United States: Cost-Benefit Analysis Of ERCOT's Future Ancillary Services (FAS) Proposal

Last Updated: January 5 2016
Article by Samuel A. Newell, Rebecca Carroll, Pablo Ruiz and Will Gorman

This report was prepared for the Electric Reliability Council of Texas (ERCOT).

Executive Summary

We were asked by the Electric Reliability Council of Texas (ERCOT) to evaluate the economic benefits of its proposed Future Ancillary Services (FAS) design. ERCOT proposed FAS to efficiently maintain grid reliability as inverter-based generation displaces traditional generation and as new technologies offer new ways to provide ancillary services.

The essential differences between FAS and ERCOT's Current Ancillary Services (CAS) design are that FAS unbundles ancillary services and fine-tunes service requirements to system conditions and resource capabilities. FAS unbundles CAS's Responsive Reserve service (RRS)—the service used to arrest frequency decay and restore frequency to 60 Hz in the event of the two largest contingencies—into three distinct services: Fast Frequency Response, Primary Frequency Response, and Contingency Reserve, as described in Section II.B. These services enable new technologies and more load resources to provide valuable services that are compatible with their capabilities.

Both of these broad changes—unbundling services and fine-tuning requirements—represent good market design in that they increase the possible ways to meet reliability objectives, and they avoid procuring more reserves than necessary. Our analysis informs the nature and magnitude of FAS's benefits, which ERCOT and stakeholders can compare to the implementation costs of FAS. We focused primarily on the economic benefits but, for completeness, we also describe reliability benefits and costs. We did not translate reliability benefits into measures of economic savings.

The reliability benefits of FAS include:

1. After a contingency, FAS will more readily arrest frequency decay by deploying very fast resources providing FFR1 (e.g., advanced batteries). This saves other frequency response (FFR2) providers in reserve in case a larger contingency occurs shortly thereafter.

2. FAS recognizes the relative effectiveness of different types of responsive reserves (PFR and FFR) through an "equivalency ratio," which depends on hourly system inertia. In FAS, the equivalency ratio is recognized in the AS market clearing engine. This allows for a tighter procurement of frequency responsive reserves but avoids the reliability risk of substituting less effective resources for more effective ones, which is a current practice under CAS.

3. FAS rates providers of frequency response based on their past performance. This mechanism ensures that the system always has as much capability as intended and provides incentive for resources to improve their performance. In contrast, CAS allows all qualified resources to provide up to 20% of their maximum capacity towards RRS, irrespective of their performance in past events.

4. FAS separates replacement reserves from other frequency reserves. This allows for more effective procurment from a larger pool of resources that can be available in 10 minutes. This leads to faster frequency restoration following a contingency event and faster replacement of frequency response resources so they can prepare for the next event.

5. FAS ensures that regulation reserves are spread among at least four resources, which improves the system response acuracy and reliability.

The economic benefits we quantified are the production cost savings from a more efficient commitment and dispatch, as FAS enables the most economic resources to meet a more finelytuned set of requirements. We estimated the savings by first comparing the quantities of each AS product needed under CAS and FAS designs—and we found that FAS requires less generation spinning and held for reserves. We then estimated the cost savings resulting from FAS's reduced quantities.

The quantities of ancillary services needed depend on AS design and system conditions. We analyzed three scenarios that ERCOT and stakeholders had requested: (1) a 2016 Current Trends scenario that reflects expected market and system conditions for next year; (2) a 2024 Current Trends scenario based on ERCOT's 2014 Long-Term System Assessment (LTSA) scenario (developed in 2013) with additional wind and gas resources; and (3) a Stringent Environmental scenario from the same LTSA with increased wind and solar generation and a $45 per ton price of CO2 allowances. This scenario was originally envisioned as a system stress case in which responsive reserve requirements increases as a result of renewable generation displacing thermal generation and lowering system inertia. However, it did not prove to have lower system inertia and correspondingly higher reserve requirements as anticipated. System inertia actually increased in most hours because coal generation was displaced by not only renewable generation but also combined-cycle (CC) generation, which has nearly twice the inertia per MW as coal.  As a result, we chose not to evaluate the Stringent Environmental scenario further. (An alternative scenario with low load growth and enough renewable generation to displace both coal and combined-cycle generation might have had lower inertia and greater requirements for responsive reserves, but we did not construct such a scenario).

For the remaining scenarios, ERCOT staff determined hourly requirements of each service based on PLEXOS simulations they conducted under our direction. We found that FAS requires less thermal generation spinning to provide Primary Frequency Response (PFR) since it enables efficient substitution of load resources and new technology providing Fast Frequency Response (FFR). This substitution results from:

  • Incorporating a PFR-FFR equivalency ratio into the market clearing engine
  • Removing the 50% limit on participation of Load Resources that exists for Responsive Reserve Service under the CAS design
  • Introducing the FFR1 product to enable new technologies

On average, we found PFR reductions (compared to Gen-RRS under CAS) of approximately 9%: 140 MW in 2016 and between 129 and 186 MW in 2024, depending on how much new technology or additional Load Resources enter to provide FFR. In addition to these savings in meeting frequency responsive needs, we also found savings in providing replacement reserves. Fine-tuning requirements to system conditions allows 756 and 790 MW less non-spinning capacity to be held in reserve in 2016 and 2024, respectively. (These PFR and non-spin reductions differ under alternative assumptions discussed below).

We estimated the economic savings from FAS's reduced AS quantities, analyzing two separate and additive components of the production cost of providing ancillary services: day-ahead energy opportunity costs, which reflect the cost of committing and holding (often inframarginal) capacity in reserves, considering only the expected value of real-time prices across all possible real-time system conditions; and real-time option value foregone, considering the volatility of real-time prices around the expected value. It reflects the cost of holding reserves and losing the option to change operations as different real-time conditions are realized. The real-time cost also accounts for the possibility of committed providers experiencing a forced outage and having to replace their capacity with other resources on short notice.

We estimated day-ahead cost savings using the PLEXOS model to simulate unit commitment and dispatch in FAS vs. CAS. PLEXOS approximates day-ahead as opposed to real-time conditions since it does not simulate the distribution of unexpected conditions that can occur in real time. In our 2016 simulations, FAS's reduced procurement of PFR reduces day-ahead production costs by $9.1 million per year because less combined-cycle capacity must be committed, avoiding startup costs and displacement of lower-cost coal generation. In 2024, day-ahead production costs decrease by $1.2 million per year without new technology and $3.4 million per year with new technology providing additional FFR. Simulated savings are less in 2024 than in 2016 because higher assumed net loads cause coal to become fully inframarginal, so marginal changes in CC commitment affect coal generation minimally. As for differences in replacement reserves between CAS and FAS (i.e., with less Contingency Reserve under FAS than Non-Spinning Reserve under CAS), they have little effect on day-ahead production costs since they are provided mainly by offline resources.

We estimated real-time optionality savings separately, by analyzing historical capacity offers into ERCOT's AS markets. Ancillary service providers bear real-time costs when they commit their capacity for reserves because they are, in effect, restricting their participation in the real-time market and foregoing potential real-time revenue. We assume that capacity offers into the AS markets are a direct representation of these real-time opportunity costs. To estimate the associated cost of each AS on a system-wide basis, we compute the area under the offer curves to arrive at an average cost per MWh for each daily hour (1 through 24) in each month in 2014. We then conservatively apply those average costs to the hourly quantities of similar services procured in each future scenario.1 We found that, with its lower quantities of PFR procured, FAS saves $3.2 million in real-time opportunity costs in 2016 and between $3.3 and $4.8 million in 2024, depending on the amount of new technology participating. In addition, with its lower quantities of replacement reserves procured (i.e., with less Contingency Reserve under FAS than Non-Spinning Reserve under CAS), FAS saves $9.2 million in real-time opportunity costs in 2016 and $11.2 million in 2024.

Combining day-ahead and real-time opportunity costs, we find total annual benefits of $21.5 million per year in 2016 and between $15.7 and $19.4 million per year in 2024 under Current Trends, depending on the participation of new technology. Assuming the annual benefits found for the study years of the analysis persist at similar levels for ten years, the cumulative benefit would be on the order of $200 million, before discounting.

However, the benefits of FAS depend on how FAS and CAS are each defined. Our analysis was based on CAS and FAS specifications that were current in the spring of 2015. But since ancillary service market rules continue to change, we analyzed two sets of alternative assumptions reflecting recent developments. One set of these assumptions increased the benefits of FAS and the other set decreased them. The ERCOT Board recently approved an amendment to CAS that would reduce the average Non-Spinning Reserve procurement from 1,931 MW to 1,464 MW in 2016 and from 2,000 MW to 1,464 MW in 2024. These reductions in CAS requirements reduce the savings attributable to FAS's tighter replacement reserve requirements by $6.4 million in 2016 and $8.4 million in 2024. On the other hand, in mid-September 2015, North American Electric Reliability Corporation (NERC) released new standards that reduced the Minimum PFR requirement from 1,240 MW to 1,143 MW. The Minimum PFR change has a greater effect in FAS than CAS due to FAS's recognition of the equivalency ratio between FFR and PFR resources as well as the removal of the 50% limit on Load Resource participation. PFR procurement savings increase from 140 to 220 MW in 2016, resulting in $6.9 million additional savings, and from 129 to between 207 and 266 MW in 2024, depending on the participation of new technology, resulting in $2.8 to $3.4 million additional annual savings. When both the NSRS and PFR changes are applied together, however, the results are similar to the savings reported in our original analysis.

While actual benefits are uncertain, we believe the general magnitude of our estimates to be robust. Our estimates reflect a simple fact: efficient procurement by FAS reduces the quantities of ancillary services needed, which will save money as long as ancillary services are costly to provide (i.e., their price is positive). Furthermore, our estimates are conservative in several ways: (1) in our CAS cases, we determined reserve requirement on a day-ahead basis, while CAS requirements are actually determined more than a year in advance, which significantly increases the quantity of reserves procured; (2) we applied average rather than marginal costs to estimate real-time opportunity costs; and (3) we did not attribute economic value to the reliability benefits of FAS.

With respect to the cost of implementing FAS, we understand that ERCOT has estimated a onetime cost of $12 to $15 million. These costs are very small compared to the estimated benefits of roughly $20 million per year. If discounting 10 years of benefits at 7.5%, their present value would be $137 million. The net present value accounting for implementation costs would be over $120 million, and the benefit-cost ratio would be approximately 10.

We do not know what costs stakeholders might incur in adjusting to FAS, but we expect any such costs could be minimized by ERCOT providing enough lead time to avoid interfering with most power supply contracts.

Some stakeholders have raised concerns about FAS's dynamic requirements imposing ongoing risks on load serving entities. Dynamic requirements (which could be adopted under either FAS or an enhanced CAS) will create uncertainty about the required quantities of ancillary services. However, we expect that the market will develop ways to financially manage those risks more efficiently than maintaining non-dynamic requirements at sufficiently high levels to meet reliability criteria under all system conditions. (Again, our benefit-cost analysis assumed that even CAS incorporates dynamic requirements; if we had not, our net benefit estimates would have been higher.)

In summary, we found that FAS is good market design, and it offers economic benefits on the order of 10 times the implementation costs. FAS will also improve reliability and provide greater flexibility for meeting reliability needs as system conditions and resource capabilities evolve.

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1 Applying the average cost is conservative since the marginal cost on the offer curve is a more economically relevant measure of the change in cost associated with marginal changes in quantities, and the marginal cost is about 4 times higher than the average cost in this case.

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