SIPA Capstone Team

James Doone, William Hernandez, Harsh Vijay Singh, Varun Soni & Vivian Xu

M a y 1 3 , 2 0 1 5

Wind in a Post-PTC Market

2

Table of Contents Acknowledgements ............................................................................................................................ 3 1.0 Introduction .................................................................................................................................. 4 2.0 Executive Summary .................................................................................................................... 6

2.1 Objective of the Project ........................................................................................................................ 6 2.2 Planning for Variability ........................................................................................................................ 6 2.3 Exogenous Factors ................................................................................................................................. 7 2.4 Avoided Costs ........................................................................................................................................... 8 2.5 Recommendations .................................................................................................................................. 9

3.0 Background ................................................................................................................................ 12 3.1 Overview of utility ............................................................................................................................... 12

4.0 Planning for Variability .......................................................................................................... 14 4.1 Existing Assets ...................................................................................................................................... 14 4.2 Wind Scheduling .................................................................................................................................. 15 4.3 Reserve Margin & Capacity Value ................................................................................................. 16 4.4 Pricing....................................................................................................................................................... 18

5.0 Exogenous Factors ................................................................................................................... 20 5.1 Underdeveloped Transmission Infrastructure ....................................................................... 20 5.2 Regulation ............................................................................................................................................... 22

6.0 Avoided Cost ............................................................................................................................... 25 6.1 Regulations on Avoided Costs ........................................................................................................ 29

7.0 Recommendations ................................................................................................................... 35 7.1 Address asymmetry in fuel price risk allocation .................................................................... 35 7.2 Standardized Avoided Cost Methodologies .............................................................................. 35 7.3 Resource Specific Avoided Costs ................................................................................................... 36 7.4 Forward Capacity Markets ............................................................................................................... 37 7.5 Security Constraint Economic Dispatch ..................................................................................... 38 7.6 Increased Geographic Network ..................................................................................................... 39 7.7 Externalities ........................................................................................................................................... 41

APPENDIX ........................................................................................................................................... 43

Bibliography ............................................................................................................................ 44

3

Acknowledgements The SIPA capstone team would like to express our deep gratitude to the following

subject matter experts, who provided insight and expertise that greatly assisted in

the research presented in this document.

John Olsen, Executive Director, Power Marketing, Westar Energy

Jay Caspary, Director R&D and Special Studies, OG&E

Cody VandeVelde, Supervisor, Market Resource Planning, Westar Energy

Richard Cornelis, Project Manager and Economic Development, OG&E

Dana Murphy, Commissioner, Oklahoma Corporation Commission

David Springe,  Consumer  Counsel,  Kansas  Citizens’  Utility  Ratepayer  Board

Dale Osborn, Transmissions Planning Technical Director, Midwest ISO

Paul Suskie, Executive Vice President and General Counsel, Southwest Power Pool

Kevin Porter, Principal, Exeter Associates

Charles Smith, Executive Director, Utility Variable-Generation Integration Group

Mark Alhstrom, CEO, WindLogics

Jacob Sussman, CEO, OWN Energy

A.J. Goulding, Professor, Columbia University and Principal, LEI

Alfred Griffin, Professor, Columbia University and President, NY Green Bank

Daniel Gross, Professor, Columbia University and MD, Oaktree Capital Management

Jeanne Fox, Professor, Columbia University and Ex-Commissioner, NJ Board of Public

Utilities

4

1.0 Introduction

In the US, wind energy has grown rapidly in recent years. At the end of 2014,

installed capacity reached 65,879 megawatts, a 145% increase since 2008.1 Much of

this growth has been fueled by incentives provided at both the state and federal

levels, which allow wind generation to compete with traditional generation

technologies. In particular, the Production Tax Credit (PTC) offered a strong incentive

by providing an inflation-adjusted per kilowatt-hour tax credit of $0.023 to wind

generators for the first 10 years of generation. However, conditional expiration of the

PTC began at the end of 2014.

As a leading manufacturer of wind turbines, our client, GE Power & Water,

would like to gain a better understanding of how utilities will evaluate wind

generation in a post-PTC market. As such, GE has asked our capstone team to:

1. Identify and analyze the factors utilities consider when evaluating wind

generation against other generation assets;

2. Analyze the alternative methodologies currently being used by utilities to

evaluate generation assets and determine the extent to which they might be

indefensible.

3. Identify and outline opportunities for GE to overcome barriers for wind

generation amongst target utilities.

The scope of this project was limited to investigating two vertically-integrated

utilities operating in the regulated Southwest Power Pool Regional Transmission

Organization – Oklahoma Gas & Electric (OG&E) and Westar Energy of Kansas. In

order to achieve the objectives of this project, the capstone team conducted research

on  each  utility’s  regulatory  environment  and  electric  supply  and  demand  portfolios.  

In addition, the team also researched various avoided cost methodologies that are

commonly used by utilities. Based on this knowledge, the team conducted a series of

1 (American Wind Energy Association, 2015)

5

interviews with relevant stakeholders in order to gain a deeper understanding of the

decision making criteria and avoided cost methodologies being used by OG&E and

Westar Energy. This included speaking with officials at both utilities as well as various

subject matter experts from the power sector.2 After synthesizing and analyzing the

information gathered from the desk research and interviews, the team came up with

recommendations that will help GE overcome barriers to wind deployment in a post-

PTC marketplace.

In general, the capstone team focused on the following key areas:

1. Variability:

A. Existing assets

B. Wind scheduling

C. Capacity margin vs. reserve margin

D. Pricing

2. Exogenous factors

A. Transmission

B. Regulation

3. Avoided cost methodologies

In this report, Section 4 and 5 describe the factors that utilities consider when

evaluating wind against other generating assets, whereas Section 6 covers

information gathered on avoided cost methodologies. Section 7 consists of

recommendations that might help GE overcome barriers that prevent utilities from

deploying wind assets in a post-PTC market.

2 A complete list of interviewees can be found in the Acknowledgements section

6

2.0 Executive Summary

2.1 Objective of the Project

In the US, wind energy has grown rapidly in recent years. At the end of 2014,

installed capacity reached 61,327 megawatts, a 145% increase since 2008. Much of

this growth has been fueled by incentives provided at both the state and federal

levels, which allow wind generation to compete with traditional generation

technologies. In particular, the Production Tax Credit (PTC) offered a strong incentive

by providing an inflation-adjusted per kilowatt-hour tax credit of $0.023 to wind

generators for the first 10 years of generation. However, conditional expiration of the

PTC began at the end of 2014.

1. Identify and analyze the factors utilities consider when evaluating wind

generation against other generation assets;

2. Analyze the alternative methodologies currently being used by utilities to

evaluate generation assets and determine the extent to which they might be

indefensible.

3. Identify and outline opportunities for GE to overcome barriers for wind

generation amongst target utilities.

2.2 Planning for Variability

Research and interviews conducted with stakeholders at both Westar Energy

and OG&E revealed that utilities regard variability and intermittency to be the most

significant vulnerabilities to wind generation. The subsequent issues that utilities

consider when evaluating wind against other generating technologies are as follows:

1. Existing Assets: Since wind is variable resource, other generating assets often

have to be dispatched in order to fill the gap between supply and load. When

planning for wind integration, utilities have to consider the dispatchability or

flexibility of existing assets, and decide whether or not to increase their

portfolio of traditional generation, so as to address the issues of wind

7

variability and intermittency. In the absence of forward capacity markets at

SPP, utilities do not have sufficient incentives to add new generation assets to

maintain appropriate reserve capacity in order to mitigate the variability

component of wind farms.

2. Wind Scheduling: Through discussions with utilities, it was revealed that

strong winds can pose a critical threat to reliability due to high wind cut out.

However, further discussions with subject matter experts suggest that high

wind cut out is not a significant barrier due to advances in wind forecasting,

technological improvements, greater   balancing   areas,   and   SPP’s   Integrated  

Marketplace.

3. Reserve Margin and Capacity Value: Utilities are required to to maintain the

reserve margin standard assigned by SPP, to demonstrate resource adequacy.

Since wind is variable, it is accredited a small percentage of nameplate

capacity  under  SPP’s  methodology.    The   low  capacity  value  of  wind  and   its  

limited  contribution  to  reserve  margin  reduce  utilities’  incentive  to  add  wind.

4. Pricing: From   a   utility’s   perspective,   limitations   associated   with   wind  

predictability in the short-term put wind at a disadvantage when compared to

more conventional assets. In particular this aspect of wind limits the ability of

a utility to offer power in day-ahead markets. This exposes utilities to greater

price risk.

2.3 Exogenous Factors

In addition to considering factors related to variability and vulnerability, utilities

also consider various other criteria when evaluating wind against other generating

technologies. These criteria include:

1. Transmission constraints: Underdeveloped transmission infrastructure has

been cited as a major deterrent of wind growth in the Plains region. However,

8

with SPPs creation of the Integrated Marketplace and the Highway Byway cost

sharing methodology, utilities are more incentivized to rate-base these

transmission projects and earn a return on their investments. Greater

transmission infrastructure will help to reduce barriers to wind generation.

Through interviews with stakeholders from SPP, we discovered that the

component of transmission cost in the rate base is applied on an average basis

to  customers  across  SPP’s  balancing  area,   irrespective  of   the   location  of   the  

source and the load.

2. Regulation: Conversations with officials at both utilities and other subject

matter experts in the power sector suggest that regulation has been a primary

driver for the deployment of wind resources in the SPP. Specifically, the three

programs that have had the greatest impact are the Renewable Portfolio

Standard (RPS), PTC and Clean Power Plan (CPP). However, from the utilities

perspective an uncertain regulatory environment introduces the risk of

stranded assets.

2.4 Avoided Costs

Utilities assess the value of electricity and capacity offered by independent

power producers on the basis of avoided costs. A  utility’s assessment of avoided cost

borrows from its Integrated Resource Plan (IRP). Among the factors that influence

avoided costs, utilities account for projections of resource sufficiency and deficiency,

fuel price projections, load growth and load shape forecasts, costs of compliance to

current and expected future compliance standards, etc. Avoided costs for small power

producers, those with less than 100 kW of capacity 3 , are defined by standard

purchase contracts, which are vetted by state regulatory commissions. However, for

qualifying facilities (QFs) that are not eligible for standard purchase agreements, the

avoided costs assessment depends upon the assumptions made by the utility for its

3 Eligibility criteria varies by state

9

IRP. Consequently, there are a variety of methods used to estimate avoided costs,

none more or less defensible than the others. On a general note, some of the common

variables that feed into avoided costs are avoided costs of energy, capacity,

transmission and distribution, line losses and environmental compliance, etc.

2.5 Recommendations

From  a  utility’s  perspective,  greater  wind  adoption  faces several barriers in a

post-PTC market. Foremost among them are issues related to variability, uncertain

regulation and limitations in transmission infrastructure. Although new

developments in the SPP alleviate some of these issues for OG&E and Westar Energy,

other issues will persist. The following recommendations are put forward to help GE

address these issues, and are based on information gleaned from desk research and

stakeholder interviews.

Address asymmetry in allocation of fuel price risk: Unlike traditional generating

assets, such as coal and gas plants, wind generation has negligible fuel price risk.

However, the Fuel Adjustment Clause (FAC) in both Oklahoma and Kansas leads to

market distortions that cause utilities to overlook this critical aspect of wind

generation. In order to provide a level playing field for wind generation, it would be

prudent for GE to help address distortions created by the FAC. Since the FAC allocates

fuel price risk to ratepayers, one way for GE to address this issue is through

consumer-motivated regulation.

Standardize Avoided Cost Methods: The avoided cost methodologies approved across

different states are consistent with their respective policy objectives. However, there

is a considerable lack of transparency with regards to these methodologies. This

creates uncertainty for QF investors and limits their ability to make investments in

the long term. As such, GE would benefit if FERC were to commission an evaluation of

avoided costs methods used across different states, assessing their strengths and

weaknesses from the perspective of small power producers.

10

Resource Specific Avoided Costs: A recent order by FERC on a petition filed by the

California Public Utilities Commission permitted multi-tiered avoided cost

calculations within a jurisdiction. Depending on the characteristics of the specific

resource, such as dispatchability, intermittency, efficiency, environmental

performance and location etc., the avoided cost of a QF should be calculated by

comparison with an operating QF with similar characteristics. Such a comparison will

determine the full extent of avoided costs. It would help equipment manufacturers

like GE, as well as wind energy developers alike to engage in discussion with state

regulatory commissions and advocate for resource specific avoided cost assessment.

Forward Capacity Markets: SPP requires a reserve capacity margin of approximately

12 percent. However, the reserve capacity margin does not offer enough incentive to

incumbent utilities to add additional conventional generation capacity beyond the

reserve margin, to compensate for the intermittency induced by variable generation

assets. A forward capacity market, on the lines of PJM, will offer the utilities a regular

stream of revenue from capacity, and improve the system's overall reliability. With

this in mind, we believe stakeholders from conventional utilities, equipment

manufacturers, wind generators, consumer forums and SPP should explore the

possibility of implementing a forward capacity market.

Security Constrained Economic Dispatch: This is a process that takes cost and liability

when optimizing a system every 5 minutes to match load. This process takes into

account the whole power system with all its different types of generators and

characteristics (failure modes, lack of certainty, etc.). So, When Dispatch nullifies the

problems associated with cut out and other associated problems caused by

variability. Therefore, we believe GE can reduce the barriers associated with

variability by informing utilities that these problems can be nullified by using the

tools already in place—primarily the Security Constrained Economic Dispatch.

Integrated Marketplace: The expansion of the Integrated Marketplace through the

growth of the SPP will reduce the variability of wind and the congestion-related

11

issues surrounding geographic areas highly concentrated with wind farms. The

inclusion of more stakeholders, as participants in this marketplace, will further the

development of high-voltage transmissions lines paid for through the

Highway/Byway shared-cost methodology. This would reduce integration costs and

promote further development of wind farms.

Externalities: While  there  isn’t  a  carbon  pricing  system  in  the  SPP, it is expected that

tighter regulation on carbon emission will eventually lead to a price on externalities

caused by greenhouse gas (GHG) emission. Since the generating assets that utilities

invest in today will endure for a several years into the future, it is important to ensure

that the generating portfolio can meet a future tighter standard on carbon emission.

Thus,  GE  could  engage  in  raising  utilities’  awareness  of the possibility of future carbon

pricing, and suggest utilities to factor in a carbon price in economic analysis.

12

3.0 Background

3.1 Overview of utility

3.1.1 Oklahoma Gas and Electric

OG&E was incorporated in 1902 in Oklahoma, and currently operates as a

regulated investor-owned public utility holding company. As an energy services

provider it offers physical delivery and related services for both electricity and

natural gas, primarily in the south-central United States. The company conducts these

activities through two business segments: (i) an electric utility and (ii) natural gas

midstream operations. The electric utility segment generates, transmits, distributes

and sells electric energy in Oklahoma and western Arkansas. The service area covers

30,000 square miles in Oklahoma and western Arkansas, including Oklahoma City,

the largest city in Oklahoma, and Fort Smith, Arkansas.4

OG&E’s  stated  mission  is  “to fulfill its critical role in the nation's electric utility

and natural gas midstream pipeline infrastructure and meet individual customers'

needs for energy and related services focusing on safety, efficiency, reliability,

customer service and risk management.”5 OG&E is focused on increased investment

to preserve system reliability and to meet load growth by adding and maintaining

infrastructure equipment and replacing aging transmission and distribution systems.

OG&E expects to maintain a diverse generation portfolio while remaining

environmentally responsible. Through its various initiatives, OG&E believes it may be

able to defer the construction or acquisition of any incremental fossil fuel generation

capacity until 2020. 6

4 (OG&E, 2014) 5 (OG&E, 2014) 6 (OG&E, 2014)

13

3.1.2 Westar Energy

A Kansas corporation incorporated in 1924, Westar Energy, Inc. (Westar) is a

vertically-integrated investor-owned utility operating in south-central and northeast

Kansas. Within these two geographic areas of Kansas, Westar Energy operates as two

separate companies – Kansas Gas and Electric (Westar South) and Westar Energy

(Westar North). As the largest electric utility in Kansas, Westar provides electric

generation, transmission and distribution services to approximately 693,000

customers in Kansas.7 Although technically comprised of two separate companies,

Westar’s  entire  system  is  dispatched  as  one  system  unit, and therefore there has been

a movement to consolidate electric rates with the ultimate goal of uniform rates

across the two entities.8

Significant   elements   of  Westar’s   corporate   strategy   involves   maintaining   a  

flexible and diverse energy supply portfolio. In doing so, Westar has made

environmental upgrades to their coal-fired power plants, developed renewable

generation, built and upgraded their electrical infrastructure, and developed systems

and programs with regard to how their customers use energy.9

7 (Westar Energy, 2014) 8 (Kansas Corporation Commission, 2015) 9 (Westar Energy, 2013)

14

4.0 Planning for Variability

While utilities consider various factors when evaluating wind against other

generation technologies, research and interviews conducted with stakeholders at

both Westar and OG&E revealed that utilities regard variability and intermittency to

be the most significant vulnerabilities to wind generation. As such, variability is a key

aspect that utilities factor into their decision making process, when comparing wind

to traditional generation assets. This section describes the subsequent issues that

utilities face due to these vulnerabilities.

4.1 Existing Assets

The extent to which utilities can add new wind assets is in part determined by

the dispatchability of their existing generation portfolio. Since wind is a variable

resource, other generating assets often have to be dispatched in order to fill the gaps

between supply and load. This issue becomes more acute in times of light load. During

periods of light load, an increase in wind generation can quickly lead to a surplus of

power in the market. In such situations utilities are forced to curtail generation from

other assets, as wind  generation’s low variable cost allows it to be dispatched before

other baseload assets in the bid stack. Those utilities with a portfolio of assets with a

low dispatchability find it more difficult to integrate wind. Broadly speaking, utilities

that have a greater percentage of gas generation are better off, since gas turbines are

highly dispatchable, or flexible to changing load conditions. Conversely, those utilities

with predominantly nuclear or coal assets find it more difficult to integrate wind as

these assets are less flexible.

When planning for wind integration, utilities have to consider whether or not

to also increase their portfolio of traditional generation, so as to address the issues of

wind variability and intermittency. For instance, the resource planning department

of Westar mentioned that it had to invest in 600MW of gas turbines to offset an

anticipated increase in wind generation. Of the 600MW, 150MW consisted of aero-

derivative turbines, which have very high dispatchability. These variable backup

15

generators amount to additional costs for the utility. Thus, wind variability and

intermittency  with  regards  to  the  existing  portfolio  of  a  utility’s  generating  assets  can  

present a barrier to adding wind generation.

4.2 Wind Scheduling

Variability is not just a problem when wind speeds drop to low levels. In a

discussion with a former director of resource planning at one utility, he described a

situation where strong winds, not light or even no wind scenarios, pose the biggest

threat to operators. He informed us that at 8 mph, wind turbines begin to produce

power; at 20 mph, they achieve maximum output; but between 40 and 55 mph

turbines hit their cut out point. For an operator, this scenario threatens the reliability

of a utility to meet demand. If a wind farm is running at full output and then shuts off

due to high wind, the utility will have to immediately make up for the shortfall. From

the point of view of a director of resource planning, strong winds can pose a critical

threat to a  utility’s  reliability.

However, other subject matter experts undermined the threat of high wind cut

out. It was pointed out that high wind cut out is only associated with high intensity

storms that result from wind speeds in excess of 55 mph. In most cases, utilities can

predict storms of this magnitude well in advance, allowing them adequate time to

prepare their supply needs. Furthermore, high wind cut out typically impacts only a

small fraction of wind turbines in a wind generation facility, and as soon as the wind

dies down, the turbines start generating again. With current technology and

modeling, wind scheduling is capable of significantly lowering the risk that a cut out

scenario poses to an operator. By utilizing wind-scheduling technology, operators

can plan for a cut out scenario, in some cases up to 48 hours before a weather system

hits its region. Finally, new turbine technology, which can mitigate the risk posed by

high winds, and the creation of the Integrated Marketplace in SPP, raises further

questions as to whether high wind cut out is a serious issue for utilities.

16

4.3 Reserve Margin & Capacity Value

In order to ensure grid reliability, utilities have to demonstrate that they have

enough installed capacity to meet peak load requirements. SPP ensures resource

capacity by mandating that each utility in its jurisdiction maintain a reserve margin

of at least 13.6%. As such, utilities need to accredit the capacity value of all their

generating assets, making sure that they adhere to this standard in their resource

planning.

Due to the variability of wind, the capacity value that is assigned to wind

generators is a smaller fraction of nameplate capacity than that associated with other

generation technologies. From the point of view of a utility, the low capacity value of

wind imposes a barrier to developing wind generation, because wind only makes a

limited contribution to reserve margin, compared with traditional generating assets.

Thus, when considering alternative generation technologies with regards to meeting

capacity requirements, utilities are more likely to choose technologies that have a

higher accreditation value.

The variability associated with wind also results in greater subjectivity in the

accreditation process. As such, each region may choose to adopt its own methodology

and assumptions when accrediting wind farms, giving wind varying degrees of

capacity value. Proponents of wind have longstanding concerns that the SPP deters

wind development by assigning a particularly low value to wind. Based on 2011 EIA

estimate of wind profiles, within NERC regions, the wind capacity value in SPP was

8.2%. Only the Midwest ISO MRO had a lower value of 8%.10

One reason that SPP assigns a low capacity value to wind is that wind speed is

negatively correlated with load in this region.11 However, in cases where output from

wind generators closely correlates with load, wind generation assets might be

10 (EIA, 2011) 11 (Southwest Power Pool Generation Working Group , 2004)

17

assigned a higher capacity credit. 12 Furthermore, SPP is revising its wind

accreditation methodology this year. The new methodology is expected to improve

wind capacity value to 12.1%.13 From  a  utility’s  perspective,  this increased capacity

credit is likely to reduce barriers associated with wind generation.

Originally in 2004, the SPP Generation Working Group (GWG) developed a

statistical-based method to accredit capacity value of wind. It first examined the

highest 10% of load hours in a month, and ranked wind generation during these hours

from high to low. The value that exceeded 85% of these values was used as the wind

capacity value. When possible, the methodology takes 10 years of data into account.14

In   April   2014,   Mitchell   Williams,   of   Western   Farmers   Electric   Cooperative’s  

Generation Working Group, proposed a revision of the wind accreditation. This

revised version is more favorable to wind for the following reasons:

1. It reduces data requirements from 10% load hours to 3%.

2. It reduces confidence interval from 85% to 60%.

3. It accepts 5% capacity for a new project instead of 3% for up to 3 years.15

In   June   2014,   SPP’s   Cost   Allocation   Working   Group   decided   to   maintain   this  

proposed revision, and planned to pay close attention to future reports on the

performance of wind assets. 16 Not only is wind accreditation becoming more

favorable to wind development, but also utilities in SPP are expecting to see more

relaxed reserve margin standards. These standards will also favor wind in an indirect

manner, since they place fewer requirements on utilities in terms of increasing

capacity value of generating assets.

12 (Milligan & Porter, 2006) 13 (Argus, 2015) 14 (Milligan & Porter, 2006) 15 (Southwest Power Pool CAWG, 2014) 16 (Southwest Power Pool CAWG, 2014)

18

Considering that approximately $1 billion could be saved over a 30-year

period for every 1% reduction in the reserve margin, SPP formed the Capacity Margin

Task Force to research the potential of reducing capacity margin or reserve margin

while still ensuring the same level of reliability. 17 Due to the high potential for

conserving capital, refining reserve margin  is  currently  one  of  SPP’s  highest  stated  

priorities.18

4.4 Pricing

Utilities claim that variability and intermittency can significantly increase

price volatility in energy markets. Although wind forecasts can provide reliable

estimates of generation over long periods of time, such as on a monthly or annual

basis, they are inaccurate over shorter   periods.   From   a   utility’s   perspective,  

limitations associated with wind predictability in the short-term put wind at a

disadvantage when compared to more conventional assets, such as gas turbines,

which are predictable and far more dispatchable.

When a utility seeks to offer its generated power into the marketplace, it has

two channels: through the day-ahead markets, or in the real-time markets. In the day-

ahead market, a utility determines the price and quantity at which it will offer its

power the following day. The day-ahead market in the SPP is scheduled in five-minute

increments. Consequently, each day consists of a total of 288 price points.

Furthermore, the utility can provide up to 10 discrete prices for each five-minute

increment, depending on the heat rate, which in turn depends on how much of an

asset is bid into the market.

By contracting in the day-ahead market, a utility gains price-assurance;

however, the quantity of power that the market purchases is dependent on the bid

17 (Nickell, 2014) 18 (Nickell, 2014)

19

stack, which in turn depends on two variables: load and price competition.

Conversely, real-time market prices vary based on demand and supply, and thus, a

utility can only determine the quantity it is willing to offer for the real-time price.

Due to the short-term variability and intermittency associated with wind

assets, the ability of a utility to offer wind in the day-ahead market is compromised.

It is all but impossible for a utility to determine the power generation of a wind asset

during a certain five-minute increment the following day. Utilities have limited choice

but to offer a large portion of their wind power in real-time markets. This increases

price risk. Furthermore, in geographies that are highly concentrated with wind

turbines, such as in the southwest of Kansas, the market experiences increased price

volatility. When wind is available, all the wind turbines in a given area produce power,

leading to a surplus of power in the real-time market. This surplus causes prices to

drop. As such, the extent of the change in price is determined by the capacity of wind

assets in that area. With continued wind development in an already highly

concentrated area, price volatility persists.

The issue of price volatility due to wind variability is further complicated by

the market distortions caused by the PTC. Wind generators who can avail the PTC can

occasionally offer power into the market at negative prices. Consequently, utilities

that are contemplating the addition of wind assets after the expiration of the PTC are

at a distinct disadvantage, since it would be impossible for them to compete with

generators that have negative marginal costs. This is one of the reasons why wind

deployment has plummeted in the post-PTC market.

The issue of price volatility can be somewhat mitigated through the use of

balancing areas and robust transmission infrastructure. There is potential to benefit

from economies of scale if several balancing areas develop cooperative arrangements

or markets for ancillary services, as SPP has created through the Integrated

Marketplace.

20

5.0 Exogenous Factors

5.1 Underdeveloped Transmission Infrastructure

Through conversations with participants in the Integrated Marketplace, the

need to rehabilitate and build new transmission infrastructure has been cited as a

major deterrent of wind growth in the Plains region. Aging infrastructure, unable to

handle the supply variations of wind along with a sparse transmissions network in

wind-abundant areas are believed to be major sources of resistance for wind

development.

One explanation for lackluster infrastructure development is historically low

load growth. Yet, in recent years, population growth in Oklahoma’s  two  largest  cities,  

Oklahoma City and Tulsa, has caused electricity demand to increase. This influx of

population is changing demographics in the OG&E service area. As such, customers

are demanding more clean energy options, in particularly wind options, as part of

their electricity fuel make-up. These demands are forcing OG&E and other utilities to

make preparatory infrastructure investments.

Prior to 2014, transmission projects in the SPP region were implemented on a

utility-by-utility basis. However, the creation of the Integrated Marketplace has given

utilities a new incentive to implement transmission renovation projects. The

“Highway/Byway”  cost  sharing  methodology  assigns  costs  regionally  and  locally  to  

those   benefiting  most   from   the   project.   “Highways”   are   high-voltage transmission

lines   above   300   kV,   while   “Byways”   are   lower-voltage (300 kv and below)

transmission lines. Costs are assigned to electric utilities across the entire SPP

footprint  based  on  their  historic  use  of  the  region’s  transmission  system.  The  SPP  uses  

a formula to assign costs more directly to the utility in whose service territory (zone)

21

the project is located. The chart below outlines the breakdown of the Highway/Byway

method.19

Voltage Paid for by Region Paid for by Local Zone “Electricity  Highways” (300 kV and above)

100% 0%

“Electricity  Byways” (100 kV to 300 kV)

33% 67%

“Electricity  Byways” (100 kV and below)

0% 100%

The Highway/Byway method significantly reduces the amount of capital

required for transmission projects. Utilities are incentivized to expand their

transmissions infrastructure through incorporation into their rate-base in order to

earn an annual return. The new system also increases the overall reliability of the grid

by improving the efficiency by which electricity flows throughout the RTO. The

combination of these changes in the SPP has led to an increase in completed

transmission projects, totaling $8 billion in 10 years, and solving the apparent

vulnerability of transmission development.

One recent success of the Highway/Byway is the Prairie Wind Transmission

Project. In 2014, Westar completed the Prairie Wind Transmission Project to build

108 miles of extra-high-voltage 345 kV transmission lines. The project links an

existing 345-kV substation near Wichita, Kansas to a new 345-kV substation

northeast of Medicine Lodge, Kansas near the Flat Ridge I Wind Farm, and then south

to the Kansas/Oklahoma border. This project will support future generation assets

joining the grid in the region.20

Stakeholder interviews suggest that had the ability to share transmission costs

been created in earlier, utilities would likely have avoided issues related to

curtailment payments. For instance, OG&E may have avoided a $4.3 million

19 (Pennel, 2010) 20 (Westar Energy, 2014)

22

settlement with wind developer Competitive Power Ventures, surrounding a

disagreement on curtailment payments caused by unreliable transmissions lines. In

August 2013, the wind developer filed a lawsuit against OG&E claiming the utility

failed to pay curtailment charges when their Keenan wind farm was in operation but

transmission issues limited it from supplying electricity onto the grid. The two parties

settled for $4.3 million and OG&E plans to recover this cost through a fuel adjustment

clause, transferring the burden of the faulty transmission system onto its rate-payers.

Underdeveloped transmission infrastructure might have been a deterrent of wind in

the past, but recent innovations such as the Highway/Byway and the Integrated

Marketplace have brought solutions to all stakeholders within the SPP territory. 21

5.2 Regulation

Conversations with both utilities and other subject matter experts in the

power sector provide consensus that regulation has been a primary driver for the

deployment of wind resources in the SPP. First, both OG&E and Westar were forced

to comply with the Renewable Portfolio Standards (RPS) in their respective states.

Second, the Production Tax Credit (PTC) offered a significant incentive for deploying

wind assets by improving wind economics. Finally, the Clean Power Plan is forcing

both utilities to rethink their resource planning objectives for the coming years.

Meanwhile, uncertainty surrounding future policy legislation introduces a certain

amount of risk. For instance, if a utility takes on additional wind assets in order to

comply with legislation, and the legislation is later repealed, the utility runs the risk

of creating stranded assets. The following sections elaborate on these aspects of

regulation and their impact on wind generation.

21 (Monies, 2015)

23

5.2.1 Renewable Portfolio Standard (RPS)

Officials at both OG&E and Westar confirmed that the RPS was a primary

driving force behind wind adoption in their respective states. In May 2010, the

Oklahoma Legislature set a suggested RPS goal that 15% of total installed generation

capacity be derived from renewable sources. There are no interim targets and the

goal is not extending past 2015.22 This RPS standard in Oklahoma is not a mandatory

regulation, but only a call for voluntary compliance. As it stands, wind capacity at

OG&E accounts for about 12% of generation capacity.23

In Kansas, the RPS was established in 2009, aiming for 15% by 2015-2019,

and 20% by 2020.24 Due  to  Kansas’  low load growth, as well as additional purchased

wind energy, Westar has achieved its 2020 RPS target of 20%. Although Westar has

technically met its RPS goals until 2020, the utility continues to weigh the economic

advantages of adding wind generation now with the PTC or possibly in the future

should wind generation technology continue to become more cost competitive. An

uncertain regulatory environment exacerbates the risk of adding wind. For example,

in a conversation with the resource planning team at Westar Energy, the concern for

creating stranded assets was communicated. However, should the utility wait until

the regulatory environment is certain, then the utility will likely face higher charges

as greater demand for wind assets will increase the price at which developers provide

wind assets.

With that said, a   utility’s ability to rate-base assets offers them greater

incentive to expand their wind portfolio, as any investment costs approved by state

regulators are able to be recovered. If utilities are forced to bear an unfair higher cost

because of a sudden change in state legislation, it has been suggested that utilities will

have a strong legal case for reparations.

22 (National Conference of State Legislatures, 2015) 23 (OG&E, 2014) 24 (OG&E, 2014)

24

5.2.2 Clean Power Plan

In 2014, the EPA proposed emissions guidelines for states to reduce GHG

emissions from tradition, fossil-fuel generation plants. Although the proposal has yet

to be enacted, the CPP has the potential to significantly impact utilities throughout

the SPP.

Insight gained from experts in the SPP and MISO suggest that the most

significant impact of the CPP will manifest through a conversion from traditional coal

generating units to more flexible, cheaper natural gas ones. For OG&E and Westar,

this means converting around 50% of coal assets to natural gas. The utility-by-utility

reaction to this will vary; it has been observed that some utilities are willing to make

slightly larger investments to lock-in longer-term contracts for their clean assets.

In the short-run, the current industry consensus is that the transition to

natural gas plants will expand wind and solar markets by determining the shadow

price for carbon in the market. Stakeholders believe that studies to analyze the impact

of the CPP are underestimating how much wind will be installed over the next few

years. Even with this favorable future, this conversion is still highly vulnerable to

policies that state regulatory authorities will enact to either facilitate or add

resistance to this process.

25

6.0 Avoided Cost

FERC’s   enactment   of   PURPA   left the calculation of avoided costs open to

interpretation, and there are several methodologies used by state utility commissions

across  the  US.  Developers  are  often  unable  to  fully  capitalize  on  PURPA’s  benefits,  due  

to complexity of avoided cost ratemaking at the state level. Under the constraints of

maintaining consistency and reliability of electricity supply, and due to the multitude

of sources used for energy production, the calculation of avoided costs is invariably

complicated.

Added to the complexity of avoided costs is the necessity of confidentiality.

Since utilities need to compete in the open market for goods and services, the

respective inputs to avoided costs and the price points need to be masked from

potential vendors, otherwise the bids will naturally gravitate towards the highest bid,

thus setting an artificial floor and forcing other utilities to meet this price point. In

our attempt to understand how OG&E and Westar Energy calculate avoided cost, the

capstone team first conducted general desk research on the most commonly used

avoided cost methodologies in the sector. This information was helpful in guiding our

conversations with officials at both utilities. That said, although the team was able to

get a general sense of how the target utilities approach avoided cost, we were unable

to get specific information for the reasons stated above.

Availability of information on avoided costs methodologies varies among

states. While information on avoided cost for some states might be more easily

accessible in public records, reliable information is not available for most states25. To

the extent possible, we collected information from publically available information,

such as testimonies in utility case filings, news reports, and rate case proceedings.

25 18 CFR § 292.302 requires utilities to submit data from which avoided costs were calculated to the state regulatory commissions every two years.

26

From testimonies and interviews of personnel from OG&E and public records at

the Oklahoma Corporation Commission, the following information gives some insight

into  OG&E’s  avoided  cost  calculation  methodology.  OG&E’s  decision  making  on  QF  

power purchases are based on their forecasts from a production cost model, for which

they  use  Power  Cost  Inc.’s  GenTrader  software.26 The following are some of the key

components  of  OG&E’s  avoided  cost  methodology:

1. OG&E’s  avoided  cost  calculation  includes purchases of wholesale energy that

would be purchased in the absence of purchase from the wind farms.

2. Due to the establishment of regional transmission operator, Southwest Power

Pool,  all  wind  QF’s  have  non-discriminatory access to the grid. Hence the QF’s  

bid into the integrated marketplace.

3. In the regional SPP market, the hourly costs are calculated at specific nodes.

This implies that at a given point of time, there are several avoided costs for

each utility.

4. The avoided capacity cost calculation is based on the assumption that OG&E's

next incremental capacity need would be fulfilled with a combustion turbine

(peaking capacity). OG&E assumes avoided capacity cost to be zero in years it

does not need an additional capacity to maintain the minimum required

capacity margin of 12% specified in section 2.1.9 of the SPP criteria. OG&E's

avoided cost calculation do not include any forecasts of capacity prices in the

region. Moreover, OG&E does not include any costs with compliance with

present or future environmental regulations in avoided capacity cost

calculations, as environmental regulations are geared towards the

preservation of existing capacity, and not the incremental need.

26 Docket No. 07-075-TF

27

5. Planned shutdowns, retirements, and retrofits of existing fossil fuel generating

facilities are usually included in the production cost analysis used to calculate

avoided costs. For instance, the O&M costs associated with retrofitting coal

and gas units with Low NOX burners was included in the production cost

model, and used to calculate the avoided energy costs.

6. OG&E includes the need and timing of future capacity needs to determine

avoided capacity costs, which takes inputs from planned shutdowns, retrofits,

and retirements.

7. Average line losses, and not marginal, are included in forecasting annual load,

which is then used to determine the forecasted reserve margin and energy

equivalents  for  each  year.  Generation  used  to  fulfil  OG&E’s  reserve  margin  is  

also included in the production cost analysis, and hence is an input for avoided

cost calculation

8. The production cost model also includes the assumption that OG&E will

comply with regional haze regulations in the manner specified in the

Oklahoma State Implementation Plan (SIP). The EPA rejected Oklahoma's SIP

and imposed a Federal Implementation Plan (FIP) on Oklahoma and OG&E.

The FIP would require OG&E to install very costly scrubbers on some of its

coal fired generators. The order has been challenged in 10th Circuit Court of

Appeals. There is some uncertainty about the requirements and costs

associated with Regional Haze and other environmental rules at the moment.

9. In addition to factors such as environmental compliance, reserve margins, line

losses, planned shutdowns, retrofits and retirements, the production cost

model is sensitive to natural gas price forecasts. OG&E does not assume any

transmission constraints in its avoided cost analysis.

28

From this information we can infer that  OG&E’s  assessment  of  long-term avoided

costs depends on the assumptions in their IRP, such as projections of fuel prices, load

growth forecasts and diurnal as well as seasonal load shape projections, planned

shutdowns, retirements and retrofits of existing generation assets, timing and type of

planned capacity additions, etc. With respect to resource sufficiency, OG&E does not

consider avoided capacity costs beyond the reserve margin of 12% as determined by

SPP, and avoided energy costs are calculated on the basis of the cost of service

incurred by OG&E to generate the power themselves from their existing generation

assets. If the resource planning considers periods of resource deficiency, the avoided

capacity payments are determined by referring to a proxy combustion turbine

generation unit (discussed below), and avoided energy costs are indicated by the

wholesale market price that OG&E might incur for purchasing the power from the

integrated marketplace. However, the above information has been obtained through

secondary   sources,   and   might   be   dated.     Insight   into   Westar’s   avoided   cost  

methodology was briefly  shared  during  a  conversation  with  officials  from  Westar’s  

Market Resource Planning department. The highlights of the conversation are

outlined below:

To determine whether a project is cost-competitive to traditional assets, the

team first uses a quantitative-based model, created by a third-party, and enters hour-

by-hour factors such as fuel price curves, load growth, and other operating

parameters. This initial model helps the team determine the optimal way to best

serve the load. Based on the potential wind generation from a wind farm, the cost of

the wind farm is compared with the cost generated from the model. The analysis looks

at 100% operation of the wind farms along with complimentary generation from

other assets. After comparing the combined system, a break-even price is determined

that establishes the basis of the economic competitiveness of the wind farm.

Additional costs such as transmission and congestion costs are factored into the

process after generating the base price. The combination of these various costs create

an avoided cost necessary to beat to purchase the wind asset.

29

6.1 Regulations on Avoided Costs

The rationale behind PURPA is to balance the interests of independent power

producers,  customers,  and  utilities.  IPP’s  lacks  the  market  power  to  compete  in  the  

open market with long established utilities. Customers need to be protected from

overpriced electricity tariffs, and utilities need to keep into consideration the

reliability and quality of power supply, air quality standards and their guaranteed

rate of return. The nature of transaction between utilities and IPPs, termed as

Qualifying   Facilities   (QF’s),   are   determined   by   the   avoided costs. PURPA defines

avoided   costs   as   the   “incremental costs to an electric utility for electric energy or

capacity or both, but for the purchase from the qualifying facility or qualifying facilities,

such utility would generate itself or purchase from another source”   (Section   210,  

PURPA, 1978).

Despite  the  mention  of  “incremental  costs”,  avoided  costs  differ  from  marginal  

costs. Marginal costs do not consider the size of the load over which changes in costs

are measured. Avoided Costs, on the other hand, require explicit consideration of the

change in costs associated with a finite change in the load, hence depending on both

timing as well as magnitude of the load changes. The incremental costs act as the price

ceilings, so that the consumer is largely indifferent to the source from which the

power is being delivered to them.

Among the various inputs that are considered in calculation of avoided costs, the

following find application in most methods:

1. Avoided purchase of energy

2. Avoided purchase of resources, such as natural gas, coal, oil etc. (and the cost

of storing and transportation of the resources)

3. Avoided transmission line costs, including construction, maintenance and line

losses

4. Avoided cost of maintenance, retrofit, and replacement, as determined by the

utility’s  integrated  resource  planning

30

5. Avoided cost of compliance with current and expected environmental

regulations

6. Avoided cost of externalities, such as health costs, benefits from improved air

quality and visibility, less noise pollution, etc.

7. Avoided  RPS  costs  (for  clean  energy  QF’s)

8. Avoided property taxes

Apart  from  the  above  mentioned  inputs,  the  utility’s  decision  making  finally  rests  

upon their resource planning, future load forecasts, and the quality of the QF power

supply.  FERC’s  regulations list the following qualitative factors which states should

consider  while  evaluating  bids  by  QF’s:  

1. The ability of the utility to dispatch the QF

2. The expected and demonstrated reliability of the QF

3. The duration of the contract

4. The extent of coordination  between  the  QF  and  utility’s  planned  /  unplanned  

outages

5. Costs and savings from changes in line losses as a result of QF purchases

6. The relationship of the availability of energy or capacity from the QF to the

ability of the electric utility to avoid costs, including deferral of capacity

additions and reduction in fossil fuel use.

6.3 Methodologies:

Surveys of avoided cost calculation methodologies have documented a variety of

methods being used across different states in the US 27 . The methods vary by

complexity,

Proxy unit: The proxy unit method assumes that the QF enables the utility to defer a future

generation unit; and the avoided costs are hence the projected energy and capacity

27 (Porter, Fink, Buckley, Rogers, & Hodge, 2013)

31

costs of the specified proxy unit, which is usually a combustion turbine power

generation asset.

The capacity costs are the fixed costs of the proxy unit, and the estimated

variable costs are used to calculate avoided energy costs. Factors such as debt

financing, tax burdens, equity costs, etc. are considered in calculate avoided capacity

costs.  The  choice  of  proxy  unit  may  either  be  in  accordance  to  the  utility’s  IRP  in  terms  

of the timing that the proxy unit comes online, capacity and type of technology, or it

may be a hypothetical unit as determined by the state utility commission.

The avoided cost hence calculated depends on the type of proxy unit selected.

Choosing a higher cost base load plant as proxy will result in higher avoided cost, and

a lower cost combustion turbine will have lower avoided cost. Although this method

lacks sound scientific basis, it is most widely used across different states in the US,

because of its simplicity.

Peaker Method: In a Peaker method of calculating avoided costs, it is assumed that the power

supplied by the QF reduced the marginal generation requirement of the utility, and

hence avoids the construction of a peaking plant. The cost if the energy component is

based on marginal costs over the life of the contract, calculated on an hourly or longer

period, as opposed to the next planned units as in the case of proxy unit method. The

production cost simulation of marginal costs with and without the QF yields the

difference between the two scenarios, which is the avoided energy cost.

The capacity component is of avoided cost is based on the annual equivalent

of  utility’s  least  cost  capacity  option  (pealing  unit),  which  is  typically  a  combustion  

turbine. Since these generation assets have less upfront capital requirement, they

minimize the avoided capacity costs, whereas the generation costs are high, as they

are assessed in a marginal generation basis. The argument in favor of this method is

32

that the sum of lower capacity costs and higher (marginal) energy costs is equivalent

to the higher capacity cost and lower fuel costs of a base load.

Since the capacity component of the contract is availed by the utility only when

required, this method assumes that the QF will recover its investment only through

energy component, whose payments vary by the hour. In case of intermittent

technologies, the payments for energy component is not only dependent on the

hourly load profile, but the resource availability as well. A recent petition at Georgia

Public Service Commission28 about this limitation of the peaker method prompted the

commission to modify the avoided cost calculation formula, with inclusion of avoided

costs of environmental compliance, and avoided start-up costs.

Differential revenue requirement (DRR) The  QF  capacity  reduces  the  utility’s  revenue  requirement.  The  present  value  

of  the  difference  between  the  utility’s  revenue  requirement  in  the  two  scenarios  of  

IRP, with and without QF capacity, represents the avoided cost.

While DRR method utilizes sophisticated modeling and forecasting technologies

in projecting the revenue requirement with and without QF output, the IRP is

sensitive to inputs considered by the utility, such as fuel price forecasts and load

forecasts. DRR assumes   that   the   QF’s   are   perpetually   marginal   resources,   and   is  

suitable only for short-term avoided cost calculation. Moreover, DRR method suffers

from a lack of transparency.

Market based pricing PURPA was amended in 2005, authorizing FERC to grant an exception from

mandatory obligation for purchase of QF power, if the QF has a non-discriminatory

access to competitive markets and open access to the transmission system provided

by the regional transmission operator. Lower natural gas prices and increased

28 (Georgia Public Service Commission, 2004)

33

competition in the wholesale markets, including competitive bidding as a way to set

avoided costs in some jurisdictions, has reduced avoided cost payments to renewable

generation  QF’s,  and  is  applicable  only  for  short  term  planning.    Some  jurisdictions

apply locational marginal price (LMP) as determined at the integrated marketplace

as  the  avoided  energy  cost.  However,  the  use  of  current  or  even  historical  LMP’s  does  

not allow the QF to estimate the future prices, due to variability in load shape, and

because   there   are   multiple   avoided   costs   (LMP’s)   at   any   given   point   of   time,  

depending upon the location of the node at which the cost is measured. The lack of

long   term   price   projections   makes   the   returns   on   investment   by   the   QF   owner’s  

uncertain, and acts as a barrier towards promotion of small power producers.

Moreover,  LMP’s  do  not  reflect  the  full  cost  of  owning  and  operating  the  generation  

facility, more specifically, the costs related to long term planning, costs of

transmission line losses, costs of maintaining reserves, etc., and hence offer an

undervalued estimate of the avoided costs.

Competitive bidding In some states, after determining the power needs based on the IRP, utilities

establish   benchmark   prices   and   allow   QF’s   to   bid   to   meet   the   benchmark. The

winning bids reflect the cost at which the utility would have procured power, and are

regarded  as  the  utility’s  avoided  costs.  

The benchmark prices set by the utilities depends on the forecasts of load and

fuel prices, resource mix as determined by the utility, term of the contract between

winning bidder and the utility and future policy projections. Theoretically,

competitive bidding rewards the QF with most efficient power generation. However,

in an open market, it places renewable energy generation facilities, especially those

with higher capacity, at a disadvantage.

All of the above-described avoided cost methodologies have their own merits

as well as merits, and none of them can yield most accurate avoided cost estimates.

34

Utilities have a broad discretion over many of the assumptions that go into calculation

of avoided costs. The choice of a specific method for avoided cost calculation in a state

is generally dictated by the policy objective, such as to promote small power

producers, incentivize particular technology, environmental considerations,

maintaining  ratepayer  neutrality  or  spreading  the  risks  of  QF  contracts  between  QF’s  

and ratepayers non-discriminately29.

Apart from the these calculation methodologies, states are required to

maintain  standard  purchase  contracts  for  purchase  of  QF’s  of  capacity  100  kW  or  less.  

In standard contracts, either the state commission establishes methodology for

calculation of avoided costs, or utilities propose both rates as well as methodologies

before the  state  commission.  Some  states  have  allowed  standard  contracts  for  QF’s  of  

higher capacity as well. For example, California allows standard contracts for facilities

of maximum capacity 20 MW, and Utah, Montana and Oregon make standard

contracts available for facilities of 10 MW capacity. Standard contracts would lend

certainty to the business of power generation from the perspective of the QF, and

enable them to plan for future investments.

29 (Elefant, 2011)

35

7.0 Recommendations

7.1 Address asymmetry in fuel price risk allocation

Unlike traditional generating assets, such as coal and gas plants, wind

generation has almost no fuel price risk. However, the Fuel Adjustment Clause (FAC)

in both Kansas and Oklahoma leads to market distortions that cause utilities to

overlook this critical aspect of wind generation when evaluating it against traditional

generating technologies.

Both Westar and OG&E are subject to the FAC. This is a mechanism that

permits jurisdictional utilities to regularly adjust the price of electricity to reflect

fluctuations in the cost of fuel, or purchased power, used to supply that electricity. By

allowing utilities to reflect fluctuations in fuel prices in electricity rates, the FAC

insulates utilities from changes in the price of fuel. Both Westar and OG&E pass the

risk of fuel price volatility straight through to their ratepayers through the FAC.

Consequently, when evaluating wind generation against traditional generation these

utilities do not factor in the benefit of mitigating fuel price risk.

The FAC encourages the use of fuel intensive technologies over renewables

since fuel price volatility is passed through to the ratepayers. In order to provide a

level playing field for wind generation, it would be prudent for GE to help address the

distortions created by the FAC. One way for GE to accomplish this goal is to facilitate

consumer-motivated regulation.

7.2 Standardized Avoided Cost Methodologies

The  guidelines  for  compensation  to  QF’s  as  defined  by  PURPA  allow  the  states  

to choose methods that are consistent with their policy objectives. Consequently, the

choice made by the states has significant implications on the prospects of alternative

generation technologies within their jurisdictions. However, the inputs that

constitute the models for estimation of avoided costs are not transparent, and hence

36

the methods are heterogeneous between, and sometimes within states. In such a

situation, there is a lack of support for long term investment planning on part of the

QF’s.    In  order  to  introduce  certainty,  an  authority  such  as  FERC,  with  the  mandate  of  

ensuring   national   electricity   reliability   and   quality   along   with   PURPA’s   goal   of  

encouraging alternative power producers, should conduct an evaluation of avoided

cost methodologies used across different states and quantify the merits and demerits

thereof. Such an evaluation will be useful in helping states choose the appropriate

methods for measuring avoided costs. Moreover, with the consolidation of multiple

jurisdictions under integrated market places, standardization of avoided cost

calculation methods will lend efficiency to the power market.

Standardization of avoided costs can be approached to some extent by

utilizing   PURPA’s   mandate   guaranteed   purchase   of   power   from   small   power  

producers. Although PURPA specifies the upper limit of such small power producers

at 100 kW, some states have increased this limit to include higher capacity

independent power producers to be eligible for standard purchase contracts, which

are vetted by the respective state regulatory commission, and provide relatively long

term certainty to small power producers. The standard purchase contracts in

Oklahoma are however fixed at 100  kW,  whereas  California  allows  for  QF’s  up  to  20  

MW to be eligible for standard purchase contracts. Similar figures were not available

for   Kansas.   The   recommendation   of   increasing   the   eligibility   criteria   of   QF’s   for  

standard purchase contracts can be taken up with the state regulatory commissions,

in the interest of encouraging small power producers.

7.3 Resource Specific Avoided Costs

Some of the methods of estimating avoided costs discussed above compare the

QF to a different generation asset, from which the utility might have purchased or

generated power in absence of the QF. These assets, categorized as proxies,

surrogates, or peakers, depending upon the method used, are usually either least cost

capacity additions or marginal units that use natural gas. The avoided cost estimates

37

resulting from comparisons of these units with wind farms do not reflect the full

extent of the avoided costs. Comparisons, if any, should be made between units with

similar supply characteristics. In a recent order on California Public Utility

Commission’s   petition 30 , FERC determined that multi-tiered avoided cost rate

structure can be deemed consistent with PURPA’s   requirements.  This   implies   that  

variables specific to a QF, such as capacity, reliability, availability, efficiency,

environmental   performance,   and   fuel   resource   used   can   differentiate   the   QF’s  

avoided   cost   from   other   generation   assets’   avoided   Allowing flexibility in pricing

mechanism will allow to include factors such as benefits of long-term contracts

between utility and QF, location of the QF, and external benefits such as creation of

employment opportunities and less reliance on local natural resources. Effectively,

the avoided cost for a wind energy QF should be compared to the costs of an existing

wind farm, including the non O&M components of the cost.

7.4 Forward Capacity Markets

An argument against addition of more renewable generation to the portfolio

has been the low capacity value that these assets offer, and hence the negative

impacts from a resource adequacy perspective. Moreover, incentives offered to

renewable generation, such as RPS and PTC for wind can sometimes lead to negative

clearing price in the integrated marketplace, and hence impair the ability of

conventional generation plants to recover their costs through the energy market

alone. This might force some of them to early retirement, hence adversely impacting

the resource adequacy of the power market. The Southwest Power Pool maintains

the resource adequacy through a capacity reserve margin, which is fixed at 12%. The

capacity margin can be met either by a particular utility on a standalone basis, or

through a reserve sharing pool.31

30 (FERC, 2010) 31 (Southwest Power Pool, 2011)

38

However, the capacity margin alone does not incentivize the generation

utilities to add more plants to their existing portfolio, as the capacity value in itself is

not monetized. A forward capacity market, such as that at PJM32, will help to maintain

resource adequacy on a forward basis for a defined period of time (three years in

PJM’s  Reliability  Pricing  Model),  by  providing  incentive  to  procure  capacity  for  a  long  

term. Forward capacity markets will offer an additional stream of revenues to

conventional generation assets, reflecting the value of their reliability, and hence will

improve their financial performance by offering stable prices for an extended period

of time. Stakeholders from equipment manufacturers (such as GE), variable power

generators, conventional utilities and SPP should explore the possibility of

implementing a forward capacity market.

7.5 Security Constraint Economic Dispatch

High  wind  speed  cut  out  came  to  our  team’s  attention  during  a  conversation  

with a former director of resource planning. Accordingly, we identified high winds as

a barrier for wind power generation. Mark Ahlstrom of Wind Logics proposed two

recommendations for rectifying the problem of high wind speed cut out. As noted

before, in a high wind scenario, to prevent damage to the equipment, an operator will

need to shut it down or feather the blades. Besides wind scheduling that will give

operators a reasonable amount of time to plan for a scenario of high wind (50-60

mph), Mark discussed how there are turbines in the market with the technology that

can change the forecast of uncertainty. New Turbines will back off even before they

get to that cut off point. With the new technology, individual blades can be turned to

take in less energy and protect it.

As our  recommendation  to  GE,  Mark’s  experience  and  work  with  an  optimizing  

tool that already is being used by SPP is instructive. In his experience, the cut out

problem   is   mostly   a   problem   for   people   who   don’t   really   think   about   the   larger  

39

system but only think about it as a single wind turbine problem. To integrate wind

into the market, it should be forecasted as well as it possibly can; and the forecast

should go in the overall system operational plans, the data unit commitment, and the

real time dispatch of all units in the system. But most importantly, cut off as well as

the other problems associated with wind power go away when using a process called

Security Constraint Economic Dispatch, a process that takes cost and liability when

optimizing a system every 5 minutes to match load. This process takes into account

the whole power system with all its different types of generators and characteristics

(failure modes, lack certainty, etc). So when it is integrated in the system, the process

of Security Constraint Economic Dispatch really nullifies the problems associated

with cut out and other associated problems caused by variability. Therefore, we

believe GE can reduce the barriers associated with variability by informing utilities

that these problems can be nullified by using the tools already in place—primarily

the Security Constraint Economic Dispatch.

7.6 Increased Geographic Network

Recently planned changes to the Southwest Power Pool have opened new

doors for wind growth. One area where the team sees opportunity for GE deals with

future transmission investments and the expansion of the SPP. In 2014, the Upper

Great Plains Region of the Western Area Power Administration was approved to join

the regional transmission organization. This inclusion would stretch   the   SPP’s  

footprint to the Canadian border. We see this as highly beneficial to future wind

growth because of the correlation between its future boundary and the abundance of

wind  resources  in  the  Plains  region  as  well  as  SPP’s  goals  to  develop  its  connected

energy market. The expansion of the RTO combined with the already progressive

actions made to integrate the energy market via the Integrated Marketplace offer a

promising future for wind development.

The expansion of the SPP footprint will promote transmission infrastructure

development, while increasing the interconnectedness of several states. However, the

40

growth of the marketplace will require more advanced infrastructure to balance and

ensure the reliability of the grid. As more wind farms are connected, the variability of

wind will significantly reduce, as abundant wind in one part of the region will be able

to be shared with other areas where wind is scarce. The inclusion of more

stakeholders -- as participants in this marketplace – will further the development of

high-voltage transmissions lines paid for through the Highway/Byway shared-cost

methodology. In a similar way, increased interconnectedness of the marketplace will

enable the SPP to dissipate power in congested areas and deliver wind resources from

their source to their need, reducing integration costs and providing greater incentive

for future wind farms.

Benefits obtained through greater adoption of wind have been shown in a

recent study by the U.S. Energy Information Agency (EIA) analyzing the reduction of

base load capacity due to higher wind generation in the SPP. The graph below shows

the reduction in base load use since 2010.

Figure 1 – September 5, 2013

The reduction in base load use is due to higher volumes of wind energy

generation supplanting generation from traditional base load units. This reduction

effect will be catalytic with the expansion of the SPP RTO, furthering the cost

41

competitiveness and the defensibility of wind as an energy option for resource

planning   decisions.   The   SPP’s   outlook   for   the   Integrated   Marketplace   and   the  

Highway/Byway cost was best summarized by Regional State Committee member

and Arkansas Public Service Commission Chairman Paul  Suskie,  “SPP  needed  a  cost  

allocation policy for transmission projects that not only enhance reliability, but also

have the potential to reduce costs for utilities and their customers. Building new

transmission will bring many benefits, such as reducing  congested  „bottlenecks‟ on

the electric grid, increasing grid reliability and efficiency, and creating jobs during the

construction and operating phases. This Highway/Byway cost sharing methodology

will provide a regional solution for building out the regional electric grid that will

meet  our  needs  into  the  future.”

7.7 Externalities

While  there  isn’t  a  carbon  pricing  system  in  the  US,  it  is  expected  to  see  a  future  

with stricter regulation on carbon emissions. Since utilities are mainly engaged in

long term investment decisions on generating assets, they will make better informed

decision by factoring in the coming tighter regulation of greenhouse gases and

including carbon pricing in its economic analysis.

As regulation gets tighter in cutting carbon emission, it is likely to have carbon

pricing as a regulatory tool in the US. Almost 40 countries and more than 20 cities,

states and provinces already use carbon pricing mechanisms or are planning to

implement them.33 Meanwhile, private sector has become more acceptable to carbon

pricing. And many companies are preparing for tighter regulation by including an

“internal  carbon  price”  in  business  planning.34

A landmark judgment by FERC on petition by California Public Utilities

Commission35 specifies   that   if   an   externality   factor   represents   “real   costs”   for   the  

33 (World Bank, 2015) 34 (CDP, 2013 ) 35 (FERC, 2010)

42

incumbent utility, it may be deemed as a valid avoided cost under PURPA. This implies

that in the event of imposition of external costs associated with the environment, the

avoided cost methodology currently applied by utilities will need to be revised to

regard these external costs as penalties for conventional generation assets, which can

be avoided by renewable energy generation facilities. Subsequently, calculation of

these external costs on a life cycle basis will yield a more scientifically accurate

estimate of the impacts on the environment, integrating emission from upstream to

downstream operations.

Currently, neither Westar nor OG&E have considered the possibility of

pricing carbon or other pollutants such as SOX, NOX, particulate matter, etc. when

comparing renewable with fossil fuel generating assets. However, once they make an

investment decision today, they will have an asset that lasts for decades. Thus, it is

important to make sure that the portfolio of generating assets designed today could

comply with the tight regulation on carbon emission.

Adding carbon pricing in economic analysis will allow utilities to better evaluate

the comparative advantage of renewable and fossil fuel generating assets, and get

better prepared for future challenges in greenhouse gas regulation.

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APPENDIX

SPP’s  Reliability  Impact  Assessment  of  EPA’s  Proposed  CPP: http://www.spp.org/publications/CPP%20Reliability%20Analysis%20Results%20Final%20Version.pdf Kansas Corporation Commission Report on Electricity Demand and Supply, 2014: http://www.kcc.state.ks.us/pi/2015_electric_supply_and_demand_report.pdf

EIA Levelized Cost and Levelized Avoided Cost of New Generation Resources,

2014:

http://www.eia.gov/forecasts/aeo/pdf/electricity_generation.pdf

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Bibliography 1. American Wind Energy Association. (2015). Wind Energy Facts at a Glance.

(Retrieved from http://www.awea.org/Resources/Content.aspx?ItemNumber=5059)

2. Argus. (2015, April 8). Analysis: SPP sees adequate summer reserve margin.

(Retrieved from http://www.argusmedia.com/News/Article?id=1019635)

3. CDP. (2013 , December). Use of internal carbon price by companies as incentive and strategic planning tool. (Retrieved from https://www.cdp.net/CDPResults/companies-carbon-pricing-2013.pdf)

4. EIA. (2011, May 13). Electricity resource planners credit only a fraction of

potential wind capacity. (Retrieved from http://www.eia.gov/todayinenergy/detail.cfm?id=1370)

5. EIA. (2014, April). Levelized Cost and Levelized Avoided Cost of New

Generation Resources in the Annual Energy Outlook 2014. (Retrieved from http://www.eia.gov/forecasts/aeo/pdf/electricity_generation.pdf)

6. Elefant, C. (2011). Reviving PURPA's Purpose . (Law Offices of Carolyn Elefant)

(Retrieved from http://www.recycled-energy.com/images/uploads/Reviving-PURPA.pdf)

7. FERC. (2010, October 21). 133 FERC ¶ 61,059. (Retrieved from

http://www.ferc.gov/whats-new/comm-meet/2010/102110/E-2.pdf)

8. Georgia Public Service Commission. (2004). Docket No. 4822-U. (Retrieved from http://www.psc.state.ga.us/factsv2/Docket.aspx?docketNumber=36499)

9. Kansas Corporation Commission. (2015). Report on Electric Supply and

Demand. (Retrieved from http://www.kcc.state.ks.us/pi/2015_electric_supply_and_demand_report.pdf)

10. Milligan, M., & Porter, K. (2006). The Capacity Value of Wind in the United

States: Methods and Implementation. The Electricity Journal , 19 (2).

11. Monies, P. (2015, April 2). Oklahoma Gas and Electric Co. plans to pass on $4.3 million wind legal settlement to customers. (Retrieved from http://newsok.com/oklahoma-gas-and-electric-co.-plans-to-pass-on-4.3-million-wind-legal-settlement-to-customers/article/5406550/?page=1)

45

12. National Conference of State Legislatures. (2015, February 19). State Renewable Portfolio Standards and Goals. (Retrieved from http://www.ncsl.org/research/energy/renewable-portfolio-standards.aspx#ok)

13. Nickell, L. (2014). A Nickell for Your Thoughts. (Retrieved from

http://www.spp.org/publications/Resource%20Adequacy%20in%20SPP%20Part%201%20Blog.pdf)

14. OG&E. (2014). 2014 Annual Report. OG&E.

15. OG&E. (2014). CDP 2014 Investor CDP 2014 Information Request. (Retrieved

from https://oge.com/wps/wcm/connect/d907496d-94c8-47d8-9cf6-b6e11c88751f/140529+2014+OGE+CDP+Response.pdf?MOD=AJPERES&CACHEID=d907496d-94c8-47d8-9cf6-b6e11c88751f)

16. OG&E. (2014). OG&E Integrated Resource Plan (IRP). (Retrieved from

https://oge.com/wps/wcm/connect/342cf742-9bb6-48f1-aaa9-34a4174b8c16/2014+IRP+-+Oklahoma+Report.pdf?MOD=AJPERES&CACHEID=342cf742-9bb6-48f1-aaa9-34a4174b8c16)

17. Pennel, E. (2010, April 19). SPP Proposes New Cost Sharing Method for

Expanding the Regional Electric Transmission Grid. (Retrieved from http://www.spp.org/publications/spp_proposes_new_cost_sharing_method_for_transmission.pdf)

18. Porter, K., Fink, S., Buckley, M., Rogers, J., & Hodge, B. (2013, March). A Review

of Variable Generation Integration Charges. Retrieved from National Renewable Energy Laboratory (Retrieved from http://www.nrel.gov/docs/fy13osti/57583.pdf)

19. Southwest Power Pool CAWG. (2014, April 17). CAWG Agenda & Background

Material. (Retrieved from http://www.spp.org/section.asp?group=381&pageID=27)

20. Southwest Power Pool CAWG. (2014, June). CAWG Minutes & Attachments.

(Retrieved from http://www.spp.org/section.asp?group=381&pageID=27)

21. Southwest Power Pool Generation Working Group . (2004, September 29). Wind Power Capacity Accreditation White Paper. (Retrieved from http://www.spp.org/publications/WindWhite04Sept8_rev5.pdf)

22. Southwest Power Pool. (2011, January). Southwest Power Pool Criteria: Latest

Revision. (Retrieved from

46

http://www.spp.org/publications/Criteria%20and%20Appendices%20July%2025,%202011.pdf)

23. Southwest Power Pool. (2014, October 8). SPP’S   RELIABILITY   IMPACT ASSESSMENT  OF  THE  EPA’S  PROPOSED  CLEAN  POWER  PLAN. (Retrieved from http://www.spp.org/publications/CPP%20Reliability%20Analysis%20Results%20Final%20Version.pdf )

24. Westar Energy. (2013). 2013 Annual Report. (Retrieved from

http://www.annualreports.com/Click/3744?_SID_=20150512175718-a4667f0b40ee9ec677a46b05b23f305e)

25. Westar Energy. (2014). 2014 Annual Report on Form 10K. (Retrieved from

http://phx.corporate-ir.net/External.File?item=UGFyZW50SUQ9Mjc0NDkxfENoaWxkSUQ9LTF8VHlwZT0z&t=1)

26. Westar Energy. (2014, October 30). Prairie  Wind  transmission’s  high-capacity

transmission line completed ahead of schedule, more than $60 million under budget. (Retrieved from https://www.westarenergy.com/content/about-us/news/2014-news-releases/pwt-energized)

27. World Bank. (2015). What Is Carbon Pricing? (Retrieved from

http://www.worldbank.org/en/programs/pricing-carbon)