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MISO enhances modeling of the gas transportation system in MTEP analyses

Increasing gas-fired generation

Technological advancements in hydraulic fracturing and horizontal drilling have provided a tremendous influx of cheap natural gas to the US, including production from regions that were not “typical” supply regions in the past. As a result of this cheap and plentiful natural gas, MISO’s usage of the fuel has increased significantly in recent years. Natural gas has gone from 18% of MISO’s energy in 2014 to 27% in 2016. These sustained low gas prices are also driving capacity additions, with over 8,000 MW of gas-fired generation in advanced stages of the MISO Generator Interconnection queue (signed GIA or in DPP as of April, 2017).

Changing flows

These major changes in the gas system are not only leading to lower prices, but also flatter prices around the US. While gas has typically been produced in regions like the Gulf South and Western Canada, it is now being produced closer to demand centers in areas like the Marcellus region of Northern Appalachia. These non-traditional supply areas are providing the MISO region with a variety of options for cheap gas.

The shale boom has also provided an opportunity to export gas in the form of Liquefied Natural Gas (LNG). The Sabine Pass facility in the MISO South region has a planned processing capacity of over 3.5 Billion cubic feet of gas per day, which is the equivalent of nearly 20,000 MW of combined-cycle generation running 24 hours per day. Additional LNG facilities are under construction around the country, including other facilities in MISO South. This increase in Gulf-area demand may increase Henry Hub prices relative to the rest of the country.

Current gas system representation is limited

In its “off-the-shelf” form, the PROMOD model uses the following equation to set gas prices at plants:

𝑆𝑡𝑎𝑡𝑒 𝐺𝑎𝑠 𝑃𝑟𝑖𝑐𝑒 = 𝐻𝑒𝑛𝑟𝑦 𝐻𝑢𝑏 𝑃𝑟𝑖𝑐𝑒 + 𝑅𝑒𝑔𝑖𝑜𝑛𝑎𝑙 𝑃𝑟𝑖𝑐𝑒 𝐴𝑑𝑑𝑒𝑟 + 𝑆𝑡𝑎𝑡𝑒 𝑃𝑜𝑜𝑙 𝐴𝑑𝑑𝑒𝑟

Gas originates at Henry Hub, and then pre-determined “regional price adders” are incorporated as gas flows to one of 24 different market locations. PROMOD then tacks on additional price adders when gas flows from these market points to one of 33 state-wide gas pools. The price adders are calculated once a year by ABB using their own set of assumptions and inputs.

In other words, the price adders in the model do not change whether the electric model represents a high-growth case or a low-growth case, a high-gas usage case or a low-gas usage case. Additionally, all generators within a state receive the same gas price. For example, a Combined Cycle unit in a remote rural area would see the same gas price at all times as a Combustion Turbine unit in a major load center if the two were in the same state.

MISO’s modeling provides a more accurate representation

of the natural gas system

Granularity – all-in burner tip gas prices are specified for each individual plant

Accuracy – burner tip prices are able to reflect differences in fuel contracting practices (IT/FT, Pipeline/LDC)

Flexibility – allows for variation in locational gas prices based on assumptions made in MTEP Futures

MISO is improving how it models the transportation and pricing of natural gas, which will produce better forecasts of the region’s long-term transmission needs


Enhancements provide granularity, accuracy, and flexibility

The proposed enhancements to the gas transportation system will utilize a process very similar to that used by ABB, but tailored to each Future and with a much higher level of detail. The enhanced gas price calculation takes the form:

𝑃𝑙𝑎𝑛𝑡 𝐺𝑎𝑠 𝑃𝑟𝑖𝑐𝑒 = 𝐻𝑒𝑛𝑟𝑦 𝐻𝑢𝑏 𝑃𝑟𝑖𝑐𝑒 + 𝐿𝑜𝑐𝑎𝑡𝑖𝑜𝑛𝑎𝑙 𝑃𝑟𝑖𝑐𝑒 𝐴𝑑𝑑𝑒𝑟 + 𝐵𝑢𝑟𝑛𝑒𝑟 𝑇𝑖𝑝 𝐴𝑑𝑑𝑒𝑟

Gas flow in the PROMOD model will still originate from Henry Hub. From there, however, the price of gas will be incremented as it flows to one of a few hundred gas pipeline zones. The costs of moving gas to these pipeline zones (referred to as “locational price adders”) are able to vary based on the assumptions included in the Future definition. For example, increased industrial production along the Gulf Coast in the proposed MTEP18 Limited Fleet Change Future will cause higher relative gas prices in this region compared to the rest of MISO. Refer to Appendix 1: Using GPCM for Locational Prices for more detail on this process.

Gas is then transported from these pipeline zones to individual generators. These price adders (referred to as “burner tip adders”) are developed through a review of public data on plant-level gas prices listed in the EIA-923 Power Plant Operations report. These burner tip price adders are the only piece in the new transportation system that will not change by Future scenario, under the assumption that a plant’s gas contracting practices will not change drastically over time. Refer to Appendix 2: Using EIA-923 for Burner Tip Adders for more detail on this process.

This enhanced transportation system increases granularity, accuracy, and flexibility in the model. Granularity is improved by specifying plant-specific gas burner tip adders. Accuracy is improved because these burner tip adders are able to reflect differences in fuel contracting practices such as firm vs interruptible transportation, as well as gas system connection factors such as whether a plant is directly connected to an interstate pipeline or if it is served by a Local Distribution Company. Flexibility is improved because the system allows for variation in locational gas prices depending on assumptions made in the MTEP Future. For a full breakdown of benchmark results, refer to Appendix 3: Results of Benchmark Testing.

Better analysis for a more efficient system

The electric and natural gas systems are more closely connected than ever. Fuel for electric generation is the fastest growing sector for natural gas usage, and gas has recently overtaken coal as the largest single source of fuel for the nation’s generating fleet. Low gas prices—a result of hydraulic fracturing and horizontal drilling—have driven capacity factors of gas-fired units up in the near term. And projections of sustained low gas prices have spurred the addition of more gas-fired plants in coming years.

These enhancements to the gas price formulation in MTEP analyses will substantially improve MISO’s ability to identify the transmission needs of the future system.


Appendix 1: Using GPCM for Locational Prices


The GPCM gas model

The Gas Pipeline Competition Model (GPCM) is a model of the gas pipeline network in North America, developed by RBAC, Inc. GPCM is a network flow model used to analyze the impacts of natural gas supply, demand, and infrastructure changes on gas prices, flow patterns, and pipeline utilization.

The model is calibrated against actual market data (prices, flows) and includes forecasted supply & demand data through 2040. The model includes over 200 interstate and intrastate gas pipelines, 100 supply plays, and 100 sub-state demand areas.

Using GPCM to model MTEP Futures

While the base GPCM dataset includes forecasts developed by RBAC, this data is completely modifiable. This allows us to input assumptions from the MTEP Futures in order to identify the impacts that these future scenarios would have on the gas pipeline system. For example, the narrative for the MTEP17 Existing Fleet Future includes the following language around natural gas:

- Natural gas prices remain low due to increased well productivity and supply chain efficiencies. - Footprint wide, demand and energy growth rates are low to model a more static system with no

notable drivers of higher growth; however, as a result of low natural gas prices, industrial production along the Gulf Coast increases

This information can be used to create a gas pipeline model for this Future. Supply of natural gas can be increased to simulate increased well productivity. And because natural gas is used as both a feedstock and an energy source for a large portion of Gulf Coast industrial production, it can be assumed that not only does electric demand in the Gulf Coast increase, but also natural gas demand. Supply and Gulf Coast demand can be increased until the model’s Henry Hub price (an output of GPCM) closely resembles the Henry Hub price developed through the stakeholder-driven MTEP Futures Development process.

This process was tested on each of the MTEP17 Futures: the Existing Fleet (increased supply from all gas basins, increased Gulf Coast demand), Policy Regulations (minimally decreased supply, no demand changes), and Accelerated Alternative Technologies (decreased supply from all gas basins, decreased Gulf Coast demand, increased demand in the rest of the country). The resulting Henry Hub gas prices (in Real $) are shown in the chart below:

We can then utilize these MTEP Futures gas models to identify Future-specific gas prices at pipeline zones across the country. These locational prices can be fed directly into PROMOD as a replacement for the 24 market points that currently exist in the model.


Appendix 2: Using EIA-923 for Burner Tip Adders


Public datasets for all-in costs

The EIA-923 Power Plant Operations report is a public dataset that contains plant-level statistics on fuel consumption and fuel costs on a monthly basis. Reported fuel costs represent all-in costs for the plant, including things like fuel losses, transportation balancing costs, transportation reservation charges, and distribution system costs.

Utilizing the data submitted by MISO members in the annual Winter Generator Fuel Survey, we are able to map each plant in MISO to a specific pipeline zone from the GPCM model. This mapping allows us to compare historic wholesale gas prices seen at these pipeline zones against reported burner tip prices from the EIA report. This is the foundation for the burner tip adders that will be utilized in MTEP analyses.

Linear regressions give approximations of variable costs

The first step in developing burner tip adders is to calculate the cost difference between the gas on a plant’s GPCM pipeline zone versus the cost of gas reported to EIA. Actual data from 2012-2016 is used for this analysis. The process is shown below.

𝐶𝑜𝑠𝑡 𝐷𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 = (𝑃𝐸𝐼𝐴 𝑥 𝑄𝐸𝐼𝐴) − (𝑃𝐺𝑃𝐶𝑀 𝑥 𝑄𝐸𝐼𝐴)

𝑊ℎ𝑒𝑟𝑒:

𝑃𝐸𝐼𝐴 = 𝑇ℎ𝑒 𝑝𝑙𝑎𝑛𝑡′𝑠 𝑏𝑢𝑟𝑛𝑒𝑟 𝑡𝑖𝑝 𝑝𝑟𝑖𝑐𝑒 𝑟𝑒𝑝𝑜𝑟𝑡𝑒𝑑 𝑡𝑜 𝐸𝐼𝐴

𝑄𝐸𝐼𝐴 = 𝑇ℎ𝑒 𝑡𝑜𝑡𝑎𝑙 𝑑𝑒𝑙𝑖𝑣𝑒𝑟𝑒𝑑 𝑓𝑢𝑒𝑙 𝑞𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑟𝑒𝑝𝑜𝑟𝑡𝑒𝑑 𝑡𝑜 𝐸𝐼𝐴

𝑃𝐺𝑃𝐶𝑀 = 𝑇ℎ𝑒 𝑤ℎ𝑜𝑙𝑒𝑠𝑎𝑙𝑒 𝑔𝑎𝑠 𝑝𝑟𝑖𝑐𝑒 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑙𝑎𝑛𝑡′𝑠 𝐺𝑃𝐶𝑀 𝑧𝑜𝑛𝑒

This cost difference is calculated for each plant, for each month from 2012-2016. These cost differences are then graphed against the delivered quantities, and a linear regression is performed to identify a best-fit line in the form Y = Ax + B. The fixed component of the regression (B) represents an approximation of any fixed charges that the plant may see associated with their fuel supply arrangements. This could be something like a firm reservation charge. The variable component of the regression (A) represents the variable cost of gas delivery to the plant—the commodity charge seen by the plant for the delivery of gas. This is the component that becomes the burner tip adder for the plant. An example of this cost difference vs delivered quantity graph—with statistics on the linear regression—is shown below. In this example, the plant would have a $0.6386/MMBTU adder to transfer gas from its GPCM pipeline zone to the burner tip.


Criteria for a “good match”

While data is available for most plants for all months from 2012-2016, occasional errors in reporting or changes in plant operation may cloud the data. For that reason, a few subsets of data were created for each plant:

- All Data: Utilize all of the reported data from the EIA-923 report - Summer Only: Utilize only the reported data from May through October of each year - Shoulder Only: Utilize only the reported data from Spring and Fall of each year - 2015-2016 Only: Utilize only the reported data from the last two years - No Outliers: Utilize only the cost and quantity data that is within two standard deviations of the median

Linear regressions were created for each plant utilizing each of these datasets. The regression with the highest weighted R2 value (R2 multiplied by the number of data points used in the calculation) was used to create the plant’s burner tip adder.

To ensure that only the most accurate data is fed into our models, a cutoff was set for R2 values on the linear regressions. Any regression with an R2 < 0.5 was ignored.

Treatment of RRF units and those without EIA data

Plants that do not exist in the EIA report—or plants whose EIA data could not produce a regression with an R2 > 0.5—are given burner tip adders consistent with plants of the same type in as close of geographic proximity as possible. In other words, a combined cycle plant that is not included in the EIA-923 report will be given a burner tip adder that is the average of any other combined cycle units in the same county. If no other combined cycle units exist in the same county, a state-wide average of combined cycles will be used. If no other combined cycle units exist in the state, an average of all combined cycles in the model footprint is used.

The same treatment is given to RRF units based on their siting locations.


Appendix 3: Results of Benchmark Testing


Benchmark results show marked improvements in accuracy

MISO’s enhanced burner-tip pricing system creates a very close match to actual plant-level historic pricing. As the charts show, the MISO-generated prices (in blue) more accurately reflect actual cost data (black) over the past four years compared to PROMOD prices (red).

Additional benchmarking work was done utilizing the PROMOD 2013 Market Benchmark model. This model was originally developed in an attempt to accurately reflect actual MISO market data from 2013. Applying MISO’s enhanced gas transportation system to this model resulted in a slight increase in overall burner tip gas prices (an average of a 1-3% increase compared to the original model).

The updated transportation system resulted in LMPs, capacity factors, and dispatch amounts that resembled actual market data slightly more closely than the original benchmark model. This can be seen in the charts to the right, which plot data from an off-the-shelf 2013 PROMOD model (blue), the original 2013 benchmark model (red), the 2013 benchmark model with MISO’s enhanced gas transportation system (green), and actual data from the 2013 MISO market (purple).


Preliminary modeling illustrates pricing variance across MTEP17 Futures

The prices of natural gas at locations around the MISO region are significantly affected by the assumptions included in MTEP Futures definitions. This pricing variability is not represented in the existing PROMOD gas pricing structure.

By modeling the MTEP Futures in the GPCM gas model, we are able to identify the changes that occur in locational gas prices as a result of these Futures assumptions. The following charts show gas prices at pipeline zones around the MISO footprint, comparing the three MTEP17 Futures. These prices are represented by their basis—the price of gas at a particular pipeline zone minus the price of gas at Henry Hub. It can be seen that while prices are relatively convergent across the Futures in summer months, there can be significant differences in the locational price of gas during winter and shoulder months.

These changes in pricing are caused by a variety of factors—such as increases in gas supply in the EF Future, or wide-spread increases in demand in the AAT Future. In the AAT Future narrative for example, Gulf-region demand for natural gas is relatively lower than the rest of the country. This is because of the industrial nature of the region, which would respond to high gas prices with low growth rates. Because of this, the price at Henry Hub (located in Southern Louisiana) sees downward pressure even while prices in the rest of the country remain relatively high due to substantial regional demands. This effect can be seen in the charts below, where the bases at pipeline zones in the AAT Future tend to be higher than the bases in the other Futures.

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