LongTermPlanning organizational behaviour

EE/Econ 552
Long-Term Planning
J. McCalley
1
A complementary treatment focused on resource adequacy is given in “Maintaining
reliability in the modern power system,” US Dept. of Energy, Dec., 2016,
www.energy.gov/sites/prod/files/2017/01/f34/Maintaining%20Reliability%20in%20the%20Modern%20Power%20System.pdf

2
What I will do in this class
1. Describe the need for adequacy;
2. Identify who ensures adequacy for
a. Traditionally regulation
b. Competitive electricity markets
3. Distinguish capacity markets from long-term planning;
4. Describe the long-term planning process;
5. Describe generation expansion planning (GEP) problem;
a. Give formulation and relate it to capacity markets
b. Describe several critical features of GEP
6. Describe two other tools:
a. Transmission expansion planning (TEP)
b. Cooptimization expansion planning (CEP)

3
Adequacy
“Adequacy is the ability of the electric system to supply the
aggregate electric power and energy requirements of the
electricity consumers at all times, taking into account
scheduled and reasonably expected unscheduled outages of
system components.”
“Definition of ‘Adequate Level of Reliability’,” North American Electric Reliability Corporation (NERC),
approved by the NERC Operating Committee and the NERC Planning Committee, December 2007,
available at http://www.nerc.com/docs/pc/Definition-of-ALR-approved-at-Dec-07-OC-PC-mtgs.pdf.
The single most influential way to maintain adequacy
is to ensure the area’s generating capacity will almost
always exceed the area’s peak requirement for each
year in a given planning horizon.
Two qualifications to the last statement…

4
Adequacy
Generator failures: The “almost always” part of this last
statement recognizes that generation may fail, and so no
matter how much generation is built, it is impossible to
ensure the area’s generation capacity will definitely exceed
the area’s peak requirement for each year in a given planning
horizon (there is always the possibility, albeit very small, that
enough generation may fail simultaneously to cause
remaining generation to be unable to meet the demand).

5
Adequacy
Non-generator means of ensuring adequacy: Adding
generation capacity is not the only way to improve adequacy.
• Other node-based options: Alternatively, one may consider
purchasing capacity from neighboring utilities, demand-
side means (e.g., conservation programs and/or load
control during peak periods), and/or storage.
• Transmission: There may be situations where the total
generation is in fact sufficient, but the transmission
between that generation and the load is insufficient to
carry all of the generation that can be produced. Although
building generation close to the load center may be an
option, it might be an expensive one. In such a case,
adding transmission may be the most cost-effective means
of achieving adequacy.

6
Who Ensures Adequacy in Traditional Regulation
In traditional regulation, for any given service area, there is a
single entity having responsibility, actually an obligation, to
maintain adequacy for the region’s customers - the vertically
integrated utility. The vertically integrated utility accepts this
obligation in exchange for a guarantee that they be allowed to
earn a “fair rate of return” on their investments through
energy rates charged to customers. Four observations to
make about this “exchange”:
1. Compact: This “exchange” is an agreement between the electric utility
and its customers, known as the “regulatory compact.”
2. Monopoly: It is usually provided that the vertically integrated utility will
be the only organization having the regulatory compact within a given
service area, thus, the regulatory compact ensures the vertically
integrated utility operates as a monopoly.

7
3. Regulator: It is awkward for the utility to make an agreement with all of its
customers. Thus, the customers it serves are represented by the state
regulator (the “utility board,” the “public service commission,” or the
“public utilities commission”). The state regulator has sole authority to
regulate the rates the electric utility charges the people of the state. The
state regulator also perceives oversight of resource adequacy within their
state to be its responsibility, e.g.,
• Iowa Utilities Board: “Performance Reports for the Iowa Utilities Board (IUB)
highlight the services the IUB provided to Iowans, along with results achieved to
ensure utility service reliability and to improve and expand utility service
infrastructure in Iowa.” (see https://iub.iowa.gov/iowa-utilities-board-performance-reports-0) Also,
“Investor-owned electric utilities and electric cooperatives must maintain records regarding electric service
reliability and outages, as required by 199 IAC 20.18.” https://iub.iowa.gov/edr-electric-delivery-reliability
• Organization of MISO States: “Resource Adequacy: (see www.misostates.org/index.php/about/strategic-priorities)
• Monitor resource adequacy implications of solutions proposed through the Resource Availability and
Need (RAN) Initiative
• Ensure market pricing changes are appropriately accounted for in resource availability
• Ensure potential new reliability requirements align w/ state & local planning processes & retail tariffs
• Evaluate and improve the OMS-MISO Resource Adequacy Survey
• Advance resource accreditation practices that properly value resource attributes while providing
accurate accounting for performance risk
The OMS was
established to
represent the
collective
interests of
state/local utility
regulators in the
MISO region.

8
4. Energy rates: It is partly through energy rates that revenues are provided
to the utility to maintain adequacy1. However, the maintenance of
adequacy is more of a capacity issue rather than an energy issue. The
difference between capacity and energy is that whereas capacity
determines whether demand can be met at a singular point in time;
energy is the integration of that demand (or the generation that supplies
it) over a time interval. Thus, to the extent to which energy rates are used
to pay for capacity needs, there needs to be an “adder” to the short-term
cost of energy to pay for the longer-term cost of capacity. Regulators are
aware of this need and understand they must be willing to allow the
electric utility to reflect this adder in their energy rates for residential and
small commercial customers.
1 Residential and smaller commercial users are typically billed only for energy use; larger
commercial users and industrial users may be also billed for their monthly peak demand,
which is a capacity-related component of the bill.

9
Who Ensures Adequacy in CEM?
When some regions in the US introduced competitive electricity markets
(CEM), the regulatory compact had to be revisited. The reason for this
was that because CEM necessarily relied on having many competitive
market participants, the vertically integrated utility
• could no longer be granted monopolistic status;
• neither could a rate of return be guaranteed, at least not for the parts
of its organization which participated in the CEM.
In CEM, because the regulator no longer provides these two guarantees
to the utility, the utility could no longer be expected to accept the
obligation to ensure the reliability of the service area. This left open the
question: what is the revenue source to maintain adequacy?
Early answer was “The day-ahead and real-
time (DART) electricity markets.”

10
The thinking: At the heart of the CEM were the day-ahead/real-time
(DART) markets where market participants provided offers to sell energy
and ancillary services.
• Because revenues received by energy suppliers was dictated by the
market clearing price, and because the market clearing price would
by definition be equal to (for the marginal units) or higher than (for
all other units) the offers to sell energy made by the market
participants, there would be a difference between what market
participants were paid and what they were willing to be paid (their
costs), and this difference, integrated over time, would be sufficient
to fund development of additional generation capacity.
• An important feature of this thinking is that the price of energy would
become particularly high during periods of peak demand, and
extremely high during the rare moments when generation is just
sufficient (or insufficient) to meet demand. This is illustrated on the
next slide.

11
Baseload units are making much money when price is established by
emergency peakers. These short-duration bursts of revenue are very
useful to incent suppliers to build additional capacity. 3 comments:
P. Cramton, A. Ockenfels, and S. Stoft, “Capacity market fundamentals,” May 26, 2013, unpublished paper, available at
http://www.cramton.umd.edu/papers2010-2014/cramton-ockenfels-stoft-capacity-market-fundamentals.pdf.
$50/MWh
$90/MWhr
$130/MWhr
$160/MWhr
$300/MWhr
Peak condition MW
Price-responsive
demand
reduction
Baseload units
Mid-range units
Efficient peakers
Emergency peakers
Expensive peakers
Solid line shows normal supply
curve. Dashed line shows supply
curve when some units (in this
case, the expensive peakers) fail.
1. True vs. offered: The figure is based on
suppliers offering true marginal costs,
which they do when capacity
significantly exceeds demand. But when
capacity is just sufficient (or insufficient)
for supplying demand, suppliers increase
their offers to push the clearing price up
based on the realization that if the
market needs all the supply it can get, it
will be impossible to offer too high a
price, a behavior that is consistent with
the following supplier thinking: “Even if I
offer far above the next highest offer, I
will be selected (and will become the
marginal unit, i.e., the price-setting
unit).” Thus, the price can soar to very
high levels during such a condition.
This is how a market operates when the commodity
is scarce. There exists a large literature on the topic
of scarcity pricing which argues that such price
increases are not bad in and of themselves and in
fact provide the very signal that suppliers need to
increase their capacity.

12
2. Price caps: Most electricity markets provide price caps to limit the energy price that can be
reached during scarcity conditions. (PJM imposes a price cap of $3.7k/MWhr; MISO
$3.5k/MWhr, ERCOT $9k/MWhr) to protect customers against extremely volatile and very high
prices, see http://files.brattle.com/files/14169_4_3-brattle-paper-shortage-pricing.pdf). It has
been argued that such price caps inappropriately skew the need for capacity investment by
limiting the additional revenues that can be obtained during scarcity conditions and therefore
should not be allowed. However, some argue that the basic problem cannot be addressed by
lifting the price cap because energy price during blackouts is not known and cannot be
identified as a market equilibrium.
3. Blackouts: The extreme form of an
event caused by a lack of adequacy is
a blackout whereby many customers
are interrupted for a significant
duration. The cost of such sustained
load interruptions has been referred
to as the value of lost load (VOLL),
and estimates vary greatly with
region and with type of customer, as
indicated in the figure (note units are
$/kWh, to be multiplied by 1000 to
get $/MWh). There is a 9/2020
MISO update on these data here.
There is uncertainty with VOLL. But VOLL is much higher
than the price caps imposed on most markets today. And so
it may follow that price caps of ~ $3700/MWhr do distort the
market. Therefore, lifting those price caps would provide a
market signal to incentivize capacity investment. However…

13
However, reference [1] argues that blackouts cannot be priced simply
because, by definition, the commodity (energy) cannot be bought and
sold during a blackout and thus it is not possible to establish a scarcity
price during a blackout. That is, “electricity markets cannot optimize
blackouts,” and “the price that is being paid to generators during
blackouts must be set by administrative rules”.
This reasoning has led to the concept of the “missing money,” which
refers to the fact that the energy markets do not provide revenue
sufficient to induce capacity investment, a concept that is consistent
with experience of several years of real-time and day-ahead market
operation, where it was observed that construction of new generation
capacity was not keeping pace with generation retirements and
demand growth, so that reserve margins were declining. Historical
installed reserve margins (IRMs) since 1999 are indicated on the next
slide for PJM and for NYISO.
[1] P. Cramton, A. Ockenfels, and S. Stoft, “Capacity market fundamentals,” May 26, 2013, unpublished paper, available at
http://www.cramton.umd.edu/papers2010-2014/cramton-ockenfels-stoft-capacity-market-fundamentals.pdf

14
Are reserve margins decreasing?
NYISO
PJM
ISONE
0%
5%
10%
15%
20%
25%
30%
2010 2011 2012 2013 2014
Planned
ReserveMargin
Actual
Reserve
Margin
Planned Reserve Margin Actual Reserve Margin
MISO
Conclusion: Unclear (all of
above have capacity markets).

15
Are reserve margins decreasing?
SPP
Conclusion: Maybe. SPP does
not have capacity market.

16
So the answer: “DART markets can provide the revenue to
maintain adequacy in CEM” is not obviously the right approach
(although, some would argue, it may not have been allowed to
work in most places around the country).
Alternative answer: Capacity markets.

17
The closest thing we have to
planning markets today is the
capacity market.
The capacity market has been
motivated by the “missing money”
problem, where
• The real-time market price is
capped so that during (rare) very
high-stress time periods, prices
(and the system) avoids socially-
unacceptable performance.
• This results in suppliers not
seeing the signal (and money) to
build more capacity.
• So “tight” real-time market
price-caps are generally coupled
with capacity markets to supply
that “missing money.”
Capacity markets today, where they
exist, only address generation
capacity. They do not address
transmission capacity. Transmission
capacity, despite its close interlinkage
with generation capacity, is
addressed in a separate process.

Today’s Capacity Markets
18
ISO Cap
mrkt
Number of auctions, time before delivery period, and delivery period
duration [1] and other info;
OR Why they don’t have cap market.
Participants Recent
prices
($/MW-
day) [1]
MISO Yes Single auction 2 mnths before 1-yr delivery period. OMS says resource
adequacy within MISO is state/local responsibility; unlike other Eastern Interconnection
RTOs, MISO is composed of traditional vertically-integrated utilities subject to state/local
regulation; OMS members have jurisdiction over type/amount of gen constructed within
their boundaries by utilities they regulate & costs recovered by those utilities [2]. Also
see MISO BPM011 [3].
Existing power plant owners 2
NYISO Yes Seasonal auction, monthly auction, final auction; from 6 mnths to few
days before 1-mnth delivery period
Existing power plant owners 73-328
PJM Yes Single auction 3 yrs before 1-yr delivery period Existing power plant owners
and project developers
77-188
ISONE Yes Single auction 3 yrs before 1-yr delivery period Existing power plant owners
and project developers
234
CAISO No Bringing cap mrkt in spurred by high wind/solar increase+concern for un-
economic gas units [4], but Cal legislatively-mandated long-term capacity
procurement plan [4]. Cal lets gas self-schedule to keep their capacity [5].
NA NA
ERCOT No Enrgy capped $9k/mwh instead of ~$2k in other energy mrkts: scarcity
price
NA NA
SPP No SPP lets coal self-schedule to keep their capacity [5]. NA NA
[1] US Government Accountability Office, GAO-18-313, “Electricity Markets: Four Regions Use Capacity Markets to Help Ensure Adequate Resources but FERC Has Not Fully Assessed Their Performance,” Dec., 2017, www.gao.gov/assets/690/688811.pdf.
[2] G. Bade, “FERC rejects generator proposal for CAISO capacity market” Utility Dive, Nov. 21, 2018, www.utilitydive.com/news/ferc-rejects-generator-proposal-for-caiso-capacity-market/542833/.
[3] MISO Business Practice Manual BPM11, “Resource Adequacy.” See section 5.5, “Planning Resource Auction.” https://cdn.misoenergy.org//BPM%20011%20-%20Resource%20Adequacy110405.zip.
[4] Organization of MISO States, “State Regulatory Sector Response September Hot Topic on Resource Adequacy,” Sept, 2016, www.misostates.org/images/stories/Filings/HotTopics/2016/Item_7_OMS_Hot_Topic_Comments_FINAL.pdf.
[5] J. Gheorghiu, “Capacity pricing changes: how each power market plans to account for resource adequacy,” Deep Dive, Dec., 2018, https://www.utilitydive.com/news/capacity-pricing-changes-how-each-power-market-plans-to-account-for-resour/542449/.

19
Capacity Market
Process &
Resource
Adequacy
Evaluation
The picture to
the left is for
PJM, but other
ISOs look the
same, with
exception of the
capacity market.
Transmission
Planning Process
(RTEP in PJM;
MTEP in MISO)
Proposed
generation
projects
Generati
on Queue
FINANCIAL MARKETS (a side comment): “Like other commodities, wholesale electricity is transacted both physically and traded financially. And
like other financially traded commodities, specialized environments, such as exchanges and electronic trading platforms, have evolved to
facilitate financial trading. For instance, financial electricity is traded on the New York Mercantile Exchange (“NYMEX”), the Intercontinental
Exchange (“ICE”) and Nodal Exchange. These exchanges offer futures, options and swaps to trade electricity specific to PJM and at multiple
locations (or nodes) on the PJM system. These so-called “secondary markets” in PJM electricity are not regulated by the FERC. They are separate
from PJM’s FERC-regulated markets and affect PJM’s markets only very indirectly. While these secondary financial markets are not the subject of
today’s hearing, I raise them only to clarify that highly developed, highly liquid and specialized forums exist for those that wish to hedge or
speculate on PJM electricity prices outside of the PJM market itself. PJM’s markets are fundamentally designed to facilitate the dispatch,
purchase, sale and delivery of physical electricity from power plants to wholesale electricity buyers, who in turn sell retail electricity to homes
and businesses.”
- V. Duane, VP Compliance 7 External Relations, PJM, “Examining the role of financial trading in the electricity markets,” Nov. 29, 2017, in testimony to the US House of Representatives Committee on
Energy& Commerce/Subcommittee on Energy. www.pjm.com/-/media/library/reports-notices/special-reports/20171129-duane-testimony-to-house-energy-subcommittee-on-financial-trading.ashx.
View of Today’s Electricity Market Systems

20
Capacity Market
Called “Planning Resource Auction” in MISO

21
Capacity Market
ZoneNewCapZ
SysNewCapZ
Existing Capacity
Bidding In
New Capacity
SysClearedCap=Σz ClearedCapz
SysNewCap=Σz SysNewCapz
ZoneNewCapz, is capacity specific to
zone z, that is not subject to export.
How does MISO know what
“SysRequiredCap” and
“RequiredCapz” should be?
CONE=cost
of new entry

22
Capacity Market
How does MISO know what
“SysRequiredCap” and
“RequiredCapz” should be?
Answer:
They evaluate reliability indices
using resource adequacy software.
LOLE (loss of load expectation) is the
amount of time during a planning
period the system can expect to
interrupt load.
Industry norm:
LOLERequired≤1 day in 10 years
So MISO identifies SysRequiredCap and
RequiredCapz to satisfy this requirement.
See http://home.engineering.iastate.edu/~jdm/ee653/ee653schedule.htm for more info on reliability eval.

23
Capacity Market
Where do the revenues come from to fund a capacity market?
An auction is conducted for suppliers using a specified demand curve, illustrated below.
The demand curve is determined based administratively, based on the cost of new entry
(CONE).
https://business.directenergy.com/understanding-energy/managing-energy-costs/deregulation-and-energy-pricing/capacity-markets
Capacity obligations are determined by a LSE’s peak load contribution (PLC) during a
certain timeframe. In MISO, an LSE PLC is determined by their usage during the peak
hour from the previous year. The peak hour is the hour during which the usage was the
highest across the ISO. The LSE is charged the market clearing price × PLC.
T. Jenkin, P. Beiter, and R. Margolis, “Capacity payments in restructured markets under
low and high penetration levels of renewable energy,” NREL Technical Report NREL/TP-
6A20-65491, Feb, 2016, available https://www.nrel.gov/docs/fy16osti/65491.pdf.

24
Three additional questions that capacity markets
do not answer…
• How do vertically-integrated rate-regulated utilities, under
traditional regulation, know what kind of technologies to build?
• How do market participants know what “Offer Price” to submit
and how do they know what kind of generation to build?
• How can ISO’s forecast generation builds beyond what is in the
interconnection queue?
Solutions to the Generation Expansion
Planning (GEP) problem can contribute to
answering these questions.

25
Generation Expansion Planning (GEP, e.g., EGEAS or Electric Generation
Expansion Analysis System)
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26
Generation Expansion Planning (GEP)
What does the solution to this problem give you?
• What to build
• Where
• When
• How much
1 2 3 4 5 6 7 8 20 21 22 23 24 25
400MW
NGCC,
bus 34
200MW
Wind,
bus 98
2000MW
Nuke,
bus 62
100MW
Solar,
bus 12
What input data does this problem require?
• Existing generation fleet:
• Cost data: Fuel cost, Heat rate, O&M
• Capacity credit
• Capacity factor
• Age, expected life, salvage value
• Data for investment options:
• Data required by existing fleet
• Investment cost
• Demand data
• Growth rate
• Load duration curve & slices/yr
• Reserve requirements
• Transmission system data
• Discount rate
• Simulation time
• Net present value
of total cost.
• Net present value or levelized cost for specific capacities.

27
Net Present Worth
Discount rate i: annual income as a percentage of amount invested
Discount factor: The discount factor is given by ζ=1/(1+i) where i is
the discount rate. Thus we have that
  1
1
1
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


 t
t
i

The objective function includes all costs of building, retiring, and
operating the generation resources over the time period t=1,…,T.




 




 






 





 





 




 





 




 





 




 

MCosts
VariableO
t i s
s
t
s
j
i
j
j
t
ionalCosts
FuelOperat
i s
s
s
j
i
j
j
j
i
t
t
MCosts
FixedO
t i j
t
j
i
fixed
j
t
ue
SalvageVal
i j
T
j
i
T
j
i
T
Costs
Investment
i j
add
t
j
i
t
j
i
t
t
h
P
OM
h
P
H
FC
Cap
OM
Cap
SV
Cap
I
&
,
,
,
var
1
,
,
,
1
&
,
,
1
,
,
,
,
1
,
,
,
,
1
min
  

 


 















































We assume the investments made in year 1 are already present
value, and so it is not until year 2 that we need to discount to
present worth; therefore we utilize ζt-1 as the discount factor.
h
FutureWort
*
th
PresentWor 1

 t


28
Salvage Value
A key issue for multi-period planning is what is referred to as end
effects. End effects refer to the difficulty of appropriately representing
the influence of investment costs and operational costs at the end of the
planning period. There are two problems to address:
• Remnant investment value: The retirement year for some facilities
occurs after the final year. For these facilities, there is a value to the
facility because it has remaining life, i.e., some of the investment
amount paid has not yet been depreciated.
• Remnant operational cost: Because the simulation must be truncated
at a particular final year, operational costs after that final year are not
included since those years are not simulated.
Both of the above effects tend to bias decisions in favor of alternatives
that have low investment costs, since ignoring the remnant investment
value and the remnant operational cost means the optimization sees
only the investment cost, and because it is minimizing costs, it chooses
the investments with the lowest investment costs.

29
Salvage Value
These issues are addressed by doing two things:
Extend the simulation time beyond the planning horizon: A multiperiod formulation
with extended planning horizon is based on the observation that end effects increase
their influence as the final year gets closer. For example, if the planning horizon is 20
years, end effects have more influence in years 5-20 than they do in years 1-5. This
observation leads to a very natural solution: extend the final year well-beyond the
planning horizon. Therefore if the planning horizon is 20 years, we may run the
optimization problem to 50 years; but the decisions for years 20-50 will be ignored. A
general guide for how far to extend the simulation beyond the planning horizon is that
the final year of the simulation should exceed the final year of the planning horizon by
the lifetime of the facility with the longest life.
Model salvage values to facilities: Salvage value is the net sum to be realized from the
disposal of an asset (net of disposal costs) at the time of its replacement or resale, or
at the end of the study period.




 




 






 





 





 




 





 




 





 




 

MCosts
VariableO
t i s
s
t
s
j
i
j
j
t
ionalCosts
FuelOperat
i s
s
s
j
i
j
j
j
i
t
t
MCosts
FixedO
t i j
t
j
i
fixed
j
t
ue
SalvageVal
i j
T
j
i
T
j
i
T
Costs
Investment
i j
add
t
j
i
t
j
i
t
t
h
P
OM
h
P
H
FC
Cap
OM
Cap
SV
Cap
I
&
,
,
,
var
1
,
,
,
1
&
,
,
1
,
,
,
,
1
,
,
,
,
1
min
  

 


 
















































30
Capacity Factor
The capacity factor of a resource identifies the actual annual energy
production as a percentage of annual energy production at the
resource’s capacity.
The capacity factor for wind is usually 0.4-0.5 in areas of very high wind
conditions, 0.3-0.4 in areas of medium wind conditions, and less than
0.3 in areas of low wind conditions.
Capacity credits for solar are lower, from 15-40%, since we do not get
any solar energy during about half the time (when it is night), and we
can get greatly reduced solar energy even during the day if it is cloudy.
t
j
i
h
Cap
CF
h
P
s s
s
t
j
i
j
i
s
t
s
j
i ,
,
,
,
,
,
,
, 

  Constraint on energy generated
8760
8760
0



rated
P
P(t)dt
CF

31
Capacity Credit
The capacity credit (or value) of a resource identifies the percentage of
the resource’s capacity to be identified for reliability calculations at peak
load. The capacity credit indicates the availability at peak load.
t
s
j
i
Cap
CC
P t
j
i
s
j
i
t
s
j
i ,
,
,
0 ,
,
,
,
,
,
, 


t
d
r
t
Cap
CC
i
t
i
i j
t
j
i
j
i 

 
 ,
1
,
,
,
1
,
, )
1
(
)
(
System reserve constraint
The capacity credit for wind is usually fairly low because wind
generation during daytime hours is usually lower. For example, MISO
was using 13.3% capacity credit for wind [1].
[1] See “Planning year 2013-2014: Wind Capacity Credit,”
https://www.midwestiso.org/Library/Repository/Study/LOLE/2013%20Wind%20Capacity%20Report.pdf
Capacity credits for solar are higher, from 40-95%, because peak loads
usually occur during the daytime when solar insolation is highest.

32
Demand Representation
One might consider to choose the demand d to be either peak load
or average load. However…
• If demand d is chosen to be the peak load, then the GEP will build
the right amount of capacity but will over-estimate the energy
requirements and corresponding generation production.
• If demand d is chosen to be the average demand, then the GEP will
identify the right energy requirements and corresponding generation
production but will underestimate the capacity.
In both cases, the solution will identify the one technology that
minimizes the objective function.
An improvement on this formulation is to increase the number of load
levels, or load blocks, so that we use ds, s=1… instead of just d. In doing
this, we must also identify the appropriate duration hs for each load
block.

33
Demand Representation
These constraints represent operating conditions for a given demand level.




 




 






 





 





 




 





 




 





 




 

MCosts
VariableO
t i s
s
t
s
j
i
j
j
t
ionalCosts
FuelOperat
i s
s
s
j
i
j
j
j
i
t
t
MCosts
FixedO
t i j
t
j
i
fixed
j
t
ue
SalvageVal
i j
T
j
i
T
j
i
T
Costs
Investment
i j
add
t
j
i
t
j
i
t
t
h
P
OM
h
P
H
FC
Cap
OM
Cap
SV
Cap
I
&
,
,
,
var
1
,
,
,
1
&
,
,
1
,
,
,
,
1
,
,
,
,
1
min
  

 


 















































t
s
i
d
S
S
b
P t
s
i
l
t
s
k
k
k
l
i
l
l
j
t
s
j
i ,
,
,
,
,
,
,
,
,
,
, 

 
 
t
s
j
i
Cap
CC
P t
j
i
s
j
i
t
s
j
i ,
,
,
0 ,
,
,
,
,
,
, 


t
j
i
h
Cap
CF
h
P
s s
s
t
j
i
j
i
s
t
s
j
i ,
,
,
,
,
,
,
, 

 
t
s
l
F
S
b l
i
t
s
i
i
l
l ,
,
max
,
,
, 

 
Power balance at each node
Constraint on energy generated
Transmission limitations
Number of hours that Load > L
L
(MW)

d1
d2
d3
h1 h1+h2 h1+h2+h3
The load duration curve provides on the abscissa
the number of hrs the load is expected to be
greater than or equal to the corresponding load
given as the ordinate. Only 3 load blocks are
shown, but the formulation generalizes to any
desired number of load blocks.
i: bus number
j: technology
t: time
s: load conditions
T: final time

34
What is coordinated expansion planning (CEP)?
If G only, then it is GEP.
If T only, then it is TEP.
If G&T or G&T&D, then it is CEP.

35
Adequacy
We could add a constraint on adequacy in our formulation,
e.g., LOLE≤0.1day/year. However, computing LOLE is
computationally intensive. A better way is to iterate between
an adequacy evaluation program (e.g., GE-MARS) and a GEP.
Expansion
Planning
Optimization
LOLE≤
0.1?
YES
Stop
Adjust
(e.g., increase
reserve
requirements)
NO
Adequacy
Evaluation
e.g.,
Multiarea
Reliability
Analysis

36
Definition: Long-Term Planning Process
“The planning process is the systematic assembly and analysis
of information about electric energy supply, transport, and
demand, and the presentation of this information to decision-
makers who must choose an appropriate course of action.”
“The plan is a statement of the choices made by decision-
makers at any one point in time in order to meet specific
goals and objectives.”
REF: International Atomic Energy Agency, “Expansion planning for
electrical generation systems,” Technical Reports Series No 241, 1984.

37
Long-Term Planning Process: Illustration
A. Gaikwad and K. Carden, “Probabilistic Risk Analysis: A consideration of risks in transmission planning,” presentation
slides, Eastern Interconnection States Planning Council (EISPC) Meeting, October 8, 2013.
Vertically-integrated
utilities develop data
input, perform analysis,
and make decisions.
RTOs obtain the data
from stakeholders, then
perform the analysis. But
they do not make the
investment decisions; they
do not build/own
equipment.
GEP

38
The Long-Term Planning Process at MISO
RTOs coordinate the regional planning processes.
GenCos solve the GEP problem (see previous slide) and then enter their
plans into the RTO’s generation interconnection queue.

39

High-Fidelity Production Cost Simulation
40
hr 1
hr 8760
A 24 hour period
Run SCUC on 24 hr
period to decide unit
commitment
A 24 hour period
Run SCED on each
hour of 24 hr period
to decide dispatch,
flows, and LMPs
Run SCUC on 24 hr
period to decide unit
commitment
Run SCED on each
hour of 24 hr period
to decide dispatch,
flows, and LMPs
(PROMOD or PLEXOS)
Must initialize hour 1, day k
with hour 24, day k-1

41
SERVM Capabilities:
• Probabilistic Production Cost Forecasts: Produce S Curve Analysis for future production cost years for any
number of zones
• Probabilistic Market Price Forecasts: Produce S Curve Analysis for future energy price forecasts for any
number of zones
• Probabilistic Energy Margin Forecasts: Produce S Curve Analysis for future energy margins by resource
dispatch price for any number of zones
• Physical Reliability Metrics: Produce Loss of Load Expectation (LOLE), Loss of Load Hours (LOLH), Expected
Unserved Energy (EUE) for any number of zones
• Intermittent Penetration Studies: Understand reliability impact of increased intermittent generation
• Intermittent ELCC Studies: Calculate the Effective Load Carrying Capability of intermittent resources on the
system
• System Flexibility Requirement Studies: Calculate the flexible resource needs for a system under varying
intermittent penetration levels

42
Financial Transmission Rights (FTRs)
Capacity Market
Process &
Resource
Adequacy
Evaluation
The picture to
the left is for
PJM, but other
ISOs look the
same, with
exception of the
capacity market.
Transmission
Planning Process
(RTEP in PJM;
MTEP in MISO)
Proposed
generation
projects
Generati
on Queue
FTR Market

43
Recall from slide 42 of LPOPF slides:
1
* *
M
j bj j dk k gk
j k load k gen
CC P LMP P LMP P

  
   
  
The load pays into the market an amount exceeding the amount gens
are paid by the congestion charges. These charges are the sum of
products of line constraint dual variables and the RHS of the constraint.
Let’s check that in the example we just did (next slide).
These charges are used to fund the FTR market.

44
Financial transmission rights (FTRs), defined between any two
nodes in a network, entitle their holder to a revenue equal to the
product of the amount of transmission rights bought and the
congestion price differential between the two nodes.
FTRs isolate their holders from the risk associated with congestion
in the transmission network when the holders make bilateral
transactions.
They are sold via an commodity market.

45

46

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