elmp iii white paper i - cdn.misoenergy.org

ELMP III White Paper I R&D report and Design

Recommendation on Short-Term Enhancements

January 31, 2019

ELMP III- Part I Short-Term Items

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Purpose Statement

This white paper summarizes the 2019 ELMP III Research and Development study and Design recommendations

on short-term enhancements. Medium to long term enhancements are expected in a future report.

Executive Summary

Following the implementation of ELMP Phase I and ELMP Phase II in MISO’s Day-Ahead and Real-Time markets

on March 01, 2015 and May 01, 2017 respectively, MISO continues to evaluate and enhance ELMP along with its

overall price formation effort. Enhancements are explored under ELMP III including short-term, medium-term and

long-term efforts. While the medium-term effort of Enhanced Combined Cycle pricing and long-term efforts of

multi-interval pricing and future scenarios are on-going, studies of short-term enhancements show plausible

benefits and design recommendations are developed.

The short-term enhancements arise from multiple sources including the original plan to improve the approximation

to Convex Hull Pricing or full ELMP, recommendations by the Independent Market Monitor (IMM) and production

experiences. A recent development of convex envelope formulation in academia allows better approximation of

full ELMP and this report studies its practical application to MISO system. The IMM strongly supports ELMP and

recommends extended eligibility of Fast Start Resources in ELMP price setting by including Day-Ahead

committed Fast Start Resources and Ramp Relaxation. Regulation Enhancement has been implemented in the

Day-Ahead market based on production experiences to address inaccurate regulation price spikes and is now

studied for the Real-Time market.

The three enhancements were prototyped in the ELMP engine and were simulated against production system.

The convex envelope resulted in modest pricing impacts, and prices could be higher, lower or most of the time

equal to production ELMP II results. Overall uplifts trended down. Simulation results of including Day-Ahead

committed Fast Start Resources were consistent with the evaluation by the IMM and prices could increase by up

to about $2/MWh depending on the operating day. Day-Ahead and Real-Time price convergence was improved

over production ELMP. After in-depth investigation of the ramp relaxation issue, solution options were developed

but more studies are needed for improved ELMP ramp modeling to avoid unintended consequences. The

simulation study showed potential to largely automate the Real-Time regulation management process and free up

operations from manual actions. The production cost savings obtained from the enhanced regulation

management logic could range from half to multi-million dollars annually.

Based on the studies, design recommendations are summarized below:


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Time Issue Recommendation

Short-Term Convex Envelope Implementation after Market System Enhancement

(Tighter formulation resulted in modest price changes and

uplift reduction; low to medium implementation complexity)

IMM-1: Include DA

committed Fast Start

Resources

Implementation in near-term

(Pricing increased up to $2/MWh, reflecting usage of fast

start resources in DA; low implementation cost)

IMM-2: Relax ramp-down

limits of Fast Start

Resources

Further Study

(Need further evaluation of identified solution options to

avoid unintended consequence or discrepancy with ex

ante)

Real-Time Regulation

Clearing Enhancement

Implementation in near-term

Simulation showed favorable production costs savings

among other benefits; low implementation cost

Medium-Term ELMP enhancement for

Enhanced Combined Cycle

On-going research

Long-Term Multi-Interval Pricing and

Future Scenarios

Coordinating with Renewable Integration and Future

Resource projects


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Table of Contents

1. Introduction ....................................................................................................................... 4

2. Convex Envelope .............................................................................................................. 6

3. IMM Recommendations .................................................................................................... 9

3.1 Include Day-Ahead Committed Fast Start Resources ............................................................................. 10

3.2 Relax the ramp-down limitation for peaking resources ........................................................................... 15

4. Regulation Enhancement ............................................................................................... 20

5. On-going research and future scenarios ...................................................................... 28

6. Conclusion ...................................................................................................................... 30


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1. Introduction Price Formation is critical to an efficient wholesale electricity market that supports reliable operation and

efficient investment1. Unit commitment requires discrete decisions and units that are dispatched at their

operating limits or costs associated with the commitment decisions cannot set prices. This inability to

participate in pricing can lead to significant uplift payments. MISO developed the Extended Locational

Marginal Pricing (ELMP) to allow these units to set prices including the commitment costs based on a

mathematical concept of convex hull. ELMP was cited by FERC as a model for Fast Start Pricing in RTO

markets.

Considering the computational challenges and the existing market structure, MISO implemented ELMP in

a staged approach. The initial implementation employed a partial commitment variable to allow Fast Start

Resources such as gas turbines to set prices. ELMP Phase II expanded the definition of Fast Start

Resources2 up to resources that can start within 60 minutes. Nevertheless, challenges remain to

continuously improve ELMP modeling, including IMM recommended enhancements. For example,

resources may still not be able to set prices if ramp constrained even if their Economic Minimum Dispatch

Limits (EconMin) are relaxed to zero. Day-Ahead committed resources are not included as Fast Start

Resources in Real-Time. The currently implemented approximation of the full ELMP needs to be further

tightened to capture more benefits of the convex hull pricing theory. New pricing needs arise as MISO

gains production experience with ELMP and as the generation fleet evolves with more renewables and

future resources.

How can ELMP be improved to address these challenges and what are the benefits or liabilities of each

change? ELMP Phase III research and analysis efforts are investigating these enhancements in short-

term, medium-term and long-term initiatives. In the short-term, three items were explored, Convex

Envelope – a tighter formulation toward full ELMP, the IMM recommendation of including Day-Ahead

committed Fast Start Resources and Ramp Relaxation, and Real-Time Regulation Enhancement.

Recently, a convex primal formulation was developed that tightens, or under certain conditions exactly

reproduces, the partial commitment variable-based approximation to full ELMP3. This model was proved

to be equivalent to the SOS2 piece-wise linear cost function formulation that MISO prototyped in 20164

1 FERC AD14-14, “Price formation in energy and ancillary services markets operated by regional transmission organizations and independent system operators,” Washington, DC, USA, Tech. Rep., 2015. [Online]. Available: http://www.ferc.gov/whats-new/comm-meet/2015/111915/E-2.pdf 2 Online Fast Start Resource: An online Generation Resource that is started, synchronized and injects Energy, or a Demand Response Resource that reduces its Energy consumption, within sixty (60) minutes of being notified and that has a minimum run time of one hour or less and that will participate in setting price as described in the process in Schedule 29A of the Tariff. 3 “A convex primal formulation for convex hull pricing," Ross Baldick and Bowen Hua, IEEE Transactions on Power Systems, 32(5):3814-3823, September 2017. http://users.ece.utexas.edu/~baldick/papers/convex_hull_2017.pdf 4 FERC Technical Conference “Improving Market Clearing Software Performance to Meet Existing and Future Challenges – MISO’s Perspective,” Y. Chen, J. Bladen, A. Hoyt, D. Savageau, R. Merring, June 2016 https://www.ferc.gov/CalendarFiles/20160804133957-3%20-%20MISO%20FERC_M1_Chen_062016.pdf

http://mathworld.wolfram.com/FunctionConvexHull.html

https://en.wikipedia.org/wiki/Special_ordered_set

http://www.ferc.gov/whats-new/comm-meet/2015/111915/E-2.pdf

http://users.ece.utexas.edu/~baldick/papers/convex_hull_2017.pdf

https://www.ferc.gov/CalendarFiles/20160804133957-3%20-%20MISO%20FERC_M1_Chen_062016.pdf


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and implemented in 2017. This formulation improved Day-Ahead unit commitment performance by

20~30% and contributed to the reduction of MISO Day-Ahead market clearing time from 4 to 3 hours5.

The convex envelope formulation allows ELMP to be solved by using existing commercial solver within

polynomial solution time. The resulting price can be higher or lower than the current ELMP. The higher

price can help to reduce make-whole payments and the lower price can help to avoid lost opportunity

costs. The ELMP III study evaluated this enhancement against MISO’s current version to understand the

pricing and uplift impact and to assess the feasibility of implementation. Prototyping the enhancement on

the ELMP production engine and simulation on actual Operating Days produced the pricing and uplift

outcomes as expected.

IMM recommendations are focused on expanding the eligibility of Fast Start Resources. In the initial

implementation of ELMP, Day-Ahead committed resources were not included as Fast Start Resources in

Real-Time pricing due to cost causation considerations and the rare commitment of Fast Start Resources

in Day-Ahead under previous market conditions and the more restrictive definition of Fast Start

Resources. As market conditions have changed and the Fast Start Resources definition has been

revised, more Fast Start Resources are being committed in the Day-Ahead market. The ELMP III study,

based on sampled production days, shows that the pricing impact could be significant, up to double

relative to the existing ELMP II. The enhancement also produced better Day-Ahead and Real-Time price

convergence. Other aspects such as start-up cost allocation were also examined to evaluate the

appropriateness of including Day-Ahead committed Fast Start resources in Real-Time price setting.

Ramp relaxation is a more complicated issue and requires appropriate modeling to avoid unnecessary

divergence between ex ante and ex post solutions. As observed by both MISO and the IMM, some Fast

Start Resources constrained by ramp may still not be able to set prices even if EconMin is relaxed to

zero. Ramp relaxation could be needed in a manner that is similar to the unit commitment problem where

a large ramp limit is used to allow the unit to ramp from above or equal to EconMin to zero during shut-

down intervals (equivalently, an online Fast Start Resource is partially committed toward zero).

Nevertheless, this should be differentiated from the inter-temporal ramp during non-shutdown intervals.

Otherwise, an inappropriate relaxation could violate ramp rate constraints and lead to unintended

incentives for resources to deviate from their ex ante dispatch schedule given the ex post prices. Such

relaxation may also fail to accurately reflect system ramping needs and distort inter-temporal pricing

which is becoming increasingly important for the non-fuel based and energy limited new resources such

as storage. Solution options are developed either by using the partial commitment variable or by using

Ex Ante information. Further study of multi-interval pricing and production cases are needed to

appropriately model the ramp down constraints under single-interval pricing scheme.

The Regulation Enhancement was developed to address a production experience with ELMP II after it

was implemented on May 01, 2017. Regulation price spikes were then infrequently observed in the Day-

5 FERC Technical Conference “Experience and Future R&D on Improving MISO DA Market Clearing Software Performance,” Y. Chen, D. Savageau, F. Wang, R. Merring, J. Li, J. Harrison, and J. Bladen, June 2017 https://www.ferc.gov/CalendarFiles/20170623123549-M1_Chen.pdf?csrt=18151806463483539378

https://www.ferc.gov/CalendarFiles/20170623123549-M1_Chen.pdf?csrt=18151806463483539378


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Ahead market, and a restrictive regulation clearing logic was identified that led to the spikes. When Fast

Start Resources were dispatched down in ex post and left with less room to provide regulation (down), it

became costly to make up the RegMW within a restricted pool of “REG-Commit” units, and RegMCP was

driven high. An enhancement was developed and implemented in December 2017 for the Day-Ahead

market by designating units that have non-stranded capacity as “REG-Commit.” ELMP III develops an

enhancement for the Real-Time market based on the Day-Ahead experience and also has an important

application of enhancing or automating the operation process of regulation management.

The medium-term enhancement for pricing of Enhanced Combined Cycle model and the long-term

enhancement of multi-interval pricing and future scenarios are on-going and will be reported in a future

white paper.

2. Convex Envelope The Bid-based Security Constrained Unit Commitment and Economic Dispatch (UCED) problem involves

discrete unit commitment decisions. Traditional Locational Marginal Pricing (LMP) is not able to reflect

the lumpy costs associated with commitment decisions and uplift payments have to be used to support

the commitment and dispatch. Full ELMP, or Convex Hull Pricing, reflects both the commitment and

dispatch costs, and minimizes overall uplift payments. It was developed from the convex hull (the closest

convex approximation from below) of the total cost function. Such prices can be obtained as the optimal

multipliers of the Lagrangian dual of the UCED problem, but can be computationally expensive and no

commercial solver is currently available.

Other convex approximations exist. The current ELMP implementation at MISO is an approximation by

relaxing the integer commitment variables to be continuously adjustable from 0 to 1, and can be solved by

using existing software in the primal space. Recently, a convex primal formulation of Convex Hull Pricing

was developed by describing for each generating unit the convex hull of its feasible set and the convex

envelope of its cost function. This model was proved to be equivalent to the SOS2 piece-wise linear cost

function formulation that MISO implemented in 2017. The formulation improved Day-Ahead unit

commitment performance by 20~30% and contributed to the reduction of Day-Ahead clearing time from 4

to 3 hours. With convex envelope of cost functions and convex hull of constraints on individual

generators, the formulation maintains polynomial solution time by using commercial Linear Programming

solvers. Although some constraints like ramp rate constraints still may not be described in exact convex

hull, the convex envelope model provides tighter approximation to convex hull pricing and is expected to

further reduce uplift payments.


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Figure 2-1 Convex Envelope (red) obtains tighter approximation or exact convex hull of the cost function (blue) as compared to

today’s ELMP implementation (green)

The convex envelope formulation for the piece-wise linear cost function is achieved by a simple

modification to the current ELMP implementation and involves modest implementation efforts.

Suppose that generator i offers piece-wise linear cost function for time period t with breakpoint �̅�𝑖,𝑛,𝑡 for

each piece or offer block n = 1, …, N (blue line in Figure 2-1):

𝐶𝑖,𝑡(𝑝𝑖,𝑡) = 𝑐𝑖,1,𝑡𝑝𝑖,1,𝑡 + 𝑐𝑖,2,𝑡𝑝𝑖,2,𝑡 + ⋯ + 𝑐𝑖,𝑛,𝑡𝑝𝑖,𝑛,𝑡 + ⋯ + 𝑐𝑖,𝑁,𝑡𝑝𝑖,𝑁,𝑡

𝑝𝑖,𝑡 = 𝑝𝑖,1,𝑡 + 𝑝𝑖,2,𝑡 + ⋯ + 𝑝𝑖,𝑛,𝑡 + ⋯ + 𝑝𝑖,𝑁,𝑡

0 ≤ 𝑝𝑖,1,𝑡 ≤ �̅�𝑖,𝑛,𝑡, n = 1, …, N

𝑃𝑖,𝑡𝑚𝑖𝑛 ≤ 𝑝𝑖,𝑡 ≤ 𝑃𝑖,𝑡

𝑚𝑎𝑥

The current ELMP formulation applies partial commitment variable Oni,t, 0 Oni,t 1, to allow EconMin

(𝑃𝑖,𝑡𝑚𝑖𝑛) to be relaxed to zero and the fixed commitment related costs to be averaged over EconMax (𝑃𝑖,𝑡

𝑚𝑎𝑥)

(green line in Figure 2-1):

𝑂𝑛𝑖,𝑡𝑃𝑖,𝑡𝑚𝑖𝑛 ≤ 𝑝𝑖,𝑡 ≤ 𝑂𝑛𝑖,𝑡𝑃𝑖,𝑡

𝑚𝑎𝑥

𝑂𝑏𝑗𝐶𝑜𝑠𝑡 = 𝐶𝑖,𝑡(𝑝𝑖,𝑡) + 𝑂𝑛𝑖,𝑡𝑆𝑖,𝑡𝐹𝑖𝑥𝑒𝑑𝐶𝑜𝑠𝑡

The convex envelope of the piece-wise linear cost function can be obtained by further applying the

commitment variable Oni,t to each offer block (red line in Figure 2-1):

0 ≤ 𝑝𝑖,1,𝑡 ≤ 𝑶𝒏𝒊,𝒕�̅�𝑖,𝑛,𝑡, n = 1, …, N

As can be seen in Figure 2-1, the convex envelope of the piece-wise linear cost function is tighter than

the convex approximation under existing ELMP implementation. It averages the fixed cost over the

quantity corresponding to the tangent point between the original cost curve and the convex envelope


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instead of averaging over EconMax. The resulting price (slope of the cost curve) thus can be higher

(below the tangent point) or lower (above the tangent point) than the current ELMP. The higher price can

help to reduce make-whole payments and the lower price can help to avoid lost opportunity costs.

Overall, uplift payments are expected to reduce as compared to the current ELMP implementation. It

should also be noted that the convex envelope formulation results in the same prices as current ELMP

under three situations:

1) Block-loaded units;

2) Single-block offer curve;

3) The tangent point coincides with EconMax.

To evaluate the actual pricing impact of the convex envelope formulation on a large-scale system, we

prototyped the enhancement on the ELMP engine and simulated the enhancement against production

cases. Four production days (1152 Real-Time ELMP cases) were sampled from May 2018:

1) 05/06/2018: A modest day when ELMP II production results were the same as ex ante LMP prices

2) 05/15/2018: Max gen alert, reg deficit; ELMP II average $2.00 higher than LMP

3) 05/28/2018: MISO hit 100F record; ELMP II averaged $0.05 higher than LMP

4) 05/31/2018: Large ELMP II impact observed and averaged $5.60 higher than LMP

As expected, simulation results show that ex post prices under the convex envelope formulation can be

higher or lower than those under ELMP II. The average daily price difference varies from $0/MWh up to a

$0.08/MWh reduction. A close review of cases with price differences showed that when prices decrease,

there were usually Fast Start Resources partially committed above the tangent point (Oni,t = 1) and when

prices increase there were usually Fast Start Resources partially committed below the tangent point (Oni,t

< 1).


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Figure 2-2 Price difference between Convex Envelope and production ELMP II over the 5 minute intervals of sampled days

As shown in Figure 2-2, the overall price impact of convex envelope is modest. The convex envelope

formulation may result in the same prices as the current ELMP under situations as noted earlier. In

addition, the price impact can also be related to the eligibility rule of Fast Start Resources and the impact

can increase as we expand the eligibility as will be discussed in Section 3.

Given the prices resulted from the convex envelope formulation as compared to ELMP II production

results, uplift payments are evaluated as the difference between optimal profit and actual profit:

{Ex Post price*Ex Post MWenergy,reg,spin,sup,ramp – Offer Cost(Ex Post MW, Ex Post Oni,t)} –

{Ex Post price*Ex Ante MWenergy,reg,spin,sup,ramp – Offer Cost(Ex Ante MW, Ex Ante Oni,t)}

As such, the uplift defined here includes both make-whole payments and lost opportunity costs, although

in production lost opportunity costs are not explicitly compensated at MISO.

Considering the complexity to replicate the two-settlement system in production, several simplifications

are made to validate whether uplift payments are trending in the expected direction while the specific

value may not be accurate due to the simplifications:

1) Use Ex Post MW to approximate profit max MW

2) Use RT price and MW for settlement, not netting with DA

3) Skip some detailed settlement rules such as reserve substitution

Uplift payments are thus calculated for each of the four sample days and compared between convex

envelope and ELMP II as shown in Table 2-1.

Day 5/6/2018 5/15/2018 5/28/2018 5/31/2018

Uplift reduction 0 -$814 -$116 -$1,112

Table 2-1 Uplift reduction under the convex envelope formulation as compared to ELMP II production

As expected, uplift payments trended down under the convex envelope formulation.

3. IMM Recommendations In the State of Market Report 2017, the IMM assessed that ELMP still has not been effective in allowing

online peaking resources to set prices when they are the marginal source of supply in MISO, attributing to

1) Eligibility rules only allow 26 percent of the online peaking resources to potentially set prices; and 2)

Modeling assumptions governing the ability of peaking resources to ramp down and other resources to

ramp up in the ELMP model.


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To address these inefficiencies, the IMM updated its recommendation 2015-1 as:

1) Expanding the price-setting eligibility to include Fast Start peaking resources committed in the Day-

Ahead market;

2) Relaxing the ramp-down limitation for Fast Start peaking resources in the ELMP model; and

3) Establishing constraints to ensure the quantity of capacity (energy plus reserves) does not increase or

decrease in the ELMP model from the physical dispatch in the UDS.

The first two recommendations will be explicitly discussed below, whereas recommendation 3) is not an

issue for the current ELMP implementation and is more of an unintended consequence of inappropriate

ramp relaxation in recommendation 2).

3.1 Include Day-Ahead Committed Fast Start Resources

Currently Fast Start Resources committed in the Day-Ahead market are not eligible to participate in the

ELMP price setting algorithm in the Real-Time market. Different design goals were considered in the

original design, including:

1) RT ELMPs should equal DA ELMPs if nothing changes between DA and RT. To meet this goal, the

start-up and no-load costs of resources committed in the DA market must be considered when setting RT

ELMPs.

2) RT ELMPs are set based upon only avoidable RT costs. Only start-up and no-load costs for resources

committed after Day-Ahead would be considered in setting RT ELMP, and virtual transactions in DA are

expected to drive DA ELMP toward RT ELMP

Nevertheless, these two goals are not compatible. Under MISO’s existing market construct, Day-Ahead

commitment decisions are binding in Real-Time, and the commitment related costs are thus sunk costs.

Even if a resource did not show up in Real-Time, it still had to buy-back its Day-Ahead position. More

importantly, when ELMP was originally designed, Fast Start Resources (start-up and notification time

within 10 minutes under ELMP I) were rarely committed in the Day-Ahead market and the pricing impact

was minimal. Therefore, Day-Ahead committed Fast Start Resources were not included in the Real-Time

ELMP pricing.


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As the generation fleet continues to evolve including low gas prices and following the expansion of Fast

Start Resources definition (start-up and notification time within 60 minutes under ELMP II), more units

meeting the definition of Fast Start Resources are being committed in Day-Ahead, and the pricing impact

of including these units in Real-Time ELMP setting becomes potentially significant.

For example, in May 2014, there were few Fast Start Resources (10 minute notification) committed in the

Day-Ahead market. In 2017, the expanded definition of Fast Start Resources (60 minute notification),

resulted in more commitments in the Day-Ahead market but the number was still modest and

commitments of more than ten Fast Start Resources in one day were infrequent. More recently in May of

2018, significant commitment of Fast Start Resources was observed in the Day-Ahead market as shown

in Figure 3-1.

Figure 3-1 Number of 60 minutes Fast Start Resources committed in Day-Ahead for each day of May

To evaluate the pricing impact, we prototyped the change to include Day-Ahead Committed Fast Start

Resources and studied the change against Real-Time ELMP cases of the same four production days as

before (1152 five-minute cases).

Day Highlights Daily Average ELMP II-LMP

05/06/2018 modest day $0

05/15/2018 max gen alert; reg deficit $2.00

05/28/2018 miso hit 100F record $0.05

05/31/2018 largest ELMP impact $5.60

Table 3-1 Four production days selected for study

0

10

20

30

40

50

1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031

Daily Count of Fast Start Day-Ahead Commitments(May 2014 and May 2018)

2014 2018 day


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By including Day-Ahead committed Fast Start Resources, prices increased over ELMP II, and this impact

was more significant than that assessed in 20166 as a result of the increased usage of Fast Start

Resources in Day-Ahead as summarized in Table 3-2 - Table 3-4, and detailed in Figure 3-2 - Figure 3-3.

5/6/2018 5/15/2018 5/28/2018 5/31/2018

ELMP II $0.00 $2.00 $0.05 $5.60

DA Units $0.00 $3.74 $2.07 $7.79

Table 3-2 Average price increase from Ex Ante by including Day-Ahead committed Fast Start Resources

# of FSR 5/6/2018 5/15/2018 5/28/2018 5/31/2018

ELMP II 0 4 0.3 6

DA Units 2 14 10 18

Table 3-3 Average number of Fast Start Resources participated in ELMP pricing

% of Inv 5/6/2018 5/15/2018 5/28/2018 5/31/2018

ELMP II 0% 62% 15% 37%

DA unit 0 62% 49% 66%

Table 3-4 Percentage of intervals where Fast Start Resources participated in ELMP pricing

6 “ELMP Phase II,” Market Subcommittee, August 2016, https://cdn.misoenergy.org/20160802%20MSC%20Item%2005b%20ELMP%20Phase%20II74705.pdf

https://cdn.misoenergy.org/20160802%20MSC%20Item%2005b%20ELMP%20Phase%20II74705.pdf


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Figure 3-2 Real-Time prices by including Day-Ahead committed Fast Start Resources as compared to ELMP phase II

Figure 3-3 Number of Fast Start Resources participated in ELMP pricing under Phase II and including Day-Ahead units

In the above charts, an interesting observation is that on 5/28/2018 when MISO hit 100F, only a modest

ELMP impact was observed in production. That was because on that day Fast Start Resources were

mostly committed in the Day-Ahead market but did not participate in the Real-Time pricing. By including

these units, Real-Time prices increased more than $2/MWh on average, resulting in better convergence

with Day-Ahead prices as shown in Figure 3-4.

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

DA RT-ELMP II RT-DA unit

$/M

Wh

Hour


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Figure 3-4 Day-Ahead and Real-Time hourly average prices for 05/28/2018

The study results suggested that it is beneficial to include Day-Ahead committed Fast Start Resources in

Real-Time ELMP price setting, given the increased usage of Fast Start Resources in Day-Ahead. During

the prototyping process, we were also able to assess the implementation efforts. The inclusion of Day-

Ahead committed Fast Start Resources requires modifying the definition of two parameters and therefore

the implementation efforts would be modest. Nevertheless, the testing can still be extensive given the

complexity of the pricing engine and interdependencies of other areas.

One important area identified during the review of impacted areas is the allocation of startup cost.

Currently, startup cost is allocated to the first min run hour. When Day-Ahead commitment is eligible, the

first min run hour can be shifted:

1) Situation one: RT extend DA commitment

2) Situation two: RT advance DA commitment

3) Situation three: RT bridge DA commitment

A key question is whether the current allocation needs to be changed. A detailed review confirms that the

current allocation method applies when we include Day-Ahead committed Fast Start Resources to reflect

cost causation, although allocated hour may not be the same as Day-Ahead given the commitment shift.

Specifically in situation one, under ELMP II no startup cost will be allocated for the RT commitment since

it is outside of the first min run hour. When Day-Ahead commitment becomes eligible, startup cost will be

allocated to the first Day-Ahead committed hour similar to the allocation in Day-Ahead market. In

situation two, Real-Time market will allocate startup cost to the first committed hour in Real-Time, and the

Day-Ahead market allocates startup cost to the first committed hour although this hour can be different

from that in Real-Time. Similarly, in situation three, Real-Time market will allocate cost to the first Day-

Ahead committed hour, but will not allocate cost again for the second commitment block since the Real-

Time commitment bridged the two Day-Ahead commitment blocks.

Based on the study results, we recommend near-term implementation of including Day-Ahead committed

Fast Start Resources in ELMP pricing setting. We further point out several on-going or potential future

initiatives that could be related to this change:

1) Startup cost allocation and multi-interval pricing: During the convex hull pricing study, startup costs

exhibited a tendency to be allocated to intervals when the resource was most needed. Under the

narrative definition of Fast Start Resources, these units tended to be started when most needed and stay

DA RT

DA RT

DA RT DA


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online for at least minimum run time. With the expansion of the price-setting eligibility or Fast Start

Resource definition, intervals when the resources was most needed may not be the first intervals over

minimum run time and there could be a potential to improve the startup cost allocation method base on

the multi-interval pricing study. The allocation can be important to provide more accurate prices for

different time periods, signalizing when resources are most needed and facilitating the optimal usage of

energy limited resources such as storage.

2) Day-Ahead commitment of Fast Start Resources: Traditionally, power systems were operated to

decide the commitment well ahead of time and then balance inelastic demand by altering the output of

conventional generation such as nuclear and coal units. Now with increasing net load variations and

uncertainties introduced by renewables, demand responses, etc., it could be the time to revisit whether

we want to bind the commitment decisions in Day-Ahead, especially for those fast start resources, or

want to make them more financial decisions and have the flexibility to re-optimize them in Real-Time

based on the latest system conditions. NYISO and PJM have similar efforts where the commitment of

fast start resources in Day-Ahead may not bind until further committed in Real-Time.

3) Short-Term Reserve: Besides the flexibility to revisit Day-Ahead fast start resource commitment,

another possibility is to reserve the capacity of fast start resources so that they can quickly come online

when needed. The Short-Term Reserve product could allow offline fast start resources to participate and

get compensated for their availability to respond fast when needed.

3.2 Relax the ramp-down limitation for peaking resources

Under the Fast Start Pricing scheme, the general concept is to allow Fast Start Resources to be partially

committed (or other variations of relaxing the minimum generation limit to zero) instead of an on/off

decision, so that they can set prices in the ex post process. Nevertheless, it has been observed that

some Fast Start Resources may still not be able to set prices if constrained by ramp. The ramp modeling

under ELMP thus needs to be improved for Fast Start Resources to more effectively set prices. To

improve the ELMP ramp modeling, it is very important to examine the unit commitment problem and

differentiate between two sets of ramp rate constraints:

1) Inter-temporal Ramp

2) Startup/Shut down Ramp

Typically, a unit is ramp constrained across intervals when it is online for dispatch.

−𝑅𝑎𝑚𝑝𝑖,𝑡 ≤ 𝐺𝑒𝑛𝑖,𝑡 − 𝐺𝑒𝑛𝑖,𝑡−1 ≤ 𝑅𝑎𝑚𝑝𝑖,𝑡 (1)

Nevertheless, during startup or shutdown periods, a different ramp limit is used to allow the unit to ramp

from 0 to EconMin or EconMin to 0, where in-between the unit is in the starting or shut down process and

is not for the RTO’s dispatch. Specifically, when an online Fast Start Resource is partially committed

toward zero, it is essentially a shutdown and the ramp constraint for shut down is:

−𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡 ≤ 𝐺𝑒𝑛𝑖,𝑡 − 𝐺𝑒𝑛𝑖,𝑡−1 (2),


16

or combining (1) and (2), the ramp down constraint can be uniformly formulated as

𝐺𝑒𝑛𝑖,𝑡−1 − 𝐺𝑒𝑛𝑖,𝑡 ≤ 𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡 × 𝑂𝑛𝑖,𝑡−1 − (𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡 − 𝑅𝑎𝑚𝑝𝑖,𝑡) × 𝑂𝑛𝑖,𝑡 (3)

The lumpiness or non-convexity thus arises associated with the shutdown intervals, and the Fast Start

Resource would not be able to set price if constrained by the normal ramp limit from being further

dispatched down below EconMin. Fast Start Resources are usually flexible with high ramp rates. With

the previous 10 minute definition of Fast Start Resources, about three quarters of Fast Start Resources

can ramp from EconMin to zero within 5 minutes. Nevertheless, with the expansion of the definition to 60

minutes, about 40% of Fast Start Resources will have the issue of being ramp constrained from EconMin

to zero in Real-Time 5 minutes pricing.

Example 1 Fast Start Resource is ramp constrained and cannot set prices

Consider a one-period three-unit problem, where units 2 and 3 are Fast Start Resources.

Time t

load 108MW

Table 3-5 Load of Example 1

Unit min max ramp cost IntMW

unit1 0 100 100 $10/MWh 100MW

unit2 12 20 10 $20/MWh 20MW

unit3 0 20 100 $30/MWh 5MW

Table 3-6 Generation offer of Example 1

The market clearing results for ex ante and ex post under the current model, as well as ex post with

relaxation of ramp down limits are obtained below.

Ex Ante $10/MWh Ex Post -Current $10/MWh

Ex Post -RelaxRamp $20/MWh

unit1 96MW unit1 98MW unit1 100MW



Table 3-7 Market clearing results for Example 1

As can be seen, unit 2 is dispatched at EconMin and cannot set prices under ex ante. It cannot set prices

under the current ex post model either since it is ramp constrained even if its EconMin is relaxed to zero.

By further relaxing the ramp limit (using a larger limit to account for the partial shutdown), it sets prices.

Nevertheless, the shutdown ramp should be differentiated from the inter-temporal ramp when a resource

is ramp constrained while being dispatched above EconMin.

Example 2 Ramp constraint binding in a two-period problem with no lumpiness


17

Consider an example with load and generation offers specified below, where EconMin is set to zero so

that there is no lumpiness at all in this example.

Time t1 t2

load 136MW 125MW

Table 3-8 Load of Example 2

min max ramp cost

unit1 0 100 100 $10/MWh

unit2 0 20 100 $20/MWh

unit3 0 20 5 $30/MWh

Table 3-9 Generation offer of Example 2

The market clearing results are obtained below.

t1 t2

Ex Ante $40/MWh $20/MWh

unit1 100MW 100MW

unit2 20MW 14MW

unit3 16MW 11MW

Ex Post-Current $40/MWh $20/MWh

unit1 100MW 100MW

unit2 20MW 14MW

unit3 16MW 11MW

Ex Post-RelaxRamp $30/MWh $30/MWh

unit1 100MW 100MW

unit2 20MW 20MW

unit3 16MW 5MW

Table 3-10 Market clearing results for Example 2

In Example 2, unit 3 was dispatched to meet a system peak at t1, and is ramp constrained at t2 before it

can be dispatched down to zero. The resource is not setting prices at t2, but its inter-temporal cost effect

is reflected in the price it sets at t1. That is, if we increase the load by 1MW at t1, unit 3 will generate

17MW at t1. Because of the ramp constraint, it can only ramp down to 12MW at t2 and unit 2 will back

down 1MW to balance with load at t2. As a result, the marginal cost to serve an incremental MW at t1 is

set by unit 3 at $40/MWh (= $30/MWh + $30/MWh - $20/MWh). Similarly, if we increase the load by 1MW

at t2, unit 2 will produce the incremental MW and is the marginal unit that sets the price at $20/MWh.

Because there is no lumpiness, the market clearing results under ex ante and the current ex post model

are the same. Nevertheless, if we relax the ramp-down limit in this case, unit 3 will set price for both

intervals t1 and t2 at $30/MWh. Such flat prices fail to reflect the different system needs at t1 and t2, and

could not provide the incentive for resources to follow dispatch. As shown in Table 3-10, the dispatch


18

results diverges from those under ex ante. Given the price at $30/MWh at t2, unit 2 would like to produce

at full capacity of 20MW, and has incentive to deviate from the RTO dispatch of 14MW.

This unintended consequence could become even more severe in the co-optimization of energy with

reserves. In example 2 under the ramp relaxed ex post case, unit 3 was unrealistically dispatched down

at t2 and unit 2 is largely dispatch up to balance the load. If unit 2 was providing reserve in ex ante, then

it will not have room to provide reserve anymore in the ex post case, resulting in decreased capacity in to

provide reserve as the IMM pointed out in its recommendation 3).

Currently, several RTOs including MISO use a single-interval pricing model, which further complicates the

problem since the inter-temporal pricing impact may not be captured by the single-interval model.

Nevertheless, the nature of inter-temporal ramping in constraint (1) is different from the lumpiness issue in

constraint (3), and the ELMP ramp modeling needs to be carefully developed to avoid any unintended

consequences. As shown in Example 2, inappropriate relaxation of ramp-down limits may result in

unnecessary divergence between ex ante and ex post. The divergence could further lead to unintended

incentive for resources to deviate from their ex ante dispatch schedule given the ex post prices. The

inappropriate relaxation may also distort inter-temporal pricing and fail to accurately reflect system

ramping needs, whereas the price accuracy across different time periods will be critical given the

increasing penetration of resources such as storage that arbitrage the temporal price differences.

Solution options are explored to address the shutdown ramp issue without inadvertently affecting the

inter-temporal ramp.

Option 1: Utilizing Partial Commitment Variable7

ELMP allows Fast Start Resources to relax their dispatch minimums to zero by allowing the partial

commitment of such resources for pricing purposes. That is, instead of an on (1) or off (0) commitment

decision in reality, ELMP allows a Fast Start Resource to be partially committed between 0 and 1. When

a Fast Start Resource is partially committed down from Oni,t-1 to Oni,t, it can be interpreted as that the

resource is shut down by a fraction of (Oni,t-1 - Oni,t), and has a fraction of Oni,t remaining committed.

Therefore, the shutdown ramp limit can be used for the shutdown fraction, and the normal limit can be

used for the remaining fraction. That is, by re-writing ramp down constraint (3), it can be obtained that

𝐺𝑒𝑛𝑖,𝑡−1 − 𝐺𝑒𝑛𝑖,𝑡 ≤ 𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡 × (𝑂𝑛𝑖,𝑡−1 − 𝑂𝑛𝑖,𝑡) + 𝑅𝑎𝑚𝑝𝑖,𝑡 × 𝑂𝑛𝑖,𝑡 (4)

Compared to the ramp down constraint (1) that is used in the current ELMP model, the ramp limit can be

relaxed to larger value that accounts for the shutdown. For example, a Fast Start Resource can generate

between 100MW to 200MW and its Ramp Rate is 10MW/min. Under the existing ramp model (1), it can

only ramp down 50MW over a 5 minutes interval and will be ramp constrained even though EconMin is

relaxed to 0. By using (4), the ex post pricing can further dispatch the unit down by pushing the partial

commitment variable Oni,t toward 0 so that the ramp limit is pushed toward the larger value of

7 Dr. Gribik’s manuscript


19

𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡. The costs associated with the dispatch and partial commitment will be able to eligible

to participate in price setting. In addition, if the resource is ramping normally between two consecutive

online intervals, i.e., Oni,t toward 1, the ramp limit will be pushed toward 𝑅𝑎𝑚𝑝𝑖,𝑡.

The shutdown ramp is usually a larger limit than normal ramp to ensure that the unit can be dispatched

down from anywhere to zero in shutdown periods. In the current unit commitment problem, it is set at

EconMax. However, real time dispatch intervals are much shorter. Assuming a large shutdown ramp may

cause significant divergence between ex-ante and ex-post even under the scenario when fixed cost is

near zero. Other possibilities include 𝐺𝑒𝑛𝑖,𝑡−1 or max {EconMin, 𝑅𝑎𝑚𝑝𝑖,𝑡}. Further studies are needed to

determine the appropriate value for shutdown ramp.

Another challenge is related to the single-interval pricing model. To calculate price at t in Real-Time,

𝐺𝑒𝑛𝑖,𝑡−1 in (4) will be a known parameter based on the latest resource output. If the resource is partially

committed or dispatched down in ex post pricing to 𝐺𝑒𝑛𝑖,𝑡, in the next interval t+1 the unit will be ramping

from 𝐺𝑒𝑛𝑖,𝑡 which can be different from 𝐺𝑒𝑛𝑖,𝑡. For example, a unit that has low incremental energy cost

and high no-load cost may be dispatched at EconMax. The ex post pricing would try to dispatch the unit

down toward zero at t, but in the next interval it will have to ramp from EconMax again. This can affect a

unit being dispatched down to zero in ex post pricing if the down ramping process takes more than one

interval. A large 𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡 can force the unit ramp to zero in one interval but may result in

significant deviation if it takes several intervals to ramp the unit to zero in ex ante. Further studies are

needed to understand the pricing impact in coordination with the value selection of 𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡.

Option 2: Utilizing information from ex ante

This option is to leverage the information from ex ante to detect the issue when the ramp-down limit

should be relaxed. For example,

1) If the dispatch ex ante is close to EconMin, then the ramp-down limit may be relaxed to shutdown ramp

to allow the unit to be dispatched down to zero when EconMin is relaxed to zero in ex post.

Nevertheless, this approach may be limited in its effectiveness if a resource is shut down from a dispatch

level above EconMin. For example, resources with high start-up and no-load costs may be dispatched

well above EconMin in Ex Ante where commitment costs are not considered, but could be dispatched

toward zero when those costs are considered in Ex Post pricing.

2) If the ramp rate constraint is binding in ex ante, it indicates an inter-temporal ramping situation and

ramp rate may not be relaxed in ex post.

MISO continues to study this problem in collaboration with its IMM and research partners. The multi-

interval pricing research could provide guidelines on the appropriate ramp modeling for current single-

interval ELMP implementation. Simulation against production cases would also be performed in selecting

the parameters discussed above such as 𝑆ℎ𝑢𝑡𝐷𝑜𝑤𝑛𝑅𝑎𝑚𝑝𝑖,𝑡.


20

4. Regulation Enhancement Following the implementation of ELMP II on May 01, 2017, Day-Ahead Ex Ante/Ex Post energy price

differences remain negligible but large RegMCP differences were infrequently observed. A restrictive

regulation clearing logic was identified that led to these regulation price spikes. More specifically, a unit

can have different operational limits depending on whether it clears regulation or not (reg capacity econ

capacity). In the Day-Ahead Market clearing process, SCUC optimize unit commitment schedule and

specifies whether a unit is committed for regulation or not (about 30 units among over 500 all committed

units). SCED regulation clearing had been limited to “REG-Commit” resources by SCUC to not impact

available capacity. With costs more fully considered in SCED-Pricing, Fast Start Resources could be

dispatched down, leaving less room to provide regulation (down). Within the very restricted “REG-

Commit” pool, it is costly to make up the RegMW and RegMCP is thus driven high.

The existing regulation clearing logic has been conservative, since capacity from resources with reg limits

= econ limits is not impacted by regulation selection. If these resources are made eligible for SCED to

clear regulation, the Day-Ahead market will continue to identify the best way to meet capacity obligations,

and SCED can clear regulation from these additional units if needed or continue not to clear regulation

from these units. An enhancement was implemented in Dec 2017 to designate units as “REG-Commit”

for potential regulation clearing if they are: 1) committed; 2) reg-qualified; 3) reg limits = econ limits. The

enhancement, implemented in both ex ante and ex post engines, effectively addressed the RegMCP

price spikes and resulted in modest production cost savings.

In the Real-Time market, regulation management tools are already available to designate units as “REG-

Commit” for potential regulation clearing as system conditions change in Real-Time. In addition, the

regulation clearing logic is more complicated in Real-Time. To name a few, a unit offers three ramp rates

in Real-Time, up ramp rate, down ramp rate and bi-directional ramp rate, and has to use bi-directional

ramp rate ( up/down ramp rate) if it is designated as “REG-Commit” to potentially clear regulation.

Another complication involves the 5 minutes Real-Time interval versus an hourly regulation selection

process.

Recently, operations had interests to automate the regulation management tool to address inefficiencies

and operation risks associated with the manual process, and if possible to enhance the Real-Time

regulation clearing process given the anticipated benefits based on experience with the Day-Ahead

enhancement. One example of the inefficiency as identified by the IMM involves units that are

designated as “REG-Commit” during high load hours but with stranded capacity (reg limits < econ limits).

A unit was noticed that cleared full economic capacity in Day-Ahead but was designated as “REG-

Commit” in Real-Time and lost more than 100MW capacity (EconMax – RegMax). Nevertheless, the unit

was a more economic resource for energy and spin and did not actually clear regulation. As a result, no

regulation was obtained from this unit but the lost capacity could result in extra GT commits and some

isolated ramp-related price spikes for the system. The unit itself also incurred significant DAMAP

payments to buy-back its Day-Ahead position. Other examples of inefficiencies include the need for


21

operations to spare time every hour for manually put units on “REG-Commit,” and any failure to do so

may introduce operational risks of regulation scarcity.

Considering the Day-Ahead enhanced regulation clearing logic and the Real-Time complications, the

enhanced regulation clearing logic is developed for Real-Time as:

Figure 4-1 Real-Time enhanced regulation clearing logic

To evaluate the possibility of automation and/or enhancement, the existing Real-Time regulation clearing

process was reviewed. Currently, FRAC regulation committed units are automatically passed to Real-

Time for regulation clearing in UDS, and Day-Ahead regulation committed units are manually added back.

As needed by the latest Real-Time conditions, operators manually designate more units as “REG-

Commit” for potential regulation clearing as recommended by the Real-Time regulation management tool.

Figure 4-2 Existing Regulation Real-Time Clearing process

In production, about 20~40 units are “REG-Commit” in Day-Ahead and a few more in FRAC, and the DA

and FRAC “REG-Commit” units can be different as shown in Figure 4-3.


22

Figure 4-3 “REG-Commit” units in Day-Ahead and FARC over four sample production days

More units added as “REG-Commit” in Real-Time to ensure there are sufficient regulation supply. In

addition, most of units manually added in Real-Time already have the same reg limits and econ limits

(non-stranded capacity) and the same bi-directional ramp and up/down ramp rates (non-stranded

flexibility).

Figure 4-4 “REG-Commit” units in Real-Time, most of which as non-stranded capacity and flexibility


23

We simulated the enhanced Real-Time regulation clearing logic against production cases to compare the

market clearing results. The same four production days as before were used, and two studies were

performed:

1) Simulate the enhanced logic against production cases, i.e., units designated as “REG-Commit” include

both those existing ones added by the existing manual regulation management (blue bar in Figure 4-4)

and those added by the enhanced logic on top of that (red bar Figure 4-4)

2) Remove operation manual regulation commitment from production cases and apply the enhanced logic

The enhanced logic is deemed effective if it improves regulation clearing relative to production solutions

based on the metrics listed in Table 4-1 and is able to capture units committed in the existing manual

regulation management tool.

Table 4-1 Market Clearing Result Measurement Metrics

Simulation results of study 1) that applies the enhanced logic to production cases are summarized in

Table 4-2 and detailed in the charts in Figure 4-5 - Figure 4-8.

Reg-Committed units 11~75 units were added on reg; generally on an hourly basis but could be

intra-hour if units offer or operating status changes within hour (like today)

Reg clearing results Reg clearing typically concentrated on a few of units add on reg, but there

could be large MW cleared on more units (1~27) at reg tight periods

Production cost Production cost reduced with more significant values at reg tight intervals;

averaged reduction of $1.8k~$20k per day

Energy/Reg price impacts

Reg price trended down with average reduction of (-$0.49/MWh)~(-

$3.55/MWh); energy price may increase or decrease through co-

optimization with averaged change of $0.02/MWh~(-$1.09/MWh)

Reg scarcity impacts The scarcity case in the sampled days was resolved with the expanded

pool of units on reg

Table 4-2 Simulation results of Study 1) Simulate the enhanced logic against production cases


24

Figure 4-5 Units that are designated as “REG-Commit” by the enhanced logic on top of production


25

Figure 4-6 Regulation actually cleared on the “REG-Commit” units added by the enhanced logic

Figure 4-7 Production cost savings per 5 minutes Real-Time interval by the enhanced logic

Figure 4-8 System-wide energy and regulation price changes by the enhanced logic

As can be seen, significant benefits are obtained by designating more units as “REG-Commit” for

potential regulation clearing, while maintaining the overall capacity and flexibility. Among these benefits,

production cost was reduced by up to $0.24 million per day. Moreover, while the pool of “REG-Commit”

units to potentially clear regulation is expanded, actual regulation clearing is still concentrated on the most


26

economic ones as determined by SCED among the pool of “REG-Commit” units. This is important result

to validate the enhanced logic. Otherwise if actual regulation clearing is spread all over the expanded

pool with small amount of cleared MW, deployment could be a challenge. Since the enhanced logic is

based on offer parameters and operating status that are mostly at an hourly granularity, the regulation

commitment is also verified to be generally on an hourly basis, although intra-hour change is still possible

due to unit offer or operating status changes similarly like today. Close review of the regulation cleared

results also shows that no regulation is cleared on units that are off-control. As such, the enhanced logic

in Figure 4-1 was found to be feasible for Real-Time regulation clearing with favorable benefits.

Study 2) essentially mimics the scenario where we automate the regulation management process by

removing operation manual regulation commitment from production cases. Results show that the

enhanced logic can capture most of units that are currently being manually committed via the regulation

management tool, and would not strand or reduce resource capacity and flexibility as compared to Day-

Ahead. As shown in Figure 4-9, more units are designated as “REG-Commit” for potential regulation

clearing when applying the enhanced logic as compared to the existing manual regulation management in

production. In addition, the enhanced logic can capture most of units (green triangle) that are currently

manually designated as “REG-Commit” by the regulation management tool and would not include those

units (the portion of red bar above the green triangle) with stranded capacity or flexibility. For high load

periods when existing manual regulation management was conscious of not stranding capacity or

flexibility, the enhanced logic can capture almost all units that were manually added in production.

Examination of regulation capacity (min {(RegMax - RegMin)/2, RampRate*5min}) shows a similar pattern

as the observation above with the number of units on regulation.


27

Figure 4-9 Units designated as “REG-Commit” by the enhance logic as compared to the manual process in production

Compared to the benefits observed in Study 1), simulation results of study 2) can be less (when missing

the economic regulation units in production), equal or more (when remove the uneconomic regulation

units in production). Compared to production, the results of study 2) are overall improved. Note that

energy price can be reduced in study 2) since units are from reg if their capacities were stranded

(RegMax < EconMax).

Reg-Committed units 2~63 units more units were on reg than production; 0~17 units were

removed from production reg due to stranded capacity or flexibility

Reg clearing results

Among the more units on reg, about 3 or 4 units on average actually

cleared reg; among the remove units about 2 or 3 units on average were

not able to clear reg anymore

Production cost Production cost reduced $2k~$16k per day than production

Energy/Reg price impacts

Price trended down but may also increase with average reg price change

of $0.48/MWh~(-$3.49/MWh) and energy price change of (-

$0.16/MWh)~(-$1.84/MWh)

Reg scarcity impacts The scarcity case in the sampled days was relieved

Table 4-3 Simulation results of Study 2) Remove operation manual regulation commitment from production cases and apply

the enhanced logic

The simulation results indicate significant efficiency gains, and support the recommendation for

enhancement and automation. The Real-Time regulation clearing enhancement is then designed for

each of processes including regulation commitment, regulation clearing, and communication of regulation

clearing results:

Figure 4-10 Design of Real-Time regulation clearing enhancement

This Real-Time Regulation Clearing Enhancement is a significant step in the overall Regulation

Enhancement Roadmap as shown in Figure 4-11.


28

Figure 4-11 Overall Regulation Enhancement Roadmap

Efficiency Grade Description

Reg Capacity New logic added more capacity/units than current RT reg tool

DA/RT convergence Units with stranded capacity/flexibility will not be put on reg

(IMM)

Reliability and

Economic Efficiency

Simulation shows no spread reg clearing; production cost

reduced from production

Operation Process

Improvement

Could largely free up operation from the manual regulation

management every hour; may still need operation surveillance

Optimality Capture majority of economic reg units; can be further improved

by LAC optimization

Table 4-4 Evaluation of the proposed Real-Time Reg Enhancement relative to the overall Roadmap

5. On-going research and future scenarios In the medium-term, ELMP III is exploring appropriate pricing for the Enhanced Combined Cycle (ECC)

model. MISO developed the ECC model to more accurately reflect combined cycle resource operational

characteristics utilizing Configurations, Components, and Transitions.8 With the existing ELMP logic,

ECC resources are not able to include transition costs in their price setting and cannot set prices if not

dispatchable such as transitioning into the Duct Burner (DB) configuration as shown in Figure 5-1.

Incorporation of the transition-related costs in price setting is explored under ELMP III by investigating

appropriate convexification of transition related decisions.

8 Enhanced Combined Cycle Task Team, https://www.misoenergy.org/stakeholder-engagement/committees/enhanced-combined-cycle-task-team-ecctt/

https://www.misoenergy.org/stakeholder-engagement/committees/enhanced-combined-cycle-task-team-ecctt/

https://www.misoenergy.org/stakeholder-engagement/committees/enhanced-combined-cycle-task-team-ecctt/


29

Figure 5-1 ECC Resource Costs Related to Transitions to DB Configurations

In the long-term, high penetration of renewables and emerging future resources post new challenges for

price formation. For example, under the future scenarios as shown in Figure 5-2, net load could ramp up

fast during sunset hours, and it will be important for resources that are committed to meet the needs to

set prices. In addition, while energy pricing may be driven down by the near-zero marginal cost

renewables, other resources might be hold online to provide reliability or flexibility services and it is

important to send the corresponding price signal to the market place.

Figure 5-2 Net load curve with high penetration of renewables

With the integration of future resources such as Storages and Distributed Energy Resources, temporal

and locational price accuracy will become critical for the efficient utilization of these resources and the

overall system reliability. For example, Storage resources are featured by their fast ramping flexibility, but

are meanwhile energy limited and their offers could be driven by the anticipated temporal price


30

differences. Different aggregation schemes are being explored for Distributed Energy Resources and

aggregation across multiple injection nodes needs to be carefully design to ensure the accuracy of local

price formation. As a result, it is important to use these resources at the right time and location, and

accurate price signals can incentivize efficient charging or discharging of these resources or appropriate

locational response. Currently, the RTO employs a single-interval dispatch and pricing model, which can

be hard to co-optimize with future intervals and inform the future prices. Multi-interval pricing is thus

studied under ELMP III. Real-Time application can be challenging where prices are calculated on a

moving window basis and the advisory prices at the future intervals may not materialize when they

become binding.9

6. Conclusion The ELMP III research and development studies show benefits of the continued price enhancements, and

the prototyping experiences help to understand the implementation complexity. Based on the study, the

IMM recommendation of including Day-Ahead Fast Start Resources in Real-Time ELMP setting and the

Real-Time Regulation Enhancement are recommended for near-term implementation considering the

significant benefits and the modest implementation efforts. Convex Envelope formulation and the IMM

recommendation of ramp relaxation are recommended to be prioritized in the implementation queue after

the new Market System is in place. Additional study and validation against production cases may also be

needed for the ramp relaxation. Medium-term and long-term efforts are under investigation and are

expected in a future report.

Endnotes

MISO acknowledges the effective collaboration with the IMM, its research partners of Prof. Ross Baldick and Bowen Hua from the University of Texas, Austin. We specially appreciate the discussions with Dr. Paul Gribik.

9 FERC Technical Conference, “Price Formation with Evolving Resource Mix,” C. Wang, D. Chatterjee, J. Li and M. Robinson, June 2017. https://www.ferc.gov/CalendarFiles/20170623124149-20170620%20MISO%20Price%20Formation_FERC%20Tech%20Conf.pdf?csrt=18151806463483539378

https://www.ferc.gov/CalendarFiles/20170623124149-20170620%20MISO%20Price%20Formation_FERC%20Tech%20Conf.pdf?csrt=18151806463483539378

https://www.ferc.gov/CalendarFiles/20170623124149-20170620%20MISO%20Price%20Formation_FERC%20Tech%20Conf.pdf?csrt=18151806463483539378

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