Appendices_V28 - BPM - California ISO

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CAISO Business Practice Manual


BPM for Market Operations













MARKET OPTIMIZATION










CAISO Business Practice Manual


BPM for Market Operations

Version 28


Last Revised: November 12, 2012


Page
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This information will be provided at a later date in
the
form of a technical bulletin
.


CAISO Business Practice Ma
nual


BPM for Market Operations













Attachment A


MARKET INTERFACES




CAISO Business Practice Manual


BPM for Market Operations



Version 28 Last Revised: November 12, 2012

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A.

Market Interfaces

This
Market Interfaces

attachment presents the data exchange betwee
n Market applications.
Refer to Section 3.3, Market Interfaces, which shows the inter
-
relationships of these
applications.

A.1

Scheduling Infrastructure & Business Rules (SIBR)
System

The SIBR system performs the following tasks:



Provides an SC interface to su
bmit Bids and Inter
-
SC Trades



Applies business rules to validate and process submitted Bids and Inter
-
SC Trades



Applies business rules to generate DAM Bids for Generating Units under the must offer
obligation (Generating Unit adequacy requirement) and Real
-
Time Market Bids for
Generating Units with Day
-
Ahead AS or RUC Awards, if these Generating Units do not
have valid Bids



Provides SCs with information about their Bid and trade validation and processing



Forwards the final (clean) Bids and trades to the rel
evant Market applications and to the
SC



Stores information for auditing purposes

A.2

Scheduling & Logging of Outages (SLIC)

SLIC only applies to Generating Units and allows Market Participants to notify CAISO when a
Generating Unit’s properties change due to p
hysical problems. Users can modify the maximum
and minimum output of a unit, as well as the Ramping capability of the unit. This data is
accessed directly by the Real
-
Time processes to override some of the Master File data.

The
BPM for Outage Management

pr
ovides further details on scheduling and maintaining facility
Outages.

A.3

Automated Demand Forecasting System (ALFS)

The elements of ALFS are described in this section.

A.3.1

Integrated Forward Market (Full Network Model)

Requires Day
-
Ahead and two Days
-
Ahead Deman
d Forecasts, in increments of one hour for the
following:



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Metered Subsystems (MSSs)



Load forecasts for Load
-
following MSSs are required.
In addition, if the other MSSs do not provide their own Load forecasts, CAISO provides
one.



Calculated Forecasts



P
resently some IOU forecasts include the MSSs. Once the
MSS forecasts become available, the IOU Load forecasts without the MSSs in their area
are used. This is accomplished within ALFS, using software from Itron.



Other Control Areas



Load forecasts for som
e control areas are necessary because
their detailed networks are included in the Full Network Model. In order to provide the
most accurate forecast, the non
-
conforming Pumping Load is forecasted separately from
the temperature
-
sensitive conforming Load.



L
oad forecast

for CFE is desirable, since it is part of the California
-
Mexico Reliability
Coordination Area. IID has recently joined the

WECC

Desert Reliability Coordination
Area and thus is not a likely candidate for Load forecasting.



Congestion Zones



In

IFM, Congestion zones are not needed except for financial
trades. However, for Ancillary Services, an additional Load forecast is required.

A.3.2

RMR Preschedule

Requires Day
-
Ahead forecasts, in increments of one hour for the following:



Local
Control

Areas (L
C
A
s)



In order to make the RMR preschedules consistent with
the IFM, it is desirable to have the RMR preschedules use the same Load forecasts as
IFM. Therefore, forecasts are needed for existing LRAs defined by Operations
Engineering. One area Load forecast

is currently provided by ALFS. Forecasts for the
LRAs may also be used to improve the application of LDFs, since LDFs can be applied
to smaller areas.

A.3.3

LMP Load Zones

Requires Day
-
Ahead forecasts, in increments of one hour for the following:



LMP Load Zones



At this time, CAISO is not considering LMP for Load forecasting.

A.3.4

ALFS Loss of Data Interfaces

ALFS updates Load forecasts every 15 minutes. In the event of failure to update data, RTM
continues to use the un
-
updated data. If data does not exist for a pa
rticular interval, RTM uses
data from the last available interval or from a CAISO Operator enterable data entry point.



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RTM alerts the user when ALFS data has not been updated for 30 minutes (configurable
parameter). RTM also alerts the user when data does
not exist for a particular interval.

A.4

Master File

The Master File is a general repository of quasi
-
static data needed to operate and support the
CAISO Markets. The Master File contains data that remain unchanged for relatively long
periods of time. Relevant

Master File data includes:



SC registration and associated attributes



Resource registration, characteristics, Market and product certifications, and associated
attributes such as location, SC association, must offer, or RMR status



Network node and branch r
egistration and associated attributes



Node aggregation definitions (LAPs, Trading Hubs, AS Regions, RUC zones, designated
Congestion areas)



Transmission interface definitions



TOR and ETC registration



Market parameters such as Bid caps and MPM thresholds

Al
though SCs do not interface directly with the Master File, they are obligated to provide
accurate data for populating and updating the Master File with their applicable Generating Unit
characteristics, such as minimum and maximum capacity, Forbidden Operat
ing Regions, Ramp
Rates, Minimum Run and Down Times, average heat rates or average production costs. This
requirement is based on Section 4.1.2 of the Pro Forma Participating Generator Agreement
(Appendix B.2 of the CAISO Tariff).

Additional information o
n the Master File is available on the CAISO web site at:

http://www.caiso.com/docs/2005/10/27/2005102715043129899.html

A.5

Open Access Same Time Information System (OASIS)

The OASIS provides a Web interface for Market Participants to retrieve public Market
inf
ormation, including:



Demand forecast



AS requirements



Aggregate Schedules



Transmission interface limits and flows



Locational Marginal Prices



Regional Ancillary Services Market Prices



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This is described in more detail in Section 13 of the

BPM for Market Instr
uments

.

A.6

Settlements & Market Clearing System (SaMC)

SaMC receives Market results from the CAISO Markets and meter data from SCs to perform
Settlement according to specific business rules and charge types. Refer to the
BPM for
Settlements & Billing

for fur
ther information.

A.7

Energy Management System (EMS)

EMS sends control data to units on regulation. It matches electricity Supply and Demand on a
four second basis. EMS has an associated database called PI to store the data.

As part of this functionality, EMS
gets telemetry and data from the State Estimator, data from
most units in the CAISO Control Area, and all of the transmission lines interfacing with other
control areas. EMS/PI is the source of this data for the Real
-
Time processes. EMS is also the
source
of the base Full Network Model.

EMS receives preferred operating point data, representing the economic Dispatch Instruction,
from RTED via the ramp tool. EMS sends this data to units on regulation as a neutral set point.
EMS also receives information on di
spatched Ancillary Services, which is used to calculate
Energy reserves for the power system

A.7.1

EMS Loss of Data Interfaces

EMS updates data every 30 seconds. In the event of failure to update data for five minutes,
RTM considers the data obsolete and alerts
the user. RTM performs the following actions in the
event of either obsolete or bad quality EMS data (note that data manually replaced in EMS is
not considered to be obsolete or of bad quality):



Marks affected data with a flag on applicable screens



Does no
t use affected regulating limits from EMS for Ancillary Services and
Supplemental Energy allocation. Instead, uses the limits from the Master File according
to the “next hour’s” allocation.



Does not use affected telemetry for the imbalance MW calculations
. Instead, assumes
that the Generating Unit attempts to comply with the DOT starting at the last good
telemetry point using the Generating Unit’s physical Ramp Rate.



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A.7.2

State Estimator Failure

A State Estimator and a full AC power flow are run in the EMS in o
rder to create the system
state that is transferred to the RTM system. This information is transferred from the EMS to the
RTM system every 5 minutes and on events that trigger the State Estimator. This data is used
to initialize the network model in the R
TM system with the current power system state.

The RTM uses the state of the power system and switch status (switch status received in both
full and incremental modes) to solve the base case power flow.

The RTM uses the most recent SE solution. RTM uses

the old solution if a new SE solution
(for a user specified number of intervals) has not been received by the RTM system.

A DC power flow solution is used in case the full AC power flow does not solve in the RTM
system.

A.8

Automated Dispatch System (ADS)

ADS

is an application developed by CAISO to communicate Real
-
Time Dispatch Instructions to
SCs. As a user of ADS, you are able to:



Receive and generally respond to in
-
hour Dispatch Instructions in Real
-
Time



Receive confirmation of accepted pre
-
Dispatch Instru
ctions



Retain a local record of the transaction



Query a database for historical instructions

SCs are able to accept or decline inter
-
tie dispatches, or may be able to communicate their
ability to respond to the dispatches.

SCs can also use ADS to record co
ntrol area approval of
intertie dispatches and to push accepted intertie instructions to CAS.

The public Internet is the method of transmitting the instruction and response information
between CAISO and the SC. ADS uses 128
-
bit domestic encryption and Secu
re Sockets Layer
(SSL) communications technology, combined with
m
edium
a
ssurance digital certificates and
smart cards, to create a secure environment. Detailed logs are maintained by CAISO to assist in
dispute resolution.

A.8.1

ADS Loss of Data Interfaces

In the

event of loss of connectivity to ADS, or particular ADS tables, or incorrect flags in
interface tables, RTM alerts the user of a problem, indicates what RTM detects as the problem,
and allows the user to retry connecting to ADS.



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If the user cannot restore

the connection before any subsequent dispatches, then a means is
provided to continually display the requested Dispatch so that CAISO Operators may manually
Dispatch the resources, or remove resources from the list. When CAISO Operators are finished,
they

indicate such to RTM and then RTM writes the results to the Dispatch log. RTM also
records the event in SIBR so that Expected Energy can be recalculated later.

A.9

Control Area Scheduler (CAS)

A detailed description of the interchange transactions and associa
ted tagging is given in Section
6.3.2 for DAM and Section 7.2.2 for RTM.

A.9.1

CAS Loss of Data Interfaces

The CAS updates Schedules every 5 minutes. In the event of loss of data updates, RTM
continues to use the un
-
updated data. If data does not exist for a par
ticular hour, RTM uses
data from the last available hour as proxy for following hours.

RTM alerts the user when CAS data has not been updated for 10 minutes (configurable
parameter). RTM also alerts the user when no data exists for a particular hour.

A.10

CAISO

Market Results Interface (CMRI)

The CAISO Market Results Interface or CMRI is the reporting interface that contains private
market information resulting from the CAISO Market Processes: MPM, IFM, RUC, and HASP.


This includes schedules and awards, resourc
e specific prices, default and mitigated bids, unit
commitments and instructions.

In addition to those mentioned above, post
-
market or after
-
the
-
fact information such as
Expected Energy (energy accounting results) and the Conformed Dispatch Notice (commonl
y
known as the “CDN”) can be accessed from the CMRI.

Detailed description of these reports can be found under the BPM Market Instruments Section
11.

A.11

Operational Meter Analysis & Reporting (OMAR) System

The OMAR system performs automated validation of meter

readings and pushes Settlement
Quality Meter Data (SQMD) to Settlements. The OMAR system notifies the CAISO Operator if
human attention is required, and provides a user interface display where manual observation,
intervention, and meter data modification
can be performed.



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A.12

Electronic Tagging System

The electric tagging system provides the means by which SCs can enter/change the e
-
Tag
information that is required for the interchange of Power transactions between the CAISO
Control Area and other Control Areas
. See Section 6.3.2 for e
-
Tags in the Day
-
Ahead Market
and Section 7.2.2 for e
-
Tags in the Real
-
Time Market.


A.13

Participating Intermittent Resource Program (PIRP)

and
Eligible Intermittent Resources

(EIRs)

This section is based on CAISO Tariff Sections 4.6.1
.1, 4.8,
9.3.10,
Appendix F
(Rate
Schedules)
and Appendix Q

(
Eligible Intermittent Resources Protocol (EIRP)
)
. All Eligible
Intermittent Resources (EIRs) with Participating Generator Agreements
(PGAs)

or QF
Participating Generator Agreements
(QF PGAs)
mus
t comply with the EIRP. The EIRP also
sets forth additional requirements for those EIRs that voluntarily elect to become Participating
Intermittent Resources (PIRs) under the CAISO’s Participating Intermittent Resource
p
rogram
(PIRP). EIRs are not requir
ed to participate in PIRP.

PIRP provides participants certain benefits and imposes certain responsibilities. The main
PIR
responsibility
that
differ
s

from the responsibilities of EIRs generally is that a PIR must submit a
Self
-
Schedule to the HASP and R
TM that equals the
f
orecast
s
ervice
p
rovider’s forecast for the
PIR

in order to receive the monthly netting of positive and negative deviations from the HASP
-
submitted
S
chedule
.

In return the PIR receives two primary benefits:



The PIR’s Real
-
Time deviation
s, although tracked on an interval basis, are summed over
each
calendar
month, negative deviation MWh are netted against positive deviation
MWh, and the net result is settled at the monthly weighted average Real
-
Time LMP at
the PIR
’s

N
ode.



The PIR is exemp
t from the Uninstructed Deviation Penalty (UDP).

Regardless of whether a
wind or solar

EIR elects to become a PIR, the EIRP imposes on EIRs
with PGAs and QF PGAs various communication and forecasting equipment and forecasting
data requirements. This secti
on facilitates compliance with the EIRP by providing additional
information for wind

EIRs
, solar thermal
EIRs
,

and
solar
photovoltaic
EIRs

regarding:



The form of the
L
etter of
I
ntent
(LOI)
to become a PIR [EIRP Section 2.2.1(c)];



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Data relevant to forecast
ing, including operational and meteorological data [EIRP
Sections 2.2.3 and 3.1];



Monitoring and communications requirements [EIRP Section 3.2];



Forecasting and communication equipment requirements [EIRP Sections 2.2.3, 6, and
6.2];



Objective criteria for
accurate and unbiased forecasts [EIRP Section 4];



PIRP Export Fee Exemption Certification Process [EIRP Sections 2.2.5 and 5.3.6]; and



Forecast Fee [EIRP Section 2.4.1].



A.13.1

Letter of Intent

The
pro forma
L
etter of
I
ntent
(LOI)
required by the EIRP
for an EI
R to become a PIR
is set forth
below. The
LOI

includes the requirement that the proposed PIR submit, as Attachment A to the
letter of intent, a copy of the California Energy Commission’s Renewable Portfolio Standard
(RPS) certification identifying the fac
ility as RPS
-
eligible.



FORM OF LETTER OF INTENT TO BECOME

A

PARTICIPATING INTERMITTENT RESOURCE


[Entity Letterhead]

[Date]


Attn: Project Manager, Model and Contract Implementation

California Independent System Operator Corporation

151 Blue Ravine Ro
ad

Folsom, CA 95630


Re: Intent to become a Participating Intermittent Resource:



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In accordance with Section 2.2.1 of the California Independent System Operator
Corporation’s (“CAISO”) Eligible Intermittent Resource Protocol (the “Protocol”), this letter
p
rovides [name of Entity]’s notice to the CAISO that it intends to become a Participating
Intermittent Resource (the “Letter of Intent”). [Name of Entity] requests that the CAISO
initiate the process of
operationally
certifying its facilities known as [pro
ject name] as a
Participating Intermittent Resource. [Name of Entity] agrees that, prior to the date of such
certification, it will execute a Participating Generator Agreement [or QF Participating
Generator Agreement] and a Meter Service Agreement for CAI
SO Metered Entities as
required by Section 2.2.1 of the Protocol and thereafter will pay the Forecast Fee as
required by Section 2.4.1 of the Protocol.


Further, [name of Entity] agrees that [project name] will remain a Participating Intermittent
Resource
for a period of at least [insert number of years greater than or equal to one]
year(s) following the date of its certification, over which time the maximum Forecast Fee
shall be as specified in Schedule 4 of CAISO Tariff Appendix F in effect as of the date

of
this Letter of Intent, and that [project name] shall thereafter continue to be a Participating
Intermittent Resource unless this Letter of Intent is cancelled with thirty (30) days written
notice to the CAISO.


Finally, attached to this Letter of Inten
t as Attachment A is a copy of the California Energy
Commissions’ Renewable Portfolio Standard (RPS) certification

identifying [name of facility]
as RPS eligible.


Sincerely,

[Name of Entity]













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A.13.2

Wind Generator Forecasting and Communication Equipmen
t
Requirements


The requirements set forth in this Section A.
1
3
.2 apply to
EIRs

powered by wind with a PGA or
QF PGA
,

except as otherwise specified below and whether or not the EIR is certified or seeking
certification as a PIR.


The detailed requirements
for forecasting and communication equipment
for wind generators are set forth in Section 13 of the BPM for Direct Telemetry.


A.13.2.1

Physical Site Data


As part of a
n

E
IRs

obligation to provide data relevant to forecasting Energy from the
EIR
, each
applicable win
d
EIR

or its Scheduling Coordinator (SC) must provide the CAISO with accurate
information regarding the physical site location of the
EIR
. The information must include (1) the
location and elevation of each wind turbine hub and (2) the location and elevat
ion of
meteorological collection devices.

These information requirements are set forth in more detail in
Section 13 of the BPM for Direct Telemetry
.

A.13.2.2

Meteorological and Production Data


Each wind
EIR

must install and maintain equipment required by the CAI
SO to support accurate
power generation forecasting and the communication of such forecasts, meteorological data,
and other needed data to the CAISO.
The requirements for c
ommunication of such data to the
CAISO
are set forth in Section 13 of the BPM
for
D
irect T
elemetry.

The objective of this
requirement

is to ensure a dataset that adequately represents the
variability in wind

velocity
within the
plant
.
Where i
ndividual
EIR
s
have circumstances that
prohibit them from reasonably satisfying this requireme
nt
, the CAISO, the
forecast service
provider
, and the wind
-
plant owner will formulate
a cost
-
effective distribution of
Designated
Turbines
by mutual agreement
that approximates this
requirement

and adequately measures
the variability of the wind
velocity
w
ithin the
EIR
.
EIR
s
seeking a variance from this requirement
should do so
in the

development of their interconnection agreement

or, for

those
EIR
s
that have
already finalized

an interconnection agreement, as part of entering into a Meter Service
Agreement
.

W
ind data collected at the nacelle will not represent the true wind value at a
plant site
, but
instead will represent the apparent wind, which can be correlated to the co
-
located turbines.


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This requirement
will help ensure:

(a) multiple data streams
for anemometer information
;

and (b)
accurate representation of the data points to calculate wind energy production at the park.

Wind
EIRs
with a PGA or QF

PGA
that are operating or have final regulatory approvals to
construct as of the effective date of th
is section that have wind turbines without nacelle
anemometers need not comply with the requirements of this section

for Designated Turbines
.


A.13.2.3

Training of Neural Network

Production and meteorological data will be collected for a minimum of sixty (60) day
s before the
EIR can be certified as a PIR. This data must be collected in advance in order to train the
forecast models (e.g., artificial neural networks) responsible for producing the power production
(MW) forecast for each site.


A.13.2.4

Maintenance & Calibra
tion

Meteorological equipment should be tested and, if appropriate, calibrated
: (1)

in accordance
with the manufacturer’s recommendations
; (2)

when
there are
indications
that the data
are
inaccurate;

or
(3) when
maintenance has been performed that may hav
e interrupted or
otherwise adversely impacted the accuracy of
the

data.



A.13.3

Solar Generator Forecasting and Communication Equipment
Requirements


The requirements set forth in this Section A.
1
3
.
3 apply to
solar thermal
and
solar photovoltaic

EIR
s
with a PGA

or QF PGA
, except as otherwise specified below and whether or not the EIR is
certified or seeking certification as a PIR.

The detailed requirements for forecasting and
communication equipment for solar thermal and solar photovoltaic generators are set fo
rth in
Section 13 of the BPM for Direct Telemetry
.





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A.13.3.1

Physical Site Data

As part of a
n

EIR
’s
obligation to provide data relevant to forecasting Energy from the
EIR
,
solar
thermal and solar photovoltaic
EIR
s
or their Scheduling Coordinators (SCs) must provid
e the
CAISO with an accurate description of the physical site of the
EIR
. The following information
must be provided for each
EIR
, including a
EIR

that consists of multiple
solar photovoltaic

Generating Units aggregated under a single Resource ID, in whic
h case the requested
information must be provided for each individual
solar photovoltaic
Generating Unit aggregated
under the single Resource ID: (1) the location and elevation of meteorological collection
devices, (2) the location, elevation, and orienta
tion angles of arrays or concentrators, (3) the
generation capacity of the Generating Facility or each Generating Unit aggregated under a
single Resource ID, and (4) the type of solar generation technology employed at the Generating
Facility or each Genera
ting Unit aggregated under a single Resource ID.


A.13.3.2

Location of Meteorological Stations

The CAISO, in coordination with its
f
orecast
s
ervice
p
rovider(s), will cooperate with the
EIR

to
identify an acceptable placement of the meteorological station(s) to ta
ke into account the
microclimate of the area.

More detailed information requirements are set forth in Section 13 of
the BPM for Direct Telemetry.


A.13.3.3

Meteorological
and Production
Data

Each solar thermal and solar photovoltaic EIR must install and maintain e
quipment required by
the CAISO to support accurate power generation forecasting and the communication of such
forecasts, meteorological data, and other needed data to the CAISO.

More detailed
requirements are set forth in Section 13 of the BPM for Direct
Telemetry.


A.13.3.4

Training of Neural Network

The
f
orecast
s
ervice
p
rovider and the CAISO require production and meteorological data for a
minimum of sixty (60) days before the
solar thermal or solar photovoltaic

EIR
is

eligible to
become a PIR. This data must
be collected in order to train the forecast models (e.g., artificial
neural networks) responsible for producing the power production (MW) forecast for each
proposed PIR.




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A.13.3.5

Maintenance & Calibration

Meteorological equipment should be tested and, if appropr
iate, calibrated
: (1)

in accordance
with the manufacturer’s recommendations
; (2)

when
there are
indications
that the data
are
inaccurate;

or
(3) when
maintenance has been performed that may have interrupted or
otherwise adversely impacted the accuracy of
t
he

data.

A.13.4

Forced Outage Reporting


The additional Forced Outage reporting requirements imposed on EIRs under CAISO Tariff
Sections 9.3.10.3 and 9.3.10.3.1 are intended to enhance the CAISO’s ability to produce
accurate forecasts of the EIR output.




A.13.5

Obj
ective Criteria for Accurate and Unbiased CAISO Forecasting


The CAISO is responsible for overseeing the development of tools or services to forecast
Energy for
EIRs
. The CAISO must develop objective criteria and thresholds for unbiased and
accurate fore
casts
to
certify
EIRs
. This certification requires validating the forecast by
assessing the sufficiency
of
the forecasting input data. The objective criteria for ensuring the
sufficiency of the data
,

and therefore the validity of the forecast
,

are set fo
rth in Sections
A.
1
3
.2.2 for wind resources and A
.1
3
.3.3 for solar resources. The criteria are further supported
by the CAISO’s use of a contractual incentive plan with its third party
f
orecast
s
ervice
p
rovider(s) that encourage
s

accurate and unbiased for
ecasting.


A.13.6

Participating Intermittent Resource Export Fee Exemption
Certification Process


The provisions governing the Participating Intermittent Resource Export Fee are found at
CAISO Tariff, Appendix Q, EIRP Section 5.3 and Appendix F, Schedule 4. In
accordance with
these provisions, the Participating Intermittent Resource Export Fee is charged to all Energy
exported from PIRs, except PIRs that are exempt under one of the following conditions:



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The owner of a PIR, as of November 1, 2006, utilizes the En
ergy generated from the
Participating Intermittent Resource to meet its own Native Load outside the CAISO Balancing
Authority Area.

The PIR has an export contract with a starting term prior to November 1, 2006.

The PIR has a contract to sell Energy to a Lo
ad Serving Entity with Native Load in the CAISO
Balancing Authority Area.

The purpose of this Section A.14.6 is to describe the steps necessary to submit the certifications
described in EIRP Sections 2.2.5 and 5.3 required to determine the PIR Export Perce
ntage for
applicable PIRs.


A.13.6.1

Participating Intermittent Resource Export Fee Exemption Certification
Required Documentation


To complete the requirements set forth in EIRP Sections 2.2.5 for a certification for exemption
from the Participating Intermittent R
esource Export Fee, the following items must be included:

1)

Cert
ification Form (see Section
A.13.6.6

below) must include:

a.

Name and address of the Participating Intermittent Resource

b.

The amount, in MW, for each exemption category

c.

Calculation of PIR Export Percentage

d.

Signature of officer for the Participating Intermittent Resource


2)

Copies of all executed contracts, including changes, supporting the exemptions listed in
the certification form. Price information may be redacted from

the contracts provided,
however, that the CAISO must be able to determine from the contract the identity of the
purchaser, quantity purchased, and the length of term of the contract for the PIR.



Submittal Address


Send a signed hard copy of the certific
ation form and copies of all relevant contracts to the
following address:


California ISO

Attn:
Julia Payton

250 Outcropping Way

Folsom, CA 95630




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A.13.6.2

CAISO Feedback


Within 30 days of receipt of the completed certification form and submitted contracts, the CA
ISO
will provide written confirmation that the Participating Intermittent Resource has satisfied the
requirements under EIRP Section 2.2.5. The CAISO will provide the Participating Intermittent
Resource with its PIR Export Percentage and the applicable ex
emption period ending date that
has been validated based on the contracts submitted.

The PIR Export Percentage will remain valid until the exemption period ending date unless the
Participating Intermittent Resource alters the composition of the resource,

changes the PMax of
the resource, or changes the purchaser, quantity purchased, or length of the term of the
contracts for the PIR.


A.13.6.3

Resubmission of Certification

The Participating Intermittent Resource Export Fee exemption certification must be updated

by
resubmission to the CAISO:

1)

Upon a request to modify the composition of the Participating Intermittent Resource
under EIRP Section 2.4.2, or

2)

Within ten (10) calendar days of the final execution of a new contract or any change in
counterparty, start and
end dates, delivery point(s), quantity in MW, or other temporal
terms for any prior certified contract. All other contractual changes will not trigger the
obligation for recertification.


A.13.6.4

Example of PIR Export Percentage Calculation

A PIR with a 100 MW PM
ax has 2 contracts: (1) a contract executed on January 1, 2005 to
export 55 MW to a Balancing Authority Area outside the CAISO Balancing Authority Area; (2) a
contract executed on January 1, 2007 to sell 20 MW to a load serving entity in the CAISO
Balancin
g Authority Area. Such facility would fill the table in the certification form as fo
llows
:



Table 4

Portion of
Participating
Intermittent
Resource
Capacity (in MW)

Exemption Category



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0

EIRP Section 5.3.1 (a): The owner of a Participating Intermittent R
esource, as of
November 1, 2006, utilizes the Energy generated from the Participating Intermittent
Resource to meet its own Native Load outside the CAISO Balancing Authority Area.

55

EIRP Section 5.3.1 (b): The Participating Intermittent Resource demonst
rates … an
export contract with a starting term prior to November 1, 2006.

20

EIRP Section 5.3.1 (c): The Participating Intermittent Resource demonstrates … a
contract to sell Energy to a load serving entity with Native Load within the CAISO
Balancing Au
thority Area.

75

Total MW eligible for Participating Intermittent Resource Export Fee exemption


The PIR Export Percentage would be calculated as follows:


PIR Export Percentage

= (PMax of PIR


Total MW eligible for Participating Intermittent
Resource
Export Fee exemption) / PMax of PIR



For example, if
PMax of PIR = 100 MW, Total MW eligible for Participating Intermittent
Resource Export Fee exemption = 75 MW then
PIR Export Percentage =
(100
-
75)/100

= 25%


A.13.6.5

Annual Certification

EIRP Section 5.3.6 pro
vides that by December 31 of each calendar year, each Participating
Intermittent Resource shall confirm on the form set forth in a BPM, signed by an officer of the
Participating Intermittent Resource, that the operations of the Participating Intermittent
R
esource are consistent with any certification(s) provided to the CAISO und
er EIRP Section
2.2.5. The certification form to be submitted to meet this requirement is set forth in Section
A.13.6.6
.


A.13.6.6

C
ERTIFICATION

FORM FOR THE
PARTICIPATING INTERMITTENT RESOURCE
EXPORT FEE EXEMPTION


Company letterhead

Date



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Participating Intermittent Resource Name:






CAISO Resource ID:








Address of principal place of business

Street:








City:







State:




Zip Code:







In accordance with Section 2.2.5
[
and/or 5.3]

of the California ISO’s Eligible Intermittent
Resources Protocol (“EIRP”), this letter provides certification
that
PIR NAME

is eligible for the
following Participating Intermittent Resource Export Fee exemptions:

Table 5

Portion of
Participating
Intermittent Resource
Capacity (in MW)

Exemption Category

[0]

EIRP Section 5.3.1 (a): The
owner of a Participating
Intermittent Resource, as of November 1, 2006, utilizes
the Energy generated from the Participating Intermittent
Resource to meet its own Native Load outside the CAISO
Balancing Authority Area.

[0]

EIRP Section 5.3.1

(b): The Participating Intermittent
Resource demonstrates … an export contract with a
starting term prior to November 1, 2006.

[0]

EIRP Section 5.3.1 (c): The Participating Intermittent
Resource demonstrates … a contract to sell Energy to

a
load serving entity with Native Load within the CAISO
Balancing Authority Area.

[0]

Total MW eligible for
Participating Intermittent
Resource
Export Fee exemption


According to the table above and based on the Participating Intermittent
Resource PMax, the
estimated PIR Export Percentage is calculated as:




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(PMax of PIR


Total MW eligible for Participating Intermittent Resource Export Fee exemption)

/
PMax of PIR

= ___ %




This certification must be updated by resubmission to the CAISO (
1) upon a request to modify
the composition of the Participating Intermittent Resource under EIRP Section 2.4.2 or (2) within
ten (10) calendar days of the final execution of a new contract or any change in counterparty,
start and end dates, delivery point
(s), quantity in MW, or other temporal terms for any prior
certified contract. All other contractual changes will not trigger the obligation for recertification.



I hereby acknowledge that I am an officer of the Participating Intermittent Resource who ha
s
sufficient authority to execute this document on behalf of
PIR NAME
.












Authorized Signature: ________________________________



Name:



Title:








A.13.7

Forecast Fee


Beginning on the date firs
t

operational
, a
EIR
with
a PGA or QF PGA

must pay the Forecast
Fee for all metered Energy generated.

Notwithstanding the foregoing, the following exemption
from the Forecast Fee applies:




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1.

EIRs meeting

all of the following

criteria
: (a) has a Master File P
M
ax of less than
10 MW, (
b)
it
sold Energy under the terms of a PURPA power purchase
agreement

before

operating pursuant to a PGA or QF PGA, and (c)
it
is not a
PIR
.


The amount of the Forecast Fee shall be determined so as to recover the projected annual
costs related to developi
ng Energy forecasting systems, generating forecasts, validating
forecasts, and monitoring forecast performance, that are incurred by the CAISO as a direct
result of participation by
EIRs

in CAISO Markets, divided by the projected annual Energy
production b
y all
EIRs
.

The current rate for the Forecast Fee is
$ 0.10 per MWh.


















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Attachment B



COMPETITIVE PATH ASSESSMENT




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B.

Competitive Path Assessment

The Competitive Path Assessment used in HASP and Real
-
Time Market is described in section
B.1 b
elow. The Dynamic Competitive Path Assessment performed in the market power
mitigation process for the Day
-
Ahead Market is described in section B.2 below.

B.1

Static Competitive Path Assessment used in the Hour
Ahead Scheduling Process

B.1.1

Frequency and Scope of
Competitive Path Assessment

The Competitive Path Assessment (CPA) will be conducted
with a frequency consistent with the
Tariff
, resulting in a set of Competitive Path designations to be used in applying Local Market
Power Mitigation (LMPM)
in the Hour Ahe
ad Scheduling Process.

B.1.2

Full
Network

Model and Constraint Specification

This
section

provides an overview description of the Full Network Model (FNM) and related data
to be used in the CPA studies
.

B.1.2.1

Baseline Full Network Model

The basis for the FNM used in

the CPA will be the FNM used in the MRTU Day
-
Ahead Market.
Modifications to this specification of the FNM for purposes of performing the CPA will be done
so through review of current CAISO Operating Procedures and/or coordinated CAISO Operating
Engineers
.

The FNM will be imported into an LMP simulation tool along with related data such as thermal
branch limits, source and sink names along with the mapping to the FNM, and corridor and
nomogram / interface constraints.

Only normal thermal branch limits
for branches with both ends at 60kV or above, branches that
reside completely within the CAISO control area, and tie lines will be enforced in the CPA FNM.

The nomogram / interface constraints are enforced with the simultaneous flow limits that the
CAISO

anticipates enforcing during normal operation.



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B.1.2.2

Additional Constraints

In addition to the transmission interfaces discussed above, additional transmission constraints
will be included in the CPA FNM in a manner consistent with the MRTU FNM. These additio
nal
transmission constraints are to be modeled in the CPA simulation model as “soft” constraints.
Some transmission constraints define import/export limits to areas within existing congestion
zones, such as the San Francisco, Fresno, and North Bay areas,
while others limit network
flows but do not surround geographic areas, such as Miguel substation in San Diego, Vincent
substation, and simultaneous flow limits within the Bay Area. This supplemental set of
transmission constrain
ts will reflect limits desc
ribed

in CAISO Operating Procedures.

B.1.2.3

Contingencies for Security Constrained Optimization

The CAISO may, at their discretion, incorporate security constraints into the simulation model.
Due to computation times and the number of simulations that must be pe
rformed to complete
the CPA, the CAISO may choose to incorporate only a representative subset of MRTU DA IFM
security constraints. If security constraints are included, the set of constraints included will be

1.

Limited to generator outages and contingencie
s that reflect the operation of Special
Protection Schemes that limit flows resulting from branch outages through automated
curtailment of generation, and

2.

A subset of those security constraints used in the CAISO DA IFM that reflect the most
likely binding
security constraints as determined by review with CAISO Operating
Engineers.

B.1.3

Identification of
Candidate

Paths

The competitiveness test is only performed for transmission lines / constraints for which the
candidate threshold is exceeded. The candidate thr
eshold is 500 hours of congestion in the
most recent twelve months prior to the beginning of the CPA study. Congestion is measured
differently, using different data, for market periods prior to MRTU compared to during the MRTU
market. There are three cal
culation regimes corresponding to pre
-
MRTU (Competitive Path
designations made prior to MRTU implementation), the first year of MRTU, and years two
forward. The congestion frequency threshold will be applied only to transmission paths /


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constraints that w
ere not existing Branch Groups in the most recent period prior to
implementation of MRTU.

B.1.3.1

Pre
-
MRTU Candidate Path Identification

Prior to the availability of actual MRTU market data, real time mitigation of intra
-
zonal
congestion will be used to identify f
requently congested paths for consideration as candidate
paths. In the pre
-
MRTU period,
Real
-
Time

RMR dispatches and
Real
-
Time

out
-
of
-
sequence
dispatches for local reliability will be used to determine the frequency of
Real
-
Time

mitigation of
intra
-
zonal
congestion for purposes of identifying candidate paths.

B.1.3.1.1

Use of Out
-
of
-
Sequence Dispatch Data

Execute the following steps for the out
-
of
-
sequence component to candidate path identification:

1.

Collect out
-
of
-
sequence dispatch data from pre
-
MRTU market systems
that include the
specific reason for which the dispatch was made.

2.

Reduce this set of data to only those dispatches made for intra
-
zonal congestion
management purposes.

3.

Use CAISO Transmission Operating Procedures (T
-
Procedures) to map general OOS
reason
s to a specific line or set of lines in cases where only a general reason is provided
with the OOS instruction.

4.

Calculate, for each reason given, the number of hours during the twelve months where
intra
-
zonal congestion

on an individual path
was mitigated
in
Real
-
Time

using out
-
of
-
sequence dispatches.

Data Requirements for
EDE

evaluation:

1.

All real time out
-
of
-
sequence dispatch instructions for the most recent twelve whole
months, including date, time, resource ID, and Operator comment indicating the specifi
c
reason for the dispatch.

B.1.3.1.2

Use of Real
-
Time RMR Dispatch Data

Individual RMR resources are used, via CAISO Operating Procedure M
-
401A (Reliability Must
-
Run References) to relieve local reliability issues in
Real
-
Time

in specific locations in the CAISO


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cont
rol area.
Execute the following process for identifying hours where specific intra
-
zonal
congestion mitigation occurred through the use of
Real
-
Time

RMR dispatches:

1.

Collect
Real
-
Time

RMR
dispatch data for the most recent whole twelve months.

2.

Use Operating

Procedure M
-
401A to map RMR resource to transmission paths /
constraints identified in that Procedure for intra
-
zonal transmission issues.

3.

For each transmission path / constraint identified as having a real
-
time RMR dispatch
issued for mitigation of that
path / constraint, count one hour of real
-
time intra
-
zonal
congestion management for that path / constraint if one or more resources were
dispatched via real
-
time RMR dispatch to mitigate that line (per M401A).

B.1.3.1.3

Candidate Path Identification

Using the out
-
o
f
-
sequence data and
Real
-
Time

RMR data, calculate the number of hours in the
most recent twelve months were each path / constraint experienced
Real
-
Time

intra
-
zonal
congestion and was mitigated for this condition. Any path / constraint that has greater th
an 500
hours of
Real
-
Time

mitigation will be a candidate path and will be tested for competitiveness in
the CPA.

B.1.3.2

First Year MRTU Candidate Path Identification

If any of the most recent twelve months occur during the pre
-
MRTU period, use the procedure
for c
alculating congested hours by path / constraint described in
B.1.3.1

for those months
occurring prior to implementation of MRTU.

For any of the most recent twelve months that occur in the MRTU market period, use

the
procedure for calculating congested hours by path / constraint described in
B.1.3.3

for those
months occurring prior to implementation of MRTU.

Use the hours of congestion / congestion management for each p
ath / constraint from these
calculations to assess whether any of the paths / constraints experienced
Real
-
Time

intra
-
zonal
congestion and was mitigated for this condition. Any path / constraint that has greater than 500
hours of
Real
-
Time

mitigation will

be a candidate path and will be tested for competitiveness in
the CPA.



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B.1.3.3

Subsequent Year Candidate Path Identification

In subsequent years, there will be sufficient MRTU market data to base candidate path /
constraint selection entirely using MRTU market da
ta. Collect actual path / constraint limits and
flows from MRTU market data and identify the set of paths / constraints that experienced
congestion in greater than 500 hours in the most recent twelve months. The CAISO may, at its
discretion, use a small
adjustment factor for congestion that will count hours where flows were
extremely close to limits as congested hours.

The set of paths that are identified as having greater than 500 hours of congestion in the most
recent twelve months will constitute the s
et of candidate paths for competitiveness testing.

B.1.4

Internal Resource Characteristics and Data

Internal generators can be broken out into the following categories: Gas
-
fired Thermal
generation, nuclear, hydroelectric generation units, pump storage units, a
nd qualifying facilities
(i.e. wind, solar, geothermal, biomass, and cogeneration).

Determination of internal resource characteristics will begin with data contained in the CAISO
master file and will be supplemented on an as
-
needed basis.

B.1.4.1

Gas
-
fired Genera
tion

Data Requirements for gas
-
fired generation to be collected from CAISO Master FIle:

1.

Resource ID and bus ID.

2.

Maximum capacity, minimum load, minimum up time, minimum down time.

3.

Ramping capability.

4.

Heat rates.

5.

Start
-
up cost.

6.

Generation owner.

For these u
nits, the bid prices are based on marginal cost as determined by the unit’s heat rate,
regional natural gas prices, and a $2/MWh VOM adder. Bid quantities for gas
-
fired generation
will sum to the unit’s maximum capacity.



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B.1.4.2

Nuclear Generation

Bid quantities
for nuclear resources are based on historical (most recent 12 months available)
metered output. The bid price for (base load) nuclear resources will be $0/MWh. Unit
commitment for nuclear resources will be empirical, according to their metered output for
the
most recent 12 months) and will not be determined by the simulation software.

Data Requirements for Nuclear Generation:

1.

Resource ID and bus ID.

2.

Metered output (hourly) for the most recent 12 months available.

3.

Resource Owner.

B.1.4.3

Hydroelectric Generation

H
ydroelectric resources are committed and dispatched by the simulation software in the CPA.
Bids are determined in two ways for these resources. First, the resource’s final hour
-
ahead
schedule for the (historical) simulation date is bid in at a price of $
0/MWh. Next, the resource’s
historical
Real
-
Time

offer quantity is used for the second step of the bid curve, with the bid price
calculated as the quantity
-
weighted average bid price from historical bids for that resource for
the relevant hydro scenario y
ear. Data for both segments of the hydroelectric bid is to be taken
from the date identified for that hydro scenario and season (see section on hydro scenario
selection). If a hydro unit has neither hour
-
ahead schedule nor real time bids in the historica
l
data for the identified hydro scenario year, no capacity is offered by that resource in the
simulation.

Data Requirements for Hydroelectric Generation:

1.

Resource ID and bus ID.

2.

Historical hourly data containing final hour
-
ahead schedules and
Real
-
Time

E
nergy Bid
s
for years identified for high, normal, and low hydro scenarios.

3.

Resource Owner.

B.1.4.4

Pump
-
load Generation

The
generation side

of the pump storage units are already included in the hydro units’ offer
quantity/offer prices, as described above. The
loa
d side

of the pump storage units is modeled


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as an energy purchaser in the simulation software, or effectively load resources that buy energy
from the pool. Each pump storage unit has a 2
-
step demand curve. For the first step of the
demand curve, bid quan
tity is calculated as the final historical hour
-
ahead load schedule with a
$5,000/MWh bid price which makes this bid segment a price
-
taking load bid segment. The
second step of the pump
-
load bid curve has total
Real
-
Time

historical bid quantity for the
q
uantity portion and the quantity
-
weighted average bid price for the price component. Similar to
hydro units, if a pump storage unit does not have historical data for the identified hydro scenario
years, that resource will not be bid into the simulation mo
del.

Data Requirements for Pump
-
load Generation:

1.

Resource ID and bus ID.

2.

Historical hourly data containing final hour
-
ahead schedules and
Real
-
Time

Energy Bid
s
for years identified for high, normal, and low hydro scenarios.

3.

Resource Owner.

B.1.4.5

Qualifying Facil
ities

All resources identified as Qualifying Facilities (QF’s) will have their unit commitment and
dispatch determined by historic metered output from the relevant load scenario year.

Data Requirements for Pump
-
load Generation:

1.

Resource ID and bus ID.

2.

His
torical hourly data containing metered output for years identified for high, normal, and
low load scenarios.

3.

Resource Owner.

B.1.4.6

Dynamic Schedules

Dynamic schedules will be modeled in the same fashion as hydroelectric resources.

Data Requirements for Dynamic S
chedules:

1.

Resource ID and bus ID.

2.

Historical hourly data containing final hour
-
ahead schedules and
Real
-
Time

Energy Bid
s
for years identified for high, normal, and low load scenarios.



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3.

Resource Owner.

B.1.5

Import/Export Characteristics and Data

Import resources
(forward schedules and spot market bids) are optimized by the simulation
model based on historical scheduled and bid energy, but are not included in a supplier’s
portfolio when one or more portfolios are removed from the supply to calculate the FI. Bids f
or
import resources are constructed in a similar fashion as bids for hydroelectric resources, where
a single aggregate supplier is constructed for imports over each individual tie
-
point, which
connects a node inside the CAISO to a node outside of the CAISO
. Each tie
-
point’s outside
node is considered to be both a generation node (for the purpose of modeling imports to the
CAISO) and a load node (for the purpose of modeling exports from the CAISO).

Intertie bids (both generation and load, as described abo
ve) are constructed using historical
data that are taken from the identified hydro scenario years and are comprised of up to eleven
bid segments. The first segment is the final hour
-
ahead scheduled quantity over that tie point,
with a quantity
-
weighted av
erage bid price. Additional segments are constructed using real time
Energy Bid
s submitted across an intertie where quantities are determined by real time bid
quantities and the bid prices are, again, quantity
-
weighted average bid prices. This is repeate
d
for each intertie for both the import (external generation) and export (external load) directions.

Data Requirements for Import and Export Bids:

1.

Intertie ID and bus IDs for terminus.

2.

Historical hourly data containing final hour ahead import and export sc
hedules by intertie
and real time import and export bids by intertie for years identified for high, normal, and
low hydro scenarios.

B.1.6

Ancillary Services

B.1.6.1

Market Structure

The market structure for procurement in Ancillary Services (AS) will be incorporated in

a fashion
that most closely reflects AS procurement in MRTU as allowed by the simulation software. The
procurement of AS will be co
-
optimized with energy in the simulation. At a minimum,
procurement of all upward AS will be modeled in the simulation. I
n addition, AS procurement


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from internal resources will be limited to only those resources that are certified to provide the
various individual AS products as indicated in the CAISO Master File.

B.1.6.2

Ancillary Services Requirements

Ancillary Service requirement
s for Regulating Reserves will be based on historical procurement
levels (generally 350 MW to 400 MW for Regulation Up and Regulation Down separately)

or
anticipated procurement levels for the next 12 months
. Operating Reserve requirements will be
calcula
ted as 7% of load for each of Spinning Reserve and Non
-
spinning Reserve. Operating
Reserve requirements may be adjusted downward to account for historical procurement across
the interties if procurement from resources outside the control area is not model
ed in the
simulation.

B.1.6.3

Supply of Ancillary Services

Internal resources that are certified to provide specific AS will be modeled to submit $0 capacity
bids for the full amount of certified (ramp
-
constrained) AS capacity.

B.1.7

Identification of Load and Hydro Sce
narios

The CPA will evaluate competitiveness across four seasons, three load scenarios within each
season, and three hydro scenarios within each season. For any combination of these system
conditions, sets of one, two, and/or three potentially pivotal sup
pliers will be withdrawn from the
pool of available supply to evaluate the FI index.

B.1.7.1

Load Scenarios

The three demand scenarios for each of four seasons are identified as follows.

1.

Construct seasonal duration curves consisting of daily peak load for the mo
st recent four
whole calendar quarters using actual load data.

2.

Within each season, choose the day corresponding to the 95
th

percentile, 80
th

percentile,
and 65
th

percentile to identify the high, medium, and low load scenario days for that
season.

Since t
he loads calculated from telemetry data are actually the sum of loads plus losses, the
estimated losses of 5% are subtracted from the data from the ACTLOAD table to produce local
area loads without losses at the take
-
out points.



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The total system load is
then allocated to load distribution points by using the fixed load
distribution factors from the MRTU FNM.

B.1.7.2

Hydro Scenarios

Three hydro scenarios, high, normal, and low,
are

identified based on California’s historical
hydroelectric production data.
To id
entify the three hydro scenario years:

1.

Collect hydroelectric metered output for the most recent five years.

2.

Calculate an annual time
-
series of monthly hydroelectric output from these data.

3.

Choose base years from these figures that reflect high, medium, an
d low hydroelectric
years.

Once identified, historic data on schedules and bids from hydroelectric resources and import /
export bids across the inter
-
ties are used as the basis for constructing bids for these types of
resources to be used in the CPA simul
ation.

B.1.8

Identification of
and Supplier Combinations to Withdraw

The initial set of suppliers that will be considered potentially pivotal will be NOT FEWER than
the three largest portfolios of internal generation system
-
wide, north of Path 26, and south of
P
ath 26. This set of suppliers will have their portfolios of internal generation withdrawn from the
simulation model in possible combinations (single supplier, two suppliers, or three suppliers).
The system
-
wide and zonal portfolios are calculated by summ
ing the installed capacity of each
net supplier having installed capacity in the CAISO control area and selecting the top three
portfolios at the system and zonal level.



The CAISO will collect information regarding ownership and contractual relationships

that
transfer control of a resource and adjust the portfolios of the net generators to account for these
relationships prior to identifying the potentially pivotal net suppliers. Also, in addition to installed
capacity, the ISO may adjust supplier portfo
lios to account for known generation additions /
retirements or transfers of ownership.

Once the CPA simulations that reflect the initial set of supplier combinations withheld have been
completed, a review is conducted to assess the potential for additiona
l pivotal suppliers given
the transmission paths / constraints that are deemed competitive in the first round of
simulations. Should the CAISO determine that there exist additional suppliers that are


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potentially pivotal, additional simulations will be per
formed that incorporate these additional
suppliers into the combinations of portfolios withdrawn.

B.1.9

Performing Simulation

B.1.9.1

Model and Data Verification

The following items must be verified prior to running simulations for purposes of executing the
CPA:

1.

Input
data for load, internal resources, supplier portfolios, and imports.

2.

FNM specification including thermal limits, interface and constraint definition, and
contingencies if applicable.

3.

FNM verification through simulation of base case scenarios and reviewing
power flow
results for consistency with actual operation of the grid. Lead CPA Analyst should
consult with Operating Engineers, Grid Operators, and CRR Staff in the event that base
case simulation results deviate from expectations.

4.

Appropriate transmissio
n limits applied: soft constraints with a penalty price of
$50,000/MW, hard constraints on “grandfathered” competitive transmission paths
(Branch Groups that existed most recently prior to implementation of MRTU), load
curtailment penalty price of $1,000,
000/MWh.

5.

Simulation software parameter specification.

B.1.9.2

Executing Simulation Runs

The simulation model must be run once for a 24
-
hour simulation period for each combination of
the scenarios listed below.
If during the course of running simulations across t
he various
scenarios a point is reached where all candidate paths have a calculated negative Feasibility
Index (see Section
B.1.10.1
) and are consequently deemed uncompetitive, the CAISO has the
discretion to ce
ase further simulation of scenarios.

1.

Season: Winter, Spring, Summer, Fall.

2.

Load: high, medium, low.



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3.

Hydro: high, medium, low.

4.

Withheld Supplier Portfolios: Base case with no suppliers removed, all seven single
supplier portfolios, all combinations of t
wo out of seven supplier portfolios, all
combinations of three out of seven supplier portfolios.

B.1.9.3

Simulation Result Verification

1.

Verify that 500kv transmission system flows (magnitude and direction) in base case
simulations for select seasonal scenarios ar
e consistent with historical operation.

2.

Spot check simulation runs with supplier capacity withheld to verify that the withheld
capacity was not dispatched in the simulation.

3.

Review individual days where load curtailment occurred in the simulation to verify

the
resources, network topology, and transmission limits are appropriately set.

B.1.9.4

Simulation Data Storage

The following items will be stored for each CPA performed in a manner that allows for
reproduction of results:

1.

All model input files and computer code
used to produce those files.

2.

Simulation software model specification file.

3.

All simulation output files and any computer code used to combine or manage those
files.

4.

All files containing data, calculations, competitive determinations and any computer code
us
ed to produce those files.

B.1.10

Competitive Path Designations

B.1.10.1

Calculating the Feasibility Index

To identify uncompetitive paths a Feasibility Index (FI) is calculated for each candidate
transmission constraint for each simulated hour.

The FI for a candidate pa
th j is calculated for each simulated hour as:



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Let

Limit (j) = Transmission Limit on Path j

Flow (j) = Simulated Power Flow on Path j (with soft limits)

Then

FI (j) = [Limit (j)
-

Flow (j)] / Limit (j).

The values for both Limit (j) and Flow (j) are take
n from the simulation files.

B.1.10.2

Determining Path Designations

For each season, construct and populate a table that contains the following fields: Candidate
Path Name, Number of Hours With FI < 0, Seasonal Competitiveness Results.

Candidate Path Name
: Values

for this field are established in the Candidate Path Identification
step described in Section
B.1.3
.

Number of Hours With FI < 0
: Values for this field are a count of the simulated hours within a
given season
where the calculated FI for a particular Candidate Path is less than zero. Data
used in this calculation are discussed in Section
B.1.10.1
.

Seasonal Competitiveness Results
: For each Candidate Path, the value
for Seasonal
Competitiveness Results is “Pass” if the number of simulated hours having a negative FI is zero
for that Candidate Path. Otherwise, the value is “Fail”.

If a Candidate Path receives a “Fail” value for Seasonal Competitiveness Results in any o
ne
season, that Candidate Path will be deemed Uncompetitive. Otherwise, the Candidate Path will
be deemed Competitive.

B.1.11

Publication of CPA Results

Within one week after the CPA is completed and a set of competitive paths is identified, that set
of competit
ive paths will be published on the CAISO web site and a Market Notice will be issued
notifying Stakeholders of the publication.

B.1.12

Incorporating CPA Results into MRTU LMPM

Within one week after CPA is completed and a set of competitive paths is identified, th
e entire
set of Competitive Paths, including grandfathered paths, will be communicated to the


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appropriate staff

for inclusion into the production MRTU software and utilized in the daily
application of MPM

for the Real
-
Time Market
.

The
staff
will update the

path designations for use
by the production market software in the day
-
to
-
day operation of the
real
-
time
energy markets.


B.2

Dynamic Competitive Path Assessment (DCPA) for the Day
Ahead Market


B.2.1

Accounting For Resource Control

The purpose of a pivotal supplie
r test is to determine whether one or more suppliers

defined on
a portfolio basis

can influence

market price through withholding.


Combining physical and net
virtual supply that correspond to a single supplier is necessary to accurately account for the
ext
ent of withholding and resulting market impact.

T
he aggregation of related resources

is
referred to

as a portfolio for purposes of conducting the pivotal supplier test
-

the potential that
one or more suppliers' portfolios may be withheld and have an impa
ct on the market.

Resources will be assigned to a supplier’s portfolio based on the

Scheduling Coordinator who
owns the

SC
ID
assigned to the

resource unless a different
Scheduling Coordinator, or an
Affiliate of a different Scheduling Coordinator,

controls

the resource. Then the resource will be
excluded from the
portfolio of the Scheduling Coordinator who owns the SCID assigned to the
resource. The resource will be added to the supplier portfolio of the Scheduling Coordinator
who controls the resource or
whose affiliate controls the resource.

Furthermore, Scheduling Coordinators who are registered with the ISO as distinct legal entities
(or companies) may be or have Affiliates. The supplier portfolios of affiliated Scheduling
Coordinators will be combin
ed in order to accurately account for the extent of possible
withholding and resulting market impact.

Please refer to the BPM for Scheduling Coor
din
ator Certification and Termination information on
Scheduling Coordinator obligations to report Affiliates an
d resource control agreements.




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B.2.1.1

Resources And Suppliers C
onsidered


1.

All Resources for D
CPA

All resources that are available to the day
-
ahead market will be considered, whether
committed in the all constraints run or not.

2.

Net Sellers as Potentially Pivotal
Suppliers:

For determination of the top three potentially pivotal suppliers:



The supplier portfolios of n
et sellers of electricity will be considered.



Net buyers of electricity do not have an incentive to exercise local market power and
increase spot who
lesale prices.



Identification of net buyers to exclude from the set of potentially pivotal suppliers will
be

determined quarterly. It will be determined by subtracting metered supply from
the metered demand of each supplier portfolio over the most recen
t 12 month period.



SCs without physical resources, for example purely financial SCs,
cannot be deemed
net buyers per the definition of net buyer in CAISO Tariff section 39.7.2.2 and
therefore
will always be categorized as net sellers.

3.

Cleared Convergence
Bids included

Cleared virtual supply bids are included in the demand for counterflow and effective
supply calculations for fringe competitive suppliers.


B.2.2

Process Flow For T
he Dynamic Competitive Path Assessment

(DCPA) In T
he Day

Ahead Market:

1.

The DCPA

wi
ll
determine which constraints are competitive and which constraints are
non
-
competitive for each hour of the IFM. The DCPA will
be assessed

as part of the

MPM process prior to the IFM market.

2.

For each congested Transmission Constraint k, calculate the to
tal demand for
counterflow (DCF) (the default constraint direction being the market AC run flow) :

DCF
k

=

i

-
SF
k,
i

* Cleared Schedule MW
i




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for physical resources and virtual supply resources i with negative SF
k,
i

more negative
than a threshold (referred to as DCPA Threshold
)
; where Cleared Schedule MW
i

is the
energy schedule for physical or virtual supply res
ource
i
.

The energy supply from pump storage and NGR LESR resources shall be included in
the counter flow calculation. The demand side of pump storage and NGR LESR
resources shall be excluded from the flow calculation. The NGR DDR, pseudo
generators associ
ated with PDR/ RDRP/Dispatched Pump resources and NGR DDR
shall be excluded from the flow calculation.

The external resources will be excluded
from the flow calculation.

3.

For each congested Transmission Constraint k, and supplier, j, calculate the total
av
ailable effective supply that can be withheld. This withheld capacity (WC) is:

WC
k,j

=

i
(
-
SF
k,i

* ENGYMAX
i
) +

i

SVCF
k,j,i

for resources
,

i
in supplier portfolio,
j with

negative

SF
k,i

more negative than the

DCPA
Threshold


Where ENGYMAX
i

= min[(MAXCAP
i



OR
i



RU
i
),(MAXECON
i

-

OR
i
)]


MAXCAP
i

= min[(PMAX
i



DERATE
i
), Maximum exceptional dispatch]


MAXECON
i

= min[(PMAX
i



DERATE
i
), Maximum exceptional dispatch point,
Max economic bid MW]


PMAX
i

is regulation pmax if on regulation oth
erwise operational Pmax


OR
i

is self scheduled spinning and non
-
spinning reserves


RU
i

is sef scheduled regulation up

Note that for MSG Plants the SF is given per plant aggregate connectivity node, and the
above calculations involve p
lant level maximums and derates. The withheld capacity
calculation shall not consider pump storage resources, pseudo generators associated
with PDR/ RDRP/Dispatched Pump resources, NGR LESR and NGR DDR.

SVCF
k,j,i
=
-
SF
k,i

*
DOP
i


for virtual resources, i,
in supplier portfolio, j,
with

negative

SF
k,i

more negative than the

DCPA Threshold
.

DOP
i

is the cleared virtual supply MW for virtual resource i.

The external resources will be excluded from the withheld capacity calculation.

4.

For each binding
Transmissi
on C
onstraint k, suppliers are ranked on WC
k,j

from highest
to lowest and the top three
suppliers
are identified as the set of potentially pivotal
suppliers

(PPS)

for that constraint
.

5.

The fringe competitive suppliers (FCS) for the constraint k are the port
folios of net
buyers and net sellers’ resources that do not belong to PPS for constraint k

6.

Calculate
the effective supply of physical counterflow (SPCF) for
fringe competitive
supplier
:

SPCF
FCS
k,j,i

=
-
SF
k,
i

* ENGYMAX
i


The energy supply from pump storag
e and NGR LESR resources shall be included in
the counter flow calculation. The demand side of pump storage and NGR LESR
resources shall be excluded from the flow calculation. The NGR DDR, pseudo


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generators associated with PDR/ RDRP/Dispatched Pump resourc
es and NGR DDR
shall be excluded from the flow calculation.

7.

Calculate cleared Virtual supply counterflow
SVCF
FCS
k,j,i

=
-
SF
k,i

* DOP
i

for
each
FCS
.

8.

Combine

the supply of physical counterflow and the supply of virtual counterflow for
each

FCS:

SCF
FCS
k,j,i

= SPCF
FCS
k,j,i

+ SVCF
FCS
k,j,i

SCF
FCS
k

=
Σ
j

Σ
i

SCF
FCS
k
,j,i


9.

Cal
culate RSI: RSI
k

= (
SCF
FCS
k

) / DCF
k

10.

K is deemed uncompetitive (NC) if residual supply index RSI
k

< 1

11.

Apply
for
each binding
Transmission C
onstraint k.
The CPA will be applied only t
o those
p
aths binding in the MPM

run.

12.

Apply for each hour.
Only paths that are tested and fail the pivotal supplier test will be
designated as noncompetitive (NC) on an hourly basis.