In-Home Storage: The Virtual Power Plant

Rapid Growth

Solar and wind are considered the most popular renewable resources across the world, but due to their intermittent and unpredictable nature, utilities are still relying on natural gas and coal. However, when renewable technologies are combined with energy storage they smooth out load fluctuations and have the potential to significantly impact the generation mix.
Total energy storage deployment has increased dramatically in the past few years because of low-carbon, clean energy policies, and is anticipated to grow even more in the near-term. By 2022, GTM Research expects the U.S. energy storage market to reach 2.5 GW annually, with residential opportunities contributing around 800 MW.


Source: GTM Research

How Does It Work?

Energy storage works as a three-step process that consists of extracting power from the grid, solar panels, or wind turbines, storing it (charging phase) during the off-peak period when power prices are lower, and returning it (discharging period) at a later stage during the on-peak period when the prices are much higher.


For electric vehicles (EV), most of the charging happens at night and during weekends, when the prices are comparatively lower, and vehicles are not used that much. As EVs continue to enter the mainstream market, they would increase the off-peak prices and contribute to load shifting.
Energy storage devices and EVs can complement each other or they may be competitive. But energy storage is the key element for EV charging during on-peak hours.

Different Market Players

Residential energy storage has been a holy grail for companies like Tesla, Panasonic, LG, Sunverge Energy, and Orison with lithium ion (Li-ion) batteries as the leading technology type. Now with plug-in electric and hybrid vehicles on the rise, automobile companies Tesla, Nissan, Mercedes Benz, BMW, Renault and Audi have also joined the residential market to integrate EV charging stations, battery storage and rooftop solar that in essence has a residence operating as a virtual power plant.
Beginning in December of last year, Arizona Public Service Company deployed Sunverge Energy’s energy storage hardware coupled with advanced, intelligent energy management systems that predict future load requirements and solar generation. Additionally, Tesla is enjoying significant market share, shown recently by Vermont-based Green Mountain Power’s launch of a comprehensive solution to reduce customer electricity bills using Tesla’s cutting edge Powerwall 2 and GridLogic software.
A few other utility companies, especially in Florida and California, are also exploring residential energy storage programs, as shown in the figure below.


Source: Hawaii PUC; General Assembly of Maryland

So, what are some other current thoughts about the pros and cons of in-home energy storage?

  • Energy storage reduces load fluctuations by providing localized ramping services for PV and ensuring constant, combined output (PV plus storage).
  • Improves demand response and reduces the peak demand.
  • Extra savings for customers through net metering systems and end-user bill management.
  • Reduces reliance on the grid; the customer can generate and store the energy during severe outages also.
  • Disposal of Li-ion batteries is not easy, and they are difficult to recycle
  • Automakers, like Nissan and BMW, are implementing second-life batteries, thereby reducing the durability and reliability of the product.


Concluding Thoughts

Clearly, a wider acceptance of energy storage resources would be a game changer in the U.S. power sector. Utilities, consumers, and automakers are profiting from this exponential growth of energy storage. With an increasing number of companies using artificial intelligence and machine learning algorithms for energy management systems, the synergy with energy storage creates a perfect, smart, personal power plant which has tremendous potential to change the landscape of the energy industry.

Filed under: Clean Power Plan, Hydro Power, Power Grid, Power Market Insights, Power Storage, Renewable Portfolio Standards, Renewable Power, Solar Power, UncategorizedTagged with: , , , , , , , , , , , , , , , , ,

Total Solar Eclipse and Its Impact on Solar Power

On August 21, 2017 a rare total solar eclipse will sweep across the United States, starting in western Oregon and passing southeast across the country to South Carolina. During this time, the sun will appear either partially or completely blocked by the moon, depending on your location. The “Great American Total Solar Eclipse” will be the first total solar eclipse to span across the United States since 1918. This event also marks the first time where the U.S. electric grid will be significantly impacted by a solar eclipse.


Figure 1. The path of August’s total solar eclipse. Source.

The eclipse is expected to cause a major dip in solar production for a period of hours on this day, especially on the west coast. California, for example, is expecting to lose about 6,000 MW from the grid due to the lack of sunlight, which California ISO (CAISO) is planning to make up for via natural gas and hydro generation. The Washington Post article goes on to discuss how another challenge for CAISO is ensuring the substitute generators are able to ramp up and down quick enough to handle the changes in solar generation. For instance, as the moon begins to block the sun, solar energy collection is expected to decrease at a rate of 70 MW/minute. Similarly, ramp up rates of around 90 MW/minute are expected once the sunlight begins to come back.

This total solar eclipse will mark the first one to be visible on any part of the contiguous United States since 1979, long before solar power held any share of market generation. It will also be the first solar eclipse of any kind in the United States since May 2012, and solar has grown at record rates since then. Luckily, Europe witnessed a similar total solar eclipse in March 2015 to give us a better context of what to expect. Germany, who alone accounts for ~40% of European solar capacity, saw a drop of solar output from 21.7 GW to 6.2 GW during the eclipse. Reuters also reported that to make up the loss of generation, they looked to gas, coal, nuclear and hydroelectric pumped storage energy, and that overall, Europe experienced a reduction of 17 GW of solar power during the eclipse and did an excellent job of successfully weathering the event through proper planning ahead of time.

Back in the U.S., solar power accounted for 9% of California’s generation in 2016 and the state is home to nearly half of the nation’s total solar capacity.  On August 21, California is expected to lose 50 to 75% of its solar production during the five or so hours. We will then see for the first time how the United States electric grid as a whole will adapt to its first significant dip in solar energy caused by a natural phenomenon.

Filed under: Clean Power Plan, Hydro Power, Renewable Power, Solar PowerTagged with: , , ,

Nuclear Retirements – The Unknown Future of Nuclear Power in the United States

Nuclear Plants Nearing Retirement

The U.S. currently has over 2 GW of nuclear capacity scheduled to be retired within the next four years.  The three planned closures are the 678 MW Pilgrim Nuclear Power Station, the 610 MW Oyster Creek Generating Station, and the 852 MW James A. Fitzpatrick Power Station.  The operators of these plants determined that while they had received extensions to their initial licenses, remaining operational was not economically viable.


Figure 1: U.S. Nuclear Capacity Source

As of August 2016, announced retirements looking even further into the future total above 7 GW with a few others being politically tenuous it further compounds the uncertainty within the nuclear fleet. Included in this 7 GW is the Fort Calhoun plant in Nebraska that was shut down by Omaha Public Power this year on October 24. However, this is just the tip of the iceberg when you consider the remaining plants and their need for future license extensions.

The Arduous Licensing Process

Nuclear plants are initially licensed for up to forty years by the U.S. Nuclear Regulatory Commission (NRC).  The operator may then apply for an additional twenty-year renewal; following that they can apply for a further extension of twenty more years.  All extensions are initiated by the operator and must be started sufficiently ahead of the expiration of their current license for the NRC to evaluate the safety and environmental impacts of an extension.  When operators apply more than five years prior to expiration, they can usually continue to operate while under this review.  If they don’t apply until within five years of the expiration, they may be forced to stop operating until they are approved.  The renewal process contains multiple cumbersome steps as shown in the diagram below.


Figure 2: License Renewal Process Source


Current Operating Nuclear Plants

The U.S. has 100 operating nuclear power plants; 45, or nearly half, have already operated through their forty-year operating license and are on their initial twenty-year extension.  Two of these are approaching the need to apply for their second extension: Peach Bottom in Pennsylvania and Surry in Virginia.


Figure 3: Active Nuclear Reactors  Source

To look at it another way, 81 plants have received their first renewal, an aging fleet in its own right.   But this means up to 30 GW of nuclear power has an unknown fate based on a not-yet-granted second license extension alone.  To date, no renewal applications have been permanently rejected but several plants have needed to make extensive improvements to gain approval.


Figure 4: Licensed Nuclear Plants Source

According to a recent Moody’s report, today’s low gas environment is making it difficult for some smaller nuclear units to survive competitively in the power market.  The future of gas will likely play a key role in the future of nuclear viability, as even without costly improvements some nuclear generators are struggling to stay afloat.

Nuclear Plants Coming Online

Interestingly, there are still a number of newly constructed plants currently in the process of becoming licensed that will bring over 5,000 MW online by 2020; these include plants in Tennessee, North Carolina and Georgia.  Additionally, there are up to six more applications for a combined 10 new reactors currently under review by the NRC.  A few companies are also looking into new designs that are smaller in scale, under 500 MW as opposed to +1,000 MW, that are more modular in design.  This new technology would give them the flexibility to be placed on more urban sites as needed to accommodate grid needs.

The Future Role of Nuclear Power

While a few sites are in the process of retiring their reactors, nuclear power is likely to be a part of the energy solution going forward for some time.  The minutiae of the policies may change, but one thing is certain: nuclear power will play a significant role in meeting U.S. electricity needs while curbing carbon pollution.  The U.S. Department of Energy reports the level of nuclear power generation for the country has been at 20 percent, the question is what hurdles will nuclear owners and operators have to overcome to maintain that level?

Filed under: Clean Power Plan, Nuclear Power, Renewable Portfolio StandardsTagged with: , , , ,

Integrated Gas-Power Modeling

Quantifying the Impacts of the EPA’s Clean Power Plan

Notwithstanding the recent legal stay from the U.S. Supreme Court, it is still important to understand the U.S. EPA’s Clean Power Plan (CPP) and its impact in the larger context of natural gas markets and its role in electric power generation. Because these two markets are becoming even more highly interrelated, integrated gas-power modeling is the most realistic approach for such analyses. EPIS has tested interfacing AURORAxmp® with GPCM®, a calibrated NG model developed by RBAC, Inc. The following is a brief discussion of our experimental setup as well as some of our findings.

Integration Approach

Monthly prices for 39 major natural gas hubs for the next 20 years are represented in AURORAxmp (as an input). They were developed utilizing GPCM’s market model (as an output) in pipeline capacity expansion mode. AURORAxmp then simulates a long-term capacity expansion that utilizes the GPCM-generated gas prices, and produces many results: power prices, transmission flows, generation by each resource/resource type including gas-consumption data. This gas-consumption (output from AURORAxmp) is fed back into GPCM as gas demand by the electricity sector (input to GPCM) for a subsequent market balancing and pipeline capacity expansion simulation which generates a new set of monthly gas hub prices. The iterative process begins at some arbitrary, but plausible, starting point and continues until the solution has converged. Convergence is measured in terms of changes in the gas-burn figures and monthly gas-hub prices between subsequent iterations.

This two-model feedback loop can be utilized as a tool to evaluate energy policies and regulations. To quantify the impact of an energy policy, we need two sets of integrated gas-power runs which are identical in all respects except the specific policy being evaluated. For example, to understand the likely impacts of emission regulation such as CPP, we need two integrated gas-power models with the identical setup, except the implementation of CPP.

Before presenting our findings on the impact of “CPP vs No CPP”, we first provide some further details on the setup of the GPCM and AURORAxmp models.

GPCM Setup Details

• Footprint: All of North America (Alaska, Canada, contiguous USA, and Mexico), including liquefied natural gas terminals for imports, and exports to rest-of-world.
• Time Period: 2016-2036 (monthly)
• CPP Program: All the effects of CPP on the gas market derived from changes to gas demand in the power generation sector.
• Economics: Competitive market produces economically efficient levels of gas production, transmission, storage and consumption, as well as pipeline capacity expansion where needed.

AURORAxmp Setup Details

  • Footprint: All three major interconnections in North America (WECC, ERCOT, and the East Interconnect; which includes the contiguous U.S., most Canadian provinces and Baja California).
  • Time Period: 2016 – 2036 (CPP regulatory period + 6 years to account for economic evaluation)
  • CPP Program: mass-based with new source complement for all U.S. states
    • Mass limits for the CPP were applied using the Constraint table
    • Mass limits were set to arbitrarily high values in the Constraint table for the “No CPP” case.
  • RPS targets were not explicitly enforced in this particular experiment. Future studies will account for these.
  • LT Logic: MIP Maximize Value objective function


  1. “CPP” – Convergent result from integrated gas-power model with CPP mass limits.
  2. “No CPP” – Convergent result from integrated gas-power model with arbitrarily high mass limits.
  3. “Starting Point” – Gas prices used in the first iteration of integrated gas-power modeling.
    • This is the same for both “CPP” and “No CPP” case.

Quantifying the CPP vs. No CPP

Impact on Gas and Electricity Prices

  1. Both No CPP and CPP cases have generally lower prices than the Starting Point case in our experiment. However, post-2030, CPP prices are higher than the Starting Point.
    • This happens due to capacity expansion in both markets.
    • We stress that the final convergent solutions are independent of the Starting Point case. The lower prices in CPP and No CPP cases compared to the Starting Point case are a feature of our particular setup. If we had selected any other starting price trajectories, the integrated NG-power feedback model would have converged on the same CPP and No CPP price trajectories.
  2. CPP prices are always higher than the No CPP case.
    • This is likely driven by increased NG consumption in CPP over No CPP case.

This behavior was observed in all major gas hubs. Figure 1 shows the average monthly Henry Hub price (in $/mmBTU) for the three cases.

Impact of CPP on Henry Hub PricesFigure 1: Monthly gas prices at Henry Hub for all three cases.

Figure 2 presents the monthly average power prices in a representative AURORAxmp zone.

Comparison of Power Prices in PJM Dominion VPFigure 2: Average monthly price in AURORAxmp zone PJM_Dominion_VP with and without CPP.

Figure 3 shows the impact of CPP as a ratio of average monthly prices in AURORAxmp’s zones for the CPP case over No CPP case. As expected, power prices with the additional CPP constraints are at the same level or higher than those in the No CPP case. However, it is interesting to note that the increase in power prices happens largely in the second half of CPP regulatory period (2026 onwards). It appears that while gas prices go up as soon as the CPP regulation is effective, there is latency in the increase in power prices.

Impact of CPP on Zone Price (CPP/No CPP)Figure 3: Impact of CPP on electricity prices expressed as a ratio of CPP prices over No CPP prices.

Figure 4 presents a comparison of total annual production cost (in $billions) for each of the three regions.

Annual Production Cost (In $billions) for each of the three regions.Figure 4: Total annual production costs by region for CPP and No CPP case.

Figure 5 presents the same comparison as a percentage increase in production cost for the CPP case. The results show that while the CPP drives up the cost of production in all regions, the most dramatic increase is likely to occur in the Eastern Interconnect.

Percentage increase in production cost total for CPP over No CPP CaseFigure 5: Percent increase in production cost for CPP case.

Electricity Capacity Expansions

Comparing the power capacity expansions in Figure 6 and Figure 7, we see that AURORAxmp projected building more SCCTs in the CPP case vs. the No CPP case in the Eastern Interconnect. We believe this is primarily driven by the higher gas prices in the CPP case over No CPP case. SCCTs typically have slightly higher fuel prices compared to CCCTs, which get their fuel directly from the gas hub for the most part. In this long-term analysis, AURORAxmp is seeking to create the mix of new resources that are most profitable while adhering to all of the constraints. The higher gas prices in the CPP case are just high enough to make the SCCTs return on investment whole.

Eastern Interconnect Build Out - No CPPFigure 6: Capacity expansion for Eastern Interconnect – No CPP Case.

Eastern Interconnect Build Out - CPPFigure 7: Capacity expansion for Eastern Interconnect – CPP Case.

Table 1: Capacity expansion by fuel type in total MW.



East Int.












































Table 1 shows the details of power capacity expansion in the three regions with and without CPP emission constraints. In addition to increasing the expansion of SCCTs, we can see that CPP implementation incentivizes growth of wind generation, as well as accelerates retirements. Coal and Peaking Fuel Oil units form the majority of economic retirements in the CPP case.

Fuel Share Displacement

Figure 8 shows the percent share of the three dominant fuels used for power generation: coal, gas, and nuclear. Figure 9 shows the same data as the change in the fuel percentage share between the CPP and No CPP case. Looking at North American as a whole, we see that coal-fired generation is essentially being replaced by gas-fired generation. Our regional data shows that this is most prominent in the Eastern Interconnect and ERCOT regions.

Percentage Share of Dominate Fuel TypeFigure 8: Percentage share of dominant fuel type.

Change in fuel share for power generation (cpp - no cpp)Figure 9: Change in fuel share for power generation (CPP – No CPP).

Natural Gas Pipeline Expansions
The following chart presents a measure of needed additional capacity for the two cases. The needed capacity is highly seasonal, so the real expansion need would follow the upper boundary for both cases.


Additional NG Pipeline Capacity RequiredFigure 10: Pipeline capacity needed for the CPP and No CPP cases.

Our analysis shows that the CPP will drive an increase in natural gas consumption for electricity generation. The following chart quantifies the additional capacity required to meet CPP demand for NG.
Additional NG Capacity Required CPP vs No-CPP (bcf/day)

While the analysis presented here assumes a very specific CPP scenario, we stress that the integrated gas-power modeling is an apt tool for obtaining key insights into the potential impacts of CPP on both electricity and gas markets. We are continuously refining the AURORAxmp®-GPCM® integration process as well as performing impact studies for different CPP scenarios. We plan to publish additional findings as they become available.

Filed under: Clean Power Plan, Natural Gas, Power Market Insights, UncategorizedTagged with: , , , ,

Integrated Modeling of Natural Gas & Power

Natural gas (NG) and electric power markets are becoming increasingly intertwined. The clean burning nature of NG, not to mention its low cost due to increases in discovery and extraction technologies over the past several years, has made it a very popular fuel for the generation of electricity. As a result, the power sector is consistently the largest NG consumer. For example, in 2014, 30.5% of the total NG consumption in the United States was used for the generation of electricity (Figure 1).


Figure 1: U.S. Natural Gas Consumption by Sector, 2014. Source

According to EIA’s Annual Energy Outlook (AEO) 2015 projections,

“…natural gas fuels more than 60% of the new generation needed from 2025 to 2040, and growth in generation from renewable energy supplies most of the remainder. Generation from coal and nuclear energy remains fairly flat, as high utilization rates at existing units and high capital costs and long lead times for new units mitigate growth in nuclear and coal-fired generation.”

Economic, environmental and technological changes have helped NG begin to displace coal from its dominant position in power production. Although it was just for a single month, NG surpassed coal for the first time as the most used fuel for electricity generation in April 2015. The EIA also notes that considerable variation in the fuel mix can occur when fuel prices or economic conditions differ from those in the AEO 2015 reference case. The AEO reference case assumes adoption of the Environmental Protection Agency’s (EPA) implementation of Mercury and Air Toxics Standard (MATS) in 2016, but not the Clean Power Plan (CPP). Adoption of CPP, along with favorable market forces, could change the projections of the AEO 2015 reference case significantly. There is a consensus within both NG and power industry that NG-fired power generation will likely increase with the adoption of CPP.

Quantifying such a trend is non-trivial, but is crucial for stakeholders and regulators in both gas and power markets to fully understand what the future holds. Proper accounting of the interdependencies between NG and power markets is integral to the quality of any long-term predictions. Approaches for modelling an integrated NG-power capacity expansion that account for economics and market operations is the key to the most effective analysis.

The issue of gas-power integration has been a topic of active interest in the industry, and that interest is increasing. For example, the East Interconnect Planning Collaborative coordinated a major study in 2013 – 2014 to evaluate the capability of NG infrastructure to: satisfy the needs of electric generation, identify contingencies that could impact reliability in both directions and review dual-fuel capability. Likewise, the notorious “polar vortex” during the winter of 2013-2014 caused unusually cold weather in the New England region, which “tested the ability of gas-fired generators to access fuel supplies,” and caused ISO-NE and others to acknowledge the need to further investigate the issues affecting synchronization between gas and electric systems. More recently, companies like PIRA Energy are sharpening their focus on the interdependencies between gas and electric power.

There is a need for new and improved modeling approaches that realistically consider this growing gas-power market integration. An even greater need is to integrate the modeling of these markets in a way that is both efficient and practical for the end user, and still able to produce commercially viable results. EPIS has extensively tested interfacing AURORAxmp with GPCM, a calibrated NG model developed by RBAC, Inc. Several organizations and agencies have found this approach successful. Utilizing the two models allows us to develop projections for endogenously derived capacity additions (in both electric generation expansion and gas-pipeline expansion), electricity pricing, gas usage and pricing, etc. which are consistent between the two markets. This consistency leads to greater insight and confidence to aid decision-makers.

Figure 2: Abstract representation of integrated NG-power modeling using AURORAxmp and GPCM..

Although the industry is now anxiously waiting for the judiciary to weigh in on the legality of CPP regulations, there is a consensus that some form of carbon emission regulation will likely be in effect in the near future. Some states, such as Colorado, have already undertaken several regulatory initiatives and may implement a state-level CPP-like emissions regulation even if the federal plan is vacated by the courts.

As part of our ongoing research on the topic of gas-power modeling, we have designed and executed a series of test scenarios comparing the standard calibrated cases of AURORAxmp and GPCM against a potential implementation of CPP. If the proposed form of CPP is upheld in the courts, states have a number of implementation options. At this early stage, there has been no good evidence to indicate that one option would be more popular over another. This necessitated we make some broad assumptions in our experimental gas-power integration process. In our test scenarios, we assumed that all states would adopt the mass-based goal with new resource complement option.

An integrated gas-power framework allows us to better understand the most probable direction for the two markets. Our integrated GPCM-AURORAxmp CPP test scenario for the Eastern Interconnect took 7 iterations to converge to a common solution that satisfied both markets. By comparing resulting capacity expansions, fuel share changes, and gas prices between the starting point (Iteration 0) and ending point (Iteration 6) we get a sense of how the markets will coevolve.

Starting capacity expansion in the Eastern Interconnect for GPCM-AURORAxmp model.

Figure 3: Starting capacity expansion in the Eastern Interconnect for GPCM-AURORAxmp model.

Figure 3 shows the capacity expansion resulting from Iteration 0, the starting point of the integrated iterations. Iteration 0 is essentially a standalone power model with no regard for the impact the capacity expansion would have on the gas market. Figure 4 shows the capacity expansion after Iteration 6.

Resulting capacity expansion in the Eastern Interconnect for GPCM-AURORAxmp model.

Figure 4: Resulting capacity expansion in the Eastern Interconnect for GPCM-AURORAxmp model.

The convergent prices of NG were lower for Iteration 6 than Iteration 0 at all major gas hubs. Figure 5 shows the monthly prices at Henry Hub for both the iterations. The lower gas prices are unintuitive, but plausible. The combined gas-power sector has several market forces that are interdependent. We are currently working with gas experts to understand some of the mechanisms that could lead to lower gas prices. We hypothesize that our accounting for capacity expansion in both the markets is one of the drivers for this behaviors and our findings will be reported in a future publication.

Comparison of starting and ending price trajectories with integrated GPCM-AURORAxmp model.

Figure 5: Comparison of starting and ending price trajectories with integrated GPCM-AURORAxmp model.

The lower gas prices highlight one of the key benefits of integrated gas-power models. Standalone modeling frameworks are likely to misrepresent the impact of the complex cross-market mechanisms. Integrated models avoid this particular pitfall by explicitly modeling each market and is a more apt tool for evaluating policies such the CPP. AURORAxmp provides the capability to model any of the implementation plans that states might adopt in the future – rate-based, mass-based, emission trading schemes and so forth. The ability to interface with widely used NG models, such as GPCM, provides a convenient option for analysts to confidently navigate the highly uncertain future of intertwined NG and power markets.

Filed under: Clean Power Plan, Natural GasTagged with: , , ,

Simple-Cycle Combustion Turbines in the CPP

The Environmental Protection Agency’s (EPA) Clean Power Plan (CPP) is full of interesting caveats and exceptions on many issues. One notable quirk is the exclusion of simple-cycle combustion turbines (SCCT) from the list of affected electricity generating units. States must detail how they intend to limit carbon emissions from combined-cycle combustion turbines (CCCT) and coal-powered steam generators, but carbon from SCCTs is not regulated under the CPP.

The EPA’s rationale is that SCCTs cannot meaningfully contribute to emission reductions because they run so rarely. In the full report, the EPA states that it does not expect this to change:

“In addition, while approximately one-fifth of overall fossil fuel-fired capacity (GW) consists of simple cycle turbines, these units historically have operated at capacity factors of less than 5 percent and only provide about 1 percent of the fossil fuel-fired generation (GWh)…the EPA expects existing simple cycle turbines to continue to operate as they historically have operated, as peaking units.”

Is this a realistic assumption? Simple-cycle units currently have low capacity factors, but that is mostly because they are relatively expensive to operate. Natural gas has historically been more expensive than coal. Among units burning natural gas, combined-cycle units are more efficient than simple-cycle units. As such, simple-cycle units are generally kept offline due to their higher operating costs. However, this is not a rule, it is a relationship. If you add costs to one set of generators and not another, the relationship may change.

To illustrate this point, let’s consider a few hypothetical units, operating in 2025, and see how they may respond to carbon pricing. One is a relatively modern and efficient simple-cycle gas plant, another is a typical combined-cycle gas plant, and the last is an older coal plant. Unit characteristics vary significantly within each of these technologies, but we will take a highly competitive simple-cycle and compare it to some of the least competitive coal generation to see where simple-cycle units may start to become cheaper than coal.

Operating characteristics for hypothetical units (2025)

Technology Heat Rate
CO2 Emission Rate
Fuel Cost
Operating Cost
Efficient SCCT 10,000 8.00 18.50 80.00
Typical CCCT 7,500 118 7.00 6.50 52.50
Older Coal ST 12,000 210 3.50 8.50 42.00

We exclude an emission rate for our simple-cycle unit, because they are not regulated under the CPP and will not experience an increase in operating costs due to carbon restrictions or pricing. If we add a carbon price ($/ton) to each of these units, their operating costs will shift accordingly.

Hypothetical Operating Costs by Source and Carbon Price

As the price of carbon reaches $10/ton, the coal unit starts to become more expensive to operate (per MWh of generation) than the combined-cycle unit (Point A). This is expected and intended by the CPP. One of the fundamental building blocks of emission reductions is a shift of generation from coal to combined-cycle units. However, by the time we reach a carbon price of around $30/ton, coal units also become more expensive to operate than simple-cycle generators! Because the SCCT unit is not subject to carbon regulations under the CPP, its costs remain constant, while the operating cost of the coal plant rise quickly as carbon pricing increases.

A carbon price of $30/ton would be unprecedented in the U.S., but not inconceivable. Depending on which discount rate you prefer, the official social cost of carbon can exceed $30/ton. At EPIS, our modeling of mass-based compliance approaches to the CPP have shown that allowance prices greater than $30/ton may be needed for some states to meet their emission goals through a carbon market.

Of course, unit operation cannot be summed up by a single operating cost. Many factors can influence a generator’s decision to run, such as start costs, other environmental regulations, and participation in reserve or ancillary service markets. There may be reasons beyond per-MWh costs why an SCCT unit would continue to provide only peaking services in a high carbon price environment. However, some power providers may find that the strict emission limits placed on coal and combined-cycle plants opens up a unique opportunity for the relatively unregulated SCCT units. Anyone concerned with modeling the CPP would do well to carefully consider the potentially changing role of SCCTs in an uneven regulatory environment, which gives them a free pass while hindering coal and combined-cycle plants.

Will simple-cycle units increase their utilization if the CPP is implemented, becoming more than just peak power providers? Only time will tell. Let us know what you think in the comments.

Filed under: Clean Power Plan, Power Market InsightsTagged with: , , , , , , , ,