3. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.
43. 43
APPENDIX
SPP’s
Reliability
Impact
Assessment
of
EPA’s
Proposed
CPP:
http://www.spp.org/publications/CPP%20Reliability%20Analysis%20Results%20
Final%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
44. 44
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