20 12:00 7/3/20 0:00 7/3/20 12:00 7/4/20 0:00

MW

Comparison of Load Following Down Requirements

Dynamic LFD(Load+Wind &Solar) Static LFD LFD_Load Dynamic LFD-Wind+Solar


Planning Challenges of Renewable Integration

Minimum Load Requirements Base load, non-flexible capacity

Ramping Requirements Continuous ramping

or trough-to- peak shapeable capacity,

including ramping needs in above

normal weather conditions

Flexibility Requirements regulation, load following

capability for forecast uncertainty

and intra-hour variability

Contingency Reserve Frequency responsive,

spin/non-spin capability

1-in-2 peak

demand

forecast

Source: CAISO, Resource Adequacy Flexibility Workshop

12

Future procurement must satisfy operating flexibility in addition to

traditional capacity requirements


EPRI Flexible System Planning R&D

Flexibility Assessment

Software Tool

• Flexibility metrics

• Screening analysis

• Detailed flexibility evaluation

Resource and Transmission

Flexibility

• Resource adequacy considering flexibility

• Transmission and flexibility

• New resource types

Utility/ISO Flexibility

Case Studies

• Insights as to time horizons concerns

• Order of magnitude of possible risk


EPRI flexibility metrics for system planning

Multi-Level Approach – Levels 1 and 2 screening

– Levels 3 and 4 detailed metrics

– Post-processed metrics based on

simulated or historical data

Three detailed metrics: – Periods of Flexibility Deficit

– Expected Unserved Ramping

– Insufficient Ramping Resource

Expectation

Currently benchmarking

various systems – White paper available on epri.com

Level 1

• Variability Analysis & Flexibility Requirement

Level2

• Resource Flexibility Calculation

Level 3

• System Flexibility Metrics

Level 4

• Transmission and Fuel Constrained Flexibility


Situational Awareness

Synchrophasor Applications

Alarm Management Processes

Ops Visualization/Awareness

• Tools to identify most critical Op Limit

and recommendations for Op action

• Operator visualization/awareness of

equipment health & protection status

Improved Operator Awareness &

Decision Making

Improved Real-Time Assessment


R&D effort to examine linking tools across different

domains

System is expected to change at a

faster pace than before

Also greater change in resource

mix – Variable Generation,

Demand Response, Energy

Storage

Consider impact of resource mix

changes on reliability and impact

of reliability constraints on

resource mix buildout

Gaps in long term economics

– Resource adequacy

– Flexibility

– Ancillary services

– Reliable transmission

– Distribution modeling

How to pass relevant info between high level to detailed results??


Distribution System Tool Research


18

Impact of Smart Grid on Distribution System Analysis

(DSA)?

What DSA framework is needed to support all features of the

SG?

Will there be a need for DSA if everything is monitored

thoroughly?

What could we do if we know more about the system?

How will merging of planning, monitoring and DSE change

DSA tools?


19

Key Smart Grid Features

Distributed Resources

– Generation

– Renewable Generation

Variable sources

– Energy Storage

– Demand Response

– Microgrids for Resilience

Communications and Control

– DMS dynamically managing resources, voltage control, etc.

– AMI deployed throughout the system

– High-speed communications to Metering and Controls

– State Estimation


20

DSA State of the Art

Full 3-phase analysis

– Some can do more than 3 phases

Primarily peak demand capacity problem

– A few perform QSTS simulations

Tools designed for uniprocessors

– Mostly satisfactory for now

Support for many SG features is still in embryonic stage

– Inverter modeling

– Storage modeling

– Probabilistic/Stochasting planning

– Dynamics analysis is not common

– LV system ignored


QSTS Simulations

Particularly useful for Solar PV analysis


Inverter Modeling

Short circuit contribution and open-circuit overvoltages

remain an concern for distribution planners

R

R

De

P, Q, I

P, Q, I

V

P, Q, I, V P, Q, I, V

De

De

De

De

De

De

De

De

De

De

De

I I I II I

Quasi-static Time Series Simulator (OpenDSS)

Norton Equivalent

Thevenin Equivalent

Non-linear Time-varying Model in C-Language DLL

Electric Power System

Inverter

University of Pittsburgh testing

and modeling results


Storage Modeling

% Eff. Charge/DischargeIdle | Discharge | Charge

Idling Losses

kW, kvar

kWh STORED

Other Key Properties

% ReservekWhRatedkWhStored%StoredkWRated

etc.

Storage

Controller

Storage “Fleet”Substation

V, IComm Link

-500

0

500

1000

1500

2000

0

1000

2000

3000

4000

5000

6000

7000

8000

1 1441

Demand_wPV+Storage

Demand_wPV

Storage Ouput

PV Output

De

ma

nd

(k

W)

PV

an

d S

otr

ag

eO

utp

ut

(kW

)

Minutes

Charging

Discharging


EPRI vision

Planning and DMS will converge into one set of tools

– (Real time monitoring/control and planning will merge)

– Emphasis of new EPRI research program

Current research into modeling DMS algorithms …


Modeling DMS with Python-based “Sandbox”

Distribution Management System

(Python Script) _

Measurements - voltage at end of each feeder

- voltage at regulators

- regulator taps, capacitor states

Sandbox Module

• Interfaces with simulated

circuit model in OpenDSS

• Monitors control actions

and can restore circuit to

original state after DMS

trial simulations

• Simulates both field

circuit and test cases

• Tracks and records

results to output file over a

time-based simulation

PV var settings

Capacitor override

Regulator voltage setting

OpenDSS

Engine Script

Parameters: relative importance

of each objective

Identify possible

remedies

to simulate

Evaluate

conformity to

objectives

Trial Solutions


Together…Shaping the Future of Electricity

Modeling for the Smarter Grid–TransCARE software provides probabilistic Trans reliability Current...

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