IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 4, NOVEMBER 2008
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A Comprehensive Assessment of the Evolution
of Financial Transmission Rights
V. Sarkar, Student Member, IEEE, and S. A. Khaparde, Senior Member, IEEE
Abstract—Financial transmission rights (FTRs) are complementary to the locational marginal pricing of energy. The basic aim
of the FTR mechanism is to guard forward contracts from uncertain congestion charges. FTRs are also useful to individual generators and loads for selling and buying power, respectively, at the
prices of other locations. The concept has evolved, encompassing
many features such as a simultaneous feasibility test, various ways
to conduct auctions and allocations and secondary trading. FTRs
also have a close relation to market power and transmission investment. This paper reviews most of the landmark research papers
on the evolution of the FTR concept. It reports a comprehensive
assessment of various facets of FTRs and allied issues. Financial
transmission rights and flowgate rights (FGRs) are compared. The
concept of long-term FTRs is discussed. The paper also touches
upon future proposals in this area.
Index Terms—Allocation, auction, auction revenue right, financial transmission right, flowgate right, market power, obligation,
option, revenue adequacy, secondary trading, transmission investment.
NOMENCLATURE:
Price of an FTR of th type.
Path-branch sensitivity factor (or power transfer
distribution factor), relating the path of the th
obligation FTR to a certain line, for a particular
network topology.
Path-branch sensitivity factor, relating the path of
the th option FTR to a certain line, for a particular
network topology.
Total number of offers (from generators) and
bids (from loads and bilateral transactions) in the
energy market.
LMP at the th price node.
LMP at the th price node minus LMP at the th
price node.
Number of rows in
.
Number of rows in .
Total number of network capacity constraints in
the day-ahead dispatch problem.
Bid price related to the th FTR bid.
Manuscript received May 22, 2007; revised June 08, 2008. First published
August 29, 2008; current version published October 22, 2008. Paper no.
TPWRS-00367-2007.
The authors are with the Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India (e-mail:
[email protected]; [email protected]).
Digital Object Identifier 10.1109/TPWRS.2008.2002182
Column vector containing the MW amounts of the
base option FTRs.
Column vector containing the MW amounts of the
base obligation FTRs.
diagonal matrix with
equals to
.
constant matrix containing the loading
factors of requested FTRs.
constant matrix containing the loading
factors of base FTRs.
MW amount of an obligation FTR.
MW amount of an option FTR.
MW amount of a physical transaction.
Column vector containing the offer and bid
variables in the energy market.
Parameter vector (column) representing the net
nodal inelastic loads in the day-ahead market.
Vector (column) of net nodal injections caused by
the physical equivalents of active FTRs.
Variable vector (column) signifying the net nodal
injections caused by .
Upper limit on .
constant matrix that converts nodal
injections into line flows.
Variable vector (column) signifying the awarded
amounts towards all the FTR bids.
Variable vector (column) signifying the awarded
amounts towards the obligation FTR bids.
Variable vector (column) signifying the awarded
amounts towards the option FTR bids.
Parameter vector (column) representing the base
amounts of all types of FTRs involved in the
auction.
Upper limit on .
Parameter vector (column) representing the
pre-existing (i.e., existing before the auction)
amounts of all types of FTRs involved in the
auction.
Column vector containing the line capacities
available in the day-ahead market.
The forward capacity (as available in the day-ahead
market) of a certain line.
The reverse capacity (as available in the day-ahead
market) of a certain line.
0885-8950/$25.00 © 2008 IEEE
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IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 4, NOVEMBER 2008
Total number of nodes.
vector of all zeros.
vector of all ones.
Value of the scalar or vector variable
at the
solution point of the power dispatch problem.
Value of the scalar or vector variable (.) at the
solution point of the FTR auction problem.
Convex social-welfare function.
Optimal social-welfare as the function of
.
Objective function of the FTR auction problem.
Optimal value of
as the function of
.
I. INTRODUCTION
ONGESTION management in restructured power systems can be carried out efficiently through locational
marginal price (LMP)-based energy pricing [1]–[7]. The basis
of the LMP mechanism is the theory of electricity spot pricing
by Schweppe et al. [8]. Under the locational marginal pricing
approach, the independent system operator (ISO) calculates
power dispatch schedules by maximizing the social welfare
function within the available network capacity. The price of
energy at a location is determined by the rate of decrease of
optimal social welfare with respect to the fixed load increase at
that location. These prices are the locational marginal prices.
Locational marginal pricing can be carried out either on a
nodal basis or on a zonal basis. However, one major problem of
zonal pricing is accurately finding the zonal sensitivity factors
[9]. Thus, each pool participant (individual generator or load)
has to pay (load) or is paid (generator) the LMP at its location, whereas each bilateral contract has to pay a congestion
charge (plus a loss charge if the system modeled in the LMP
calculation is lossy) according to the LMP difference between
its sink and source locations. The net collection (which is
generally nonnegative) of the ISO is termed the merchandizing
surplus. This kind of energy pricing can generate useful price
signals that assist in identifying suitable locations for building
new generators, load centers, and transmission facilities. For
instance, if the LMP at a certain location consistently displays
a higher value, it provides an initial indication that this location may be a suitable place for building new generators.
At the same time, by penalizing each bilateral contract with
a location-dependent network usage charge, strong financial
incentive is applied, making it account for the congestion in
the transmission network. The pool prices also recognize the
system limits. The possibility of administrative transmission
load relief (TLR) thus becomes very small. Moreover, due to
the auction-based allocation of transmission capacity, relative
needs of the market players for the transmission usage are
suitably assessed.
Although the LMP mechanism has an appeal for efficient congestion management, this mechanism inherently creates price
risk (in the form of unpredictable congestion charges), especially for long-term forward contracts. This may hamper longterm power trading. However, long-term (or, at least, medium-
C
term) forward contracts are desirable to increase competition in
the market as they play an important role in curbing the market
power of generators [10]–[12]. Therefore, the LMP mechanism
also needs the support of some complementary methodology or
tool to guard the long- and medium-term forward contracts from
congestion price risk.
Financial transmission rights (FTRs) are risk-hedging instruments designed mainly with the aim to minimize the congestion price risk for forward contracts [1], [13], and [14]. FTRs
are now successfully implemented in many power markets such
as PJM, New York, New England, and others [15]–[22]. Similarly to the physical transmission rights (PTRs), FTRs also define transmission property rights, but in financial form. Under
PTR methodology, a market player must have sufficient transmission reservation to get his transaction scheduled without any
network usage charge. A PTR is an option (i.e., the owner may
or may not use it) transmission right that may be either firm or
of use it or lose it type. Unlike PTRs, FTRs are completely financial in nature and do not interfere with the power scheduling
process. Basically, an FTR provides its owner with some financial support to pay the congestion price that he is charged in
the day-ahead energy market for his transaction. An individual
generator or load can also buy an FTR to adjust its sale or buy
price, respectively, to the LMP of a different location. For this
purpose, a generator needs to buy an FTR “from” its location,
whereas a load needs to buy an FTR “to” its location.
The basic parameters defining an FTR are a source, a sink, a
validity period, and a MW amount. The source/sink of an FTR
need not be a single bus. It could be a load zone, or a hub, or an
interface for which an LMP is calculated and posted (i.e., it can
be any price node). For instance, in PJM, a network transmission service customer [23] can ask the ISO for an FTR from a
generator node to a load zone [17]. Moreover, in the case where
energy prices are calculated on a zonal basis [24] rather than
a nodal basis, FTRs are to be issued between individual zones
rather than between nodes. Under a hybrid pricing approach, in
which some energy prices are calculated at the node level and
others at the zone level, FTRs are available even between a node
and a zone.
Each FTR is assigned a monetary value for each hour depending upon the day-ahead (or real-time if the day-ahead
market is absent) LMP outcomes for that hour (if network loss
is also considered in the dispatch model, only the congestion
components of LMPs are to be used for calculating the hourly
values of FTRs [22]). The FTR owners are paid by the ISO
according to the hourly values of their FTRs. However, the
settlement can be over multiple hours at a time.
The FTR mechanism has evolved with success since its inception in 1992. The motivation of this paper is to acquaint
the reader with a comprehensive assessment of the evolution of
the FTR mechanism. An attempt is made to summarize all the
salient features of this mechanism in a comprehensible format.
The contribution of the paper is to provide insights into the
subtle and intricate aspects of the FTR evolution from various
perspectives. Later developments which stem from the need for
more flexible FTRs are also addressed in an integrated fashion.
The rest of the paper is organized as follows: The risk hedging
functionality of FTRs is described in Section II. The revenue
SARKAR AND KHAPARDE: COMPREHENSIVE ASSESSMENT OF THE EVOLUTION OF FTRS
adequacy issue and the concept of simultaneous feasibility test
are discussed in Section III. In Section IV, the FTR issuance
processes are described in detail. Some current practices and
proposals for the treatment of the revenue shortfall problem
are discussed in Section V. The scope of the secondary trading
of FTRs is discussed in Section VI. A comparison between financial transmission right and flowgate right is carried out in
Section VII. The interrelationship between financial transmission right and market power is explained in Section VIII. A
small discussion regarding how FTRs can incentivize private
transmission investments is presented in Section IX. The concepts of long-term FTR, contingent transmission right, and locational FTR are outlined in Section X. Finally, the paper is concluded in Section XI.
II. RISK HEDGING FUNCTIONALITY OF FINANCIAL
TRANSMISSION RIGHTS
With regard to the hedging adjustability, currently exercised
FTRs can be classified into two categories: options and obligations. An obligation FTR is basically a fixed hedge FTR that always remains active. In contrast, an option FTR is an adjustable
hedge FTR that becomes active only when congestion occurs
in the forward direction. Irrespective of whether it is an option
or an obligation, the value of an active FTR is always given by
the product of its MW amount and the LMP differential on its
path. Note that in the FTR context, a path is simply defined
by a source-sink pair rather than an alternating series of lines
and nodes. The value of an inactive FTR automatically becomes
zero. Therefore, an obligation FTR may incur negative values at
certain hours owing to the occurrence of congestion in the reverse direction, whereas the value of an option FTR is always
nonnegative. The ability to implement transmission rights as
obligations is one of the major advantages of FTRs over PTRs.
The risk hedging functionality of FTRs is described below.
At a certain hour, the target payment (TP) towards the portMW obligation FTR and a
MW option FTR
folio of a
is given by
on Path
if
if
(1)
Now, in this hour, the owner of this FTR portfolio has a physical
transaction of
MW on the same path. His payment for this
transaction towards network congestion is given by
(2)
Therefore, the net payment made by the player for this transaction and FTR combination is given by
if
if
(3)
From this expression of net payment, the following risk hedging
functionality of the above FTR portfolio can be seen.
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, the player always gets
1) If
benefit from (or, at least, never loses money due to) network congestion. The player collects a net nonnegative
if
, and
payment of
if
. Therefore, he does not
of
see any price risk for this transaction.
, the actual transaction is, in effect,
2) If
divided into the following three parts:
MW on Path
.
a) A transaction of
MW on Path
.
b) A transaction of
MW on Path
.
c) A transaction of
The first of the above transactions is always charged with
the LMP difference between the sink and source locations.
The second transaction is charged with this LMP difference
only when the sink LMP becomes lower than the source
LMP. Finally, the third transaction is never charged with
the LMP difference. The above set of transactions is equivalent to the original transaction and FTR combination in
the sense that for both cases the net payment to the ISO remains the same. Thus, it is clear that the player never loses
money for the second and third transactions. Moreover, the
in case
second transaction gives him a benefit of
is negative. However, the second part does not give
any benefit when the player has to make a positive pay. Therefore,
ment for the first part, i.e., when
the first part remains completely risky for the player, but
he observes no price risk in the second and third parts.
, the obligation FTR itself creates a price
3) If
risk for its owner in that the player will have to make a net
on the occurrence
positive payment of
of congestion in the reverse direction (i.e., when
).
It can be seen that only a fixed physical transaction can be
fully hedged by an obligation FTR alone. This transaction must
be of the same MW amount as that of the obligation FTR and
must be on the same path. That is why it is called a fixed hedge
FTR. Even if the MW amount of this transaction falls below the
MW amount of the respective obligation FTR, the market player
has risks having to make a net positive payment under network
congestion. This price risk is generated by the obligation FTR
itself and, therefore, is termed the downside risk. In case the
price risk is due to the physical transaction, it is called the upside
risk. For a case in which the transaction amount is not fixed, both
the upside risk and the downside risk can be avoided by using
a portfolio of an obligation FTR and an option FTR instead of
only an obligation FTR. This is because an obligation-option
combination is able to remove risk completely for a band of
transactions. The MW amount of the obligation FTR defines the
lower boundary of this band, and its upper boundary is indicated
by the total portfolio amount. Therefore, the option FTR allows
its owner to adjust his hedge position, or, in other words, this
FTR provides to its owner an adjustable hedge.
Although option FTRs can provide more benefit than do obligation FTRs, there is a certain trade-off that often makes obligations preferable to options, and this is explained in Section IV.
Moreover, the above discussion on risk hedging is based upon
the assumption that the direction of congestion is quite uncertain on a path. In a real system, there may be certain paths where
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the probability of congestion in the reverse direction is very low,
and for those paths option FTRs are redundant. This is because
the per MW value of an obligation FTR will most of the time be
the same as that of an option FTR on such a path.
One point that should be explicitly mentioned here is that
the discussion above basically explains how FTRs perform risk
hedging for which, actually, they have been designed. As far
as the settlement is concerned, each obligation or option FTR is
settled individually and without any bearing on the actual energy
schedules. Therefore, a market player does not need to have a
transaction on the path of his FTR to get the value of this FTR. In
practice even, a market player may sometimes choose to hedge
the congestion price risk on a certain path by means of an FTR
on a different path. However, upon such a decision, the market
player becomes exposed to the risk of the difference between
the LMP differentials on these paths.
III. SIMULTANEOUS FEASIBILITY TEST
AND REVENUE ADEQUACY
Revenue adequacy is an important consideration in the issuance of financial transmission rights. There should be enough
collection from the network congestion to pay full FTR credits.
Revenue adequacy can be ensured through a mechanism called
simultaneous feasibility test (SFT) [10], [13], [17], and [25],
which can be stated as: If the network capacity available in a
day-ahead market is sufficient to accommodate the power flow
caused by the physical equivalents of active FTRs at the relevant hour, the congestion collection (day-ahead) must be greater
than or equal to the total FTR target payment at this hour. Ideally, the network model to be used in the SFT should be the
same as that used for power scheduling. The relationship between simultaneous feasibility and revenue adequacy is established below.
The day-ahead dispatch problem can be mathematically formulated as follows:
ward and reverse directions assigned to the lines. The elements
are the line loading limits as available in day-ahead
of
market. Constraint (5) is the power balance constraint and other
constraints are self-explanatory. A numerical illustration of the
power dispatch problem can be found in [26]. However, the Lagrangian of this optimization problem can be written as,
(9)
where , , ,
and
are the vectors of Lagrangian multipliers. The LMP at a node is defined as the rate of decrease of
optimal social welfare with respect to the increase of fixed (or
inelastic) load at that node. Therefore, from the theory of sensitivity analysis [27]
(10)
Each pool contract is settled according to these LMP values. The
congestion price to be paid by a bilateral contract is given by
the rate of decrease of optimal social welfare with respect to the
increase of the fixed transaction amount on the respective path.
Therefore, this price is equal to the LMP difference between the
corresponding locations. The net congestion collection (NCC)
of the ISO is given by the sum of the payments made by the
bilateral contracts, plus the sum of the payments made by the
loads, minus the sum of the payments made to the generators,
i.e.,
(11)
According to complementary slackness condition of KKT rule
[27]
s.t.
(12)
(4)
Therefore, the expression for NCC can be finally written as
(5)
(13)
(6)
(7)
(8)
Let the net injection pattern
caused by the physical equivalents of active FTRs results in a feasible power flow condition
within the network capacity that is available in the above energy
market. Therefore
where
(14)
if
is a generation at Node
if
is a load at Node
if
is not related to Node
Constraints (4) are the network capacity constraints. The matrix
converts nodal injections into the line flows both for the for-
The total target payment (TTP) towards these FTRs can be calculated as
(15)
SARKAR AND KHAPARDE: COMPREHENSIVE ASSESSMENT OF THE EVOLUTION OF FTRS
It should be mentioned again that irrespective of whether it is
an obligation or an option, the target payment towards an active
FTR is always given by the product of its MW amount and the
LMP differential on its path. Finally, the surplus amount (SA)
of the congestion collection is given by
(16)
Equation (16), in conjunction with (14) and the nonnegativity
condition of , proves that the surplus amount of the day-ahead
congestion collection must be nonnegative if the physical
equivalents of the active FTRs are simultaneously feasible.
Note that such a relationship between simultaneous feasibility
and revenue adequacy can be proven only for a linear power
flow model, where each constrained network quantity can be
expressed as a linear function of nodal injections [as in (4)]. A
linear power flow model may be either a linearized ac power
flow model or a dc power flow model. It was argued in [13]
that the above relationship between the simultaneous feasibility
of FTRs and revenue adequacy equally holds, even for an
ac power flow model (which is nonlinear and nonconvex in
nature). Currently, NYISO is the only market that employs this
type of power flow model to perform power dispatch calculation and SFT. However, the proof provided in [13] assumes
that in the dispatch problem, the injection at a node never hits
its lower or upper limit. This may not be a valid assumption,
since at certain hours, the injection at a node may touch a limit.
More prominently, if the load at a certain node is inelastic,
the injection at this node always remains at the limit. This is
because the upper and lower limits for a variable representing
an inelastic load must be the same. In reality, an SFT based on
an ac power flow model cannot guarantee revenue adequacy
[28].
In the above derivation, a lossless power dispatch model has
been considered. It should be mentioned that FTRs are able to
provide hedges only against network congestion. Still no revenue adequacy test model is available to support loss-hedging
(i.e., providing hedges against both network congestion and
loss) FTRs. In the case in which network loss is also considered in the power dispatch model, each LMP is divided into
energy, congestion and loss components, and the congestion
components of LMPs are used to calculate the hourly values
of FTRs. The total collection of the ISO is also accordingly
divided in a net congestion collection and a net loss collection.
As before, the payments towards FTRs are made from the fund
of net congestion collection. The power dispatch problem still
employs a lossless power flow model for the calculation of line
flows, but some additional loads are created at the system nodes
to represent network loss [2]. As before, revenue adequate
congestion collection can be ensured by testing simultaneous
feasibility of the active FTRs on this lossless power flow model.
IV. FTR ISSUANCE PROCESS
FTRs are issued by the ISO by means of auction and/or allocation. There may be different time horizons for the issuance
of FTRs. As an example, FTRs are auctioned both annually and
monthly in the PJM market.
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A. FTR Auction
The FTR auction is basically a central mechanism by which
the requirements of the participating market players are jointly
assessed, compared, and then fulfilled to the best possible extent. In general, any market player can participate in an auction. First introduced in 1999 by NYISO, the auction mechanism is currently in practice in PJM, NYISO, ISO-NE, MISO,
and CAISO. The different aspects of the FTR auction process
are discussed below.
1) Participation Types: Market players can participate in an
FTR auction mainly in the following four ways.
Self-scheduling: In this category of participation, a market
player submits a price-insensitive FTR request to the ISO,
i.e., the player is ready to spend any amount of money in
order to procure his required FTR.
Buy bid: In this category of participation, a market player
requests to the ISO for an FTR along with specifying the
maximum price he is willing to pay for this FTR.
Surrendering: In this category of participation, a market
player returns a portion of his current FTR to the ISO.
The player is ready to accept any payment (even negative
payment) for the returned FTR.
Sale offer: In this category of participation, a market player
offers a portion of his current FTR for sale, while specifying the minimum sale price. A sale offer can be thought
of as a combination of a buy bid and a surrender. For instance, a sale offer of 100 MW FTR at $20/MW is equivalent to the combined participation of a buy bid for 100 MW
FTR at $20/MW and a surrender of 100 MW FTR.
There is also a proposal for the following type of participation
[29].
Conversion bid: In this category of participation, a market
player requests to the ISO to convert a portion of his current option or obligation FTR into an obligation or option
FTR, respectively. The player also specifies the maximum
price (nonpositive for option-to-obligation conversion) he
wishes to pay for this conversion.
2) Auction Formulation: Each FTR auction is cleared
through an optimization calculation. A generalized auction
formulation for the clearance of obligation FTRs can be found
in [30], whereas [31] and [32] explain how to modify this
formulation when option FTRs are also included in the auction.
The objective function (which is similar to the social welfare
function in the energy market) of the auction optimization
problem is the negated quote-based sum of the issued amounts
towards all the FTR bids, and the function should be minimized.
The cleared amount towards each bid must lie within its lower
(which is zero) and upper (which is the requested amount)
limits. In order to ensure revenue adequacy, the simultaneous
feasibility condition (derived from the concept of SFT) must
be satisfied while issuing FTRs. In case all the FTRs are issued
for a same set of hours and conversion bids are absent, the
simultaneous feasibility condition can be stated as: The physical equivalent of each possible active-inactive combination
of individual FTRs (base as well as requested) must result in
a feasible power flow condition for each possible topological
scenario of the network. Here, the base FTRs are those entities
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whose quantity values are considered to be constants during
the auction calculation. As an example, the FTR awarded to
a market participant in an annual auction is to be considered
as a base FTR in the subsequent monthly auctions. Similarly,
a self-scheduled FTR is a base entity in an auction. FTR
surrenders are also considered through base case modeling by
subtracting the surrendered amounts from the original FTR
amounts.
Note that we have to consider different active-inactive combinations of individual FTRs. This is because an option FTR
becomes inactive if congestion occurs in the reverse direction.
Similarly, different topological conditions of the network have
” contingencies into acto be considered in order to take “
count. Thus, using dc power flow model, the simultaneous feasibility constraints for a certain line under a particular network
topology can be written as
(17)
The vectors ,
,
and
contain the loading factors (i.e., coefficient factors) of the different FTR terms in the
,
above simultaneous feasibility constraints. Here,
, and
. The scaling
factors and
vary between 0 and 1. The value of a scalling
factor would be 1 in case the corresponding constraint is already
overloaded or 100% of the available network capacity (i.e., capacity that is available for awarding new FTRs) is offered in the
auction. However, in the annual auction of ISO-NE, only 50%
of the available network capacity is offered to the auction participants. In this case, both and are less than 1. The formulation of the simultaneous feasibility constraints is numerically
illustrated in [32].
Note that, similarly to PTRs, counterflows caused by the
physical equivalents of option FTRs are also not considered in
the line flow constraints. In order to consider conversion bids
in an FTR auction, only a small amendment is required to the
above formulation. A conversion bid can be considered as the
buy bid for a special type of FTR, termed a conversion FTR.
The bid for a conversion FTR is to be treated in the same way
as an obligation or option FTR bid is done. The upper limit on
a conversion FTR variable is given by the requested conversion
amount and the lower limit is zero. The loading factor of a
conversion FTR term in a simultaneous feasibility constraint
can be calculated simply by subtracting the coefficient factor of
the original FTR from that of the new FTR. For example, the
loading factors of an obligation FTR and an option FTR on Path
and 0, respectively, in a simultaneous feasibility
1–2 are
constraint. The loading factor of an obligation-to-option conversion FTR on Path 1–2 in the given simultaneous feasibility
. Simconstraint can be then calculated as
ilarly, the loading factor of an option-to-obligation conversion
. Next, consider
FTR can be calculated as
that a market player initially (i.e., before the auction) had an
obligation FTR of 50 MW on Path 1–2. Upon a conversion
request, the market player is awarded an obligation-to-option
conversion FTR of 20 MW on the same path in the auction.
At the end of this auction, in essence, the player retains an
obligation FTR of 30 MW and an option FTR of 20 MW on
Path 1–2.
3) Auction Pricing: Financial transmission rights are priced
following the same marginal pricing rule as that for the pricing
of energy [17]. The auction optimization problem can be compactly formulated as
s.t.
(18)
(19)
(20)
Here, the vector
contains all the requested obligation, option and converted FTR terms. Constraints (18) are the simultaneous feasibility constraints. and contain the loading factors of requested and base FTR terms, respectively, in simultavector of scaling
neous feasibility constraints. is the
factors. The network capacity offered in this auction is given
, whereas
indicates the total
by
network capacity available for awarding new FTRs. Now, the
Lagrangian of the above optimization problem can be written
as
(21)
The price
as
of an FTR similar to
can be calculated
(22)
In general, two FTRs are said to be similar (or of the same type)
if they have the same loading factor in any simultaneous feasibility constraint. Therefore, according to (22), the price of an
FTR can be simply calculated by taking the sum of the products
of its loading factor and constraint shadow price over all the simultaneous feasibility constraints. The auction participant pays
or is paid this price depending upon whether this FTR is issued
or bought back, respectively, by the ISO.
The FTR prices exhibit the following properties.
• Total collection from an FTR auction must be nonnegative
.
if
• In the case an FTR bid is fully or partially selected, the
price to be paid to the ISO for this FTR must be lower than
or equal to its bid price.
• In the case an FTR offer is fully or partially accepted, the
price to be paid by the ISO for this FTR must be higher
than or equal to its offer price.
• An FTR bid would be fully selected if its bid price is higher
than the clearing price of a similar FTR.
• An FTR offer would be fully accepted if its offer price is
lower than the clearing price of a similar FTR.
SARKAR AND KHAPARDE: COMPREHENSIVE ASSESSMENT OF THE EVOLUTION OF FTRS
It is beyond the scope of this paper to provide the mathematical proofs of these properties. Furthermore, obligation FTRs
are, in general, cheaper than option FTRs. This is because [as
obvious from (17)] the loading effect of (i.e., capacity consumed
by) an option FTR on any simultaneous feasibility constraint
cannot be lower than that of the obligation FTR with the same
parameters.
4) Time Differentiation of FTR Products: In order to track
the time variations (seasonal, weekly, or daily) of load, financial transmission rights are generally issued for different time
intervals over any time horizon. For example, separate FTRs are
issued for on-peak hours and off-peak hours in the PJM market
[17]. The PJM market also issues multi-interval FTRs with 24-h
validity within a day. A multi-interval FTR basically spans two
or more individual time intervals, whereas a single-interval FTR
remains valid only for the hours of a particular interval. In the
absence of multi-interval FTRs, an independent auction can be
conducted for each individual interval. However, if multi-interval provision is also included, the auction has to be cleared
through a joint optimization calculation accounting for all the
time intervals simultaneously. There must be a separate set of
simultaneous feasibility constraints for each individual time interval. The buyer of a single-interval FTR has to pay the price
for the corresponding interval only. However, the price to be
paid for a multi-interval FTR is the sum of the prices of the individual intervals spanned by this FTR [15].
5) Multi-Round Auction: Multi-round auctions are becoming
increasingly popular. For instance, the annual auction in the
PJM is conducted in four rounds [17]. In each round, a quarter of
the available network capacity (i.e., available for the auction as
a whole), plus any capacity not awarded in the previous round,
is offered to the auction participants. The results of a round are
published before the next round begins. Any FTR awarded in a
certain round can be offered for sale in subsequent rounds. The
main motivation behind the multi-round approach is to make the
auction process more flexible and competitive. This gives both
the winners and losers the opportunity to revise their bids and
try again following the result of an auction round [29].
B. FTR Allocation
Unlike an FTR auction, FTR allocation is not a bid-based
mechanism. Therefore, no market-based measure is associated
with the FTR allocation process as to the relative needs of the
participating market players. As a result, FTR allocation is generally kept restricted to the firm transmission customers only.
Furthermore, as option FTRs consume more network capacity
than do obligation FTRs, FTRs of the former type are generally
not issued via allocation. Different measures in different markets exist for the allocation of FTRs, such as existing transmission reservations, past transmission usages and load ratio shares
[17], [22], and [33]. FTR allocation can be carried out either on
a first-come-first-serve basis or through a joint clearance. There
are two alternative approaches for allocating FTRs, and these
are discussed below.
1) Direct Allocation: In this approach, an eligible market
player is awarded a firm FTR quantity completely free of cost.
Direct allocation of FTRs is currently carried out in MISO,
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NYISO and CAISO [22], [33], and [34], and was formerly in
practice in the PJM market. The same simultaneous feasibility
condition as described in Section IV-A2 should again be satisfied when allocating FTRs directly. In order to enhance the
retail-side competition, directly allocated FTRs are reassigned
among the load serving entities (LSEs) on a daily basis following the movement of retail customers [33]. This reassignment is realized by assigning counterflow FTRs to the loadlosing LSEs. A counterflow FTR is basically an obligation FTR
that is assigned to a certain party in order to compensate the
power flow caused by the FTR assigned to another party [33]
and [35].
2) Auction Revenue Right: Auction revenue right (ARR) is
a mechanism through which the proceeds from an FTR auction
are distributed among the firm transmission customers. For instance, in the PJM [17], ARR mechanism is used to distribute
the annual auction collection among the firm point-to-point and
network service customers. Each ARR is defined between a certain source-sink pair and for a certain MW amount. The ARRs
issued in the PJM market are all obligations, whereas only option ARRs are issued by the ISO-NE [17] and [33]. Similar to
FTRs, ARRs can also be time-differentiated (such as on-peak
ARRs, off-peak ARRs, and 24-h ARRs). The value of an ARR is
calculated in the same way as the value of an FTR is calculated.
Here, the term “LMP difference” indicates the obligation FTR
price on the ARR path for the relevant time interval. If the FTR
auction is multi-round, the weighted average of the LMP differences from all the rounds is used to calculate the value of an
ARR. The ratio of the weight factors should be the same as that
of the basic network capacities offered in the individual rounds.
Basic network capacity means the total network capacity that is
offered in a round minus the capacity that is carried over from
the previous round. The total network capacity, offered in the
auction as a whole, is given by the sum of the basic network capacities offered in all the rounds.
In order to ensure revenue adequate auction collection, simultaneous feasibility must be checked while issuing ARRs, i.e., the
physical equivalent of each possible active-inactive combination
of ARRs issued for any time interval should collectively result
in a feasible power flow condition within the network capacity
offered in the corresponding FTR auction. Although ISO-NE
offers only option ARRs, all ARRs are considered to be obligations in the SFT model, and their MW amounts are adjusted
later depending upon the price outcomes of the corresponding
FTR auction. However, in case an ARR owner is paid the full
value of his ARR, this revenue completely neutralizes the payment (plus giving him some additional benefit if it is an option)
that he has to make for getting an obligation FTR of the same
MW amount on the same path, i.e., ARR mechanism is, in effect, an indirect procedure for allocating FTRs. The PJM market
offers an additional flexibility to ARR owners, which is to convert their ARRs directly into FTRs. Similar to directly allocated
FTRs, ARRs also follow the shift of loads among the LSEs.
It is often argued that the ARR mechanism is better than the
direct allocation approach because the revenue from an ARR
can be used to buy an FTR not only on the ARR path but also
on a different path. However, the same benefit can also be obtained from a directly allocated FTR. The owner of the directly
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allocated FTR can surrender this FTR in the forthcoming auction to generate an ARR equivalent revenue that can be utilized
to buy an FTR on a different path. Furthermore, the FTR quantities awarded through a direct allocation are firm having zero
procurement cost. The ARR mechanism does not guarantee this
benefit. In the case of the ARR mechanism, FTRs are physically
released only through the auction while the firm transmission
customers are provided with some financial support to buy their
required FTRs. The main benefit of the ARR mechanism is that
it helps in better management of the simultaneous feasibility of
FTRs. In addition, the ARR mechanism provides more flexibility to the ISO to deal with the problem of revenue deficiency
in an auction. However, it is beyond the scope of this paper to
present a detailed discussion on this matter.
V. TREATMENT OF REVENUE SHORTFALLS
Although every FTR issuance process employs some SFT
model that is generally linear, there may be certain hours when
day-ahead congestion collection becomes insufficient to pay full
FTR credits. The reason behind such revenue shortfall is that
FTRs are issued over a period of time during which the pathbranch sensitivities, base power flows (e.g., loop flows from
the neighboring control areas), and the contingency consideration in the power dispatch model may vary. Therefore, the
SFT model may not be precise enough to cover all the hours
of the time horizon of interest successfully. Also, the network
topology may get changed because of accidental line outages. In
addition, line capacities may degrade. Owing to all these factors,
the active FTRs at a certain hour may not be simultaneously feasible with respect to the actual network constraints in the power
dispatch model. Such infeasibility may, in turn, lead to inadequate congestion collection from the day-ahead market. Also, it
may not be possible to bridge completely the gap from the fund
of the real-time congestion collection.
However, as an ISO is a nonprofit-making entity, there must
be some mechanism to compensate for any such revenue shortfall. In NYISO, revenue shortfall is compensated by imposing
uplift charges on the transmission owners [36]. The objective
here is to link transmission maintenance standards with revenue
inadequacy. NYISO also allocates net congestion surplus and
FTR auction revenues to the transmission owners. However, the
NYISO approach seems unable to provide proper maintenance
incentives due to the uniformity of uplift charges [37].
In another practical approach, as followed by the PJM,
CAISO, and MISO [37], FTR payments are derated when
revenue shortfall occurs. In the PJM [38], the positive FTR
payments are reduced (but never made negative) in proportion
to the respective target payments when revenue deficit occurs.
FTRs with negative targets are given full credits. The excess
congestion collection that gets accumulated over a month
is transferred (if nonnegative) into a balancing fund. This
balancing account also accumulates the excess FTR auction
revenue from this month. After the balancing account is updated, the ISO first uses this fund to compensate partially
(on a pro-rata basis) or fully the unpaid FTR credits of the
particular month. The remaining amount in this fund is used to
compensate (partially or fully) the unpaid FTR credits from all
the previous months. The same sequence is repeated for each
month within a planning period.
Unlike FTRs that are settled daily, ARRs are settled on a
monthly basis in the PJM market. The shortfall in the auction
collection is managed by derating the ARRs in the same way
as described above. At the end of each planning period, the unpaid ARR credits are partially or fully compensated with the
amount that remains in the above balancing fund after compensating the shortfalls in FTR payments. In the case some amount
still remains in the balancing fund, it is distributed among the
firm transmission customers on a pro-rata basis irrespective of
whether or not they hold FTRs for their transmission services.
In [37], it was shown that the above procedure for derating
FTRs may create a gaming opportunity for certain market
players, in that they can artificially create congestion on the
transmission system. In order to suppress such gaming opportunity, a direct assignment technique was suggested in
[37] based on the constraint shadow prices, their capacity
degradations, MW amounts of the FTRs, and the path-branch
sensitivity factors. The assumption behind this approach is that
the network capacity degradation is the only reason for revenue
inadequacy. Now, as mentioned earlier, there are also some
other factors which may create a revenue shortfall situation. As
a result, the suggested method may fail at certain instances, e.g.,
when revenue shortfall is caused by a line outage. However,
the shortcoming of this direct assignment algorithm can be
eliminated by use of a small modification. Initially, the net
load caused by the physical equivalents of active FTRs on each
simultaneous feasibility constraint is to be calculated. If the
total load on a simultaneous feasibility constraint is found to be
greater than its limit, the amount of overload is to be measured.
For example, if the limit of a constraint is 100 MW and the total
load on it is 120 MW, the amount of overload is 20 MW. Once
all the overload amounts are calculated, these quantities should
be used in the formula of [37] in lieu of capacity degradation
amount.
VI. SECONDARY TRADING OF FTRS
Once awarded through central auction or allocation, FTRs
can be traded bilaterally in a secondary market. In the secondary
market, an FTR can be split into multiple FTRs with different
MW amounts and different validity periods. The new ownerships are registered on the market database. However, in order
to meet revenue adequacy criteria, the original FTR is not allowed to be broken into a collection of derived FTRs that loads
some simultaneous constraints more than does the original. Following are some simple rules followed in the PJM [17] for the
secondary trading of FTRs.
1) Rule 1: Option and obligation FTRs must be traded as options and obligations, respectively.
2) Rule 2: Each of the derived FTRs must be defined on the
same path as that of the original FTR.
3) Rule 3: The validity periods of two derived FTRs must not
partially overlap.
4) Rule 4: The sum of the MW amounts of all the derived
FTRs with the same validity period must be equal to the
MW amount of the original FTR.
SARKAR AND KHAPARDE: COMPREHENSIVE ASSESSMENT OF THE EVOLUTION OF FTRS
5) Rule 5: The validity period of any derived FTR must not
exceed the validity period of the original FTR.
In addition, an incremental limit has to be respected when
splitting an FTR. In the PJM, this limit is 0.1 MW, i.e., the MW
amount of each derived FTR transferred to a new owner must
be an integer multiple of 0.1.
However, due to the point-to-point nature of FTRs, the above
set of rules does not provide sufficient scope for the secondary
trading of these instruments. The extent of secondary trading
can be enlarged by means of the exchange mechanism described
in [39]. A simple interpretation (with a small modification) of
this exchange mechanism is that a market player can exchange
an existing FTR with the ISO for a new set of FTRs at no additional cost, where
1) the validity period of each new FTR must be less than or
equal to that of the original FTR;
2) the collective loading effect (may it be negative) of the new
set on any simultaneous feasibility constraint must not be
higher than that of the original FTR for any hour within the
validity period of the original FTR.
In a sense, this exchange mechanism complements the above
secondary trading rules by providing market players with an
additional provision to reconfigure their current FTRs.
VII. FINANCIAL TRANSMISSION RIGHT
VERSUS FLOWGATE RIGHT
Flowgate right (FGR) mechanism is the alternative to the FTR
mechanism in LMP markets. This mechanism was in practice in
the formerly ERCOT [19] zonal market. Unlike an FTR, which
is point-to-point (PtP), an FGR is defined on a transmission link
(or flowgate) in a certain direction. By definition, each FGR is
an option. The product of its MW amount and the shadow price
of the corresponding link gives the hourly value of an FGR in
the case that the link gets congested in the same direction. The
shadow price of a link in the energy market is defined as the rate
of increase of optimal social welfare with respect to the same
capacity increase in both directions of this link. However, if the
relevant link remains uncongested or congestion occurs in the
opposite direction, the value of the FGR becomes zero.
In order to preserve revenue adequacy, the total FGR amount
in any direction of a link is not permitted to be higher than
the capacity of the link in the particular direction. However,
no overall network-based SFT is required when issuing an
FGR. Initially, FGRs are issued through the central auction or
allocation process. In an auction, the purchaser of each FGR has
to pay the shadow price of the capacity constraint considered
in the auction. Once issued through central auction or allocation, FGRs can be freely traded in the secondary market. The
secondary trading rules for FGRs are similar to the secondary
trading rules for FTRs. A point-to-point transaction can be
fully hedged by a certain portfolio of flowgate rights. The MW
amount and direction of the required FGR on a flowgate are the
same as those of the physical flow caused by the transaction on
the particular flowgate.
The motivation behind the development of this link-based
concept was to enhance the decentralized trading of transmission rights [40]. Owing to its link-based nature, an individual
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FGR is more tradable than an FTR. The flowgate approach is
based upon the following assumptions [41]:
1) power transfer distribution factors (PTDFs) are relatively
stable;
2) the number of commercially significant flowgates (CSFs)
is small and predictable.
Commercially significant flowgates are those flowgates
which are likely to be congested very often. FGRs are to be
issued only on CSFs. The higher tradability of an individual
FGR combined with a small number of CSFs can without doubt
enhance the overall tradability of transmission rights.
The applicability of the FGR mechanism to a system relies on
the structure of this particular system. This methodology is by
far compatible with zonal pricing with radial interconnections
among the individual zones. However, as discussed in [42] and
[43], FGRs may not be suitable for a meshed system owing to
the following reasons:
1) varying values of PTDFs;
2) presence of a large number of contingent flowgates.
The PTDF between a link and the path of a transaction may
vary depending upon the system loading condition. Also, other
controls, such as tap changing transformers’ tap positions, affect the PTDF values. Now, the matching portfolio of FGRs for
a certain transaction has a direct functional relationship with the
actual PTDF values. Therefore, the uncertainty in PTDFs is finally translated into the form of uncertainty that a market player
faces about the risk hedging capability of his FGR portfolio.
However, a combined study of [44] and [45] indicates that the
DC PTDFs with current nominal network parameters may be
good references for defining the risk hedging ability of an FGR
portfolio over a long period of time.
A very serious problem arises, however, owing to the contingency consideration in the power dispatch problem. The energy
market is generally cleared in such a way that the system can
” contingencies. Now, the PTDF values are difsustain “
ferent for different topologies of the network. As a result, each
physical line corresponds to multiple links or flowgates—one
for each topological condition of the network (i.e., each flowgate is defined by a physical line and network topology pair).
This, in turn, may lead to a multitude of CSFs. For example, let
the number of potentially congested lines in a power network
be only 10. However, apart from the base network topology, 20
different contingent topologies are also considered in the power
dispatch model for the sake of system security. Therefore, the
total number of CSFs can be as large as 200 (i.e., 20 10).
Such myriad CSFs clearly invalidate Assumption-2 and indicate the impracticality of the FGR approach for this system.
Moreover, an additional problem arises in case the base network
topology gets changed because of some accidental line outages.
As a flowgate is defined by a certain line-topology combination, most of the previous flowgates become undefined in this
new system. This, in turn, creates an extra task of redefining the
existing FGRs with reference to the new system configuration.
In the case of the FTR mechanism, the field of influence of the
above factors is the revenue adequacy issue. However, in most
” contingencies are also considered in the
of the markets, “
SFT model. Although line outages and distribution factor variations can create a revenue shortfall problem, its severity may be
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reasonably minor [43]. The main reason for this is that simultaneous feasibility is sufficient but not necessary to make congestion collection revenue adequate. Moreover, the set of FTRs
issued may still be simultaneously feasible. In addition, any revenue shortfall can be compensated in future with excess congestion collections. As a result, most of the LMP-based power markets running successfully have found FTRs rather than FGRs
to be more suitable for their systems. Even in a radial system,
FTRs can be made equally tradable to FGRs through the implementation of the FTR exchange policy, which is discussed in
Section VI.
may fall below even the corresponding day-ahead prices. This,
in turn, causes a load movement from day-ahead to real-time. If
the load movement is large, the day-ahead prices again fall. As a
result, the loads now become attracted to the day-ahead market,
which again increases the day-ahead prices. When the transient
subsides (or becomes sufficiently attenuated), the constrained
in LMPs in the day-ahead market may be higher than those that
would have been present if the FTR owners had not behaved
strategically. However, it is debatable whether the strategy can
be continuously employed by an FTR owner.
IX. FTRS AND MERCHANT TRANSMISSION INVESTMENT
VIII. FTRS AND MARKET POWER
With regard to the interaction between FTRs and generators’ market power, there is consensus among some studies in
previous literature on the point that FTRs increase the market
power of the generators at the importing nodes [46]–[48]. On the
other hand, an analysis based upon the prisoners’ dilemma and
Cournot competition was presented in [49] with the inference
that FTRs are able to curb market power. However, the analysis presented in [49] is basically concerned with the long-run
profits of strategic generators rather than the long-run effect of
their strategies on market prices [50]. But, in the end, the relation of the term “market power” is with market prices, not with
the profits of generators. Therefore, [49] cannot properly justify
its proposition.
The market power, induced by FTRs themselves, counteracts to the competitive benefit that can be obtained by hedging
the LMP risk of the forward contracts. In order to suppress
the growth of such market power, FTRs should be prevented
from falling into the hands of strategic generators. In [51], it
was proposed that any FTR should be issued either from or to
a common point, determined by a certain measure called relative cross-price sensitivity. However, this approach seems to
interfere with the risk-hedging objective of the FTR mechanism
since a market player may not be able to collect the same quantity for both the load end and generator end FTRs to hedge his
transaction. As a result, it may not be accepted for practical implementation. FTR-induced market power should be mitigated,
but not at the cost of the risk-hedging benefit obtainable from
FTRs.
Unlike firm PTRs, FTRs cannot be used to withhold transmission capacity. This is because FTRs are purely financial instruments. However, by submitting a false schedule, an FTR
owner, having no physical transaction to hedge, may artificially
increase the congestion level on the transmission system for
earning a higher profit. The situation is nicely exemplified in
[52]. The player, then, has to withdraw this false schedule in
the real-time market. As the direction of congestion usually remains the same in both the day-ahead and real-time markets,
the real-time LMPs do not offset the day-ahead profit of the
strategic market player. Although this kind of strategic activity
does not indicate market power abuse, it causes a price rise at the
constrained in (i.e., importing power) nodes in the day-ahead
market. At the same time, as the unsold cheaper generations in
the day-ahead market now appear in the real-time market, and as
the previously blocked transmission capacity is also released in
the same market, the real-time prices at the constrained in nodes
The transmission system has a key role to play to make
competition successfully materializes in the power sector. New
investments are required in transmission system in order to get
increased power supplies from cheaper generators. Apart from
regulated investments, private (or merchant) investments can
also be considered to reinforce the existing network. Unlike regulated investments, a private investment is not passed through
any central planning process, neither is there any regulated
tariff-based return on any private investment. However, efficient
transmission investments should be sufficiently incentivized. A
transmission investment is efficient if it increases social welfare.
It may be that there will be investments that are beneficial to
the investor but harmful to the society. Disincentives should be
provided to prevent such inefficient or detrimental investments.
The work of Bushnell and Stoft [53] suggested that incremental FTRs (IFTRs) may provide correct investment incentives to private investors. Under this paradigm, the additional
FTRs, made possible by an investment, are issued to the investor. Bushnell et al. proved that if the risk-hedging FTRs
match the power dispatch schedules in aggregate before the expansion, the net value of the incremental FTRs will be no greater
than the increase of social welfare owing to this expansion. An
interesting two-bus example illustrating the incremental FTR
concept can be found in [54]. Incremental FTRs are currently offered in CAISO, MISO and NYISO, whereas PJM and ISO-NE
offer incremental ARRs (IARRs) [33]. However, there are many
obstacles to this particular market approach of transmission investment. The first problem is regarding the long-term issuance
of IFTRs. Before issuing an IFTR, a base case must be prepared
as to how many risk-hedging FTRs can be issued on the existing
network. An accurate modeling of such a base case is a difficult task as risk-hedging FTRs are issued periodically (yearly
and/or monthly). In [55] and [56], a proxy-award mechanism
was proposed to solve this problem, but the basis on which the
algorithm for determining proxy awards is built is not clear. Another problem is that it may not be possible to restore simultaneous feasibility by issuing IFTRs according to the investor’s
preference. In this context, a combined flowgate right and admittance right approach was proposed in [57] as an alternative
to the IFTR approach. However, the suggested approach seems
not to be able to differentiate new investments from existing resources. Rather, this problem can be solved by issuing IFTRs in
the reverse directions of some of the investor’s preferred paths.
Other critical problems regarding merchant transmission investments are the possibility of the destruction of LMP differences
owing to a transmission investment, lack of coalition between
SARKAR AND KHAPARDE: COMPREHENSIVE ASSESSMENT OF THE EVOLUTION OF FTRS
the investor and the market players that benefit (i.e., free rider
problem), and the need for some regulatory oversight to prevent
potentially harmful investments [58]–[61]. There is also a threat
of a reduction in the value of an IFTR owing to the future investments.
X. OTHER FTR INSTRUMENTS
A. Long-Term Financial Transmission Right
A long-term (LT) FTR is an FTR (or ARR) with a term longer
than one year. LT FTRs can secure infrastructure financing and
can provide more price certainty to the transmission customers
serving long-term power contracts [33]. The interest in LT FTRs
has started growing among various market participants in the
U.S. markets since 2005. In July 2006, the Federal Energy Regulatory Commission (FERC) of the U.S. issued its final guidelines [62] for the implementation of LT FTRs in organized [63]
electricity markets. These are summarized below.
1) An LT FTR must be a PtP transmission right.
2) LT FTRs must be fully funded unless the situation is extraordinary or voluntary agreements have been signed between LT FTR owners and the ISO.
3) LT IFTRs must be made available upon request to any party
that pays for transmission upgrades or expansions.
4) The term lengths of LT FTRs must be sufficient to fulfill
the needs of LSEs to hedge their long-term power supply
obligations.
5) LSEs must have priority over non-LSEs in the allocation
of long-term risk-hedging FTRs.
6) LT FTRs must follow the movement of retail customers.
7) The initial allocation of LT FTRs should be independent of
FTR auction.
8) Allocation of LT FTRs should balance any adverse economic impact between participants receiving and not receiving the right.
B. Contingent Transmission Right
Contingent transmission right (CTR) [64] is basically a
group-FTR concept. A CTR allows its owner to hold FTR on
a number of alternative paths. This added flexibility provides
market players with an additional (and cheaper) support to
overcome the congestion price risk originating from the uncertainty in their transaction paths.
Structurally, a CTR is defined by a MW amount and a set
of paths. The owner of the CTR can choose any path (but only
one at a time) from the given path set to convert his CTR into an
FTR. A CTR can be an obligation or an option. If it is an obligation, any FTR that it generates would be considered as an obligation FTR. Similarly, if it is an option, any FTR that it generates
would be considered as an option FTR. The generalized form of
the contingent transmission right is the multidimensional financial transmission right which is discussed in detail in [65].
C. Locational or Unbalanced Financial Transmission Right
Unlike a PtP FTR, a locational FTR (LFTR) [13] is defined
only for a point of injection (injection type) or a point of withdrawal (withdrawal type). The hourly value of a withdrawal type
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LFTR is given by the product of its MW amount and the LMP
(or the congestion component, or the congestion component
plus the energy component of the LMP) of the corresponding
location. If the LFTR is of the injection type, the negation of
the above product gives its hourly value. The bid price associated with an injection type LFTR request is usually nonpositive,
whereas it is usually nonnegative for a withdrawal type LFTR
request. Thus, an LFTR allows an individual load or generator
to freeze its buy or sale price, respectively, in advance (when
the auction is conducted) for a certain MW quantity. In other
words, an LFTR is similar to a forward contract between the
ISO and a generator or load. Therefore, LFTRs may increase
the traded volume of power in the forward market, leading to the
enhancement of market competitiveness. An LFTR must be an
obligation. Apart from satisfying network capacity constraints,
the physical equivalents of the LFTRs must be in balance (i.e.,
power balance) to ensure revenue adequacy.
XI. CONCLUSION
This paper provides a comprehensive insight into the FTR
mechanism employed in centralized power markets to provide
price guards to the forward contracts. An obligation FTR alone
can hedge a fixed transaction only, whereas a band of transactions can be fully hedged by an obligation-option portfolio.
Simultaneous feasibility is an important consideration in the
issuance of FTRs. Auction and allocation are two alternative
mechanisms for issuing FTRs. Market players can participate
in an auction in a number of ways. In order to have revenue adequacy at any hour within the time horizon of the auction, it
must be ensured that each possible active-inactive combination
of the FTRs be simultaneously feasible. All the FTRs issued in
an auction are marginally priced. Time-differentiated FTR products and multi-round auctions enhance the flexibility of market
players. The allocation of FTRs can be carried out directly or
through ARRs. Any centrally allocated or auctioned FTR can
be freely traded later in a secondary market. By means of an
exchange mechanism, it is also possible to reconfigure an FTR
without entering into any auction. Accidental line outages, line
capacity degradations, and imprecisions in the SFT model employed may sometimes cause revenue shortfall. Imposition of
uplift charges on transmission owners and temporary reduction
of FTR values are two major approaches to compensate revenue
shortfall. Strategic generators may acquire additional market
power through FTRs. This implies a need for some well-defined
and feasible rules for appropriately restricting the ownership of
these transmission rights. The alternative to the FTR mechanism
is the FGR mechanism. However, FGRs may not be suitable for
a highly meshed network. Apart from risk hedging, FTRs can
also be used to incentivize merchant transmission investments.
LT FTRs can provide more price certainty to long-term power
contracts. The future CTR will provide market players with an
additional support to get relief from the congestion price risk
originating from the uncertainty in their transaction paths. Finally, by means of LFTRs, individual generators and loads can
develop the flexibility to lock their sale and buy prices, respectively, in advance.
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1795
.V. Sarkar (S’07) received the B.E. degree in electrical engineering from Burdwan University, Bardhaman, India, in 2002 and the M.E. degree in electrical
engineering from the former Bengal Engineering College (currently Bengal Engineering and Science University), Kolkata, India, in 2004. He is currently pursuing the Ph.D. degree in the Department of Electrical Engineering at the Indian
Institute of Technology, Bombay, India.
His current research involves power system restructuring issues.
S. A. Khaparde (M’87, SM’91) received the Ph.D. degree in 1981 from the
Indian Institute of Technology, Kharagpur, India.
He is a Professor of electrical engineering at the Indian Institute of Technology, Bombay, India. He has authored several research papers and has coauthored two books. He is a member of the advisory committee of Maharastra
Electricity Regulatory Commission, India. His current research activities are in
the areas of power system restructuring.
Dr. Khaparde is on the editorial board of the International Journal of
Emerging Electric Power Systems.