Possibilities & Limitations of

Extending the Wholesale / Bulk Power Transactive Techniques to

Retail Markets & Distribution Operations Ralph Masiello

Jessica Harrison

DNV GL Energy ralph.masiello@dnvgl.com

jessica.harrison@dnvgl.com

1

What is Markets 3.0?

2

U.S. wholesale electricity markets are

characterized by the following trends: • Need to manage new products

e.g., Demand Response, Variable Energy

Resources, Microgrids, Self-Optimizing Customers

& Energy Storage

• Penetration of & coupling with retail resources use of distributed generation and smart load

resources from the industrial, commercial and

residential sectors

Markets 1.0 • Wholesale day ahead

energy on hourly schedules • Ancillary services • Balancing and regulation • Transmission rights

Markets 2.0 • Co-optimized energy &

ancillary services • Congestion pricing • Nodal real time dispatch • Capacity markets for DR

Markets 3.0 • Dynamic retail pricing • DR for ancillary services • Capacity markets for firming & DR • Intra-hr scheduling of renewables • Storage as a resource

1995 - 2003

2001-2010

2011-2020

Real-time wholesale markets meet retail resources

Recent History FERC NOI & NOPR on VER Integration & Cost Allocation FERC Report on Demand Response & NOPR 745 on compensation FERC NOPR on Fast Regulation from Storage

Integrating Distributed Energy Resources

• Early euphoria being subdued by challenge realization! – Visibility – no telemetry (AMI is NOT the solution !)

– Control (Definitely NOT AMI; multiple technologies for each end use / resource

– Grid Security - Backfeed, fault ride through, frequency response

– Market Integration “estimated response” for settlements; estimating elasticity in market clearing

• DER Categories – Distributed Generation – PV, CHP, micro-wind

– Distributed Storage

– Dynamic Pricing – autonomous demand price elasticity

– Dispatchable Demand Response

3

Integrating Demand Response: Key Research Questions

• What are the potential impacts of greater DR integration into the wholesale market? – What are the effects on real time markets prices & supply dispatch

over time?

– What are the conditions for preserving market convergence?

4

• Dispatchable Demand Response (DDR): – planned changes in consumption in response to direction from

someone other than the customer

– modeled as a supply resource dispatched similarly to generation

• Dynamic Pricing (DP) response: – customer decides whether and when to reduce consumption

– modeled as a voluntary customer response to market prices DNV KEMA study with NYISO, Market Dynamics of Integrating Demand Response into Wholesale Energy Markets, The Electricity Journal, April 1, 2013.

• Distributed Energy Resources (DERs) include a variety of supply-side and demand-side resources. Those examined in this study include:

Categories of Distributed Energy Resources

5

SOC – Self Optimizing Customers

DR – Demand Response (Including Autonomous Price

Responsive Load (Dynamic Pricing)

DES – Distributed Energy Storage

DG – (PV – Distributed and “Behind-the-meter”

PhotoVoltaics; CHP – Combined Heat and Power)

PEV – Plug in Electric Vehicles

Re

lative F

ore

casting C

om

ple

xity

Primary Control

Secondary Control

Tertiary Control

Time Control

Spinning Reserve

Non-Spinning Reserve

Load Following

InertiaGovernor Response

Regulation

Economic Dispatch

Supply Stack

Seconds

Minutes

Minutes

Hours

ContingencyReserve

Forecast ErrorMinutes

10 minutes

30 minutes

6

Time Domains for Flexibility

Microgrid Resource Configuration

7 Source: Quanta

8

8/6/2014

DER

Profile*

High

DER (Max MW)

Mid

DER (Max MW)

Low

DER (Max

MW)

Penetration

Assumptions Variability Drivers

PV 7812 4757 1747 Scaled according to ISO scenarios for distributed PV

Clearness index and PV Technology. Based upon forecast errors calculated in LTPP High Load case.

CHP 4468 3092 1732 Based upon CEUS Prices, temperature, conforming load

SOC 1277 806 337 Based upon CEUS Prices, temperature, conforming load

PEV -882 -662 -625 Based upon research by NREL

Commute time and traffic congestion

DES -2808 -1920 -1033 Based upon CEUS PV smoothing requirements and prices

DR -2466 -1926 -1390 Based upon existing utility programs

Prices, load and temperature

High DER Penetration leads to forecast uncertainty and increased

production costs.

Impacts by DER Type & Penetration

9

8/6/2014

No Visibility Case

Ma

x L

oa

d

Follo

win

g D

ow

n

Ma

x L

oa

d

Follo

win

g U

p

Ma

x

Re

gu

latio

n

Up

Ma

x

Regu

lation

Dow

n

5,079 MW

5,683 MW

1,084 MW

760 MW

Ma

x L

oa

d

Fo

llow

ing

Do

wn

M

ax L

oa

d

Follo

win

g U

p

Ma

x

Re

gu

latio

n

Up

Ma

x

Re

gu

latio

n

Dow

n

4,652 MW

4,753 MW

1,083 MW

749 MW

Visibility Case

Visibility provides a large reduction in the 95th percentile of Load

Following requirements. Minimal Impact on Regulation.

Estimated Load Following & Regulation Requirements by Visibility Scenario

10

Density (units/square mile)

Rate of DER

State Change

PVgrid PVBehindMeter

CHPPrice Taker

CHPDynamic

StorageUtility StorageBehindMeter

DP

Re

al-T

ime

DD

RD

isp

atc

h

DP1-HourAhead

EVSmart

EVPassive

1 min

5 min

1 hour

SOC

Device density and rate of change are the drivers

for communications technology and costs

Information Requirements

B. Technical requirements for monitoring and control to achieve market and operational benefits

Communication Architectures Various Stakeholders play in own time and density domain

11

Coverage / Availability Density

System Polling

Time

Utility DA

Private Network

Customer

Internet

Other/3rd-Party Private Network

1 min

5 min

1 hour

Public Carrier Wireless

Utility AMI

Private Network Broadcast Semi-Control

Only

8/6/2014

Communications Architectures

12

Ownership /

Timeline

Present SCADA AMI Mesh

Networks

Broadcast

Radio

Cellular GPRS

SMSWi-Fi

Internet POP /

Ethernet/WiFi

BAS

Networks -

larger

commercial

EmergingDistribution

Automation

AMI Mesh

Networks700 MHz Cellular LTE

Wi -Fi public

hot spots

pervasive in

C&I and most

residences

EV GPRS/

Wireless

BAS

penetration

and Open

ADR

DER

maintenance

via cellular /

internet

2020SCADA / DA

on fiber / 700

MHz

not EOL for

current AMI

systems yet

migrated to

other

spectrum?

Adopted for

DA and

mobile

apps/ AMI?

Not Availablenext

generation?next evolution? pervasive

EV on next

generation

BAS

ubiquitous

in C&I

DER

maintenance /

ops via next

generation

Pros

Low Latency

NERC CIPS

inherent for

utility DER

assets

Ubiquitous

and Low Cost

Modems

Available

Very Low Cost

potential

spectrum re-

allocation to

utility use.

ubiquitous and

low costs

already used

for PV

ubiquitous

high

performance

new cellular

standard

low modem

costs and nil

data cost

ubiquitous and

low modem /

nil data cost

rely on auto

industry

directions

and

capabilities

support of

Open ADR

likely no

incremental

cost for DER

low

incremental

cost for DER

monitoring

Consexpensive /

proprietary

/not on LV

Utility owned

and

controlled

provisions for

3rd party

access

Ubiquitous but

with spots of

non-access

only one way

Utility

owned and

controlled

provisions

for 3rd party

access

obsolete and

carriers will

abandon 3-5

years

higher

modem costs

and higher

service

impacts/cost

s for DER

data

not ubiquitous;

security

authentication

and validation

required

possibily

encryption

proprietary

and closed

proprietary

and closed

proprietary

and closed

DER

Applications

Utilty scale

PV and utility

storage

Rooftop PV;

Residential

HVAC;

Distributed

Storage

small DR

assets

residential hot

water and AC

Unknown

adoption in

CA

Distributed PV

Residential AC

distributed

storage

GPRS targets

And DER near

an Internet POP

with WiFi

access indoor

esp

Any C&I

facility DER

and most

residential

EV smart

charging

commercial

DER, all

SOC, most

CHP

distributed PV

and

distributed

storage

UTILITY COMMON CARRIER 3rd Party

13

CAISO Benefits in millions $ for 2020

Generation

Cost & Start/

Stop

CO2

Emissions

CAISO Production

Cost With Visibility

Savings/year

$7,541/yr

$7,932/yr

$391/yr for

Monitoring

$307/yr

$84/yr

Less Large

Plant

Generation &

Fewer start/stop

costs on plants

Lower

Emissions

CAISO Production

Cost With No Visibility

Benefits of monitoring and control are significant compared to the

communication, monitoring, and forecasting infrastructure costs

C. What are the CAISO costs and expected benefits to increased DER visibility and control?

Price Elastic Load = Sequential Markets 1. Market Measures / Forecasts Load

2. Market Clears the Supply Side Bids and Sets Prices

3. Load Reacts to Price

4. Repeat

• Anecdote – UK in the 80’s (courtesy of Richard Tabors)

– First UK Markets had industrial customers exposed to market prices

– Customers would react to prices once set

– Some price oscillations observed

• Market did not take elasticity / behavior into account

• Anecdote – A 2013 Swedish study had similar findings (Sweco Energy Markets)

• Economists are familiar with the iterative interaction between elastic supply & elastic demand:

The “Cobweb Theorem”

14

- Relative elasticities dictate convergence or divergence

However, the Cobweb Theorem does not consider time dynamics

Key to Understanding Behavior:

• Price is a control signal • Market clearing and the

establishment of supply and demand curves are dynamic processes

Simulation

Process Control Model

Simple market model based on control theory - captures generation & demand time dynamics • Supply-demand imbalance is input to clearing

function which adjusts price according to supply & demand elasticities.

• Feedback gain is inverse of sum of supply & demand elasticities. Delay equals periodicity of market clearing function.

• Critical parameters: price elasticity ratios, time delay ratios ; demand elasticity error

System Dynamics Model

Detailed dynamic model of a market operation using system dynamics • Non-linear supply curves representative

of a real market and non-linear demand curves based on published demand elasticity research.

• Integrates day ahead, hour ahead, and real time energy market processes.

• Includes residential and commercial end-uses (HVAC, lighting, water heating, refrigeration).

• Does not predict price but captures market dynamics

15

Imbalance

Demand

Supply

Price

price

-1Z

delay-demand

z

1

z

1

-K-Supply time delay

-K-

Supply elasticity

Step

-K-

Market Gain

1Market

Demand/Supply

-K-Demand time delay

-K-

Demand elasticity

-1Z

1 time step delay-supply

-1Z

delay-priceforsupply

-1Z

delay-price

RT Dispatch

RT Imbalance

RT Total Demand

RT DDR

ResponseRT Supply Curve

RT Generation

Response

RT Total Supply

-+

+

+

+

+RT Price

RT DP Response+

+

-

RT Total

Responsive Demand

RT Unresponsive

Demand

+

-

Forecast DemandForecast Supply

RT Commitment-

+

++

RTC DDR

Response+

RTC Generator

Response+

+

+

RT DP ResponseRT Supply Response RT DP Response

RT DDR Response

RTC DDR ResponseRTC Supply Response

Theory

Market Models

Control Theory Modeling Results

16

Under some scenarios of DR integration, the markets can become unstable.

A simple example considers how the dynamic response of generation, demand, and market operations affect market stability over ranges of relative supply and demand elasticity.

In this case, the market misestimates demand elasticity (i.e., 100% error)

Where generation is less elastic than demand, the system goes unstable.

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1-10

-8

-6

-4

-2

0

2

4

6

8

10

Real part

Ima

gin

ary

pa

rt

error = 100%

Real Part

Imagin

ary

Part

Stable region

Routh Hurwitz

Criterion

Solving Analytically for System Poles

(Root-Locus)

There are scenarios for which the overall system will not be stable when the market misestimating demand elasticity (i.e., 100% error). Misestimating elasticity is akin to operating the market as it is operated today.

The Real World is MUCH MORE Complex

• Multiple Markets – Day Ahead, Hour Ahead, Real Time

• Multiple Supply Resources with Different Time Dynamics

• Multiple Load Side Elements

• More Complex Load Side Behaviors

• Non-linear / Time Varying Elasticities

First Key Observation

18

At scaled up penetration, DP response

becomes unstable as shown when the

duration is 60 min. Added to information

latencies, this means the market is clearing

for load that responded to the prior period

price but is not aware of that effect.

DP responding to an hourly price signal

with a 60 min duration affects RTD prices

but 20 min durations do not.

RTD Price

1,000

750

500

250

0

0 138 276 414 552 690 828 966 1104 1242 1380

Time (Minute)

$/M

W

RTD Price : 7BC

RTD Price : 7dumbdp_20

RTD Price : 7dumbd60

$/M

Wh

July - Base Case

July - DP, 20 min duration

July - DP,60 min duration

Market impacts depend on: penetration, timing of price signals, and relative duration of DP compared

to the frequency of the market dispatch & price publication.

Total Aggregate DP Response

4,000

2,000

0

-2,000

-4,000

0 138 276 414 552 690 828 966 1104 1242 1380

Time (Minute)

MW

Total Aggregate DP Response : 7BC

Total Aggregate DP Response : 7dumbdp_20

Total Aggregate DP Response : 7dumbd60

July - Base Case

July - DP, 20 min duration

July - DP,60 min duration

Second Key Observation

19

DP impacts are very sensitive to DP penetration, demand elasticity, and the accuracy of estimated

demand elasticity in the market clearing algorithms.

As the amount of responsive DP in the

market increases, price potentially

increases and can grow to be volatile

As the amounts of viable DP in the market

grow, load oscillations grow. Increased

“penetration” of DP in effect increases the

ratio of demand elasticity to supply

elasticity and increases instability.

Total Aggregate DP Response

20,000

10,000

0

-10,000

-20,000

0 138 276 414 552 690 828 966 1104 1242 1380

Time (Minute)

MW

Total Aggregate DP Response : 7 dumb dp 2-5 RTCH

Total Aggregate DP Response : 7 dumb dp 2 RTCH

Total Aggregate DP Response : 7 dumb dp 1 RTCH

July - DP, 2.5 x penetration

July - DP, 2 x penetration July - DP, 1 x penetration

Graph for RTD Price

1,000

750

500

250

0

0 138 276 414 552 690 828 966 1104 1242 1380

Time (Minute)

$/M

W

RTD Price : 7 dumb dp 2-5 RTCH

RTD Price : 7 dumb dp 2 RTCH

RTD Price : 7 dumb dp 1 RTCH

July - DP, 2.5 x penetration

July - DP, 2 x penetration

July - DP, 1 x penetration

$/M

Wh

RTD Price

Thinking about ISOs, DSOs & MGOs

20

Registration

Bidding

Market Clearing

Notification

Measurement & Validation

Settlements

Wholesale Markets

T

F

Suppliers

Demand Side Aggregators

Wholesale Takeout Point

DSO

Microgrids

The Devil is in the Details

21

Rules of the Game • Can one entity have multiple roles? - Direct access; DSO resource; MGO

Bi-lateral Transactions & “Open Access Distribution” (OADIS)

• Some microgrid operators will have multiple sites on different takeout points (e.g., DOD)

Settlements • What constitutes a revenue meter? - e.g., EV and chargers have meters and

comms; why duplicate?

Validation • The inevitable DR “what would it have been?” question

Market Co-ordination • Timing of bidding closure, market clearing, notification across layers

Gaps in Understanding

• Information Arbitrage

– Interaction of DSO and ISO markets in time and opportunity to influence pricing

– Stability of Market Behavior with layered clearing processes

• Interaction of gate closures, processing time, notification, participant decision making

• Business Models for New Resources in Markets

22

Business Models – Example - Storage

• Storage as a Generator

– Must separately bid discharging and charging and take risks of not clearing / duplicate clearing

• Storage co-optimized by market operator

– Basis of bidding? Paid clearing price like a generator?

– New asset class offering storage services?

• Hybrid: Storage as a (regulated) asset class and 3rd parties “own” energy in storage

23

And – Reliability Issues

• Today DG MUST disconnect on grid low voltage for safety reasons

• At high penetrations this can cause grid level event “magnification”

– Routine cleared line fault becomes loss of 000’s MW of PV

• So Fault Ride through, low voltage ride through standards needed

• And – rules on “pre-emptive disconnect”

24

Conclusions

• If We Want to Use Price as a Control Signal

– Better do the Control Systems Design

– Artificial Volatility is NOT a Good Thing

• The More Complex the Market Design – the More Opportunities for “Strategic Bidding” and Unexpected Outcomes

25