fcm pi impact assessment update

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FCM PI Impact Assessment Update Assessment Method, Assumptions and Data

Paul J. HibbardAnalysis GroupJune 4, 2013

FCM PI vs. FCM Status Quo (and alternatives)

March 1 Meeting

Overview of impact analysis

Role of Analysis Group

Potential additional scope items

April 10 Meeting

Proposed analytic approach

Key elements of scenarios

Expected sources of data and assumptions

Today

Model construct and status

Scenarios and assumptions, data sources

Examples of outputs

Feedback on inputs

Overview

Comparison

Status Quo FCM PI NRG Alternative (under review by AG, ISO)

What is the difference?

With FCM PI, existing and new resources will adjust offers based on expected performance revenues (positive and negative) and perceived risk

This will effectively alter the supply curve for the capacity market …changing clearing prices, cost to load, and revenues to

suppliers …changing the mix of resources in the market …changing system reliability

Impact on supply curves depends on many assumptions

Initial review of a realistic set of scenarios

Reminder: Analytic Approach

Approach to estimating offers by market participants in the FCM PI case (see ISO April 9th MC presentation)

Analytic Approach

The offers (B) used to determine the supply curves reflect a Common Value Component (CVC) and a Private Value Component (PVC), which are defined as follows:

max 0,

B CVC PVC

PPR r H GFC PPR H A

where the variables are defined below.

Variable Description

PPR Performance Payment Rate (dollars per MWh)

r Average of Balancing Ratio during scarcity condition hours:

load reservesr

ICR

H Number of scarcity condition hours

GFC Net Going Forward Costs (dollars per MW)

A Actual (average) unit performance during scarcity condition hours

Status Quo Offers

DemandNet ICR from RSP for 2018/2019

High/Low sensitivities to represent potential range of outcomes over time

ResourcesExisting generation from FCA7, including delists

Passive DR from FCA7

AG estimates of active DR and imports based on FCA results and ISO data

Renewables (on-shore wind) sufficient to meet RPS requirements per RSP for 2018/2019

Additional new generation CC/CT (based on ORTP costs, with market revenue estimates updated by AG)

Key Data Sources, Assumptions

System Parameters: expectations based on past performance

Reserve shortage hours (H) based on system data 2010-2012, and ISO modeling of at criteria conditions

Actual reserve shortages under current RCPFs ($500 system) (simulated 1/10 – 5/12) ~ 3.2 hours/year

Sensitivities to capture potential future conditions (e.g., low and high values with the system “at criteria”)

Unit performance (A) based on 2010 – 2012 operations, with variations based on seasonal pattern of assumed shortages

Shortages spread across all months Shortages mostly in summer (2011 pattern) Shortages mostly outside of summer (2010 pattern)

Balancing ratio based on review of system data 2010-2012

PPR set to $5,000 (high/low sensitivities at $4,000, $6,000)

Key Data Sources, Assumptions (cont’d)

Going-Forward Costs (GFCs)

Fixed Costs (FC) and Variable Costs (VC) based on unit-specific data from SNL

Investment Costs (I) reflect annualized cost of new capital investments (e.g., new plant, environmental compliance, dual fuel upgrades) AG estimates, using updated ORTP financial assumptions

Net generation (Q) based on actual unit output 2010-2012

Heat rates (HR) based on unit-specific data from SNL

Fuel prices (Pfuel) based on NYMEX forward prices (natural gas), SNL (uranium), ORTP (biomass), and EIA (the rest)

Market prices (P) reflect energy and reserve/AS revenues from 2010-2012, adjusted for forecast fuel price expectations

PI Risk Premium (RF) based on AG estimates


* * FuelGFC FC I Q P VC HR P RF

Variations on GFC related to incremental investment in existing assets: Dual fuel capability costs (based on AG analysis)

Fixed costs to maintain Investment costs to establish, or recommission Investments made if additional net FCM PI revenues (due to

improved performance) exceed incremental GFC

Environmental compliance investment Identify units potentially affected by EPA air, water, and ash

regulations (ISO analysis, AG review) between now and 2020 Estimate investment and annual fixed cost increments for

compliance (ISO and NERC analysis, AG review) Consider 3 scenarios

No compliance investments Moderate compliance investments Severe compliance investments


Existing Units: unit- and plant-level data from SNL, ISO

• Operating capacity, net generation (historical)• Variable non-fuel production costs ($/MWh)• Fixed production costs ($/kW-yr)• Heat rate• Potential for dual fuel capability• Environmental compliance obligations, estimated costs• Missing values extrapolated with representative

technology/fuel-type class data

New Units: based on ORTP analysis, updated for current market conditions

Model Inputs

• Supply curves based on GFC and PI offer adjustments for existing and new units

• Developed for a number of scenarios

• Generate results with PI, without, and difference:

• Clearing price• Supplier

payments, surplus• Load payments

Sample Model OutputsExhibit A

FCM Bidding Model Results

ICR Quantity (MW) 34,500 $K:$K

With Performance Incentives 12

FCA Clearing Price w/PITotal Payments to Suppliers w/PI ($bil)

Total Surplus of Suppliers w/PI ($bil)Average Payments by Load ($/MWh)

Without Performance Incentives

FCA Clearing Price w/o PITotal Payments to Suppliers w/o PI ($bil)

Total Surplus of Suppliers w/o PI ($bil)Average Payments by Load ($/MWh)

Difference Between Non-PI and PI

FCA Clearing Price ($)Total Payments to Suppliers ($bil)

Total Surplus of Suppliers ($bil)Average Payments by Load ($/MWh)

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

FCM

Bid

($/

kW

-mon

th)

Cumulative MW

Supply Curve

Supply Without PI

Supply With PI

ICR (MW)

• With and without PI, and difference

• Changes to resource mix by asset class

• Units that clear, delist

Sample Model OutputsResults With PI

Total MW of Units that Clear Total MW of Units that Delist

Total

Payme

Unit Fuel Type

DR/ImportCombined Cycle (Natural Gas)Gas Turbine - GasGas Turbine - OilHydroelectric - AllInternal CombustionOtherPhotovoltaicSteam Turbine - CoalSteam Turbine - Natural GasSteam Turbine - NuclearSteam Turbine - Residual Fuel OilSteam Turbine - Wood/Wood Waste SolidsWindTotal

Results Without PI


Total

Payme

Unit Fuel Type


Difference Between non-PI and PI


Total

Payme

Unit Fuel Type


How does FCM PI affect clearing prices? Revenues to generators? Costs to load?

Do offers from new entry increase or decrease as a result of FCM PI? Existing asset classes?

To what extent would FCM PI drive retirements for units with poor performance or compliance investments?

How sensitive is the FCM PI clearing price to various system parameters?

To what extent may FCM PI change the resource mix?

How would FCM PI affect reliability through improving aggregate system performance due to resource mix changes?

Directionally, how would FCM PI likely affect energy market outcomes (e.g., fewer RT price spikes, reductions in NCPC)?

Areas of Inquiry

Complete preparation of input data analysis and quality control checks on model

Review results, compare outcomes under various scenariosHigh/low ICRFCM PI parameters (H, A, BR, PPR)Environmental compliance obligations

Construct analysis of NRG alternative

Review results with stakeholders (July)

Next Steps

Paul J. HibbardAnalysis Group111 Huntington Avenue, 10th Floor Boston, MA [email protected]

fcm pi impact assessment update

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