Cost Allocation for Merchant Transmission

8/4/2019 Cost Allocation for Merchant Transmission

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Cost Allocation for Merchant Transmission

by

Richard Benjamin1

EconomistRound Table Group

Abstract

Cost allocation for transmission expansion is a continuing problem, especially in the casewhere a new line crosses state boundaries, because payments for transmission investment and itsuse are made at the state level, but the economic impacts from these investments extend beyondstate boundaries. The paper advances a solution to this problem by means of a two-part approachto transmission financing. The approach features a variable component, (i.e. an FTR, adjusted for

lumpiness) and a fixed component, determined by the increase in import capability that the newline enables.

1 I would like to thank Ross Baldick and workshop participants at the 2010 IAEE North AmericanConference for helpful comments on this version of the paper. Any remaining mistakes are my own.


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Introduction

Cost allocation for transmission expansion is a particularly thorny problem, especially in

the case where a new line crosses state boundaries. As Sauma and Oren (2007) note, sometimes

there are misalignments between costs and benefits associated with investments in transmission,

because payments for transmission investment and its use are made at the state level, but the

economic impacts from these investments extend beyond state boundaries. As a consequence,

transmission expansions that maximize social welfare may not produce Pareto superior outcomes,

resulting in justifiable local opposition.

It appeared that Hogans (1992) introduction of financial transmission rights (FTRs)

solved this problem in restructured electricity markets. A point-to-point FTR gives its holder the

right to collect congestion rents equal to the difference in locational marginal prices (LMPs) at

the sink and the source locations (nodes). Bushnell and Stoft (1997) suggest awarding (or

punishing, in the case of detrimental grid expansions) developers with the incremental FTRs

associated with their new lines.

Merchant transmission development has been slow moving in the United States,

however. As many note (see, e.g. Joskow and Tirole (2005) and Barmacket al. (2003)),

lumpiness of transmission additions narrows, or even eliminates, the difference in LMPs between

the nodes connected by the transmission addition, causing the value of incremental FTRs

allocated to a project fall below the redispatch-cost savings attributable to the line, which several

economists have argued to be the projects social benefit,2and frustrating FTR allocation as a

means of financing new transmission. As a result of the difficulties merchant transmission has

faced in the United States, the Federal Energy Regulatory Commission (FERC) has backed away

from its endorsement of the former in its unsuccessful rulemaking on Standard Market Design,

2 See, e.g. Joskow and Tirole (2005), Barmacket al. (2003), and Leautier (2000).


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and instead advanced incentive ratemaking to encourage new transmission development in Order

No. 679.3 With the marginalization of merchant transmission, however, the problem of cost

allocation for new transmission lines remains. In recognition of this problem, on March 23, 2010,

Chairman Jon Wellinghoff indicated FERC would consider initiating a rulemaking on

transmission cost allocation.4

The paper advances a two-part approach to financing transmission expansions, whose

roots are found in Loeb and Magats (1979) scheme, in which the regulator subsidizes the firm

according to the total surplus it generates. Gans and King (2000) apply a variant of this

methodology, the incremental surplus subsidy (ISS) scheme, developed by Sappington and Sibley

(1988). However, the ISS scheme is ill-suited to transmission investment, as this paper argues.

The paper thus contributes to the literature by extracting the strengths of Gans and Kings

proposed methodology while pruning the weaknesses. In so doing, it derives a plausible scheme

for allocating costs for new transmission projects in the United States. Sections II and III present

background information regarding the papers proposed approach and the approach itself,

respectively. Section IV briefly considers the methods consistency with transmission pricing

principles presented in the literature. Section V concludes.

II. Background

A logical point of departure for a study on transmission funding mechanisms is a review

of the desirable properties of such mechanisms. In their seminal paper, Prez-Arriaga et al.

(1995) note that remunerating transmission owners with the merchandizing surplus (the

difference between revenue collected from consumers and that paid to generators) will recover

3 Final Rule, Docket No. RM-06-4-000,Promoting Transmission Investment Through Pricing Reform, 113FERC 61,182.4 Testimony of Chairman Jon Wellinghoff, Federal Energy Regulatory Commission Before the Energy and

Environment Subcommittee Of the Committee on Energy and Commerce United States House ofRepresentatives Oversight Hearing for the Federal Energy Regulatory Commission, March 23, 2010


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only a fraction (approximately 25%) of required network revenue.5Nonetheless, Prez-Arriaga

et al. argue that a regulatory approach to transmission should implement nodal pricing to

encourage transmission expansion, because nodal prices transmit optimal price signals. But

because the merchandizing surplus is in general insufficient to remunerate transmission

investment, they maintain that a complementary charge is needed to fully finance investment,

which should:

1. distort short-term price signals as little as possible, in order to preserve efficiencyof the market;2. distort long-term decision making as little as possible, providing network usersthe initiative to propose network reinforcements (promote long-term efficiency); and3. use historical network performance as a baseline for measuring networkoperation and maintenance activities (be both objective and simple to implement and

understand).6

Vogelsang (1999) considers a two-part tariff as well. He argues that the complementary charge

(or, fixed fee) should satisfy at least two requirements. They should: (1) be fair (subsidy-free);

and (2) not depend on usage (for then they would be variable fees). He argues that fairness

implies that the complementary charge should depend on the transmission capacity cost caused

by the customer and/or the customers net benefit.

Next, the Stanford Energy Modelling Forum (Green 1997) recommends the following

principles to assess the performance of transmission pricing mechanisms:

1. Promote efficient daily operation of the bulk power market.2. Signal locational advantages for investment in generation and load.3. Signal the need for investment in the transmission system.4. Compensate the owners of existing transmission assets.5. Simplicity/transparency.6. Political feasibility.

Green argues that an LMP system accomplishes the first task, while recognizing that lumpiness of

transmission investments, fragmentation of grid ownership and the accompanying externality

5 Chile, in its pioneering electricity statutes, recognized the need for a charge to complement marginal costpricing for transmission (See Rudnick et al. (1995), referencing Electricity Service Law Decrees, Chile,1982, 1985, and 1990). The Chilean system, however, did not price congestion (Rudnick et al. 1995, p.1127.)6 Of the aforementioned principles, long-term efficiency naturally receives the most play in the literature(short-run efficiency already being covered by efficient locational prices).


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issues complicates, and perverse incentives for FTR-holders to sustain congestion complicate the

satisfaction of Principles 2 and 3. Principle 4 is based on the simple tenet of no regulatory

appropriation. Principle 5 is based on the argument that transmission prices must be

understandable in order to send clear price signals. Finally, it is necessary that a transmission

pricing scheme satisfy principle six in order to make it coalition proof.7 Vogelsang (1999) adds

regulatory Principle 7:

7. Encourage innovative pricing by market participants.

Vogelsang recommends that the regulatory mechanism accommodate both simple and

sophisticated transmission tariffs.

Along with advocating efficiency and simplicity, Rubio and Prez-Arriaga (2000) add

regulatory Principle 8:

8. Objectivity

Rubio-Odriz and Prez-Arriaga believe that a good regulatory mechanism should be based on

sound economic and engineering principles. They suggest implementing a two-part tariff for

transmission whose complementary charge would be based on the economic benefit that each

network facility causes to each agent (the benefit factor method). They maintain that consumers

benefit is the reduction in total electricity charges based on spot prices, while producer benefit is

their increment in net revenues. And, as they mention in n.7, they take only positive benefits into

account, not losses accruing to generators from competition.

Of course, it is unrealistic to expect consensus with respect to these principles. For

example, Vogelsang (1999) agrees that the regulatory mechanism for transmission has to be

based on transparent data. But he notes that the level of complexity of actual tariffs depends on

the trade off between efficiency and complexity that market participants and regulators are

willing to make and that participants in the transmission market are largely sophisticated firms.

7 As argued by Rubio and Prez-Arriaga (2000) and Vogelsang (1999), political feasibility need not implythat generators be protected from increased competition. Vogelsang adds that eliminating cross-subsidiesis no great crime, either.


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He therefore questions the necessity of simplicity of a regulatory mechanism for transmission.

Likewise, many works ignore the importance of political constraints. While many acknowledge

lumpiness of transmission projects,8in most cases they do so in the context of the feasibility of

using FTRs to finance (merchant) transmission investment (e.g. Joskow and Tirole (2005), Gans

and King (2000), Hogan (2003, 2011)).

However, political constraints form important barriers to siting new transmission projects

and should not be overlooked. For example, Green (1997) cites the case in England and Wales,

where increases in transmission charges attributable to a new project were capped, so that the

changes had to be phased in over four years. Morrison (2005) notes that the most significant

reason low-cost states oppose centralized markets is the concern that liberalization will hurt

consumers in these regions. He also notes that regulators in low-cost states cannot legally

support a policy that will lower electricity prices in a neighboring state if it does so at the expense

of consumers in their own state. Barmacket al. (2003) add that losers from transmission

investment can be expected to expend up to the amount of the rents they stand to lose to block

transmission investment. Finally, Vogelsang (1999, 2006), Rubio and Prez-Arriaga (2000), and

Hayden and Michaels (2006) (the latter implicitly) argue that political constraints imply that no

interest group involved is made noticeably worse off. Hayden and Michaels acknowledge

political constraints by proposing to cap any nodal price that increases due to the new line at its

old level. Vogelsang (1999) and Rubio and Prez-Arriaga qualify their arguments by allowing

for increased competition among affected generators to reduce generator profits.9

Sappington and Sibley (1988) proposed the ISS scheme as a method for providing

regulated monopolies with the incentive to operate and price efficiently (i.e. minimize production

cost and charge a price equal to marginal cost, respectively). Under the ISS scheme, the regulator

8 See, e.g. Joskow and Tirole (2005), Gans and King (2000), Barmacket al. (2003), Hayden and Michaels(2006), Hogan (2003, 2011)

9 At a more fundamental level, Reta et al. (2005) reject the principles-based approach entirely.They argue that there is no satisfactory methodology for allocating transmission costs in any power systembecause allexisting approached have their associated advantages and disadvantages that depend on thetheir own characteristics, the characteristics of the power system, and the price structure of the market


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grants the monopolist the increment in total surplus that its activities (e.g., price charged and

investment undertaken) generate in each period, subtracting from this sum accounting profits,

lagged one period. The authors apply the scheme to the firms investment spending by noting

that under ISS, the firm is reimbursed with a lag of one period for any investment expenditures it

makes, while reaping the social benefits of its investment for one period as well.

Gans and King (2000) apply the ISS scheme to the problem of electricity transmission

regulation in Australia, arguing that the existence of market power (on behalf of the transmission

provided) and the lumpy nature of transmission investment imply that rewarding transmission

owners with FTRs based on nodal prices will send suboptimal signals for transmission

investment.

Consistent with Leautier (2000), Joskow and Tirole (2002, 2005), Barmacket al. (2003),

Hayden and Michaels (2006), and Hogan (2011) inter alia, Gans and King approximate the social

value of a new transmission line by the dispatch cost reduction the line enables.10 Applying the

ISS scheme to transmission investment, they propose that the regulator allow the investor to

retain the social surplus created by any transmission augmentation during the first year of the

projects life.

Gans and King note measurement of the increment of social surplus generated by the

investment requires the calculation of the measurement of the counterfactual: what would social

surplus have been without the investment. The authors propose that this counterfactual be

approximated by calculating what the system marginal prices would have been for the same

demand and generator bids if the transmission network were configured without the investment.11

Presuming the investor to incur the projects capital costs that same year, Gans and

Kings scheme then has the regulator reimbursing the investor for the projects entire capital cost

after a lag of one year. Gans and King conclude that the ISS scheme will provide builders with

10 New transmission lines may also increase system reliability and reduce generator market power.11 They continue that the difference between the price with and without the investment multiplied byquantity demanded approximates the social value generated by the new investment during the year,


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the incentive for optimal investment timing, because under the scheme the investor will delay

investment up until the point where the marginal gain and marginal cost of waiting equate.

Arguably, the least practical and most problematic element of the ISS scheme as applied

to transmission or other large projects is paying the developer total construction cost in a single

period. For example, the Midwest Independent System Operators (Midwest ISO) planned

interstate transmission projects (Starter Multi-Value Projects, or Starter MVPs) have a total

estimated cost of $4.68 billion. MISO customers will pay the cost of these projects in rates over a

40-year period. Anderson et al. (2011) estimate that customers across MISO will pay

approximately one-tenth of a cent per kilowatt hour for these projects over this period (or about

$0.77 per month for the average Michigan residential user). Paying off the $4.68 billion in one

year would result in a politically unacceptable one-year rate shock. Given the long life of

transmission projects, lumping a 40-year payoff into a single year is clearly problematic.

A second weakness of Gans and Kings methodology is that it assumes a fixed project

size (i.e., the authors assume that the optimal investment size is that which will eliminate

congestion). While this may be the case, it need not be. A more systematic approach will

account for the proposition that one size does not necessarily fit all. However, as mentioned

previously, the ISS scheme aligns social and private incentives and thus elicits optimal

transmission investment timing. Therefore, this paper does not argue that we should abandon the

ISS schemes application to merchant transmission expansion. Rather, this paper thus seeks to

tweak the ISS scheme to make it a better fit for funding merchant transmission expansion.

III. Proposed Approach

This paper proposes to compensate merchant transmission projects according to the

reduction in congestion costs (RICC) they enable. In doing so the paper presents a mechanism

that (practically, as explained below) equates social and private incentives for transmission

expansion, thus attaining efficient transmission investment. We propose a two-part tariff, whose


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variable and complementary components sum to the projects incremental social benefit. As with

other mechanisms, a complementary component is necessitated because the variable part of the

tariff will not necessarily recover total redispatch cost savings.

The mechanism proceeds as follows: Like Gans and King (2000) and Hayden and

Michaels (2006), we propose to approximate redispatch cost savings attributable by

implementing two runs of the regional transmission organizations (RTO) dispatch mechanism:

one reflecting the transmission system with the line in place, and the other assuming it had not

been built.12 Having conducted the two runs, the RTO would then calculate RICC attributable to

the line.13 The RTO would then award the transmission developer the total RICC, as calculated,

demonstrated below for a two-node network. The RTO awards the transmission developer

through use of a two-part tariff. The first component is based on the merchandizing surplus, as

with FTRs. The second component, based on pre-existing RTO collection of transmission

revenues, is equal to the total RICC minus the amount of revenue collected under the variable

component.

Let us now calculate RICC in a simple two-node example. We assume that the two

nodes are unconnected prior to the transmission expansion, as shown below:

12 Of course, how often the system operator should calculate the counterfactual is an open question, whoseanswer will necessarily be arbitrary. One would desire that the answer to this question be based on ananalysis of the cost and benefit of increasing frequency of calculations, but such is beyond the scope of thepresent work. In line with someone, who noted that congestion costs can vary substantially on an hourlybasis, we suspect that the counterfactual should be derived either hourly or half-hourly, with any furtherrefinement probably not worth the additional cost.13 If the RTO performs the counterfactual calculation less often then the actual dispatch, then it wouldcompute average reduction in congestion costs for the relevant period.

Node i:

Price =pi1

Load = Dispatch = Qj

Nodej:

Price =pj1

Load = Dispatch = Qj

Figure 1: The two-node model


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Without loss of generality, let us assume that marginal cost of generation is linear in

supply at each node, so that:

,igqyc i += .0,


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The ISS scheme, Hayden and Michaels RICC approach, Joskow and Tirole (2005) and

this paper all suggest rewarding the developer with the trapezoid dace, that is, the redispatch

savings attributable to a new line of capacityK. .16

After calculating the surplus, the next step is to remunerate the transmission developer.

Gans and King suggest that the difference between the price with and without the investment

multiplied by the quantity demanded approximates the social value generated by the project.

Therefore, they recommend charging consumers the without- price and paying generators the

with-price to raise the relevant funds.17 Referring to Figure 2, this would imply charging nodej

consumers the pricepj1 while paying node i producers the pricepi.

16Gans and King argue that the calculation of this counterfactual is straightforward. The authors note thatthe electricity spot market organized under the Australian National Electricity Market (NEM) employs adispatch procedure utilizing line loss and constraint information as well as generator bids in calculating its

generation dispatch (i.e., the supply schedule which forms the least-cost solution to supplying electricitydemand at every node in the system). They posit that it would be a relatively simple matter to alsocalculate what the system marginal prices would have been for the same demand and generator bids for thepre-existing transmission network. Hayden and Michaels also note that this counterfactual is an exercise insystem simulations. While Rubio-Odriz and Prez-Arriaga (2000) also argue for benefit calculation basedon this counterfactual, they argue that this exercise is computationally expensive.17 It is not quite clear to which nodes their mechanism applies. However, since they suggest that thisamount approximates the incremental surplus generated by the line, the most apt reading is charge nodejconsumerspj1 (without price) and pay node i producerspi(with price). Since they remain silent on theother parties, one assumes they do not recommend any additional adjustment.

Quantity

Net supply of generatori to nodej :

p =pi1+gq

Net demand at nodej = Cost savingsfrom backing down generatorj:

p =pj1

- hq

a

c

pj

f

nd

pi 1

Price

pj 1

pi

Figure 2: Redispatch-cost savings from line ij.

K

b

e


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Following Gans and King, we obtain the first two steps of the methodology for

computing the variable component.

1. Credit the transmission developer with the standard FTR revenue, ij ppK .

2. Credit the transmission developer with additional revenue jjppK

1 .

The amount of revenue available for payment of conventional FTRs in this example is

ij ppK . As noted previously, however, this amount falls short of the social value of the

line. To correct for this shortcoming, we transfer the area jji ppK from load-pocket

consumers to the transmission developer.

However, it remains to determine the price to charge nodej producers and node i

consumers. This warrants a closer examination of political factors. First, and most obviously, the

not-in-my-backyard effect (NIMBY) serves as an impediment to undesirable projects such as

unsightly transmission lines. As Brennan (2006) notes, exurban population growth and the

corresponding increase in property values have increased resistance to new transmission lines in

the last 20 years or so. While Hirst (2000) attributes some of this increase to a decline in a sense

of community in Americans, he and Brennan agree that land use concerns are legitimate.18

Next, as previously noted, the lumpy nature of transmission implies that new

transmission projects will result in price changes. In our simple example, prices at both ends of a

radial line will change.19 As Barmacket al. (2003) note, these price changes have important

distributional impacts. In general, transmission investment produces rent transfers from load

pocket generators and generation pocket consumers to load pocket consumers and generation

pocket generators, as seen by the price changes at nodes i andj in our example. Therefore, our

mechanism will extract consumer surplus from load-pocket (nodej) consumers and profits from

generation-pocket (node i) generators in order to fund the new line.

18 While we further consideration of NIMBY is beyond the scope of this article, we would be remiss toignore it in a section regarding political concerns.19 More generally, loop flow will result in price changes at several different nodes in a network a point wewill address in future work.


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When a transmission project falls entirely within a single states jurisdiction, the relevant

state agency can legitimately weight the benefits and losses of the various groups involved when

making transmission siting decisions. However, interstate lines have no such fallback. As

Morrison (2005) observes, regulators in low-cost states have a statutory obligation to guard the

interests of their consumers. They cannot legally support a policy that will lower electricity

prices in other states if doing so disadvantages their states consumers. To blunt this opposition,

therefore, we suggest charging generation-pocket consumers the before pricepi1. As exposited

above, though, increased competition among affected generators is a positive development, which

argues against compensating load pocket generators for their losses. Therefore, we suggest

remunerating load-pocket generators with the post-line price,pj.20,21 Combined with our previous

energy market recommendations, this yields the energy market settlements shown in Table 1

below:

Table 1: Energy Market Settlements Under the Proposed Mechanism

20 While one might object to the presence of two different prices at a single node, one must remember thatRTOs do not settle load at a nodal basis, anyway. Much to the chagrin of economists, load does not seereal-time, nodal prices. Rather, RTOs settle load on an average zonal basis. Therefore, whether or not theRTO settles load atpj orpj1, the cost of serving nodej load is simply thrown into the pot and averaged inwith the rest of the load in nodejs zone. In essence, then, there are virtually always two different energy

prices at every node in the network. To our knowledge, the existence of these multiple prices has not ledto any arbitrage opportunities in restructured electricity market.21 To demonstrate arbitrage opportunities present in poorly structured energy markets, let us consider theold zonal pricing regime of the California ISO, generators were accused of playing the dec game, inwhich generators in generation-constrained resources submitted relatively high prices in the day-aheadmarket, and a low bid in the real-time market. In the day-ahead market, the resource would be paid a highprice based on its bid. In real-time, when congestion existed, the generator would buy back, or theCalifornia ISO would dec the generator, in order to relieve congestion. Given a high sale price andpaying a lower buy-back price allowed the generator to pocket the difference without actually producingany electricity! (see, e.g. Alaywan et al. (2004)).

Entity Energy Market Settlement

Generation ati ( )KQp ii +

Load at i ( )ii Qp 1

Generation at j ( )KQp jj

Load atj jj Qp 1

Transmission Owner N/A


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Charging generation pocket consumers the pre-line price, 1ip , for the power they consume

results in a deficit equal to ( ) iii Qpp 1 , equal to area (2) in Figure 3 below. The major source

of funding for this collection is the excess payments collected from load-pocket consumers over

revenue paid to load-pocket producers, equal to the energy produced and consumed at nodej

times the difference in prices paid by consumers and to producers at this node, i.e. jjj Qpp 1


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, or area (1).

We may now further our description of the calculation of the variable component of the

tariff and the associated transfers as follows:

1. Credit the transmission developer with the standard FTR revenue, ij ppK .

Quantity

pj

pi 1

Price

pj 1

pi

Qi

(2)

Qj-K

(1)

Figure 3: Energy Market Adjustments


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2. Credit the transmission developer with additional revenue jj ppK 1 .

3. Collect the value jjj Qpp 1 from energy produced and consumed in the load pocket

by charging consumers the pre-line price and paying generators the post-line price.4. Transfer this value to node i generators as a credit toward the deficit created by paying

generation- pocket generators more revenue than is charged to generation-pocket

consumers.

A final, common-sense adjustment is dictated by political considerations as well. In

order to ensure that load-pocket consumers benefits from the transmission line amount to more

than any reliability improvements associated with the addition, they must pay less for energy.

Therefore, instead of paying the pricepj1 per unit of electricity consumed, load pocket consumers

should instead pay a fraction, ,10with,


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for at least two reasons.23 The first is gaming. If only those generators who bid high receive a

higher price for their electricity, then all generators will have the incentive to raise their bids, and

not only those who are likely to be marginal. This leads to the well-appreciated problem of pay-

as-bid electricity auctions yielding inefficient dispatch.24 The second is political considerations.

Node i producers will be much more likely to lobby their state regulatory agency for siting of the

new line ifallof their generation stands to profit from it.

This funding method leaves incentives for generation location intact, by paying

generation at each node the LMP. It provides a practically optimal signal for transmission

developers, as they receive almost the entire social value of their investment, and will therefore

wish to develop projects whose social benefit is positive, only (and will turn down only those

projects whose net social benefit is minimal). A possible criticism with respect to incentives is

that it does not send true signals for loads. However, this method does nothing to alter the price

signals to load under the current RTO practice of charging load the zonal price.

These transfers will not, in general, fully-fund the transmission expansion. In order to

allocate the full social benefit created from the project to the transmission developer, then, the

ISO would have to generate additional revenue through a complementary charge. Since the

variable charge extracts rent from downstream consumers, the complementary charge would

apply to the conjugate party benefiting from the expansion, that is, node i generators.

Roughly speaking, the complementary charge should be equal to the difference between

the total payment to the developer (as argued above, the social surplus created by the project) and

the amount of revenue collected from the variable charge, as based on LMP differences, above.

Vogelsang (1999) argues that under this approach, one cannot determine the complementary

charge exantebecause fluctuating spot prices necessitate an adjustable complementary charge as

well. While accepting the argument, we reject the conclusion, however, because in our view this

23 The RTO could pay an uplift to generation bidding in abovepi1.24See, e.g. Cramton and Stoft (2007) and Holmberg (2009)


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(i) does not jibe with the existing methodology for collecting transmission fees in United States

RTOs, and (ii) introduces unnecessary complexity into the mechanism.

With respect to the first point, in the United States, RTOs routinely allot grid usage

according to physical transmission rights (PTRs). An RTO generally allocates the load serving

entities (LSEs) in its service area firm PTRs for network load. This ensures that the LSE has

sufficient transmission capacity available to meet its load obligations. The RTO charges the LSE

for these rights, and then reimburses them with FTRs (based on the principle that the LSEs were

the ones who built the grid, so they should be reimbursed for their investments). The RTO will

award non-firm transmission rights for subordinate transactions, such as power marketers

moving power. Such rights are non-firm in the sense that the RTO may choose to preclude

the associated transactions through transmission loading relief (TLR) procedures.25

With procedures for charging customers for transmission service currently in effect, it is

only logical to adapt the mechanism to them. RTOs calculate charges for transmission service

based on the revenue requirements of their participating transmission owners (TOs).26 Therefore,

we argue that the RTO incorporate the complementary charge into these pre-existing RTO

transmission charges.

With respect to the second point, it is not necessary that the complementary charge be

correct (in the sense that, combined with the variable charge, it compensates the transmission

developer the desired amount) every period. Rather, it need only be correct in expectation.

Therefore we recommend calculating the complementary charge as follows:

1. Through system simulations, calculate the average shortfall between RICC and thevariable component.

25See, PJM Open Access Transmission Tariff, Section II: Point-to-Point Transmission Service for adetailed description of PJMs methods for allocating firm- and non-firm Point-to Point Transmission rights,and Schedule 7: Long-Term Firm and Short-Term Firm Point-To-Point Transmission Service, andSchedule 8: Non-Firm Point-To-Point Transmission Service for prices for these services (available athttp://www.pjm.com/documents/~/media/documents/agreements/tariff.ashx).26 For example, PJMs transmission charges include a monthly demand charge (based on the customersdaily network service peak load contribution) and charges for firm- and non-firm point-to-pointtransmission service.


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2. Attach a relative social welfare weight on consumer surplus vs. firm profit to calculatethe values of the variable and complementary components.

3. Adjust the RTOs demand and point-to-point transmission charges so as to create asurplus in revenue collected (above the revenue requirement of the relevant TOs) equal tothe average difference, calculated in step 1.

The first step is straightforward. In order for the mechanism to work reasonably well, the

complementary charge should be set to provide the transmission developer with the RICC, on

average, and the RTO has no better way to estimate this average other than simulations. The

second step involves calculation of , which determines how much better off load-pocket

consumers will be as a result of the transmission line. To calculate , we must weigh

consumers surplus against generator profits.

As for the third step, in light of Greens fourth principle, the complementary charge will

be an adder on top of the pre-existing TOs combined revenue requirement. Therefore, the RTO

must determine the change in the demand and point-to-point transmission charges necessary to

cover the existing revenue requirements and provide the revenue calculated in

step 1.27

For sake of expositional simplicity, we will ignore the demand charge and the difference

between firm-and non-firm transmission reservations while demonstrating the calculation of the

complementary charge. We will also ignore variability of demand, treating all values as

averages. For sake of generality, we also relax the assumption that ji QQ = . Total revenue

collected in the energy market is then:

jjii QpQpTR 11 += (4)

While total energy cost is:

27 In the event that the fixed charge does not fully cover the amount owed to the transmission line,a supplemental, or true-up charge would apply to all transmission line users at the end of the relevantperiod (e.g. monthly or yearly).


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( ) KQpKQpTC jjii ++=

(5)

Taking total energy market revenues minus total cost yields the amount collected by the variable

component:

( )

( ) ( ) ( ) ( ) ( ) 211

12 KhghQzQgQhQKKyz

KQpKQpQpQpVC

jjij

jjiijjii

++=

+++=

(6)

We note that the variable component is strictly decreasing in the slope of the cost function for

node i generation, as well as the quantity of load served at that node. The two terms combine to

play a huge role in determining the amount of compensation paid to node i consumers and their

influence could expunge the mechanisms merits.28

With that qualification in place we continue by calculating the value of the

complementary charge. As argued above, on average the complementary charge will equal the

amount paid to the transmission developer minus the variable charge. The amount paid to the

developer is given by

( ) ( )

( ) ( )( ) ( )

h

hQzK

hgKpp

dqhqpdqgqphqp

jij

pq

j

K

ij

j

2

1

2

22

11

)(

01

011

1

+=

+

(7)

Where( )

h

ppq

jj

=

1)(

11 .

Finally, taking the difference between these two quantities yields the amount to be collected by

the complementary charge.

28 More specifically, when hQj=gQi, the only difference between this mechanism and traditional merchant

transmission is the revenue correction ( ) .1 jp A situation such as this might call for relaxation of theconstraint that node i consumers be held harmless from the price effects of the transmission line.


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( ) ( )( ) ( )

( ) ( ) ( )( ) ( )

+

+=

+

=

h

zQhzhQgQhQK

Khg

VCh

hQzK

hgKpp

jjij

jij

2

1321

2

2

1

2CC

2222

22

11

(8)

In our simple example, we had no existing transmission owners to keep whole with

respect to the new line. In general, though, this will be a concern. This problem is easily solved,

however. Let the load-pockets pre-existing average level of imports be equal toA and letthe

new line bring a change in average imports equal to ,A where the RTO uses data from the

same counterfactual exercise to compute the latter value. For simplicity, assume that all pre-line

transmission rights are priced atpa, and post-line rights are priced atpb. The mechanism (1) calls

for the RTO to keep the original transmission owners whole, so that after the lines imposition

their revenue is equal to Apa ; and (2) requires the RTO to set the post-line price so that the

attendant complementary component combines with the variable component to remunerate the

transmission developer. Denote byPRb the amount of revenue to be collected in physical

transmission rights after development of the line. The two above conditions require

( ) ApVCTRAApPR abb +=+= )(

(9)

This allows us to solve forpb as

( )AA

ApVCTRp ab

+

+=

(10)

Thus, the increase in the charge for physical transmission rights due to the new line is:

( )

AA

ApVCTRpp aab

+

= (11)

Because the payments to the transmission investor, i.e., the lines net social benefit, will

vary with load and generation dispatch, the merchant investor seeking a more stable revenue


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stream may issue contracts for differences of differences, as per Baldick (2007). Like Baldick,

our method values transmission by its contingency-constrained transport of lower value energy to

higher value locations and does not require the RTO to be intimately involved in the allocation

and reconfiguration of forward transmission rights.

IV. Consistency with transmission pricing criteria

This section discusses the mechanisms consistency with the criteria suggested for

transmission pricing mechanisms. First, we believe that this mechanism has minimal impact on

price signals for generation and load. The mechanism has no impact on the prices that generators

see. It does involve some alteration in settlements for load, because it attempts to keep

generation-pocket load whole with respect to the imposition of the new line and alters the

payments load at the downstream end make. However, because load almost universally does not

see nodal prices anyway, due mainly to political constraints, settlement alteration will have

minimal impact on the price that downstream load sees.

By rewarding merchant transmission with virtually all of the net social benefit due to the

project, the methodology should distort long-term transmission decisions only minimally. It

should also have minimal impact on decisions for new residential load, as previously argued.

Commercial and industrial rates are determined separately from residential rates, so the

methodology need not have any impact there. The bigger long-term issue is the amount of time

the methodology may be deemed as being relevant. Over longer time periods, the pre-line

transmission network will no longer resemble a reasonable baseline against which to judge the

impact of the transmission addition. It is likely then, that it would be necessary to infer the lines

contribution to net social benefit in later years based on its contribution in the years immediately

following the line addition.

Admittedly the method is not simple. It involves multiple runs of dispatch mechanisms

based on actual and hypothetical network conditions. We see this, along with changing network


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configuration over time, as being the methods main drawback. The methodologys political

appeal tends to counteract these drawbacks. As discussed above, keeping electricity prices low at

the upstream end of the line can help blunt line opposition.

Finally, we quickly examine promotion of efficient daily operation of the bulk power market,

signals for locational advantages for investment in generation, and compensation for owners of

existing transmission assets. The method imposes no new distortions on generation decisions,

because it uses pre-existing mechanisms ( PTR revenue) for charging for transmission service.

Neither does it have any obvious impact on nodal prices paid to generators. It will not affect

dispatch, either, as it alters loads nodal prices only retroactively. Because it affects neither

dispatch nor generator prices, it maintains locational advantages for generation, as well as

preserving low prices for upstream load. As it preserves FTR revenues for existing transmission,

and is consistent with preserving PTR revenues for owners of existing transmission assets, it

compensates the owners of existing transmission assets as well as the extant FTR system does.

IV. Conclusion

This paper presents a hybrid methodology to financing transmission expansion, which we

see as being a significant step forward in the search for a practicable cost-allocation method for

new projects. By adjusting for lumpiness, the methodology measures the transmission

expansions net social benefit, equal to the redispatch-cost savings it enables. The second

component of the method, the usage-based fixed charge, where usage is determined according to

standard load-flow analysis. One calculates this component as that portion of the PTR charge

attributable to flow over the new line. One great advantage of the methodology is that it is

equally applicable to rate-based, as well as merchant transmission expansions. For rate-based

additions, the fixed component is trued up to equal the lines revenue requirement. For merchant

transmission expansions, equal to the net social benefit the line confers.


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We find that this methodology fairs well with respect to a number of criteria advanced for

a transmission financing mechanism. We argue that it performs well with respect to the

beneficiaries pay principle, providing accurate signals for transmission expansion, promoting

efficient operation of the bulk power market, being politically feasible, and preserving price

signals. The methodology is, admittedly, complex, but it is certainly not impenetrable. Another

acknowledged weakness is that it applies comparative statics to an inherently dynamic problem,

but that is a weakness shared by any comparative static analysis. We judge this weakness to be

tempered by the observation that project remuneration far into the future can be determined based

on knowledge gained in early years of the projects life.

This papers methodology for financing transmission expansions imputes transmission

with a value basedsolely upon the ability of transmission to transport low-cost power from one

region to another. But transmission has always played a role in improving system reliability. We

see the study of this attribute as a promising area for future research. Along the lines of Blumsack

et al. (2006), one can decompose a change in network topology into a congestion effect and a

reliability effect. Adding line limits in the model would allow one to use Blumsacket al.s

methodology to examine the congestion effect of a new line. The standard technique for valuing

reliability improvements associated with a new line is measure the change in a reliability metric

(e.g., theN-kcriterion, loss of load probability, loss of energy expectation) attributable to the new

line, then value that change using value of lost load (VOLL).

However, we suggest a more direct approach. Remunerating a new line through a VOLL

estimation is both speculative and potentially politically contentious, especially in regions that

have already seen large rate increases in restructured electricity markets. Instead, one could

simply credit a new line with the additional revenue brought about by the lines reliability

improvement, as suggested by Benjamin (2007). Further work along these lines, as well as

simulations using a larger network model, would yield important insights into the promise of the

methodology our paper exposits.


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Cost Allocation for Merchant Transmission

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