long-run incremental cost pricing for negative growth rate
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Chapter 1
Introduction
The electricity power utilities in many countries have been, or are being,
restructured. This has been driven by the desire of Government to meet the increasing
demands for electricity by encouraging independent power producers. The consumers are
allowed to choose their electricity supplier on the basis of price and service provided. In a
deregulated system, operator’s goals are balancing consumer power demand using the
available generation and ensuring that economical and technical constraints are respected.
The prime economical aspect is the social benefit, i.e. power suppliers should obtain
maximum prices for their produced energy, while consumers should pay the lowest prices
for the purchased electric power. Prices have to be defined in a free market economy and
restricted only by power exchange rules. Charging methodology is one important scheme
in the deregulated environment in the way that it can be utilized to recover the investment
cost from network users according to their different impact on the network [3].
The long-run incremental cost (LRIC) pricing methodology developed by
University of Bath in conjunction with Western Power Distribution (WPD,UK) and
Ofgem (the office of gas and electricity markets, UK) has drawn lots of attention from
industry and academic circles and found its application in practice. Compared with the
existing long-run cost pricing methodologies, this charging model can produce forward-
looking charges that reflect both the extent of the network needed to serve the
generation/demand and the degree to which the network is utilized. The traditional LRIC
pricing is based on the premise that the demand in the system is continuously growing
over time, and there will always be a need for network reinforcement some time in future,
which has been modified to reflect how a nodal increment might change the loading level
of the distribution system with a negative load growth, and how this change can be
translated into the costs/benefits to the network [1, 2].
1
GENERATION
TRANSMISSION
DISTRIBUTION
Chapter 2
Power System Restructuring and Deregulation
Since power cannot be stored for marketing but must be sold the instant it is
produced, it was generally assumed that power sector had to be a vertically integrated
monopoly of generation, transmission and distribution [2].
Fig.2.1Vertically Integrated Structure
2.1 Forces behind the Restructuring of Power System
2.1.1 Unfair Tariff Rates-
Since transmission, distribution and generation were handled by a single utility,
the tariff was the average of all the costs of the different services including generation,
transmission and distribution and distributed among all consumers equally.
2.1.2 Lack of Public Resources for Future Development –
Since the power system was run by a single entity, mostly the central government
which work on the least cost method, this caused a financial failure in many developing
countries as they could not generate enough public resources for future expansion and
development of power system.
2.1.3 Political and Ideological Changes-
The reform structure depends or influenced by party politics in most cases.
2
GENERATION TRANSMISSION DISTRIBUTION
ELECTRICITY MARKET
2.1.4 Technological Advancement-
The advance in technology makes low cost power plants owned by independent
power producers very efficient. These independent power producers would not emerge
without reform.
2.1.5 Environmental Impact-
Without the reforms most of the generation was dependent on fossil fuels and
hence reform movement was required to decrease the dependence of electricity
generation on fossil fuels and introduction of renewable energy like solar, wind etc. and
thus decreasing the environmental impact of electricity generation.
2.2 Important Features of Deregulation
2.2.1 Vertically Integrated System Changed to Unbundled System-
Earlier the three components were bundled, if power system were operated and
monitored by a single utility but with the reregulation the components of power system
were unbundled.
Fig. 2.2 Different components of Reregulated Power System
The structural components representing various segment of electricity market are:
Generation Companies (Gencos) -
They are responsible for operating and maintaining generating plant in the
generation sector and in most cases owns the plant.
3
Distribution Companies (Discos) –
Discos assume the same responsibility on the distribution side as in a traditional
supply utility. However, a trend in deregulation is that Discos may now be restricted to
maintaining the distribution network and providing facilities for electricity delivery while
retailers are separated from Discos and provide electric energy sales to end consumers.
Another trend in developing countries is to sell to an investor, or to corporatize, portions
of the distribution system so that investment for reinforcement can be raised and better
operating practices implemented
Transmission Owners (TOs) –
A basic premise of open transmission access is that transmission operators treat
all users on a non-discriminatory basis in respect of access and use of services. This
requirement cannot be ensured if transmission owners have financial interests in energy
generation or supply. A requirement, therefore, is to designate an independent system
operator to operate the transmission system.
Power Exchange (PX) –
The PX handles the electric power pool, which provides a forum to match electric
energy supply and demand based on bid prices. The time horizon of the pool market may
range from half an hour to a week or longer. The most usual is the day-ahead market to
facilitate energy trading one day before each operating day.
Functions of PX-
receive bids from power producers and customers.
match the bids, decide the market clearing price and prepare scheduling time.
provide schedules to the ISO or transmission system operators.
adjust the scheduling plan when the transmission system is congested.
4
Independent System Operator (ISO) –
The ISO is the supreme entity in the control of the transmission system. The basic
requirement of an ISO is disassociation from all market participants and absence from
any financial interest in the generation and distribution business.
The ISO has three objectives-
security maintenance.
service quality assurance.
promotion of economic efficiency and equity
Scheduling Coordinators (SCs)-
SCs aggregate participants in the energy trade and are free to use protocols that
may differ from pool rules.
Fig. 2.3: Market Components and Functions
2.2.2 Regulated Cost Changed to Unregulated Price-
Since earlier the power system was a monopoly the tariff plans etc. were decided
and fixed single handedly in a regulated manner. With deregulation many companies
entered in the business of power system and tariffs etc. were decided by the market forces
in an unregulated manner.
5
Ancillary ServicesCompeting Generators
DispatchBid
Power Exchange Independent System Operator
ForecastSell ControlMonitor
Distributors Transmission Facilities
2.2.3 Consumer Changed to Customer-
With deregulation many companies entered in the business of power system and
hence the consumers which earlier had no choice changed to customer who can chose
from a verity of tariff plans, suppliers etc.
2.2.4 Monopoly Changed to Competition-
Earlier power system was a single utility and hence was a natural monopoly. With
deregulation many players came into the market and competition was introduced.
6
Chapter 3
Transmission Pricing
3.1 Introduction
Pricing of transmission services plays a crucial role in determining whether
providing transmission services is economically beneficial to both the wheeling utility
and the wheeling customers. Transmission pricing is one of the most complicated issues
in restructuring electricity supply because of the physical laws that govern power flow in
transmission network, and the need to balance supply and demand at all times. Since
generators and customers are all connected to the same network, actions by one
participant can have significant consequences on others making it difficult to investigate
the cost each participant is responsible for. Electricity unlike many other commodities
cannot be stored easily and supply has to match demand at all times. The transportation
of electricity is constrained by physical laws which need to be satisfied constantly in
order to maintain the reliability and security of the power system. It became obvious that
the transmission network is the main impediment to energy privatization. In all power
markets around the world, generation and distribution parts are horizontally unbundled
and have competition, but the transmission system is a natural monopoly and therefore it
should be regulated. In this situation, defining a pricing scheme for transmission services
to reduce the effects of transmission monopoly on market competition is very important.
In this respect, transmission pricing in an equitable transparent manner to provide
coherent economic incentives for efficient transmission operation and its expansion. To
compensate for the revenue requirements of the owners of the transmission system and
encourage its future expansion, transmission pricing schemes should be designed fairly.
Also the schemes must aim to achieve the objective of maintaining system security by
encouraging proper operation and maintenance of existing and investment in new
facilities [2].
7
3.2 Objectives of Transmission Pricing
Ideally, the transmission tariff policy and methodology should satisfy the
following objectives:
- Ensure revenues adequate to compensate for the costs of operation and
maintenance of the transmission system;
- Encourage the efficient use and development of the network, both in the short and
long term;
- Ensure equitable treatment of, and non-discrimination among, market participants
who use the transmission system;
- Establish a price structure which is economically sound, simple enough for users
to understand and transparent to administer;
- Provide pricing stability over time;
- Provide flexibility to adapt to changing circumstances in the short and long term;
- Accommodate embedded generators and private generation stations [2].
3.3 Transmission Pricing Paradigms
The goal of the pricing schemes is to allocate and/or assign a part of the existing
and the new cost of transmission system to wheeling customers. Transmission pricing
paradigms are the overall processes of translating transmission costs into overall
transmission charges. These paradigms are:
3.3.1 Rolled-in transmission pricing
In this paradigm all existing transmission system and the new costs of system
operation and expansion, regardless of their cause, are summed up (“rolled-in’) into a
single number. This cost is then allocated (divided) among various users of the
transmission system, including the utility native (retail) customers, according to their
”extent of use” of the transmission system. Some of these “allocation” methods are:
8
Postage Stamp Method-
It depends only on the amount of power moved and the duration of use,
irrespective of supply and delivery points, distance of transmission usage or the
distribution of loading imposed on different transmission circuits by a specific
transaction.
Contract Path/MW Mile Method-
In this method, a specific path between the points of delivery and receipt is
selected for a wheeling transaction called contract path. Loading of each transmission
line due to each transaction is obtained and multiplied by the line length and summed
over all lines in grid to find use of grid by the transaction. Transaction charged in
proportion to their utilization of grid. But in this power flow outside the contract path and
to neighboring utilities is not considered.
3.3.2. Incremental Transmission Pricing-
According to this paradigm only the new transmission costs caused by the new
transmission customers will be considered for evaluating transmission charges for these
customers. The existing system costs will remain the responsibility of utilities present
customers .Incremental cost of a transaction is evaluated by comparing the transmission
system cost with and without the entire transaction. It also considers the reinforcement
cost in it.
Short-run incremental cost pricing (SRIC)
Long-run incremental cost pricing (LRIC)
3.3.3. Marginal Cost Pricing-
It is the cost of loading a marginal increase in transacted power. In this approach
multiply the cost for a unit of additional transaction by the size of the transaction [2].
Short-run marginal cost pricing (SRMC)
Long-run marginal cost pricing (LRMC)
9
Chapter 4
Long Run Incremental Cost
Network charges are charges against network users for their use of a network in
order to recover the costs of capital, operation and maintenance of a network and provide
forward-looking, efficient messages to both consumers and generators. Network charges,
therefore, should be able to truly reflect the extent of the use of the network by network
users. Efficient charges can help to release constraints and congestion in the network,
deferring prospective network expansion or reinforcement. The present pricing
methodology adopted by the majority of the distribution network operators (DNOs), the
distribution reinforcement model (DRM), however, cannot provide location economic
signals as the costs of network assets are averaged at each voltage level. Long-run cost
charging methodologies, due to its merits of being able to reflect the cost of future
network reinforcement caused by the nodal increment are recognized as more
economically efficient. Most long-run cost pricing methods evaluate costs associated
with projected demand/generation pattern and subsequently allocate the costs among new
and existing customers. These approaches, however, can only passively react to a set of
projected patterns of future generation or demand, failing to proactively influence the
patterns of future generation or demand through economic incentives. Up to2005,
investment cost-related pricing (ICRP) utilized, which works based on distance or length
of circuits, is the most advanced long-run pricing model. One recent development in
long-run cost pricing methodology is the long-run incremental cost (LRIC) pricing
methodology developed by the University of Bath in conjunction with Western Power
Distribution (WPD, UK.) and Ofgem (the office of gas and electricity markets, UK.).This
charging approach examines how a nodal increment of generation/demand might impact
the time to reinforce system assets and then translate the time change into charges .The
decision concerning of being penalty or reward is based on whether the nodal
perturbation advances future investment or defers it. This method, compared with
existing long-run cost pricing approaches, can produce cost-effective charges that reflect
both the extent of the network needed to serve the generation or demand and the degree
10
to which the network is utilized. As being able to send forward-looking signals to
influence prospective network connections, this charging model has been adopted by
WPD in its EHV network and is being under consideration by several other DNOs [2, 4].
4.1 Long-Run Network Charging ModelIn the original LRIC pricing model, for components in network that are affected
by a nodal injection, there will be a cost or a credit associated for the injection according
to Whether the network investment is accelerated or deferred. In this charging model, the
time to reinforce is evaluated by assessing the time for a loading level to reach the full
capacity of system components under a certain load growth rate with and without the
nodal injection. The proper modeling and calculation of load growth rate, as a result, is
essential for this charging model.
The LRIC model is implemented using the following steps [2,4].
4.1.1. Present Value of Future Investment
If a circuit l has a maximum allowed power flow ofC l, supporting a power flow of
Pl, the number of years it takesPl, to grow toC l, under a given LGR (load growth rate) r,
can be determined with
C l=Dl∗(1+r )nl ( 4.1 )
Where, nl is the number of years taking to PlreachC l, taking the logarithm of it gives,
nl=logC l−log Dl
log (1+r )(4.2)
Assume that investment will occur in thenlth year when the circuit utilization reaches C l,
and with a chosen discount rate of d, the present value of future investment will be
PV l=Assetl
(1+d )nl(4.3)
Where, Assetl, is the modem equivalent asset cost.
11
4.1.2. Cost Associated With Power Increment
If power flow change along line C is ∆ Pl as a result of anodal injection, the time horizon
of future reinforcement will change from yearnl, to year nlnewdefined by
C l=( Dl+∆ Pl )∗(1+r )nlnew(4.4)
new investment horizon nlnew
nlnew=
log Cl−log(Dl+∆ P l)log (1+r )
(4.5)
The new present value of future reinforcement becomes,
PV l=Asset l
(1+d )nlnew
(4.6)
The change in present value as a result of the injection is given by
∆ PV l=PV lnew- PV l =Assetl ( 1
(1+d )nlnew
− 1(1+d)nl
) (4.7)
The incremental cost for circuit l is the annuitized change in present value of future
investment over its life span,
IC l=∆ PV l∗annuityfactor (4.8¿
4.1.3. Calculation of LRIC
The nodal LRIC charges for a node are the summation of incremental cost over all
circuits supporting it, given by
L RIC N= ∑l IC l
∆ Pinl (4.9)
Where,∆ Pinl is the size of power injection at node i, and here we assign it to be 1 MW.
12
Input system data
Base case power flow analysis
Base power flow
Incremental power flow analysis
LRIC charge evaluation
Use of system charges
4.1.4. Flowchart of LRIC The core of flow chart is contingency analysis, incremental power analysis and
charge assessment [4].
Fig 4.1 Flow Chart of LRIC Charging Model
4.2Parameters Influencing LRIC Charging
4.2.1 Load Growth RateDemand growth represents the increase in energy demand over time, occurring
through natural growth of a service territory resulting from the increased prosperity,
productivity or population. Load growth rate is an averaged index derived by annuitizing
the load growth in a particular time span. In the LRIC charging model, in order to
simplify the process of assessing time to reinforce without and with nodal injection,
assumed uniform loading growth rate along each circuit. In reality, however, loads at
13
different buses may grow at quite different rates, leading to relatively diversified loading
growth rate for each circuit.
4.2.2 Component Reinforcement CostGenerally, the reinforcement costs of circuits or transformers need to be recovered
though LRIC charging model. Based on their different functions or ownerships, these
branches can be roughly divided into two different categories:
Transformer/circuit branches which have certain reinforcement costs;
Transformer/circuit branches which have no costs (zero-cost branches).
Those zero-cost branches are mainly branches, whose costs have been recovered
from network users, or branches which are owned by network users, or branches which
are used to connect different part of the substations, such as circuit breaker, and switches.
All the components costs are annuitized through annuity factor into annuity costs, which
is the actual amount of reinforcement costs that are recovered each year [2].
4.2.3 Annuity FactorAn annuity factor is the present value of an income stream that generates fixed
income each period for a specified number of periods .The annuity factor can therefore be
multiplied by the periodic annuity payment to determine the present value of the
remaining annuity payments [2].
4.2.4 Discount rate
The interest rate used in discounted cash flow analysis to determine the present value of
future cash flows. The discount rate takes into account the time value of money (the idea
that money available now is worth more than the same amount of money available in the
future because it could be earning interest) and the risk or uncertainty of the anticipated
future cash flows (which might be less than expected).
14
Chapter 5
LRIC Pricing for Negative Load Growth Rate
5.1 Introduction
Long-run marginal or incremental cost pricing models account for capital
investment cost in the network as a result of generation/demand increment at a given
location. Traditionally, long-run incremental cost (LRIC) models assume that the demand
in the system is continuously growing (positive growth rates assumed); thus, the network
reinforcement is always required some time into the future. This positive growth rate
assumption however does not reflect the whole reality that distribution network operators
(DNOs) are facing. Some parts of the distribution network experience prolonged negative
load growth. This can be driven by heavy industries shifting to elsewhere in the country
or to other parts of the world [4,5].
Negative load growth rates could have two consequential impacts to the network
planning and operation:
when the network assets come to the end of their useful life, their replacement
can be smaller, and there would be cost savings to DNOs with smaller
replacements;
If the assets’ loading levels fall to zero before the end of their useful lives, then
the assets become redundant. There would be cost-saving in the maintenance and
operation of these assets and in the capitals if the assets are re-used elsewhere.
For an underlying negative load growth rate, the asset utilization in the network
can still vary significantly from one place to another. If the asset’s loading level is very
low, i.e., the asset has a huge spare capacity, and if this capacity is still increasing due to
a negative load growth, then there are great benefits to the network operator if the asset’s
loading level drops to zero. Through network charges, DNOs can encourage demand
customers to leave early or encourage distribution generation (DG) to connect at an
appropriate point in the network. If on the other hand, the assets’ loading level is very
high, then there would be little benefit to encourage demand to leave or DG to connect.
15
An extended LRIC model that calculates network charges for network assets with
prolonged negative load growth rates. The model aims to reflect:
The magnitudes of benefit to the network in the future when the asset’s utilization
drops to zero and
How a nodal perturbation might accelerate or delay the future benefits. For
network components that support a nodal power injection or withdrawal, there
will be an associated credit if the benefit is accelerated or a cost if it is delayed.
5.2 Mathematical Formulation of Long-Run Incremental Cost Pricing
For Negative Growth RatesThe time horizon to reach the network benefit is the time taken for the circuit’s
loading level to fall from the current level to zero, or for the unused capacity to grow
from the present level to the full capacity. The LRIC charge for the circuit is the
difference in the present value of future benefits with and without the nodal perturbation.
The proposed charging model can be implemented through the following steps.
Deriving the Time Horizon to Reach Network Benefit:
C l=Dl∗(1−r d)nl+Sl∗(1+rs)
nl (5.1)
Where circuitl has a maximum allowed power flow ofC l, supporting a power flow ofPl,
the number of years it takesPl, to grow toC l, under a given LGR (Load Growth Rate), rd,
Sl is the Spare capacity increasing with the rater s.
For a very small r s andrd, (1) can be expanded using Taylor’s series:
C l=Dl+Sl+(S l∗r s−Dl∗rd)nl (5.2)
For (5.2) to be true for all future yearsnl, the second term in the bracket at the RHS of the
equation must be zero; this leads to (3) giving the relationship between the growth rate of
the spare capacity and the load growth rate:
r s=(D¿¿l∗r D)/Sl ¿ (5.3)
Using r s from (5.3), the number of years for the circuit’s spare capacity to grow from Sl
to C l can be determined by
C l=(C l−Dl )∗¿¿ (5.4)
16
Rearranging the equation gives the time to reach the benefit as
nl=logC l−log (C l−Dl )
log (1+r s) (5.5)
Evaluating the Present Value of the Future Benefit: Assume that investment will
occur in thenlth year when the circuit utilization reaches C l , and with a chosen discount
rate of d, the present value of future investment will be
PV l=Assetl
(1+d )nl (5.6)
Where, Assetl, is the modem equivalent asset cost.
Evaluating the cost of an additional Power Injection or Withdrawal at node N.
If power flow change along line C is ∆ Pl as a result of a nodal injection∆ P¿ at node N,
the time horizon of future reinforcement will change from yearnl, to year nlnewdefined by
C l=(C l−Dl−∆ Pl)∗¿¿ (5.7)
Equation (5.8) gives the new investment horizon nlnew as
nlnew=
log Cl−log(C l−Dl−∆ Pl)log ¿¿
(5.8)
The new present value of future reinforcement becomes,
PV l=Asset l
(1+d )nlnew
(5.9)
The change in present value as a result of the injection is given by
∆ PV l=PV lnew- PV l =Assetl ( 1
(1+d )nlnew
− 1(1+d)nl
) (5.10)
Calculating the Long-Run Incremental Cost: The long-run incremental cost for
circuit l is the annuitized change in present value of future investment over its life span,
17
the nodal LRIC charges for a node are the summation of incremental cost over all circuits
supporting it, given by
LRICN=∑l ∆ PV l∗annuityfactor
∆ P¿
(5.11)
Where,∆ P¿ is the size of power injection at node i.
18
Chapter 6
Case Study and Results
The demonstration of the proposed approach is on a simple two-busbar network
as shown in fig. 6.1. The circuit Lf connecting busbars 1 and 2 is rated at 45 MW and
costs £31293400 at its modern equivalent asset value.
Assuming a discount rate of 6.9% and a load growth rate of ±1%, Fig. 6.2 gives
the LRIC charge versus circuit utilization for withdrawal power from busbar 2.
Bus 1 Lf Bus 2
D
Fig. 6.1 Two busbar network with demand D
×104
3.6
3.3
3.0
2.7
2.4
2.1
1.8
1.5
£/MW/year 1.2
0.9
0.6
0.3
0 20 40 60 80 100
% Utilization
Fig. 6.2 LRIC charges for Negative and positive Load Growth rates
19
1% Negative Growth Rate
1% Positive Growth Rate
For a negative growth rate, withdrawing power will increase the loading level of
the circuit, thus delaying the network benefit. The customer will be charged; this is
illustrated by the solid line in Fig.6.2.
When the circuit utilization is high, it takes a long time to reach the network
benefit; thus, the present value of future benefit would be very small. However, if the
circuit utilization is low, there would be imminent benefit to the network if the last few
customers would leave the network, thus having huge charges for additional power
withdrawal.
In contrast, a positive load growth rate will require network reinforcement in the
future; withdrawing power from node 2 will bring forward the time to reinforce the
circuit, thus giving rise to LRIC charges as shown by the dotted line. At high utilizations,
additional power withdrawal would trigger imminent reinforcement, hence having huge
network charges.
20
Chapter 7
ConclusionsLong-run incremental cost pricing methodology utilizes the headroom of network
components to translate the investment horizon with and without the nodal increment into
an incremental cost to the network .Unlike the existing long-run charging models, it does
not need to assume the size and siting of future generation or demand. Instead, it relies
entirely on the capability of the existing network to accommodate future generation and
demand, and thus provides a forward-looking economic price signal to proactively
influence the development of future generation/demand. This in turn helps the network
planners to form a more realistic projection in the future generation/demand patterns in
forward planning their networks. This charging model respects both the extent to which a
network is used as well as the level of utilization of the network components. The LRIC
charges monotonically increase as the degree of the circuit utilization increases reflecting
the acceleration of future reinforcement. The present LRIC charging principle is based on
the assumption that demand across the entire distribution network is continuously
growing over time and there would always be a need for network reinforcement some
time in future. In reality, there may be some parts of the network with prolonged negative
growth rate. The proposed pricing principle seeks to directly relate a nodal power
perturbation to its benefit to the network. This report illustrated that network charges
could vary drastically depending on the assumption of underlying load growth rates.
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References
[1] Furong Li, Chenghong Gu, “Long-Run Incremental Cost Pricing for Negative Growth
Rates”, IEEE Transactions on Power Systems, 2011.
[2] Chenghong Gu, Furong Li, Lihong Gu , "Application of long-run network charging
to large scale systems",2010 7th International Conference on the European pp.1–
5,2010.
[3] Loi Lai Lei Power System Restructuring and Deregulation, (Edited), John WileySons
Limited, 2001.
[4] D. Shirmoharnmadi, X.V. Filho, B. Gorenstin et al., "Some fundamental, technical
concepts about cost based transmission pricing , IEEE Transactions on Power
Systems , vol. 11, no. 2, pp. 1002-1008,1996.
[5] F. Li, and D. L. Tolley, "Long-Run Incremental Cost Pricing Based on Unused
Capacity," Power Systems, IEEE Transactions on Power Systems, vol. 22, no.4, pp.
1683-1689, 2007.
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